X-Planes: X-52, the Designation Refused
Filed under: aerospace, history, engineering
In 2006 somebody asked for the number 52 and was told no. The designation X-52A was requested for a programme to test active aeroelastic wing technology, and it was disapproved because of possible confusion with the B-52 series, and the designation X-53A was allocated to the programme instead [Missing USAF and DOD Aircraft Designations].
This is the fifty-third article in the X-Planes series, following the X-1, the X-2, the X-3, the X-4, the X-5, the X-6, the X-7, the X-8, the X-9, the X-10, the X-11, the X-12, the X-13, the X-14, the X-15, the X-16, the X-17, the X-18, the X-19, the X-20, the X-21, the X-22, the X-23, the X-24, the X-25, the X-26, the X-27, the X-28, the X-29, the X-30, the X-31, the X-32, the X-33, the X-34, the X-35, the X-36, the X-37, the X-38, the X-39, the X-40, the X-41, the X-42, the X-43, the X-44, the X-45, the X-46, the X-47, the X-48, the X-49, the X-50, and the X-51.
Every other article in this series on a designation is about an aeroplane, or about a number that never became one. This one is about a number that was refused, which differs from both. The X-39 was reserved and then lost because nobody wrote the letter that would have assigned it [Missing USAF and DOD Aircraft Designations]. The X-52 was asked for in writing, considered, and declined. The paperwork was done correctly and the answer was no.
The article turns on the reason given. Not that the aircraft was unworthy, not that the programme was cancelled, and not that the number had been used. The number was refused because it resembled a number already in use [Missing USAF and DOD Aircraft Designations].
The record does not say through which sense. It gives possible confusion as the reason, in one clause. Whether the worry was a radio, a maintenance card or a line in a budget is not stated anywhere this article could find, and the sections below argue for the radio from the neighbouring cases rather than from this one.
The Research Question
The designation X-52 had no research question of its own, because it never named a vehicle. The number was requested for a programme to test active aeroelastic wing technology, and that programme’s question belonged to the aircraft that received X-53A instead [Missing USAF and DOD Aircraft Designations]. That question is the subject of the next article in this series and is not pursued here.
The question this article asks is administrative rather than aeronautical. It asks under what rule a design number that the sequence named could be refused for resembling another number already in use, and what that refusal shows about the designation system. The record supplies the reason, and the article sets out to find the rule behind it.
Programme Origin, What the Record Says Happened
The request was for X-52A and the answer was X-53A. The specialist registry that maintains the record of United States military aerospace vehicle designations states the case in two sentences [Missing USAF and DOD Aircraft Designations]. No other public source read for this article adds to them, and the encyclopedia entry for the X-53 repeats the reason in a single sentence [Boeing X-53 Active Aeroelastic Wing]. The designation X-52A was requested in 2006 for a programme to test active aeroelastic wing technology. It was disapproved because of possible confusion with the B-52 series, and X-53A was allocated instead.
The programme was the Active Aeroelastic Wing. A modified F/A-18A, flown at the space agency’s flight research centre at Edwards in cooperation with the Air Force Research Laboratory and Boeing Phantom Works, to find out whether a wing can be twisted deliberately to roll an aeroplane rather than being stiffened until it stops twisting [Active Aeroelastic Wing Flight Research, NASA Facts FS-2005-03-061 DFRC] [Air Force Research Laboratory]. It had already flown before it had a number. The programme began in 1996, the aircraft first flew in modified form in November 2002, and the flight research concluded in March 2005 [Clarke et al. 2005] [Boeing X-53 Active Aeroelastic Wing].
The number arrived over a year after the flying stopped. The encyclopedia entry for the aircraft dates its designation as X-53 to 16 August 2006, by memorandum of the Air Force Deputy Chief of Staff for Strategic Plans and Programs [Boeing X-53 Active Aeroelastic Wing], and the Air Force Research Laboratory announced on 11 December 2006 that the demonstrator had been assigned the Mission Design Series number X-53 [Active Aeroelastic Wing flight research vehicle receives X-53 designation, Air Force Research Laboratory, 11 December 2006]. The announcement gives no date for the memorandum, so the August date rests on the encyclopedia entry alone. The space agency’s account of the programme calls the aircraft X-53 and gives no date [F/A-18 Active Aeroelastic Wing, NASA]. What the aeroplane did with the number is left for later.
The Office That Said No
The decision was made by one office and the instruction names it. A request for a designation goes from the programme office to the Department of Defence Control Point, which the 2005 instruction names as the Asset Identification Branch of Air Force Materiel Command at Wright-Patterson [Air Force Joint Instruction 16-401, 14 April 2005], and that office checks the proposal against the regulations and forms a recommendation. The recommendation and the original request then both go to the Directorate of Programs, Program Integration Division at the Pentagon, where the decision is made [Allocation of Official Aerospace Vehicle MDS Designations].
That office changed its own designator in the year it refused this one. Its symbol was HQ USAF/XPPE and became AF/A8PE with effect from 1 February 2006 [Allocation of Official Aerospace Vehicle MDS Designations]. The office that refused a number for resembling another number spent that same year renaming itself, and nothing in the record suggests anybody noticed.
Refusal is the exception and not the rule. The registry’s account of the process records that in most cases the originally requested designation is approved even when the coordinating office recommends a different one, and gives the F-35 and the KC-767A as the examples [Allocation of Official Aerospace Vehicle MDS Designations]. A request that is refused outright is therefore unusual, and this one was refused on a ground the instruction does not mention.
The Rule That Refused It Is Not in the Instruction
The governing document is a joint instruction of the Air Force, the Army and the Navy, and the issue in force in 2006 was dated 14 April 2005 [Air Force Joint Instruction 16-401, 14 April 2005]. It is not long. It says what a designation is made of, who may ask for one, and who decides. It was read for this article, in full, and the reading is the article’s central evidence.
It requires the next number and provides no way of skipping one. Section C, paragraph 5 directs that the coordinating office will assign and reserve the next available consecutive design number within each basic mission for new vehicles [Air Force Joint Instruction 16-401, 14 April 2005]. There is no qualification, no exception and no discretion attached to it. Formally, if $A_m$ is the set of design numbers already used up within basic mission $m$, whether allocated or passed over, the instruction defines what is to be assigned as
\[n^{\star}(m) \;=\; \min\bigl\{\,k \in \mathbb{N} \;:\; k \notin A_m \,\bigr\} \tag{1}\]and in 2006 every X number from 1 to 51 had been used up, although two of them, X-23 and X-39, were never allocated to anything [Missing USAF and DOD Aircraft Designations], so $n^{\star}(X) = 52$. The number that was refused is the number the instruction names.
The rule describes a set that only ever shrinks. Writing $V_m(t)$ for the numbers still available within basic mission $m$ at time $t$, and taking the range the instruction gives,
\[V_m(t) \;=\; \{1, 2, \ldots, 999\} \setminus A_m(t), \qquad n^{\star}(m) \;=\; \min V_m(t). \tag{2}\]Nothing returns a number to that set. The instruction directs that a retired designation is not used again for another vehicle [Air Force Joint Instruction 16-401, 14 April 2005], so the allocated set is non-decreasing in time and the available set is non-increasing,
\[t_1 \leq t_2 \;\implies\; A_m(t_1) \subseteq A_m(t_2) \;\implies\; V_m(t_2) \subseteq V_m(t_1). \tag{3}\]A design number is therefore consumed and not borrowed.
But a refusal consumes one by a route this model has no term for. The instruction knows two states, allocated and available, and the master list of designations records a third. The C-16 correspondence directs that the number be marked not used [Missing USAF and DOD Aircraft Designations], which is neither, so the used-up numbers divide in two and the full partition is
\[\{1, 2, \ldots, 999\} \;=\; \underbrace{A_m(t)}_{\text{allocated}} \;\sqcup\; \underbrace{U_m(t)}_{\text{marked not used}} \;\sqcup\; \underbrace{V_m(t)}_{\text{available}}, \tag{4}\]with $n^{\star}(m) = \min V_m(t)$ as before. The instruction defines the first and the third and never mentions the second, and yet the X-52 went into the second, along with C-16, C-42, C-43, C-44, P-6, F-19 and the design numbers 13 that custom skips [Missing USAF and DOD Aircraft Designations].
What was assigned is not what the sequence rule names. With $n^{\star}(X) = 52$ and 53 allocated,
\[\text{assigned} \;-\; n^{\star}(X) \;=\; 53 - 52 \;=\; 1, \tag{5}\]which states the anomaly as arithmetic.
The word skip does not appear in the 2005 issue at all. Neither does discretion, nor any criterion by which a proposed number might be judged unsuitable. The issue provides that requesters are notified of approval or disapproval, but it states no ground for disapproval and no authority to pass over the next available number [Air Force Joint Instruction 16-401, 14 April 2005]. The document that governed the decision contains no provision under which the next number could be passed over.
Nor did the issues before it. The 1997 issue of the same joint instruction and the 1994 issue it superseded were read as well, and they say the same things in the same order. The coordinating office will assign the next available consecutive design number within each basic mission for new vehicles. Design numbers run consecutively from 1 to 999. Requested popular names are checked for duplication against the master list, the Judge Advocate General conducts a trademark search of them, and final coordination comes from the Assistant Secretary of Defence for Public Affairs. The only mention of confusion attached to a designator is the prohibition of I and O as series symbols [Air Force Joint Instruction 16-401, 1 September 1997] [Air Force Joint Instruction 16-401, 1994] [United States Department of Defense Aerospace Vehicle Designation].
So the instruction carried no authority to skip a design number for nearly twenty years, across at least three issues, while the practice of skipping them ran from before the earliest issue read here to after it, from P-6 in 1962 and C-16 in 1981 to X-52A in 2006 [Missing USAF and DOD Aircraft Designations].
The Instruction Screens the Other Half of the Name for Confusion
The document did not forget about confusion. It has an apparatus for it, pointed somewhere else. Section E governs the popular name, meaning the word Stratofortress rather than the string B-52. A requested popular name is checked for duplication against the master list of popular names. It is reviewed by public affairs at command level and then at service level. The Air Force Judge Advocate General conducts a trademark search of the proposed name. It is coordinated among the services, the Secretary and the Chief of Staff both coordinate on it, and the Assistant Secretary of Defence for Public Affairs concurs or does not [Air Force Joint Instruction 16-401, 14 April 2005].
A design number goes through none of that. It is issued in sequence by a logistics office [Air Force Joint Instruction 16-401, 14 April 2005] [Allocation of Official Aerospace Vehicle MDS Designations].
The instruction also states which half is the official one. Section F states that the designation is the official identification, that it represents a specific category of vehicles for operations, support and documentation, and that the popular name characterises the mission and aids communications and media references [Air Force Joint Instruction 16-401, 14 April 2005]. So the confusability controls, the duplication check, the legal search and the four levels of review sit on the informal half of the identifier, and the half the instruction calls official is issued by a counter.
The Only Written Anti-Confusion Rule for the Designator Concerns Two Letters
There is exactly one. The series symbol, the letter that follows the design number and identifies the production model, runs consecutively from A, and the instruction prohibits the letters I and O for that symbol in order to avoid confusion [Air Force Joint Instruction 16-401, 14 April 2005]. The confusion in question is with the digits 1 and 0, a claim about how a character looks on a page or a panel.
The consequence is a smaller alphabet,
\[|S| \;=\; 26 - 2 \;=\; 24, \tag{6}\]so a design number supports twenty-four production models before the instruction requires the design number to advance to the next unused value [Air Force Joint Instruction 16-401, 14 April 2005].
The two limits together give the size of a mission’s designation space. With design numbers running from 1 to $999$ and twenty-four permitted series symbols,
\[N_m \;=\; 999 \times 24 \;=\; 23{,}976, \tag{7}\]and the 2020 issue, which expands the design number to four digits once 999 is reached [Department of the Air Force Instruction 16-401, 3 November 2020], raises that to
\[N_m' \;=\; 9{,}999 \times 24 \;=\; 239{,}976. \tag{8}\]Fifty-one of the nine hundred and ninety-nine design numbers had been consumed when the request was made, and the X series had used no more than a few of the twenty-four series symbols under any of them [List of X-planes]. Scarcity is not why 52 was refused, and no reading of the instruction suggests that it was.
That rule exhausts the system’s written thinking about a confusable designator, and its subject is typography. It does not consider what happens when the number is spoken. It does not consider another mission series.
The Authority Was Written Down Eight Years Later
The instruction was reissued on 16 May 2014 and again on 3 November 2020, the later issue jointly as a Department of the Air Force Instruction, an Army Regulation and a Naval Air Systems Command Instruction [Air Force Instruction 16-401, 16 May 2014] [Department of the Air Force Instruction 16-401, 3 November 2020]. Both carry a clause that the 2005 issue does not.
In both, Attachment 2, paragraph A2.1.6.1.2 reads that the office, HAF/A8PE in 2014 and AF/A8PE in 2020, reserves the authority to skip design number at discretion. The 2014 issue adds that skipped design numbers cannot be requested or used [Air Force Instruction 16-401, 16 May 2014].
That is one sentence, it names the office that refused the X-52A, and it supplies no criterion whatsoever. It does not say to avoid confusion. It does not say when, or on what evidence, or subject to what review. It converts a thing that office had been doing into a thing that office is entitled to do, and it does so without describing the thing.
The two intervals that matter are both long and they are the article’s timeline in one line,
\[\underbrace{2014 - 2006}_{8 \ \text{years after the refusal}} \qquad\text{and}\qquad \underbrace{2014 - 1994}_{20 \ \text{years after the earliest issue read here}}. \tag{9}\]The practice ran throughout the second interval and the authority arrived at the end of it.
Every other provision quoted above survives into the 2020 issue unchanged in substance. Design numbers still run consecutively. The series symbol still forbids I and O to avoid confusion with the design number. The popular name still goes to a trademark search and still gets its four levels of review [Department of the Air Force Instruction 16-401, 3 November 2020]. The two later issues add one more provision that bears on this article, and it points the same way. The 2014 issue, at paragraph 4.2.1.3.1, states that for vehicles with an extensive history of designations requests are not accepted for designators in reverse or skipped sequences, and the 2020 issue, at paragraph 4.2.1.3, states the same without the qualification [Air Force Instruction 16-401, 16 May 2014] [Department of the Air Force Instruction 16-401, 3 November 2020]. A requester may not ask to leave the sequence and the office may leave it at discretion, so the departure the X-52A decision made is now reserved to the office that made it.
The Same Office Had Manufactured the Same Collision Four Years Earlier
In 2001 the Joint Strike Fighter needed a designation and the sequence said F-24. The nomenclature office recommended that number, on the stated ground that design numbers are to be assigned consecutively, the same provision the X-52A refusal set aside [Non-Standard DOD Aircraft Designations].
It was overruled. The number that was approved on 5 June 2002, by HQ USAF/XPPE, was 35 [Non-Standard DOD Aircraft Designations] [Lockheed Martin F-35 Lightning II]. It came from a press conference, at which the Under Secretary and the programme manager announced the production aircraft by taking the demonstrator’s designation and replacing the X with an F. No designation had been reserved or approved for the production aircraft at that point.
So the F-35 exists because somebody deliberately made a production fighter share a number with an experimental aeroplane across a series boundary [Lockheed Martin X-35].
Four years later the same office, under a symbol it had changed in the interim, refused a number because it would have shared a number with a bomber across a series boundary.
The structure of the two cases is identical. In each, two designations differ only in the mission symbol and agree in the design number. In 2002 that identity was treated as desirable continuity worth breaking the sequence rule to obtain. In 2006 it was treated as a hazard worth breaking the sequence rule to avoid. The instruction in force said the same thing in both years and it authorised neither [Air Force Joint Instruction 16-401, 1 September 1997] [Air Force Joint Instruction 16-401, 14 April 2005].
Sizing From First Principles
There was no vehicle to size. The X-52 was a number that was requested and refused, and no airframe, engine or mass was ever attached to it. The aircraft the number was requested for was a modified F/A-18A that had already flown and finished its flight research before the request was made [Clarke et al. 2005], and its engineering is treated with the X-53.
This article sizes only the designation space. It is derived above from the instruction’s limits, being 999 design numbers and twenty-four permitted series symbols, and fifty-one of the design numbers had been consumed in the X series when the request was made. Scarcity of numbers did not drive the refusal.
Dependent Systems
A designation depends on paperwork rather than hardware, and the record names the offices this one passed through. The request went from the programme office to the Department of Defence Control Point, the Air Force Asset Identification Branch at Wright-Patterson, and from there to the Directorate of Programs, Program Integration Division at the Pentagon, where the decision was made [Allocation of Official Aerospace Vehicle MDS Designations]. The governing document was the joint instruction in its 14 April 2005 issue [Air Force Joint Instruction 16-401, 14 April 2005], and the outcome is recorded by the specialist registry [Missing USAF and DOD Aircraft Designations].
The aircraft the number was meant for depended on three partners, being the space agency’s flight research centre at Edwards, the Air Force Research Laboratory and Boeing Phantom Works [Active Aeroelastic Wing Flight Research, NASA Facts FS-2005-03-061 DFRC] [Air Force Research Laboratory]. Its systems are not described here.
The Flight Test Record
Nothing flew as the X-52. The number was refused, so no flight was ever made under it [Missing USAF and DOD Aircraft Designations].
The aircraft for which it was requested had already completed its flying. The programme began in 1996, the modified aircraft first flew in November 2002, and the flight research concluded in March 2005, more than a year before the designation X-53 was issued, on 16 August 2006 by the encyclopedia entry’s account and in any case before the laboratory announced it on 11 December 2006 [Clarke et al. 2005] [Boeing X-53 Active Aeroelastic Wing]. This article states only that the aircraft’s flight record existed and that it preceded the number.
Comparison With Ground Prediction
There is no flight result to set beside a ground prediction, because nothing flew under this designation. The record reports no wind tunnel work, analysis or simulation attached to the X-52, and the aeronautical predictions made for the Active Aeroelastic Wing are left to the X-53 article.
The only prediction in this record is the refusal’s. The deciding office anticipated possible confusion with the B-52 series [Missing USAF and DOD Aircraft Designations], and because the number was refused, that forecast was never exposed to an outcome. No confusion between an X-52 and a B-52 could occur, so none was observed, and the record can neither confirm nor refute the forecast.
The nearest the record comes to a forecast set against an outcome runs the other way. The 1953 requests to redesignate two drones were made because confusion with unmodified aircraft was already occurring, and they were refused, a case set beside the X-52 decision below under The System Declined to Fix the Confusion It Actually Had. A later section, Measuring the Judgement That Was Not Recorded, supplies the kind of measure a stated forecast would have needed, and records that no measure or threshold accompanied the decision.
What the Data Changed, What the Anomaly Reveals About the Designation System
The Refusal Belongs to a Documented Family
The X-52 is not an isolated decision, and the registry that records it records the others [Missing USAF and DOD Aircraft Designations].
C-16 was skipped, and the reported reason names the mechanism precisely. The number was on reservation for the aircraft that became the C-17, and the nomenclature office recommended C-16A on the ground that 16 was the next available number and that skipping it conflicted with the regulation then in force. One day later that letter was withdrawn and replaced by one concurring in C-17, and C-16 was to be marked in the master list as not used. No reason was recorded. It is reported that the number was skipped because of concerns over confusing the plane with the F-16 during the stress of high combat radio traffic [Missing USAF and DOD Aircraft Designations] [Boeing C-17 Globemaster III] [General Dynamics F-16 Fighting Falcon].
That sentence is the clearest statement in the record of what these refusals concern. It points away from the register, the paperwork and the eye, and toward a voice, a radio, and a crew under load.
Civil aviation studied that hazard and counted it. The United Kingdom’s aviation authority published a dedicated call sign confusion study in April 2000, drawing on the 482 call sign confusion reports filed by controllers and flight crews in 1997 [CAP 704, Aircraft Call Sign Confusion Evaluation Safety Study, United Kingdom Civil Aviation Authority]. Of those 482, 405 involved call signs whose suffixes are numbers only, and 198 involved call signs ending in the same two digits [CAP 704, Aircraft Call Sign Confusion Evaluation Safety Study, United Kingdom Civil Aviation Authority], the same shape as every collision this article examines. The European guidance that followed recommends avoiding phonetically similar call signs on the same frequency at the same time and names the formats most likely to be confused [Air-Ground Communications Briefing Note 2, Call Sign Confusion]. The hazard the C-16 note gestures at in passing has a literature, a reporting scheme and a count, and none of it is referenced anywhere in the designation instruction.
C-43 and C-44 were skipped to avoid confusion with the existing T-43 and T-44, and the registry reports unofficial information from the department that an informal policy is in effect to avoid duplication of well-known numbers [Missing USAF and DOD Aircraft Designations]. An informal policy is a rule that is not written down, and the X-52 case reaches the same finding from the other side.
P-6 was skipped for the Navy in 1962, on the nomenclature forms themselves, most probably to avoid future confusion with the P6M. T-50A is reserved and unassigned because a foreign trainer is marketed under that number and assigning it to a different model was regarded as too confusing. C-42 was skipped over concern about legal exposure to a widely sold light aircraft marketed as the C42 [Missing USAF and DOD Aircraft Designations].
XV-14 was allocated and then withdrawn, and the withdrawal letter is quoted. In May 1973 the Army and the space agency asked for a designation for a tilt-rotor demonstrator and XV-14 was allocated on 30 May. On 7 August a change was requested to avoid confusion with the Bell X-14B, and the request argued the point at length. Both aircraft were built by companies known shortly as Bell. Both would be flying at the same research centre. It warned of serious errors if the service and maintenance records of the two were mixed up, and of unnecessary resultant confusion to the aeronautical research and development community in general. The redesignation was approved on 22 August and the aircraft became the XV-15 [Missing USAF and DOD Aircraft Designations] [Bell XV-15].
And F-19 was skipped under a stated reason that the registry says was not the real one. The official explanation was to avoid confusion with the MiG-19. The manufacturer had in fact asked to skip it because it wanted an even number to distinguish its export fighter from Soviet competitors that all used odd ones, and the approving letter repeated the confusion story anyway [Missing USAF and DOD Aircraft Designations] [Northrop F-20 Tigershark]. Confusion is available as a reason whether or not it is the reason, and a reader of the two-sentence entry about the X-52 should hold that in mind.
A number is also skipped for reasons that have nothing to do with confusion. F-13 was rejected by the manufacturer or the Navy for superstitious reasons, and since the late 1960s it has been an unwritten rule that a design number 13 is always skipped, which has cost A-13, C-13, G-13, Q-13 and V-13 as well [Missing USAF and DOD Aircraft Designations]. A system that skips the number 13 by unwritten custom will not find skipping 52 difficult.
That custom is measurable, and it accounts for the largest single deletion in the record. Counting the mission symbols whose thirteenth number is absent by it,
\[\bigl| \{\, m \in M \;:\; 13 \notin A_m \text{ by custom} \,\} \bigr| \;=\; 6, \tag{10}\]being the fighter, attack, cargo, glider, drone and vertical-take-off series. One unwritten rule has removed six numbers, and no line of the instruction mentions it.
Every One of These Collisions Crosses a Series Boundary
Look at what collides in each case. X-52 with B-52. C-16 with F-16. C-43 and C-44 with T-43 and T-44. V-14 with X-14. P-6 with P6M. In every instance the two designations differ in the mission symbol and agree in the design number.
A designation is formally a pair. Writing $M$ for the set of basic mission symbols and $A_m$ for the numbers issued within mission $m$, an assigned designation is an element of
\[\mathrm{MDS} \;=\; \bigl\{ (m, n) \;:\; m \in M,\; n \in A_m \bigr\}, \tag{11}\]and within that space the pairs are unique by construction, because each mission counts its own sequence. X-52A and B-52H are distinct elements and no rule of the instruction is broken by having both.
The refusals are evidence that somebody did not believe the first coordinate survives the journey. If the channel a designation travels down preserves only the number, the effective identifier is the projection
\[\sigma(m, n) \;=\; n, \tag{12}\]and under $\sigma$ the two designations are the same object. The C-16 reason names that channel explicitly as a radio.
The designations a listener cannot separate are the fibre of that projection, and its size is the quantity the rest of this section turns on,
\[\sigma^{-1}(k) \;=\; \bigl\{\, (m, k) \;:\; m \in M,\ k \in A_m \,\bigr\}, \qquad \bigl| \sigma^{-1}(k) \bigr| \;=\; o_k. \tag{13}\]The problem lies in the sizes of the two spaces, which differ greatly. The register holds
\[\sum_{m \in M} \bigl| A_m \bigr| \tag{14}\]distinct designations, while a listener who hears only the number can distinguish at most
\[\Bigl| \bigcup_{m \in M} A_m \Bigr| \;=\; \max_{m \in M}\, \max A_m \tag{15}\]of them. The first grows with the number of mission series and the second does not. Adding a mission symbol adds capacity to the register and adds none to the radio.
Collisions are therefore not accidents in this system. They are its arithmetic. Writing $o_k$ for the number of mission series that have issued the design number $k$,
\[o_k \;=\; \bigl| \{\, m \in M \;:\; k \in A_m \,\} \bigr|, \tag{16}\]the count of colliding pairs across the register is
\[C \;=\; \sum_{k \geq 1} \binom{o_k}{2}, \tag{17}\]which is zero only if no number is ever issued twice across all series. Every low design number in this system has been issued in several series, because every series starts at one and counts up. There is an X-4 and an F-4. There is an X-5 and an F-5. There is an X-15 and an F-15, an X-16 and an F-16, an X-22 and an F-22, an X-35 and an F-35 [List of X-planes] [1962 United States Tri-Service Aircraft Designation System].
The average of $o_k$ over the numbers in use is the factor by which the register outruns the radio,
\[R \;=\; \frac{\sum_{m \in M} \bigl| A_m \bigr|} {\Bigl| \bigcup_{m \in M} A_m \Bigr|} \;=\; \operatorname*{mean}_{k \,\in\, \bigcup_m A_m} o_k, \tag{18}\]and $R > 1$ whenever any two series have both reached the same number. The public record does not permit computing $R$ for this system, because no complete allocated set is published for every mission symbol, and the article claims no value for it.
If the mission letter is lost, the chance of attributing a spoken number to the right series is at best
\[P(\text{correct} \mid k) \;=\; \frac{1}{o_k} \tag{19}\]under a uniform prior over the series holding that number. This is an idealisation and the article says so, since a listener has context, expectation and an aerodrome full of clues. It is stated because it shows the shape of the thing. The quantity the system controls is $o_k$, and the system increases it every time a new series is opened.
The same quantity in bits is the part of the identifier the channel throws away. A listener who has heard the number and not the letter carries a residual uncertainty of
\[H(k) \;=\; \log_2 o_k \tag{20}\]bits, which is zero when a number belongs to one series and one bit when it belongs to two.
The two decisions this article compares act on that quantity in opposite senses, at two different numbers, and by the same one bit. One of them spent the bit and the other withheld it. The X-35 had been allocated and the F-35 was approved on top of it, so
\[\Delta H(35) \;=\; \log_2 2 - \log_2 1 \;=\; +1 \ \text{bit}. \tag{21}\]The B-52 had been allocated and X-52A was refused, so the multiplicity stayed where it was and
\[\Delta H(52) \;=\; \log_2 1 - \log_2 1 \;=\; 0 \ \text{bits}, \tag{22}\]against the $+1$ bit the approval would have added.
One office added a bit of ambiguity in 2002 and declined to add the same bit in 2006, and wrote down its reason for neither.
The System Declined to Fix the Confusion It Actually Had
Two designations were requested in 1953 for the express purpose of ending a confusion that was already happening, and both requests were refused.
The Wright Air Development Center asked to redesignate a drone converted from the B-17 as Q-7, and a drone converted from the F-80 as Q-8. The stated reason was problems and delays in the production and support of the drones, because they were too easily confused with unmodified aircraft of the type they were built from. That is not a hypothetical about a radio. It is a report of a supply system misdelivering. The Air Research and Development Command did not concur with the reasoning and turned both requests down in March 1954 [Missing USAF and DOD Aircraft Designations].
Set the two decisions beside each other. In 1954 an office declined to change a designation although confusion was occurring and was costing time and parts. In 2006 an office declined to issue a designation because confusion might occur. The same system, on the same question, refused to act on evidence and acted on possibility.
That asymmetry is the sharpest thing the X-52 case reveals, and it shows only because the registry preserved the failures as carefully as the successes.
A Number Is Occupied for as Long as the Aeroplane Lives
A design number becomes unavailable when it is allocated and stays unavailable until the last aircraft carrying it retires, since the instruction directs that a retired designation is not used again for another vehicle [Air Force Joint Instruction 16-401, 14 April 2005]. The duration is
\[T_{\text{occupied}} \;=\; t_{\text{retire}} \;-\; t_{\text{allocate}}, \tag{23}\]and for most aeroplanes this is a few decades.
The B-52 is the extreme value of that quantity, by a wide margin. The Air Force has operated it since 1955 and its operational aircraft are expected to serve into the 2050s, a working life approaching a century [Boeing B-52 Stratofortress]. Taking 1955 and 2050 gives
\[T_{\text{occupied}} \;\geq\; 2050 - 1955 \;=\; 95 \ \text{years}, \tag{24}\]and at the moment of the refusal in 2006 the aeroplane had already held the numeral for fifty-one of them.
Split at the year of the decision, the two halves are of comparable size and both are large.
\[\underbrace{2006 - 1955}_{51 \ \text{years already served}} \;+\; \underbrace{2050 - 2006}_{44 \ \text{years still expected}} \;=\; 95 \ \text{years}. \tag{25}\]Whoever refused the number in 2006 was standing near the middle of its occupancy and not near the end of it.
So the request in 2006 was not unlucky in some general way. It asked for a number held by an aeroplane that had already served for fifty-one years and was expected to serve for more than forty more. A request for 52 made at any time in that span would have met the same aeroplane.
The aeroplane whose number blocked the X-52 is named in the prose of ten of the fifty-two articles that precede it in this series, which is 19.2 percent of them, across 26 mentions. The count includes its lettered variants and leaves aside the titles of surveyed records and of cited sources. It carried the X-15, the X-24, the X-38, the X-43 [Boeing B-52 Stratofortress] and the X-51 aloft. The article immediately before this one is about an aeroplane a B-52 dropped, and the number immediately after that aeroplane’s was refused because of the aeroplane that dropped it.
Nothing Was Lost
Compare the two anomalies without a vehicle that this series has now examined.
The X-39 produced a permanent hole. The number was reserved and the allocation request was never submitted, and the reservation was never cancelled either, so the number could not be reused before the next one was allocated. Two documents were never written, the request and the cancellation, and once the next number was allocated the gap was permanent [Allocation of Official Aerospace Vehicle MDS Designations].
The X-52 produced nothing of the kind. The request was made, considered and refused. The programme got a designation. The register records why 52 is absent [Missing USAF and DOD Aircraft Designations]. The cost of this refusal, measured in anything the designation system exists to provide, is zero.
That makes it the cleanest case in the series for asking what the rule is for. There is no damage to argue about and no cancellation to explain. There is only a decision, a reason, and an instruction that does not contain the reason.
Measuring the Judgement That Was Not Recorded
The refusal was a similarity judgement, and no measure, threshold or method was recorded with it. This section states what such a judgement looks like when it is written down. It offers analysis and gives no account of anything the Air Force did.
The standard measure of how far apart two strings are is the edit distance, being the least number of single-character insertions, deletions and substitutions that turns one into the other [Levenshtein Distance]. For strings $a$ and $b$ it is computed by the recurrence
\[d_{i,j} \;=\; \begin{cases} \max(i, j), & \min(i, j) = 0, \\[4pt] \min\bigl\{\, d_{i-1,j} + 1, \; d_{i,j-1} + 1, \; d_{i-1,j-1} + \mathbb{1}[\,a_i \neq b_j\,] \,\bigr\}, & \text{otherwise}, \end{cases} \tag{26}\]with the edit distance being the value at the far corner, where $\ell_a$ and $\ell_b$ are the lengths of the two strings. The letters $m$ and $n$ are not reused here, since they name the basic mission symbol and the design number above. For the pair in question the value is 1, since substituting B for X is the only operation required. Normalised against the longer string,
\[s(a, b) \;=\; 1 - \frac{d_{\ell_a,\, \ell_b}}{\max(\ell_a,\, \ell_b)} \;=\; 1 - \frac{1}{4} \;=\; 0.75. \tag{27}\]Three of the four characters are shared, and the three that are shared are the ones the instruction issues in sequence. Those three form the longest common subsequence, which gives a second measure that agrees with the first,
\[s_{\mathrm{LCS}}(a, b) \;=\; \frac{\bigl| \mathrm{LCS}(a, b) \bigr|}{\max(\ell_a,\, \ell_b)} \;=\; \frac{3}{4} \;=\; 0.75. \tag{28}\]The measure a drug regulator uses is its own, and the program that computes it is public. The Food and Drug Administration screens every proposed prescription drug name against the names already approved, using a program it wrote called Phonetic and Orthographic Computer Analysis, and it makes the program publicly available [Phonetic and Orthographic Computer Analysis Program] [Phonetic and Orthographic Computer Analysis, public access]. A third measure works on character bigrams, comparing the sets of adjacent letter pairs rather than the positions, so that it does not depend on aligning the two strings. The two names give
\[\mathcal{B}(\text{X-52}) = \{\,\texttt{X-},\ \texttt{-5},\ \texttt{52}\,\}, \qquad \mathcal{B}(\text{B-52}) = \{\,\texttt{B-},\ \texttt{-5},\ \texttt{52}\,\}, \tag{29}\]sharing two of three, and the Dice coefficient on those sets is
\[s_{\mathrm{Dice}}(a, b) \;=\; \frac{2 \bigl| \mathcal{B}(a) \cap \mathcal{B}(b) \bigr|} {\bigl| \mathcal{B}(a) \bigr| + \bigl| \mathcal{B}(b) \bigr|} \;=\; \frac{4}{6} \;\approx\; 0.667. \tag{30}\]Three measures, three values between 0.667 and 0.75, and not one of them is a decision.
Saying It Aloud Moves the Two Names Closer Together
If the refusal was about a spoken designation, the spoken forms are the ones that matter, and
measuring them reverses the intuitive answer. Rendered as they would be said, ex fifty two against
bee fifty two, the character edit distance is 2 over strings of
12 and 13 characters, so
That is higher than the 0.75 the written pair scores, and higher means closer. Spelling the designation out does not separate the two names. It pushes them together, because the shared part expands into two long words while the part that distinguishes them stays one short syllable at the front.
At the level of whole words the picture is the reverse again, since one token in three differs,
\[s_{\text{word}} \;=\; 1 - \frac{1}{3} \;\approx\; 0.667. \tag{32}\]So the answer depends on what you think a listener is matching, and a decision that records no measure has not said which of these it meant, or whether it meant any of them.
The Missing Threshold
Every one of the measures above is a number in the unit interval. Turning one into a refusal takes one more object, a threshold, and the rule is then
\[\text{refuse } b \quad \text{if and only if} \quad \max_{a \,\in\, \mathcal{A}} s(a, b) \;\geq\; \tau, \tag{33}\]where $\mathcal{A}$ is the set of designations already in use, $s$ is whichever measure has been adopted, and $\tau$ is where the line is drawn.
The 2006 decision supplies $b$ and it supplies the outcome. It supplies no $s$, no $\tau$ and no $\mathcal{A}$. The 2014 instruction, which finally granted the authority, supplies none of them either, and nor does its 2020 successor.
The Other Naming Authority Publishes All Three
A comparison is available, and it does not flatter the designation system. The Food and Drug Administration’s guidance on proprietary drug names states the measure, the comparison set and the thresholds, in a numbered document with a date on it [Best Practices in Developing Proprietary Names for Human Prescription Drug Products, Guidance for Industry, December 2020].
The comparison set is named. A proposed name is queried against drug reference databases, so $\mathcal{A}$ is a specific list rather than an unstated one.
The measure is named, being the combined orthographic and phonetic score the program returns.
And the thresholds are published as three bands,
\[\text{band}(s) \;=\; \begin{cases} \text{highly similar}, & s \geq 70\%, \\[2pt] \text{moderately similar}, & 55\% \leq s \leq 69\%, \\[2pt] \text{low similarity}, & s \leq 54\%, \end{cases} \tag{34}\]with a highly similar pair at greater risk of confusion and a moderately similar pair sent for further evaluation. The screening threshold itself is stated to rest on evidence, the guidance recording that the combined score of 55 percent is set on the validation work done on the algorithms rather than chosen for looking reasonable [Best Practices in Developing Proprietary Names for Human Prescription Drug Products, Guidance for Industry, December 2020].
Run the article’s own measures against those bands and the two answers differ. The bigram coefficient computed above is about 66.7 percent, which falls in the moderately similar band. The normalised edit similarity is 75 percent, which falls in the highly similar band. This is an illustration and not a result, since neither figure is the combined score that program returns, and the comparison is offered only to show that the choice of measure decides the band.
That contrast is the finding this section exists to report. One authority publishes the measure, the comparison set, the thresholds and the evidence the thresholds rest on. The other refused a designation in 2006 and recorded a phrase.
None of this proves the refusal was wrong, and none of it proves the refusal was right. What the measurement establishes is that the judgement was of a kind that can be made explicit, and was not. The literature surveyed below holds, among much else, the record of other people making this kind of judgement explicit, under published criteria, in fields where getting it wrong kills somebody.
The Contemporary Literature
| Cluster | Records |
|---|---|
| Measuring how alike two strings are | 359 |
| Names refused because another name was near them | 247 |
| Medication safety, which is where this question is studied hardest | 171 |
| Identifiers as administered objects | 147 |
| Reading a code, and the shapes of its characters | 114 |
| Confusing similarity as a legal test | 112 |
| Call signs, readback and the spoken identifier | 96 |
| Confusable sounds and words in perception and memory | 55 |
| Aviation, and the designations it actually uses | 21 |
| Human error, and the taxonomies built to describe it | 13 |
| Total | 1,335 |
Measuring how alike two strings are
The largest cluster, and it is the one the refusal actually needed. Edit distance, phonetic encoding, approximate matching, name matching, record linkage and the similarity measures built on them. AF/A8PE made a similarity judgement in 2006 and recorded no measure, no threshold and no method, and this shelf is what such a judgement looks like when somebody is required to show their working.
359 records. [Abdel Ghafour et al. 2011] [Aborot 2017] [Abraham and Raj 2014] [Afanasev and Lyashevskaya 2024] [Ahmed et al. 2022] [Aksoy et al. 2019] [Akutsu 1994] [Akutsu 1995] [Akutsu 2006] [Akutsu et al. 2006] [Akutsu et al. 2008] [Al-Bakry and Al-Rikaby 2016] [Aldwairi and Flaifel 2012] [Amir et al] [Amir et al. 2010] [Annisa Sihotang 2024] [Approximate String Matching 1994] [Peng and Mackay 2014] [Aratsu et al. 2009] [Aratsu et al. 2010] [Arslan 2006] [Arslan and Egecioglu] [Ashish et al. 2016] [Atallah et al. 2001] [Audhkhasi and Verma 2007] [Austin 1957] [Author 2026] [Ayad et al. 2016] [Aygun 2017] [Baeza-Yates and G. Navarro 1999] [Baeza-Yates and Navarro] [Baeza-Yates and Navarro 1996] [Baeza-Yates and Navarro 1997] [Baeza-Yates and Perleberg 1992] [Baeza-Yates and Perleberg 1996] [Bakar et al. 2000] [Baloi et al. 2023] [Baroni et al. 2002] [Bartolini et al. 2002] [Barton et al. 2014] [Batu et al. 2006] [Beck and Kerschbaum 2013] [Belazzougui and Venturini 2012] [Belazzougui and Venturini 2015] [Berghel et al] [Bernard and Ajah 2025] [Bille 2011] [Bille et al] [Bille et al. 2009] [Blair et al. 2021] [Boitsov 2002] [Branting 2003] [Bunke and Csirik 1995] [Bánki et al. 2023] [Calvo-Zaragoza et al. 2016] [Cantone et al. 2025] [Carbonnel and Anquetil] [Chang and Lampe 1992] [Chang and Lawler] [Chang and Lawler 1994] [Chang and Marr 1994] [Chaware and Rao 2010] [Chernyak 2017] [Chi-Chien Pan et al. 2002] [Christen 2006] [Christen and Gayler 2015] [Christopher Jaisunder et al. 2017] [Chung et al. 2011] [Ciobanu and Dinu 2014] [Cole and Hariharan 2002] [Colomer 2012] [Cormode and Muthukrishnan 2007] [Crochemore and Lecroq] [Dai and Zhao 2009] [DanishAli and Farooqui 2013a] [DanishAli and Farooqui 2013b] [Das et al. 2025] [Davuth and Kim 2013] [de la Higuera and Micó 2008] [Debbarma et al. 2014] [Degroot 2004] [Degroot 2014] [Dimov 1994] [Ding et al. 2009] [Dinh 2023] [Dong Deng et al. 2013] [Droppo and Acero 2010] [Duan et al. 2020] [El-Mabrouk and Crochemore 1996] [Essex 2019] [Fenna 1984] [Fered et al. 2026] [Ferri et al. 2018] [Fiori et al. 2021] [Fischer 1982] [Fredriksson 2003] [Fredriksson 2004] [Fredriksson 2006] [Fredriksson and Navarro 2003] [Fredriksson and Navarro 2004b] [Fredriksson and Navarro 2004a] [Gadd 1988] [Gali et al. 2019] [Galil and Giancarlo 1988] [Galil and Park 1990] [Gawrychowski 2012] [Generalized String Matching 2015] [Gewurz and Vietri 2007] [Giegerich et al. 1997] [Gong et al. 2009] [Grigor’eva 1983] [Guo et al. 2019] [Gvasalia et al. 2025] [Hall and Dowling 1980] [Hancox and Polatidis 2013] [Hanmei et al. 2019] [Heggarty et al. 2005] [Hema 2024] [Herzog et al] [Herzog et al] [Ho et al. 2017] [Holub and Melichar 2000] [Hon et al] [Howard 2020] [Hrbek and Holub 2016] [Htun Htet Htet and Sornlertlamvanich Virach 2018] [Huerta 2010] [Huynh et al. 2004] [Hyyrö 2003] [Hyyrö 2004] [Hyyrö 2005b] [Hyyrö 2005a] [Hyyrö 2008] [Hyyrö and Navarro 2002] [Hyyrö and Navarro 2004] [Ifada et al. 2023] [Jeong et al. 2014] [Jiang et al. 2013] [Jiang et al. 2014] [Jin Hwan Park] [Jokisch and Hain 2017] [Judson 2005] [Jumde and Keskar 2020] [Jupin et al. 2012] [Jupin et al. 2016] [Kaleem et al. 2014] [Kamali 2026] [Kant et al. 2020] [Karpov et al. 2023] [Kashyap and Oommen 1981] [Katsumata and Miura 2009] [Katsumata et al. 2010] [Kavros and Tzitzikas 2022] [Kessler 2005] [Khalid et al. 2022] [Khan et al. 2022] [Kianfar et al. 2018] [Kiawkaew et al. 2023] [Kim 2021] [Kim and Shawe-Taylor 1992] [Kirubakaran and Aramudhan 2018] [Kiwi et al] [Kiwi et al. 2011] [Klensin et al. 1998] [Knox 2019] [Komatsu et al. 2014] [Kondrak 2003] [Kondrak 2005] [Kondrak and Sherif 2006] [Koneru et al. 2016] [Kontorovich and Trachtenberg 2012] [Korotkov 2010] [Krauthgamer 2013] [Kuboi et al. 2014] [Kucherov et al. 2014] [Kucherov et al. 2016] [Kunchukuttan and Bhattacharyya 2021] [Kunchukuttan et al. 2018] [Kysela 2018] [Kärkkäinen and Na 2007] [Kärkkäinen et al. 2000] [Ladefoged 1969] [LaMonica 2014] [Landau and Vishkin 1989] [Li et al. 2013] [Li et al. 2023] [Libovický and Fraser 2022] [Lin and Chen 2002] [Lin and Wang 2011] [Lin et al. 2014a] [Lisbach 2011a] [Lisbach 2011c] [Lisbach 2011b] [Lisbach 2011d] [Lisbach and Meyer 2013a] [Lisbach and Meyer 2013c] [Lisbach and Meyer 2013d] [Lisbach and Meyer 2013b] [Liu et al. 2007] [Liu et al. 2014] [Liu et al. 2025b] [Loo 2014] [Lopresti and Tomkins 1997] [Lopresti and Wilfong] [Lu et al. 2013] [Lu et al. 2014] [Luján-Mora and Palomar 2001] [Man et al. 2013] [Martinek et al. 2007] [Marzal et al. 2003] [Matsumoto et al] [Matveev] [McCallum et al. 2005] [McCarley 2009] [McClanahan and Li 2024] [Mednis and Aurich 2012] [Melichar 1995] [Mergen 2022] [Michailidis and Margaritis] [Mishra et al. 2013] [Mittal et al. 2014] [Mohammed and Aliwy 2024] [Mohd Anuar et al. 2014] [Mollineda et al] [Montalvo et al. 2012] [Moreau et al. 2008] [Morris et al. 2026] [Mutalib and Noah 2011] [Muthukrishnan] [Myers 1998] [Nakagawa et al. 2018] [Nakano 2012] [Nakano 2013] [Narita et al. 2012] [Navarro 2001] [Navarro 2008] [Navarro 2016] [Navarro and Baeza-Yates 1999a] [Navarro and Baeza-Yates 1999b] [Navarro and Chávez 2006] [Navarro and Fredriksson 2004] [Navarro et al] [Navarro¹² 1997a] [Navarro¹² 1997b] [Nguyen and Conrad 2014] [Nguyen and Conrad 2015] [Novitra 2023] [Ohtake et al. 2004] [Owolabi and Ferguson 1988] [Owolabi and McGregor 1988] [Vinod-prasad 2016] [Howard 2018] [Papamichail and Papamichail 2009] [Paramonov et al. 2016] [Perbandingan Algoritma Edit Distance 2014] [Petty et al. 2022] [Pevzner and Waterman] [Phoophuangpairoj et al. 2024] [Phuduhudu et al. 2025] [Piskorski et al. 2009] [Pissis and Retha 2015] [Policriti and Prezza 2015] [Post and Toussaint 2011] [Pouliquen 2008] [Rama and Borin 2015] [Rani and Singh 2018] [Revesz 2021] [Ribeiro et al. 2025] [Rice et al. 1997] [Rico-Juan et al. 2020] [Ristad and Yianilos 1998] [Rochmawati and Kusumaningrum 2016] [Russo et al] [Russo et al. 2008] [Russo et al. 2009] [Sadeh] [Saikrishna and Ray 2013] [Salmela and Tarhio 2010] [Salmela et al. 2009] [Chaware and Rao 2011] [Sangurai et al. 2024] [Sariyar 2027] [Sastry and Ranganathan] [Sauleau et al. 2005] [Schraagen 2011] [Schumacher et al. 2023] [ShabnamHasan et al. 2015] [Shah and Singh 2014b] [Shah and Singh 2014a] [Shaikh et al. 2011] [Shang and Merrettal 1996] [Shapira and Storer 2003] [Shelake and Shekokar 2022] [Siew 2018] [Sihotang 2023] [Simpson et al. 2010] [Sitbon et al. 2007] [Smith and Pierzchala] [Snae and Brueckner 2009] [Stanchev et al. 2019] [Sukharev et al. 2014] [Sun and Wang 2018] [Sung 2008] [Sung 2016] [Sung-Hwan Kim and Hwan-Gue Cho 2017] [Susik 2017] [Sutinen and Tarhio 1996] [Tagliacozzo et al. 1970] [Tai 2018] [Takabatake et al. 2014] [Takabatake et al. 2016] [Takasu] [Takeda 2001] [Tarhio and Ukkonen 1990] [Tarhio and Ukkonen 1993] [Telsang et al. 2025] [Ternikov 2024] [The Role of Orthographic 2019] [Thumsuwan et al. 2024] [Tissot and Dobson 2019] [Top et al. 2007] [Treeratpituk and Giles 2021] [Tseng and Chen 2016] [Tsur 2010] [Tsuruoka et al. 2007] [Ukkonen] [Ukkonen 1983] [Ukkonen 1985] [Ukkonen 1992] [Ukkonen 1993] [Ukkonen and Wood 1993] [Uryupina 2004] [Vaiwsri et al. 2024] [Valarakos et al. 2004] [Van Court and Herbordt] [Van Court and Herbordt 2007] [Varol and Talburt 2011] [Vilares et al. 2004] [Wang et al. 2011] [Wang et al. 2014] [Watcharapinchai and Rujikietgumjorn 2017] [Wieling et al. 2012] [Winkler 2014] [Winter et al. 2020] [Kang 2015] [Wright 1994] [Yan et al. 2026] [Yang et al. 2022] [Yarkoni et al. 2008] [Yencken Lars and Baldwin Timothy 2008] [Yu et al. 2016] [Yuan et al. 2014] [Žgank and Kacic 2012] [Zhang and Zhang 2020] [Zhang et al. 2014] [Zhang et al. 2017] [Zhou et al. 2006] [Zobel and Dart 1996] [Ögeyik 2022]
Most of it is algorithmics rather than judgement. 166 of its 359 titles name string matching and 80 name edit distance or Levenshtein, against 54 that name a name. The measures are mature, and what the cluster rarely asks is where a measure should be cut to turn a score into a decision, which is the subject of Thin Subjects below.
Names refused because another name was near them
The same administrative act, performed somewhere it is studied. Look-alike and sound-alike names, proprietary against nonproprietary naming, and the refusal of a proposed name because an approved one is near it. A drug regulator does what the Air Force did to X-52A, and does it against criteria it publishes [Best Practices in Developing Proprietary Names for Human Prescription Drug Products, Guidance for Industry, December 2020].
247 records. [Nabeta et al. 2011] [Addressing LASA Medication Errors 2026] [Adiana et al. 2026] [Ahuja and Ahuja 2024] [Alsalameen et al. 2024] [Altbach 2015] [andNa 1996] [andNa 1997] [andNa 2004] [andNa 2005] [andNa 2006] [Anggiratih 2025] [Are Electronic Prescribing Systems 2026] [Aronson 1995] [Aschenbrenner 2025a] [Aschenbrenner 2025b] [Assessment of Look-Alike Sound-Alike 2020] [Baker 2002] [Balabanis and Craven 1997] [Balashov and Nikiforov 2019] [Balocco et al. 2025] [Bansal et al. 2026] [Basco et al. 2010] [Basco et al. 2016] [Ben Cheikha et al. 2024] [Benito Fernández et al. 2026] [Beyea 2007] [Bhat and Gutzwiller 2026] [Bonner 2020] [Boring 1997] [Brauneis and Heald 2010] [Brodell 1997] [Bryan] [Bryan et al. 2020] [Buckley 1980] [Burt et al. 2017] [Carney 2008] [Carney et al. 2011] [Carothers 1999] [Challenges in Drug Identification 2026] [Chan et al. 2018] [Chanakit 2013] [Chen et al. 2024] [Cheng et al. 2018b] [Chiche et al. 2008] [Ciociano and Bagnasco 2013] [Clinical Consequences of Look-Alike 2026] [Cocoros et al. 2019] [Coding of Adverse Events 2025] [Cohen 2000b] [Cohen 2003] [Cohen 2004a] [Cohen 2004b] [Cohen 2005] [Cohen 2006] [Cohen 2008] [Cohen and Davis 1992] [Cohen and Smetzer 2010a] [Cohen and Smetzer 2010b] [Cohen and Smetzer 2018] [Computer Algorithm Targets Possible 2017] [Confusing Drug Names 1985] [Dasopang et al. 2022] [Davis 1999] [Dealing With Look-Alike Sound-Alike 2026] [DeHenau et al. 2016] [Dembicki 1967] [Dhande et al. 2021] [Dispensing Errors/drug Name Confusion 2018] [Dixit 2014] [Dolle and Rovnov 2017] [Dosunmu and Adisa 2025] [Dowling et al. 2019] [DRUG NAMES 1964] [Drug Names That Look 1979] [E.J. 1918] [Elmzughi et al. 2025] [Emmerton and Rizk 2011] [Emmerton et al. 2020] [Faure 2018] [Ferber and Weitz 1960] [Festa et al. 2021] [Filik et al. 2004] [Filik et al. 2006] [Filik et al. 2010] [Filik et al. 2019] [Fraser 1980] [Galanter et al. 2014] [George 2023] [Hachemi et al. 2024] [Haertzen and Ross 1980] [Hamad Abdelaziz et al. 2024] [Hampton 2011] [Her and Toh 2019] [Hilton 1980] [Hisa 1996] [Hoffman and Proulx 2003] [Howard et al. 2000] [Hristina Viktorova Lebanova 2012] [Hussey 1974] [Identical or Confusingly Similar] [Integrated Strategies for Preventing 2026] [Introduction to Look-Alike Sound-Alike 2026] [Jongprasithporn et al. 2018] [Joshi et al. 2007] [Karakoyun et al. 2024] [Karet 2023] [Kelling 2017] [Kim and Lim 2019] [Kondrak and Dorr 2004] [Kondrak and Dorr 2006] [Kovacic and Chambers 2010] [Kronrod and Lowrey 2016] [Kundig 2011] [Lakoan et al. 2024] [Lambert 1997] [Lambert et al. 1999] [Lambert et al. 2001] [Lambert et al. 2002] [Lambert et al. 2003b] [Lambert et al. 2003a] [Lambert et al. 2005] [Lambert et al. 2015a] [Lambert et al. 2015b] [Lau 2001] [Leslie 2026] [Levien 2006] [Lewis 1979] [Lewis and Blackstone 1982] [Lilley and Guanci 1997a] [Lilley and Guanci 1997b] [Lilley and Guanci 1997c] [Liu et al. 2019] [Liu et al. 2025a] [Liu et al. 2026] [Look-Alike and Sound-Alike Drugs 1976] [Look-Alike and Sound-Alike Medication 1997] [Look-Alike Sound-Alike in Dietary 2026] [Look-Alike Sound-Alike Medication Errors 2026a] [Look-Alike Sound-Alike Medication Errors 2026c] [Look-Alike Sound-Alike Medication Errors 2026b] [Lévesque et al. 1991] [Mamunuwa et al. 2023] [Marovino et al. 2022] [McCoy 2005] [Mhiri et al. 2022] [MHRA 2018] [Michelet-Huot et al. 2017] [Miftahurrozik 2023] [Millán-Hernández et al. 2020] [Milton et al. 2015] [Moini 2025] [Monograph of Look-Alike Sound-Alike 2026] [More on Drug-Name Confusion 1995] [Mostafa et al. 2021] [Muchu 2024] [Muhlis et al. 2019] [Mukherjee et al. 2025] [Munshi et al. 2019] [Mursiti et al. 2022] [Nagamotoo et al. 2022] [Nagata et al. 2014] [Naik et al. 2009] [Naunton et al. 2015] [Nchinech et al. 2023] [Neelakantan et al. 2024] [Oerthel et al. 2020] [Ohtani et al. 2006] [Oral Liquid Medications 2026] [Ostini et al. 2012] [Paramathma 2015] [Perveen 2026] [Phipps 2025] [Practice to Enhance Identification] [Prakash 2010] [Predicting Drug Name Confusion 1997] [Pronunciation of Drug Names 1970] [Propp 2000] [R. g. d. 1926] [Rahman and Parvin 2015] [Rash-Foanio et al. 2017] [Rastogi 2015] [Rataboli et al. 2015] [Reines 2005] [Rider et al. 2019] [Rigan Ramadhani and Usviany 2024] [Robins 2001] [Ruutiainen et al. 2021] [Ryan et al. 2025] [Sagawa et al. 2024] [Samudra et al. 2022] [Sanders and Shaw 1991] [Sardana and Rose Mathachan 2023] [Schulmeister 2006] [Seoane-Vazquez et al. 2017] [Shah et al. 2017] [Shastay 2023] [Siddiqui 2020] [Similar Drug Names 2004] [Simpson 1979] [Singh and Singh 2017] [Sound-Alike Drug Names Produce 2005] [Stewart 2005] [Stiftung Für Patientensicherheit Schweiz 2010] [Stockbridge and Taylor 2015] [Study of Deviant Use 2020] [Supapaan 2026] [Supapaan et al. 2024a] [Supapaan et al. 2024b] [Svahn 1978] [Tamaki et al. 2012] [Tan and Choo 2023] [Teakel 1999] [Teplitsky 1977] [Teplitsky 1978] [Teplitsky 1979b] [Teplitsky 1979a] [Teplitsky 1980] [Teplitsky 1981] [Teplitsky 1982] [Teplitsky 1984] [Teplitsky 1992] [Teplitsky 1994] [Teplitsky 2001] [Tfeplitsky 1986] [Thakkar and Billa 2013] [The Prescription and Drug 2020] [The Role of Typography 2006] [Tradename. Company. Similarity 1912] [Tranchard et al. 2016] [Trbovich and Hyland 2016] [Tseng et al. 2016] [Tu 2019] [Tuohy and Paparella 2005] [Vázquez et al. 2020] [Wang] [Wang et al. 2021] [Weitz 1960] [Wong 2014] [Yoshikawa et al. 2023] [Young 2000] [Yu et al. 2020] [Zacher et al. 2018] [Zaijul et al. 2026] [Zaini et al. 2026] [Zhao et al. 2018] [Zhu et al. 2025]
147 of its 247 titles name look-alike or sound-alike medicines, which is the pharmacist’s term for exactly the hazard the registry recorded in one clause about the B-52.
Medication safety, which is where this question is studied hardest
A discipline built around counting the consequences of a confusable name. Medication error, its prevention, and above all the reporting systems built to count it. The pharmacology is not the subject and none of it is cited for any claim here. What is relevant is that an entire safety literature exists on the judgement the Air Force made without recording one.
171 records. [Abdulrouf et al. 2019] [Abuelsoud 2018] [Agoglia et al. 2024] [Tumuhaise and Namukwaya 2026] [Aljedaani et al. 2025] [Alsaif 2018] [Alshaikh et al. 2013] [Anderson et al. 2009] [andNa 1985] [andNa 1993] [andNa 1995] [andNa 1999] [andNa 2004] [andNa 2005] [andNa 2005] [andNa 2011] [Antonow et al. 2000] [Arora 2020] [Aydemi̇r and Esenkaya 2023] [Baghcheghi and Koohestani 2025] [Bailey] [Balan and Irawati 2026] [Barriers to Reporting Medication 2009] [Bassi et al. 2025] [Bc et al. 2015] [Birdwell et al. 2003] [Blum et al. 1988] [Boyer et al. 2009] [Brabcová et al. 2014] [Byrne and Bury 2018] [Cavell et al. 2001] [Chalasani and Madhan 2017] [Chalasani et al. 2018] [Chanyagorn et al. 2016] [Chauhan and Gaur 2025] [Cohen 1996] [Costello et al. 2007] [Crossman 2009] [Cunningham 2012] [Cusano et al. 2008] [Davis 2000a] [Davis 2000b] [Dejos 2021] [Dickens et al. 2007] [Dodek et al. 2010] [Dyab et al. 2018] [Edgar et al. 1994] [ElLithy et al. 2023] [Elnour et al. 2007] [Elvretta et al. 2021] [Fayaz-Bakhsh and Khezri 2014] [Folli et al. 1987] [Friedman 2005] [Furukawa et al. 2003] [George et al. 2018] [Goedecke et al. 2016] [Grant 2017] [Grindrod et al. 2002] [Grissinger et al. 2019] [Guo et al. 2025] [Hajibabaee et al. 2014] [Handler et al. 2004] [Hartnell et al. 2012] [Hauk 2018] [Hayati and Piramoon 2023] [Hicks and Becker 2006] [Holmström et al. 2012] [Holmström et al. 2015] [Horsham 2015] [Hritz et al. 2002] [Hung et al. 2015] [Hung et al. 2016] [Hutchinson et al. 2015] [Jae Jeong 2017] [Jember et al. 2018] [Joiner 1994] [Keefer et al. 2017] [Kennedy and Littenberg 2004] [Keshtkar et al. 2023] [Kim 2012] [Kim 2013b] [Kim 2016] [Kim and McPherson 2012] [Kim et al. 2022] [Koo 2012] [Kuitunen et al. 2023] [Lee 2016] [Tidman 2022] [Mansour and AL-Gethami 2013] [Maidment and Thorn 2005] [Manik 2020] [Marappa and Reha Mallika 2020] [Masmali et al. 2020] [Massah et al. 2021] [Mathew et al. 2021] [McArdle et al. 2003] [McKaig et al. 2014] [McNally and Sunderland 1998] [Khan 2021] [Medication Error Prevention 2004] [Medication Error Prevention 2017] [Devine 2012] [Medication Error Reporting System 2008] [Medication Safety and Error 2020] [Mehanna et al. 2024] [Miller 2006] [Miller 2007] [Mohanty 2016] [Moureaud et al. 2020] [Mukriani 2026] [Natalia et al. 2026] [Ni et al. 2023] [Novi Yulianti et al. 2019] [Nydert et al. 2020] [Ogamba et al. 2023] [Ohunyon et al. 2026] [Pal et al. 2025] [Panca et al. 2018] [Paparella 2008] [Patrician and Brosch 2009] [Perez 2026] [Peshek and Cubera 2004] [Naif H. Helman et al. 2020] [Phillips 2001] [Phillips 2014] [Poornima et al. 2015] [Rached] [Rask et al. 2006] [Rawat 2008] [Richmond 2011] [Ringseis and Caird 1995] [Rinke et al. 2010] [Rutledge et al. 2018] [Saad et al. 2025] [Saada 2023] [Saada et al. 2023] [Samaei et al. 2017] [Samsiah et al. 2016b] [Samsiah et al. 2016a] [Samundeeswari 2018] [Sandlin 2008] [Santos 2020] [Sarvadikar et al. 2010] [Savage et al. 2005] [Scheirman 2001] [Schlosser et al. 2025] [Sears and Generali 2005] [Senft 2007] [김민정 and SeongSook Jun 2016] [Shanty] [Shiima et al. 2022] [Shivanand H Honakeri et al. 2026] [Smetzer 2001] [Smetzer and Cohen 2007] [Smith et al. 2006] [Statutory Protection for Medication-Error 2019] [Stump 2000] [Sulastri et al. 2023] [Thabet et al. 2022] [The Pharmacy Technician’s Role 2014] [Tisdale 1986] [Tumuhaise and Namukwaya 2024] [Utilisation of Neonatal Medication 2018] [Vallabhaneni et al. 2023] [Weant et al. 2007] [Weant et al. 2010] [Wertheimer 2014] [Witt et al. 2024] [Wysocki et al. 2022] [Yoo and Keshavarzi 2020] [Zellmer 1993]
114 of its 171 titles concern the reporting of errors, which is the same instrument the civil aviation authority used to count call sign confusion.
Identifiers as administered objects
Identifiers considered as things somebody has to issue, keep and retire. Namespaces, numbering schemes, part numbering, registries and unique identifier standards. The designation system is one of these, and many of the titles are other issuers’ published rules for assignment and registration.
147 records. [A Syntactic Namespace 2011] [J-P. Evain 2008] [Adamson and Williams 2016] [Aerospace. Part numbering for] [alves Da Silva et al 2015] [Anderson 1970] [Apodaca 2010] [Appendix C 2003] [Appendix C. Numbering System 1974] [Arunachalam and Madhan 2021] [Assaker et al. 2020] [Author Name Processing 1983] [Bar coding. Unique identifier] [Beale and Rajwany 2022] [Berendsohn 2023] [Bessho et al. 2007] [Best and Walsh 2001a] [Best and Walsh 2001b] [Bolton et al. 2026] [Campbell and Tschofenig 2012] [Carpenter and Joffe 2011] [Celko 2010] [Cerf 1990] [Chandra 2011] [Chaturvedi et al. 2020] [Chen and Yuan 2011] [Cheng et al] [Chrétien 2026] [Cloud 1998c] [Cloud 1998b] [Cloud 1998a] [Cloud 1998d] [Coates et al. 2001] [Comer 2025] [Copper and copper alloys] [Cosma 2025] [Daigle et al. 1999] [Dawodu et al. 2023] [Definition identifier URNs in] [Development of a 14-Digit 1999] [Dhiman 2015] [Digital token identifier DTI] [Document management. Portable Document] [Earth-moving machinery. Product identification] [Elsmore 1986] [Embossed credit cards. Specifications] [Fenner 2010c] [Fenner 2010b] [Fenner 2010a] [Financial services � Natural] [Financial services � Unique] [Financial services. Legal entity] [Financial services. Unique transaction] [Francis 2013] [Gahrns and Newman 1998] [Geographic information. Place Identifier] [Goth 2009] [Gschneider 1976] [Harrison] [Health informatics. Health cards] [Humphrey and Barnard 1998] [Identity Crisis 2008] [World Bank Group 2016] [Inecik et al. 2026] [Information technology. Unique identifiers] [Ishikawa 2012] [Ivory and Beale 2025] [Jacobson 2018] [Jethanandani 2016] [Jethanandani and Reina Ortega 2019] [Karas 2016] [Klensin and Hakala 2017] [Kumari 2014] [Leach et al. 2005] [Lehnert et al. 2019] [Lemieux 2014] [Lemieux 2016] [Machine readable cards. Health] [McAlpin 2003] [Meadows and Koester 2015] [Mealling 2000] [Mealling 2001] [Mealling 2004] [Menouar et al. 2011] [Metals and Alloys 2017] [Metals and Alloys in 2025] [Moats 1999] [Narten and Johnson 2011] [Naval Material Command Washington DC 1980] [Nesbitt and Murphy 2022] [Nomenclature, Aircraft Hydraulic and] [Nomenclature, Aircraft Oxygen Equipment] [None 2021] [Numbering System for Designating] [Numbering System for Food 2001] [Numbering System for Multiple] [Numbering System for Reamers] [Numbering System for Single] [Numbering System for Single] [Numbering System for Standard] [Numbering System for Standard] [Numbering System for Taps] [Olden et al. 2016] [Omoro et al. 2018] [Oppolzer and Bestak] [Oppolzer and Bestak 2012a] [Oppolzer and Bestak 2012c] [Oppolzer and Bestak 2012b] [Oppolzer and Bestak 2013] [Page 2008] [Palanivelrajan and Alli 2018] [Pang-Yen Hsu 2006] [Patel 2023] [Pebrianto 2022] [Polk 2014] [Polychronakos 2012] [Position Terms and Numbering] [Practice for Numbering Metals] [Product Identification Numbering System] [Recommended Part Numbering Guidelines] [Riva and Pesole 2009] [SAE Numbering System for] [Saint-Andre 2013] [Securities and related financial] [Sensmeier and Carroll 2021] [Soman et al. 2015] [Sorathia 2015] [Soukup and Hammond 1982] [Specification for international securities] [Specification for key numbering] [ST 330:2004 2004] [Suzuki 2001] [Kalin and Molina 2007] [Tea 2021] [Tesink and Fox 2005] [Tessman 2005] [The Unified Numbering System 2010] [Thomas 2017] [Tracked Changes. Earth-moving machinery] [Trpkoska and Vukikjevikj 2022] [Uniform Dash Numbering System] [Unique Digital Media Identifier] [Asian Development Bank 2018] [Unique Material Identifier UMID] [Wackerow 2024] [Wold 2017] [Zhao et al. 2014]
Reading a code, and the shapes of its characters
The identifier as a thing seen rather than heard. Legibility, typography, character and digit confusion, alphanumeric codes and labelling. The instruction’s only written anti-confusion rule for a designator lives in this cluster, being the prohibition on the series letters I and O because they resemble the digits 1 and 0.
114 records. [Adhe et al. 2023] [Alexeeva 2023] [AlJassmi and Perea 2024] [Alwitt 1973] [Aten et al. 2002] [Barbre and Price 1983] [Barnard et al. 1978] [Bell 1967] [Bernard et al. 2001] [Bhise and Hammoudeh 2004] [Brown and Goodman 1983] [Butterbaugh 1981] [Butterbaugh and Rockwell 1982] [Cai 2011] [Cai 2017] [Cardosi 1986] [Chapanis et al] [Chaparro et al. 2006] [Charness and Dijkstra 1999] [Chastain 1982] [Chrysler et al. 2001] [Cohen 2000a] [Colby 1992] [Dorris and Davis 2003] [Duncan and Konz 1974] [Dunn-Rankin et al. 1968] [Effects of Perceptual Similarity 2005] [Eggemeier et al. 1990] [Erdmann and Neal 1968] [Fell and Laughery 1969] [Fox et al. 2008] [Garvey et al. 2001] [Godwin et al. 2013] [Gonzales et al. 2018] [Greco et al. 2008] [Greene et al. 1994] [Greene et al. 1995] [Gunderson et al. 1991] [Harris et al. 2013] [Hemingway and Erickson 1969] [Ho et al. 2016] [Hsiao and Cheung 2015] [Kelso 1965] [Kim et al. 2000] [Kimura et al. 2020] [Kinney et al. 1966] [Kinoshita et al. 2021] [Koehler et al. 1994] [Kovesdi 2022] [Laarni 1999] [Legibility of Colored Print 2006] [Li and Liu 2013] [Liang et al. 2023] [Lippert 1963] [Lippert and Lee 1965] [Little 1973] [Loucks 1944] [McGlannan and Thorson 1976] [McLean 1965] [McTyre 1982] [McTyre and Frommer 1985] [Menneer et al. 2014] [Micrographics. Alphanumeric computer output] [Moody] [Morrison and Rayner 1985] [Mustonen et al. 2004] [Nilsson and Kaiserman 2004] [Olson and Bernstein 1979] [Pastoor 1990] [Petrun et al. 1985] [Phonetic features, vocalisation and 2019] [Plaisant and Sears 1992] [Podgorny and Garner 1979] [Preczewski and Fisher 1990] [Rasmussen et al. 1980] [Riley and Glenn 1996] [Roca et al. 2018] [Rose and Cornog 1964] [Rose and Cornog 1967] [Sawyer et al. 2017] [Schieber 1994] [Schieber 1998] [Schieber 2005] [Schieber and Kline 1994] [Schnell and Zwahlen 1999] [Serrano et al. 2016] [Sheedy et al. 2005] [Showman 1967] [Shurtleff 1966] [Shurtleff and Wuersch 1979] [Sivak et al. 1981] [Smith 1979] [Snyder 1979] [Sohn et al. 2024] [Some Factors Affecting Legibility 1981] [Spiker and Rogers 1984] [Spoto and Babu 1989] [Starrfelt et al. 2015] [Tullis 1981] [Tullis 1983] [van Nes 1988] [Van Nes and Bouma 1980] [Vartabedian 1970] [Vaughan et al. 1982] [Wang et al. 2024] [Ward et al. 1995] [West 1954] [Wetzel and Hernandez 2010] [Williams 1967] [Wolf 1982] [Wolff 1971] [Young et al. 1992] [Zineddin et al. 2003] [Zwaga 1979]
Confusing similarity as a legal test
The same judgement made where it has to be defended. Trademark, likelihood of confusion, passing off and consumer confusion. A court deciding whether two marks are confusingly similar is doing what AF/A8PE did, and the instruction itself sends popular names to a trademark search while sending design numbers to nobody.
112 records. [Assessment of the Risk 2022] [Assessment of the Similarity 2023] [Austin 2008] [Bartholomew 2025] [Bartow 2005] [Basire and Darnand 2017] [Batty 2025] [Batykov 2020] [Bayrak 2026] [Beebe 2006] [Beebe and Fromer 2020] [Beebe et al. 2026b] [Beebe et al. 2026a] [Blum et al. 2009] [Boling 2015] [Brengman et al. 2001] [Buerke 2016] [Bunker* 2015] [Carraway 1994] [Celik and Koc 2026] [Chiampi Ohly 2024] [Choi 2026] [Dornis 2017] [Eko 1998] [Empirical Studies of Trademark 2019] [Fhima 2026] [Fhima 2024] [Fhima and Denvir 2015] [Fhima and Gangjee 2019a] [Fhima and Gangjee 2019b] [Fhima and Gangjee 2019c] [Foxman et al. 1990] [Foxman et al. 1992] [Fritch 2006] [Bone 2021] [Gao and Wang 2018] [Giannino 2022] [Giordani 2025] [Greene 2003] [Greene 2006] [Guvenkaya 2026] [Jacoby 2000] [Jiang 2024] [Jintcharadze 2024] [Kaeding 1992] [Kaur 2026] [Kearny and Mitchell 2001] [Kim 2024] [Kuncheria 2008] [Laustsen 2019b] [Laustsen 2019a] [Laustsen 2019c] [Laustsen 2020] [Lee 2008] [Leek and Kun 2006] [Lemley and McKenna 2026] [Levy 2018] [Li 2018] [Likelihood of Confusion between 2022] [Likelihood of Confusion 2020] [Lutzker 2013] [Liu and Cheng 2019] [Loken et al. 1986] [Lomax et al. 1999] [Lou 2024] [Lunsford 1949] [Lutzker 2002] [Maksurov 2021] [McCutcheon 2023] [Miaoulis and D’Amato 1978] [Mishra et al. 2026] [Mitchell and Kearney 2002] [Mitchell and Papavassiliou 1999] [Mixed Messages 2024] [Moon 2018] [Morrin and Jacoby 2000] [Mupangavanhu and Vuke 2023] [Nadeau 1937] [No Cumulative Protection against 2023] [No Likelihood of Confusion 2025] [Nowak-Gruca 2018] [Ortolani 2009] [Peterson et al. 2024] [Radack 2002] [Reichert 2025] [Reichert 2026a] [Reichert 2026d] [Reichert 2026c] [Reichert 2026e] [Reichert 2026b] [Ritchie 2026] [Salim 2026] [Schweizer 2005b] [Schweizer 2005d] [Schweizer 2005c] [Schweizer 2005e] [Schweizer 2005a] [Scott 2013] [Sheff 2024] [Shiu 2021] [Strauch 2006] [Chen and ITing Cheng 2012] [Thouvenin et al. 2025] [Trade-Mark Registration. Similarity 1938] [Walsh 2023] [Wang 2024] [Wang 2025] [Yash 2020] [Zeisel and Kaye 1997] [Zhang and Cui 2022] [Zhou 2024b] [Zhou 2024a]
37 of its 112 titles name the likelihood of confusion, the test by which a court records, in a reasoned judgement, the comparison the designation office did not record.
Call signs, readback and the spoken identifier
The channel the X-52 would have travelled down. Call sign confusion, readback and hearback, radiotelephony phraseology, the phonetic alphabet and pilot-controller communication. This is the cluster nearest the reason actually given for the C-16 skip, which was recorded as concern about confusing an aircraft with the F-16 during the stress of high combat radio traffic.
96 records. [A Fused Situational Awareness 2025] [Monan 1983] [Allott 2016] [An error-resistant linguistic protocol for air traffic control] [Morrow et al. 1990] [Andrade 2023] [Aragão and Scaramucci 2020] [Blatt et al. 2022] [Bogush and Kovtun 2019] [Borowska 2025] [Boschen and Jones] [Brammer 2003] [Brown 2004] [Busch and King 1964] [Chen 2016] [Cheng et al. 2018a] [Chung 2026] [Clark and Williams 2020] [Corps Of Engineers Washington Dc 1986] [Dai 2022] [Pranoto and Susanto 2024] [DaPolito et al. 1989] [Air Force Instruction 33-217 1997] [Design of the Teaching 2024] [Digital Voice Communication Systems 2008] [Drayton] [Drayton and Coxhead 2023] [Eier and Kampichler 2026] [Falzon 2009] [Giolas et al. 1971] [Giolas et al. 1973] [Glushanytsia 2020] [Guclu 2017] [Hamzah et al. 2022] [Huang and Wang 2015] [Improved Air-Traffic Control Voice-Communications 2005] [Lees and Williamson 2013a] [Ishihara and Lee 2021] [Jia and Li 2022] [Jia et al. 2017] [Jia et al. 2018] [Johnson 1994] [Kerpatenko et al. 2024] [Kim 2013a] [Kim 2023] [Kocour et al. 2021] [Lees and Williamson 2020] [Lees and Williamson 2022] [Lombardi et al. 2024] [Lu et al. 2016] [Lynn] [Manning et al. 2002] [Mattox 1990] [Moe 1970] [Montalyo and Lebacqz 1994] [Monteiro 2022] [Morrow et al. 1993] [Morrow et al. 1994] [Morrow and Lebacqz 1994] [Murry 1970] [Neely 1956] [Nitayaphorn] [Osipova 2016] [Pan et al. 2025] [Pellegrini et al. 2019] [Pidlubna 2019] [Pilot-Controller Communication 2020] [Pilot-Controller Communication Problems 2016] [Prokhozhay 2011] [Lees and Williamson 2013b] [Radul 2025] [Rakas and Yin 2005] [Rakas et al. 2022] [Rakas et al. 2023] [Rakas et al. 2024] [Rosenshine 1968] [Rosmayanti et al. 2024] [Sadler et al. 2023] [Shen and Jia 2025] [Shetty et al. 2022] [Siti Fitriani 2021] [Skaltsas et al. 2011] [Skaltsas et al. 2013] [Smith 2008] [Stahel 2008] [Stuntz 1963] [Tavares Monteiro] [The Communicative Aspect 2023] [Tuncal 2026] [Vallioor et al. 2025] [Xiang et al. 2012] [yanqing et al 2025] [Jae-Yun and Choi 2023] [Yuniar et al. 2024] [Zhu and Ma 2015] [Zuluaga-Gomez et al. 2020]
It is mostly a literature of language rather than of names. 41 of its 96 titles name radiotelephony, much of it aviation English and phraseology, against ten that name a call sign.
Confusable sounds and words in perception and memory
How listeners and readers confuse what they hear and read. Confusion matrices of speech sounds, acoustic confusion in short-term memory, and the effect of similar letters, sounds and lexical neighbours on the recognition and recall of words. The section headed Saying It Aloud asks what a listener is matching, and these are the experiments that measure it.
55 records. [Aguasvivas et al. 2021] [Allington 1977] [Andrews 1997] [Baddeley 1971] [Bisson 2024] [Brochhagen et al. 2025] [Bruder and Silverman 1972] [Burt and Porter 2022] [Cebrian et al. 2025] [Clopper et al. 2010] [Corter 1987] [Cutler 2005] [Duñabeitia et al. 2007] [Frances et al. 2020] [Frances et al. 2021] [Frances et al. 2022] [Hacquard and Walter 2003] [Hall and Hume 2013] [Han and Oh 2018] [Hartmann and Fosler-Lussier 2009] [Hashem 2025] [Hershenson and Ryder 1982] [Hout et al. 2023] [Jani et al. 2015] [Kang and Cohen 2016] [Khan 2013] [Kim et al. 2021] [Klassen 2022] [Lee and Taft 2010] [Lin et al. 2014b] [Lupker 1982] [Manning and Shofner 1991] [Morgan et al. 1973] [Morris and Still 2012] [Moser et al. 1961] [Murray 1968] [Nelson and Borden 1973] [Nozawa and Wayland 2025] [Pelamatti et al. 1983] [Peressotti et al. 2003] [Post and Carrecker 2002] [Room 2013] [Scarborough 2003b] [Scarborough 2003a] [Scott and Baddeley 1969] [Sergent 1983] [Kinoshita and Lupker 2004] [Weisenberger 1996] [Westbury and Yang 2024] [Yang and Chen 2026] [Yencken and Baldwin 2008] [Yoneyama 2001] [Yuan and Shih 2004] [Zhang and Osth 2024] [Zhou et al. 2023]
Aviation, and the designations it actually uses
Aviation safety reporting, cockpit speech intelligibility, controller-pilot data link communication, aircraft identification training and two flight reports on the aircraft that received X-53A. Not one record takes aircraft designation as a subject in its own right. The literature of why the X-52 was refused lies almost entirely outside aircraft designation, and an article in a series about aeroplanes should say so rather than pad this row.
21 records. [Bergeron 1983] [Bogunenko et al. 2010] [Chan and Simpson 1990] [Connell and Reynard 1993] [Corrie and Corrie 1997] [Cui and Liu 2019] [Clarke et al. 2005] [Gurtov et al. 2018] [Subalakshmi 2025] [Khan et al. 2021] [Kristanto and Indriyanto 2024] [Lehto et al. 2021] [Mackintosh et al. 1999] [NASA Aviation Safety Reporting 1978] [NASA Aviation Safety Reporting 1980] [O’Leary and Srivastava 2012] [Orye et al. 2023] [Rankin and Mattson] [Stanford and Homan 1990] [Lizotte and Allen 2007] [Vicory 1968]
Human error, and the taxonomies built to describe it
Small, and small for a reason worth stating. Error taxonomies, slips and lapses, human error identification and human reliability. The cluster is small because the partition counts each record once, so a paper about call sign error is counted with call signs and a paper about medication error with medication.
13 records. [Butterbaugh 1982] [5Chapter Human Error Identification 2009] [Dekker 2017] [Hartwig et al. 1991] [Hull 1976] [Human Error Identification 2009] [Human Error Identification 2017] [Human Error in Medication 2003] [Human-Error Identification in Human-Computer 2007] [Human-Error Identification in Human 2009] [Sankaran and Rajkumar 2016] [Task Analysis for Error 1992] [Williamson 2009]
Where the Framing Breaks Down
The series framing assumes an aeroplane, and this article has none. Every canonical section that asks about sizing, systems, flight or flight data returns the same answer here, that the number never named a vehicle. The framing is kept so that the X-52 sits in its place in the sequence, and the sections it imposes are short because the record is.
The framing of a decision with a recorded reason also breaks down. The registry gives the reason as possible confusion with the B-52 series, but no document giving the reasoning has been seen, and whether that phrase quotes the decision or paraphrases it cannot be determined [Missing USAF and DOD Aircraft Designations]. The F-19 case shows that confusion can be stated as a reason when it is not the reason, so the stated ground is evidence of what was written and not necessarily of what was weighed.
The argument for a spoken channel is borrowed rather than found. The opening states that the radio is argued from the neighbouring cases and not from this one, and the C-16 note is the only entry in the family that names a radio. The Epistemic State section below separates what the record establishes from what this article infers, and the inference that the refusal lacked written authority stands on an absence in a document, weaker evidence than a presence would be.
The Source Base
The thirty curated sources that carry the argument and the 1,335 research records that map the field are different things, and this article keeps them apart on purpose.
The evidentiary base is small because the subject is. Thirty curated references and four books carry every claim made here, and the ones that matter most are the five issues of the governing instruction that precede and follow the decision. Those are not commentary on the evidence. They are the evidence, because the central question is what a document does and does not contain, and the only way to settle that is to read it.
The survey base maps the field. Its 1,335 research records are drawn from the scholarly registry of digital object identifiers, Crossref, and from two report servers, the Defense Technical Information Center and the space agency’s Technical Reports Server. A few of them are cited in the prose, being the flight test report of the aircraft that received X-53A, for that programme’s dates, the three report-server studies of pilot-controller communication named under The Definition of Primary, and the titles named under Thin Subjects to show what the literature does and does not contain. None is cited for a claim about the X-52 decision, and the argument about the decision would stand unchanged without the survey.
The research survey holds 1,335 research records drawn from Crossref, the Defense Technical Information Center and the NASA Technical Reports Server, of which 30 are report primaries, being 2.2 percent, by the identifier rule set out under The Definition of Primary. The median publication year is 2012. Of the 1,280 dated records, 843 were published in 2006 or later, the year of the refusal and after it, being 65.9 percent.
The Definition of Primary
Primacy is a property of the document, and this survey derives it from the identifier. A record is a report primary when its address is on the space agency’s Technical Reports Server, the Defense Technical Information Center or the energy department’s report server, or when it carries a digital object identifier under the 10.21236 prefix, which Crossref registers for Defense Technical Information Center reports.
The report-primary fraction is 2.2 percent, being 30 records of 1,335, which is the third-lowest of the 72 articles in this series that carry research references, counting in each article the research definitions whose address meets that rule. The lowest is the X-39, an anomaly without a vehicle, at 0.52 percent, being 4 records of 768, and that is not a coincidence. The second-lowest is the later article on the seven numbers from X-69 to X-75, at 1.79 percent, being 22 records of 1,232, and its subject is likewise a run of designations that no aeroplane carries.
The measure means less here than it does anywhere else in this series and the article will not dress it up. It counts identifiers issued by the space agency’s report server and the defence technical information centre, which is the right instrument when the subject is an aeroplane and the wrong one when the subject is a refusal. The primary documents this article actually argues from are the five issues of the governing instruction, the registry that records the decision, the drug regulator’s naming guidance and the civil call sign study, and not one of them carries an identifier the measure can see.
So the count is reported alongside the fraction. Eleven curated sources are primary documents rather than descriptions of one, being five issues of the governing instruction, three of the drug regulator’s naming publications, the civil aviation call sign study, the air-ground communications briefing note and the flight research centre’s own fact sheet. A number that falls because the subject changed is reporting something true, and the X-39, the seven numbers from X-69 to X-75 and the X-52, whose subjects are administrative acts rather than aeroplanes, are the three at the bottom of the ranking.
The report literature of the armed services does not hold this subject. It holds aeronautical engineering, and the confusability of spoken identifiers is studied in medicine, in civil aviation safety and in linguistics. The report literature that does bear on it is the space agency’s own study of addressee errors in air traffic control communications, which treats the call sign problem directly, with its neighbours on pilot-controller communication [Monan 1983] [An error-resistant linguistic protocol for air traffic control] [Morrow et al. 1990].
Thin Subjects
Six subjects that this article’s derivations depend on have thin literatures. Each count below is the number of research records in this survey whose title carries at least one of the listed terms, with a hyphen read as a space. Where a row joins two groups of terms with the word together, a title must carry a term from each group.
| Subject | Title terms counted | Records |
|---|---|---|
| a threshold for deciding that two names are too alike | threshold, cutoff, decision rule, false positive, false negative, ROC, sensitivity and specificity, or a word beginning criteri, discriminat or validat | 9 |
| the longest common subsequence | longest common subsequence, LCS | 0 |
| the bigram set and the Dice coefficient | bigram, bigrams, Dice | 1 |
| aircraft designation as a subject | designation, designations, nomenclature together with aircraft, airplane, aeroplane, military, Air Force, Navy, Army | 2 |
| the reuse or retirement of an issued identifier | reuse, recycle, retire, reassign and their inflections together with identifier, number, numbering, name, code, designation | 0 |
| a collision between issued identifiers | collision, collisions, collide, colliding together with identifier, namespace, name, DOI, number | 3 |
A threshold is the thing this literature most rarely names, and the evidence a threshold would rest on is a pharmacy literature. Of the 9 titles that carry a threshold term, two concern the similarity of strings or sounds as such, being [Fischer 1982] and [Austin 1957], and one the criteria of the likelihood of confusion in trademark law [Moon 2018]. The term rule misses the closest work, which is a small literature whose titles relate a measure of drug name similarity to experimental data or to observed errors [Lambert et al. 1999] [Lambert et al. 2002] [Tamaki et al. 2012] [Lambert et al. 2015a] [Sagawa et al. 2024]. The drug regulator’s guidance states that its screening threshold rests on the validation work done on its algorithms, and that in its postmarketing experience the combined similarity measure has been positively correlated with errors involving name confusion [Best Practices in Developing Proprietary Names for Human Prescription Drug Products, Guidance for Industry, December 2020]. The claim that a similarity threshold can rest on evidence therefore has a literature, and nothing comparable exists for designations.
Two of the three measures the article computes have almost no titles of their own. No title names the longest common subsequence, and the one title that names a bigram concerns open-bigram coding of letters in recognition memory rather than a similarity coefficient.
Aircraft designation is not a subject of this literature. The two titles that pair designation or nomenclature with an aircraft or service term are standards naming aircraft hydraulic, pneumatic and oxygen equipment, and neither concerns a mission design series designation.
The occupancy argument has no literature, and collision between issued identifiers has three titles. No title concerns the reuse or retirement of an issued identifier, which is the rule on which the B-52’s occupancy of the number 52 rests. The three titles on collision concern namespace collisions, collisions between author names, and colliding digital object identifiers.
What the Survey Admits
A record is admitted only when a person reading its title finds it on this article’s subject, which is the refusal of an identifier because an identifier already in use is near it, together with what such a refusal draws on. That means the similarity of strings, names and spoken forms, confusable names and their screening, medication error where names, labels or reporting are concerned, the spoken and the written identifier, the administration of identifiers, the legal test of confusing similarity, human error, the perception of confusable sounds and words, and aviation’s own designations and channels. The survey therefore reaches into medicine, law, linguistics and psychology where a title concerns confusable names or identifiers, because refusing a proposed drug name because an approved name is near it is the same administrative act as refusing X-52A because a B-52 exists. The pharmacology is not the subject. The refusal is.
The survey has no residual cluster. Every admitted record belongs to one of the ten named literatures in the table above, under the same rule.
Several classes are excluded because this subject’s words also name other things. Readback names the signal read back from storage and from programmable logic, as well as the pilot’s repetition of a clearance. Radiotelephony names a branch of radio engineering as well as a phraseology, and verbal communication names a social skill as well as a spoken exchange. A generic name is a rank in the naming of fungi and trematodes as well as the pharmacist’s term for a nonproprietary drug name. Legibility names a social and political idea as well as a property of print. An identifier is also a molecular tag, a device fingerprint and a name in a program, a namespace is also a library of program classes, and a numbering system is also a numeral system, a notation for teeth and a term of textiles. Also excluded are confusion as a clinical symptom or a conceptual muddle, the brand name as a marketing or pricing variable, consumer confusion over sustainable products, machine recognition of speech, characters and images where the machine is the subject, similarity measures on graphs, trees, images, trajectories, music and molecules, the similarity of documents by meaning, exact pattern matching, orthography and phonetics studied as philology, medication error with no name, label or reporting element, glossary definitions of terms, drug handbook name lists, textbook appendices, correction notices and second deposits of one document. A review of a book, a notice such as front matter, an editorial or a news item, and a reference or definition entry of two pages or fewer are excluded on the same ground, since none of them is a research work in its own right.
Doubtful classes are kept where the title concerns a confusable, spoken or issued identifier, and a reader may reasonably discount them. They are consumer confusion studied as a marketing construct, because confusion between similar brands is one of its kinds, general medication error prevention, machine recognition of call signs and readbacks, numbering schemes for tools, alloys and engine positions, unique identifiers designed for data systems, and encyclopedia entries on string matching and record linkage.
Every research title has been read for relevance, so the off-topic share that remains is a matter of reading judgement. A reading of titles cannot show that a record is relevant in substance, so this is a statement about titles only.
The Literature of This Refusal Is Not a Literature of Aircraft Designation
Of the 1,335 research records, 21, or 1.57 percent, sit in the aviation cluster, and not one of them is about aircraft designation as a subject in its own right. Seven concern aviation safety reporting, ten controller-pilot data link communication, one cockpit speech intelligibility, one aircraft identification training, and two are flight reports on the aircraft that received X-53A. The aviation literature the survey does hold is the literature of the radio channel, being the 96 records of the call sign cluster, which concern phraseology, readback and miscommunication rather than designations. The literature of why the X-52 was refused lies almost entirely outside aircraft designation, and an article in a series about aeroplanes should report that rather than pad the row.
The Book Identifiers Match Title and Author
All four resolve to the books the labels name [Cushing, Fatal words] [Reason, Human error] [Bowker and Star, Sorting things out] [Norman, The psychology of everyday things]. The match is made in the repository’s search index on title and author, because its work endpoint returns the same internal error for records that exist and for keys that do not, so it cannot tell a wrong identifier from a dead one.
Epistemic State
Historical Fact
The designation X-52A was requested in 2006 for a programme to test active aeroelastic wing technology, was disapproved because of possible confusion with the B-52 series, and the designation X-53A was allocated to the programme instead. This is recorded by the specialist registry of United States military aerospace vehicle designations [Missing USAF and DOD Aircraft Designations].
The Active Aeroelastic Wing programme began in 1996, first flew in modified form in November 2002, and concluded its flight research in March 2005 [Active Aeroelastic Wing Flight Research, NASA Facts FS-2005-03-061 DFRC] [Clarke et al. 2005] [Boeing X-53 Active Aeroelastic Wing]. The fact sheet gives the start of flight testing as late 2002 and the flight test report as November 2002.
The aircraft was designated X-53 by memorandum of the Air Force Deputy Chief of Staff for Strategic Plans and Programs, dated 16 August 2006 by the encyclopedia entry [Boeing X-53 Active Aeroelastic Wing], and the Air Force Research Laboratory announced the designation on 11 December 2006 [Active Aeroelastic Wing flight research vehicle receives X-53 designation, Air Force Research Laboratory, 11 December 2006].
The office symbol of the deciding office changed from HQ USAF/XPPE to AF/A8PE with effect from 1 February 2006 [Allocation of Official Aerospace Vehicle MDS Designations].
The F-35 designation was approved on 5 June 2002 against a nomenclature office recommendation of F-24A made on the ground that design numbers are to be assigned consecutively [Non-Standard DOD Aircraft Designations].
The requests to redesignate two drones as Q-7 and Q-8, made because the drones were being confused with unmodified aircraft, were refused in March 1954 [Missing USAF and DOD Aircraft Designations].
The Food and Drug Administration screens proposed prescription drug names against approved names using its Phonetic and Orthographic Computer Analysis program, makes that program publicly available, and publishes three similarity bands, being a combined match percentage score of 70 percent or more for a highly similar name pair, 55 to 69 percent for a moderately similar pair, and 54 percent or less for a low similarity pair. The guidance states that the 55 percent screening threshold is set on the validation work done on the algorithms [Best Practices in Developing Proprietary Names for Human Prescription Drug Products, Guidance for Industry, December 2020] [Phonetic and Orthographic Computer Analysis Program].
The United Kingdom’s civil aviation authority published a dedicated call sign confusion study in April 2000, resting on the 482 call sign confusion reports of 1997, of which 435 were filed by controllers, 44 by flight crews and 3 by both [CAP 704, Aircraft Call Sign Confusion Evaluation Safety Study, United Kingdom Civil Aviation Authority].
Verified by Reading the Document
The following are statements about the contents of five issues of one instruction and were checked against the text of each rather than by consulting a description of any of them.
The 14 April 2005 issue of the joint instruction directs that the coordinating office will assign and reserve the next available consecutive design number within each basic mission for new vehicles [Air Force Joint Instruction 16-401, 14 April 2005].
That issue contains no authority to skip a design number, no occurrence of the word skip, and no criterion by which a proposed design number may be judged unsuitable.
Its duplication check, its trademark search and its four levels of review apply to the popular name and not to the designation.
Its only provision citing confusion in connection with a designator is the prohibition of the letters I and O as series symbols [Air Force Joint Instruction 16-401, 14 April 2005].
The 1 September 1997 issue of the same instruction and the 1994 issue it superseded carry the same sequence requirement, the same popular-name duplication check and trademark search, and the same prohibition of I and O, and likewise contain no authority to skip a design number [Air Force Joint Instruction 16-401, 1 September 1997] [Air Force Joint Instruction 16-401, 1994].
The 16 May 2014 issue adds, at Attachment 2 paragraph A2.1.6.1.2, that HAF/A8PE reserves the authority to skip design number at discretion and that skipped design numbers cannot be requested or used, and attaches no criterion to the authority [Air Force Instruction 16-401, 16 May 2014]. The 3 November 2020 issue keeps the authority at the same paragraph under AF/A8PE, and at paragraph 4.2.1.3 it states that requests are not accepted for designators in reverse or skipped sequences [Department of the Air Force Instruction 16-401, 3 November 2020].
Analysis
The edit distance between the strings X-52 and B-52 is 1, the normalised edit similarity is 0.75, the longest common subsequence is three characters giving the same 0.75, and the Dice coefficient on character bigrams is two thirds. These are computed and not quoted from any source.
Rendered as they would be spoken, the two names are more similar than they are in writing. The character edit distance between ex fifty two and bee fifty two is 2 over strings of 12 and 13 characters, giving a normalised similarity of about 0.846 against the written pair’s 0.75. At the level of whole words one token in three differs, giving about 0.667, so the ordering depends on what a listener is taken to be matching.
The X-35 was allocated before the F-35 was approved, so that approval raised the number of series holding the design number 35 from one to two and added one bit of residual uncertainty to a listener who hears the number without the mission letter. The refusal of X-52A held the corresponding quantity at 52 unchanged and added none.
The B-52 has been operated by the Air Force since 1955 and is expected to serve into the 2050s, so the numeral has been and will be occupied for something near a century, and had been occupied for fifty-one years at the moment of the refusal [Boeing B-52 Stratofortress].
Every collision named in this article is between two designations that differ in the mission symbol and agree in the design number.
The count of cross-series numeric collisions in a system where each mission series counts from one is structurally non-zero and grows as series are added.
Placing this article’s own similarity figures in the drug regulator’s published bands is an illustration and not a result. The bigram coefficient of about 66.7 percent would fall in the moderately similar band and the normalised edit similarity of 75 percent in the highly similar band, but neither figure is the combined orthographic and phonetic score that program computes, and no claim is made that the program would return either value.
Inference
That the X-52A refusal was made under an authority the instruction did not then contain is an inference from the absence of any such provision in the 2005 issue, and an absence in a document is weaker evidence than a presence. It is possible that the authority existed in another issuance not consulted here.
That the 2014 clause regularised the practice is an inference from its content and its timing, and no document has been seen that connects the two.
That the F-35 and X-52 decisions are inconsistent is an interpretation. The two were made four years apart under one office symbol and then another, and the individuals need not have been the same. The inconsistency asserted here is of the system and not of any person.
What the Record Does Not Settle
Who asked for X-52A is not stated in any source consulted. The registry says the request was made for a programme to test active aeroelastic wing technology and does not name the requesting office.
The date within 2006 is not stated, so whether the request preceded or followed the 1 February office-symbol change is unknown.
No document giving the reasoning has been seen. The phrase possible confusion with the B-52 series is the registry’s summary. Whether it quotes the decision or paraphrases it is not determinable from the public record.
Whether the B-52 was named in the decision because of its fame, its longevity, or its role as the carrier aircraft for X-planes is unknown, and the third possibility is the one this article finds most interesting and has the least evidence for.
Whether anyone considered the F-35 precedent in 2006 is unknown.
Whether the refusal was correct is not settled by anything here. No measure and no threshold were recorded, and this article supplies a measure only to show what was missing, not to supply the answer retrospectively.
Out of Scope
The Active Aeroelastic Wing itself. The aeroelastic engineering, the control laws, the roll-reversal problem and the flight-test results belong to the next article in this series, which is about the X-53. This article names the programme and stops.
The unmanned series consuming numbers from the same pool. The X-58 and X-67 slots were taken by aircraft designated XQ-58A and XQ-67A, a different mechanism from a refusal, treated in its own articles later in the series [Missing USAF and DOD Aircraft Designations].
The pre-1962 designation systems. Everything here concerns the joint system implemented in September 1962 [1962 United States Tri-Service Aircraft Designation System].
Foreign designation systems, and the question of whether they exhibit the same behaviour.
The surveyed literature itself. The survey is a map for a reader who wants to pursue the general question, and its records are listed by title. None of them is cited for a claim about the X-52 decision. The cluster commentary carries one citation and it is a curated source rather than a survey record, being the drug regulator’s naming guidance, which is cited because the commentary makes a claim about what that regulator publishes.
Conclusion
The X-52 is the only number in the X-series that was asked for properly and refused on the merits of its own string. The registry’s other missing X numbers are the X-23, requested in 1965 and refused because the vehicle was unmanned and then never requested again, the X-39, reserved and never requested, and the X-58 and X-67, whose slots were skipped after aircraft designated in another series took the numbers [Missing USAF and DOD Aircraft Designations].
The instruction in force required the next number in sequence, provided no authority to skip one, and reserved its entire confusability apparatus for the popular name, the half of the identifier it describes as aiding communications and media references rather than the half it calls official. Its only written anti-confusion rule for a designator is that the series letters I and O are prohibited because they look like digits.
On the issues read here, the refusal was therefore made under a rule that did not exist in writing, and eight years later a sentence was added to the instruction granting the office the authority to skip a design number at discretion, with no criterion attached. The issue before the one in force said the same as the one in force, so the authority was absent for nearly twenty years while the practice ran throughout them.
The decision was not eccentric. It sits in a long and documented family, and the reasons recorded across that family are operational rather than clerical. A radio under combat load. Maintenance records mixed up between two aircraft built by two companies both called Bell. In every case the collision crosses a mission boundary, so the system’s formal guarantee of uniqueness depends on a coordinate that the channel does not carry.
And the same office had spent 2002 manufacturing such a collision on purpose, taking the X-35’s number for the F-35 against its own nomenclature office’s advice that numbers are assigned consecutively.
A judgement of that kind can be written down, and elsewhere it is. The drug regulator that screens every proposed prescription name against the names already approved publishes the program it uses, the databases it compares against, and three numbered similarity bands, and records that its screening threshold rests on validation work rather than on somebody’s ear. Measured against those bands, the two designations land in different categories depending on which measure is chosen, and for that reason the choice of measure has to be stated. One naming authority publishes all of it. The other refused a designation and recorded a phrase.
What the X-52 case finally shows is a designation system doing something a numbering scheme is not supposed to do. A counter does not care what its numbers resemble. This one does, the record of it weighing resemblance runs back to at least 1954, it has never written down what it is comparing or against what threshold, and in 2006 it looked at a bomber that had already been flying for fifty-one years and was expected to be flying more than forty years longer, and said no.
Equations
This section collects the 34 display equations of the article in the order they appear, each under its number and reproduced exactly as it stands in the text. A title in bold names an established result, and a title in italics beginning with the word Bespoke names a construction made for this analysis. Of the 34, 18 are established and 16 are bespoke. Design numbers, counts and multiplicities are dimensionless integers, durations are in years, the ambiguity measure is in bits, and every similarity score is a dimensionless number between zero and one that depends on which measure and which rendering of the two names is adopted, so scores from different measures are not interchangeable.
Equation 1, Bespoke Next Available Design Number. The article formalises the instruction’s next available consecutive number as the least natural number not already used up within the basic mission, counting numbers passed over as used up. Air Force Joint Instruction 16-401, 14 April 2005
\[n^{\star}(m) \;=\; \min\bigl\{\,k \in \mathbb{N} \;:\; k \notin A_m \,\bigr\} \tag{1}\]Equation 2, Available Design Numbers Within a Mission. The numbers still available are those of the instruction’s range from one to 999 that are not already used up, and the next assignment is the least of them. Air Force Joint Instruction 16-401, 14 April 2005
\[V_m(t) \;=\; \{1, 2, \ldots, 999\} \setminus A_m(t), \qquad n^{\star}(m) \;=\; \min V_m(t). \tag{2}\]Equation 3, Monotonicity of the Allocated and Available Sets. Because the instruction forbids reuse of a retired designation, the used-up set can only grow over time and the available set can only shrink. Air Force Joint Instruction 16-401, 14 April 2005
\[t_1 \leq t_2 \;\implies\; A_m(t_1) \subseteq A_m(t_2) \;\implies\; V_m(t_2) \subseteq V_m(t_1). \tag{3}\]Equation 4, Bespoke Three-State Partition of the Design Numbers. The article partitions the range into allocated, marked not used and available numbers, adding the middle state that the master list records and the instruction never mentions. Missing USAF and DOD Aircraft Designations
\[\{1, 2, \ldots, 999\} \;=\; \underbrace{A_m(t)}_{\text{allocated}} \;\sqcup\; \underbrace{U_m(t)}_{\text{marked not used}} \;\sqcup\; \underbrace{V_m(t)}_{\text{available}}, \tag{4}\]Equation 5, Departure of the Assigned Number From the Sequence Rule. The assigned number 53 exceeds the number 52 that the sequence rule names by one. Missing USAF and DOD Aircraft Designations
\[\text{assigned} \;-\; n^{\star}(X) \;=\; 53 - 52 \;=\; 1, \tag{5}\]Equation 6, Size of the Series Symbol Alphabet. Excluding the letters I and O, which the instruction prohibits as series symbols, leaves an alphabet of twenty-four letters. Air Force Joint Instruction 16-401, 14 April 2005
\[|S| \;=\; 26 - 2 \;=\; 24, \tag{6}\]Equation 7, Designation Space of a Mission Under the 2005 Issue. With 999 design numbers and twenty-four series symbols, a basic mission can hold 23,976 designations. Air Force Joint Instruction 16-401, 14 April 2005
\[N_m \;=\; 999 \times 24 \;=\; 23{,}976, \tag{7}\]Equation 8, Designation Space of a Mission Under the 2020 Issue. Extending the design number to four digits, as the 2020 issue provides, raises the space to 239,976 designations. Department of the Air Force Instruction 16-401, 3 November 2020
\[N_m' \;=\; 9{,}999 \times 24 \;=\; 239{,}976. \tag{8}\]Equation 9, Intervals Before the Written Authority to Skip. The 2014 issue that first grants the authority to skip came eight years after the refusal and twenty years after the earliest issue read. Air Force Instruction 16-401, 16 May 2014
\[\underbrace{2014 - 2006}_{8 \ \text{years after the refusal}} \qquad\text{and}\qquad \underbrace{2014 - 1994}_{20 \ \text{years after the earliest issue read here}}. \tag{9}\]Equation 10, Count of Missions Skipping Thirteen by Custom. Six basic mission series lack the design number 13 by the unwritten custom of skipping it. Missing USAF and DOD Aircraft Designations
\[\bigl| \{\, m \in M \;:\; 13 \notin A_m \text{ by custom} \,\} \bigr| \;=\; 6, \tag{10}\]Equation 11, Designation as a Pair of Mission and Number. An assigned designation is a pair of a basic mission symbol and a design number issued within that mission, and such pairs are unique by construction.
\[\mathrm{MDS} \;=\; \bigl\{ (m, n) \;:\; m \in M,\; n \in A_m \bigr\}, \tag{11}\]Equation 12, Bespoke Projection Onto the Design Number. The article models a channel that preserves only the design number as a projection that discards the mission symbol, a supposition it infers from the refusals.
\[\sigma(m, n) \;=\; n, \tag{12}\]Equation 13, Bespoke Fibre of Indistinguishable Designations. The designations that a listener hearing only the number cannot separate form the fibre of the projection, and its size is the multiplicity of that number.
\[\sigma^{-1}(k) \;=\; \bigl\{\, (m, k) \;:\; m \in M,\ k \in A_m \,\bigr\}, \qquad \bigl| \sigma^{-1}(k) \bigr| \;=\; o_k. \tag{13}\]Equation 14, Number of Distinct Designations in the Register. The register holds as many distinct designations as the sum of the sizes of the allocated sets over all missions.
\[\sum_{m \in M} \bigl| A_m \bigr| \tag{14}\]Equation 15, Bespoke Number of Designations Distinguishable by Number Alone. The count of design numbers in use is equated with the largest number issued in any mission, which holds only when every number up to that maximum has been issued in at least one series.
\[\Bigl| \bigcup_{m \in M} A_m \Bigr| \;=\; \max_{m \in M}\, \max A_m \tag{15}\]Equation 16, Multiplicity of a Design Number. The multiplicity of a design number is the number of basic mission series that have issued it.
\[o_k \;=\; \bigl| \{\, m \in M \;:\; k \in A_m \,\} \bigr|, \tag{16}\]Equation 17, Bespoke Count of Colliding Designation Pairs. The article measures collisions as the number of unordered pairs of series that share a design number, summed over all numbers.
\[C \;=\; \sum_{k \geq 1} \binom{o_k}{2}, \tag{17}\]Equation 18, Bespoke Ratio of Register Size to Channel Capacity. The article defines the factor by which the register outruns a number-only channel as the ratio of designations to distinct numbers, equal to the mean multiplicity.
\[R \;=\; \frac{\sum_{m \in M} \bigl| A_m \bigr|} {\Bigl| \bigcup_{m \in M} A_m \Bigr|} \;=\; \operatorname*{mean}_{k \,\in\, \bigcup_m A_m} o_k, \tag{18}\]Equation 19, Bespoke Probability of Correct Attribution. Under a uniform prior over the series that hold a number, an idealisation the article states, a listener attributes a spoken number correctly with probability one over its multiplicity.
\[P(\text{correct} \mid k) \;=\; \frac{1}{o_k} \tag{19}\]Equation 20, Bespoke Residual Uncertainty in Bits. The same uniform prior gives a residual uncertainty of the base-two logarithm of the multiplicity, the information a number-only channel discards.
\[H(k) \;=\; \log_2 o_k \tag{20}\]Equation 21, Bespoke Ambiguity Added by Approving the F-35. Approving the F-35 on top of the X-35 doubled the multiplicity of 35 and so, under the uniform prior, added one bit of ambiguity.
\[\Delta H(35) \;=\; \log_2 2 - \log_2 1 \;=\; +1 \ \text{bit}. \tag{21}\]Equation 22, Bespoke Ambiguity Withheld by Refusing the X-52. Refusing the X-52 left the multiplicity of 52 at one, so under the uniform prior the refusal added no ambiguity.
\[\Delta H(52) \;=\; \log_2 1 - \log_2 1 \;=\; 0 \ \text{bits}, \tag{22}\]Equation 23, Occupancy Duration of a Design Number. A number is occupied from its allocation until the last aircraft carrying it retires, since the instruction forbids reuse. Air Force Joint Instruction 16-401, 14 April 2005
\[T_{\text{occupied}} \;=\; t_{\text{retire}} \;-\; t_{\text{allocate}}, \tag{23}\]Equation 24, Bespoke Occupancy of the Number 52. The occupancy of the B-52 is bounded below by taking 2050 as the retirement year, a representative value the article takes from expected service into the 2050s. Boeing B-52 Stratofortress
\[T_{\text{occupied}} \;\geq\; 2050 - 1955 \;=\; 95 \ \text{years}, \tag{24}\]Equation 25, Bespoke Split of the B-52 Occupancy at the Refusal. The ninety-five year occupancy is divided at 2006 into fifty-one years served and forty-four expected, the latter resting on the assumed retirement year of 2050. Boeing B-52 Stratofortress
\[\underbrace{2006 - 1955}_{51 \ \text{years already served}} \;+\; \underbrace{2050 - 2006}_{44 \ \text{years still expected}} \;=\; 95 \ \text{years}. \tag{25}\]Equation 26, Levenshtein Edit Distance Recurrence. The edit distance between two strings is the least number of single-character insertions, deletions and substitutions, computed by the standard dynamic programming recurrence. Levenshtein Distance
\[d_{i,j} \;=\; \begin{cases} \max(i, j), & \min(i, j) = 0, \\[4pt] \min\bigl\{\, d_{i-1,j} + 1, \; d_{i,j-1} + 1, \; d_{i-1,j-1} + \mathbb{1}[\,a_i \neq b_j\,] \,\bigr\}, & \text{otherwise}, \end{cases} \tag{26}\]Equation 27, Normalised Edit Similarity of X-52 and B-52. One minus the edit distance divided by the length of the longer string gives a similarity of 0.75 for the written pair.
\[s(a, b) \;=\; 1 - \frac{d_{\ell_a,\, \ell_b}}{\max(\ell_a,\, \ell_b)} \;=\; 1 - \frac{1}{4} \;=\; 0.75. \tag{27}\]Equation 28, Longest Common Subsequence Similarity. The length of the longest common subsequence divided by the length of the longer string also gives 0.75 for the written pair.
\[s_{\mathrm{LCS}}(a, b) \;=\; \frac{\bigl| \mathrm{LCS}(a, b) \bigr|}{\max(\ell_a,\, \ell_b)} \;=\; \frac{3}{4} \;=\; 0.75. \tag{28}\]Equation 29, Character Bigram Sets of the Two Designations. Each designation is reduced to its set of adjacent character pairs, and the two sets share two of their three members.
\[\mathcal{B}(\text{X-52}) = \{\,\texttt{X-},\ \texttt{-5},\ \texttt{52}\,\}, \qquad \mathcal{B}(\text{B-52}) = \{\,\texttt{B-},\ \texttt{-5},\ \texttt{52}\,\}, \tag{29}\]Equation 30, Dice Coefficient on Character Bigrams. The Dice coefficient, twice the shared bigrams over the total, is about 0.667 for the written pair.
\[s_{\mathrm{Dice}}(a, b) \;=\; \frac{2 \bigl| \mathcal{B}(a) \cap \mathcal{B}(b) \bigr|} {\bigl| \mathcal{B}(a) \bigr| + \bigl| \mathcal{B}(b) \bigr|} \;=\; \frac{4}{6} \;\approx\; 0.667. \tag{30}\]Equation 31, Bespoke Edit Similarity of the Spoken Forms. The edit similarity is evaluated on the spoken renderings ex fifty two and bee fifty two, a spelling of the spoken forms the article chooses, and gives about 0.846.
\[s\bigl(\text{ex fifty two},\ \text{bee fifty two}\bigr) \;=\; 1 - \frac{2}{13} \;\approx\; 0.846. \tag{31}\]Equation 32, Bespoke Word-Level Similarity of the Spoken Forms. Treating the spoken forms as sequences of three words, a tokenisation the article chooses, one differing word in three gives about 0.667.
\[s_{\text{word}} \;=\; 1 - \frac{1}{3} \;\approx\; 0.667. \tag{32}\]Equation 33, Bespoke Threshold Rule for Refusing a Designation. The article states the decision rule that a written refusal would need, refusing a proposed designation when its greatest similarity to any designation in use reaches a threshold.
\[\text{refuse } b \quad \text{if and only if} \quad \max_{a \,\in\, \mathcal{A}} s(a, b) \;\geq\; \tau, \tag{33}\]Equation 34, Similarity Bands of the Drug Name Guidance. The Food and Drug Administration guidance classes a combined orthographic and phonetic score as highly similar at seventy percent or more, moderately similar from fifty-five to sixty-nine percent and of low similarity at fifty-four percent or less. Best Practices in Developing Proprietary Names for Human Prescription Drug Products, Guidance for Industry, December 2020
\[\text{band}(s) \;=\; \begin{cases} \text{highly similar}, & s \geq 70\%, \\[2pt] \text{moderately similar}, & 55\% \leq s \leq 69\%, \\[2pt] \text{low similarity}, & s \leq 54\%, \end{cases} \tag{34}\]Notation
- $n^{\star}$, the next available design number that the sequence rule names
- $A_m$, the set of design numbers used up within basic mission $m$
- $V_m$, the set of design numbers still available within basic mission $m$
- $U_m$, the set of design numbers marked not used within basic mission $m$
- $M$, the set of basic mission symbols
-
$ S $, the number of permitted series symbols - $N_m$, the size of the designation space of a basic mission
- $\mathrm{MDS}$, the set of assigned designations, each a pair of mission symbol and design number
- $\sigma$, the projection that keeps only the design number
- $o_k$, the multiplicity of design number $k$, the number of series that have issued it
- $C$, the count of colliding designation pairs
- $R$, the ratio of register size to the number of distinct design numbers
- $H(k)$, the residual uncertainty in bits after hearing design number $k$ alone
- $T_{\text{occupied}}$, the time a design number stays occupied
- $d_{i,j}$, the edit distance between the first $i$ characters of $a$ and the first $j$ characters of $b$
- $\ell_a$, the length of string $a$, with $\ell_b$ that of string $b$
- $s(a, b)$, the normalised edit similarity of two strings
- $s_{\mathrm{LCS}}$, the longest common subsequence similarity
- $\mathcal{B}$, the set of character bigrams of a string
- $s_{\mathrm{Dice}}$, the Dice coefficient on character bigrams
- $\mathcal{A}$, the set of designations already in use
- $\tau$, the similarity threshold for refusal
References
Primary Sources, Peer-Reviewed
- Abdel Ghafour, Hesham H., Ali El-Bastawissy, and Abdel Fattah A. Heggazy. 2011. “AEDA: Arabic Edit Distance Algorithm towards a New Approach for Arabic Name Matching.” In The 2011 International Conference on Computer Engineering & Systems. IEEE. https://doi.org/10.1109/icces.2011.6141061
- Abraham, Dona, and Nisha S. Raj. 2014. “Approximate String Matching Algorithm for Phishing Detection.” In 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE. https://doi.org/10.1109/icacci.2014.6968578
- Abuelsoud, Nermeen Nabeel. 2018. “Improving Medication Safety through Implementation of Medication Error Reporting Systems in Different Medical Specialities.” Journal of Pharmacy Practice and Research 48 (6): 537–42. https://doi.org/10.1002/jppr.1453
- Ahmed, Tafseer, Muhammad Suffian, Muhammad Yaseen Khan, and Alessandro Bogliolo. 2022. “Discovering Lexical Similarity Using Articulatory Feature-Based Phonetic Edit Distance.” IEEE Access 10: 1533–44. https://doi.org/10.1109/access.2021.3137905
- Akutsu, Tatsuya. 1994. “Approximate String Matching with Don’t Care Characters.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-58094-8_21
- Akutsu, Tatsuya. 1995. “Approximate String Matching with Don’t Care Characters.” Information Processing Letters 55 (5): 235–39. https://doi.org/10.1016/0020-0190(95)00111-o
- Akutsu, Tatsuya. 2006. “A Relation between Edit Distance for Ordered Trees and Edit Distance for Euler Strings.” Information Processing Letters 100 (3): 105–9. https://doi.org/10.1016/j.ipl.2006.06.002
- Akutsu, Tatsuya, Daiji Fukagawa, and Atsuhiro Takasu. 2006. “Approximating Tree Edit Distance through String Edit Distance.” In Algorithms and Computation. Springer Berlin Heidelberg. https://doi.org/10.1007/11940128_11
- Akutsu, Tatsuya, Daiji Fukagawa, and Atsuhiro Takasu. 2008. “Approximating Tree Edit Distance through String Edit Distance.” Algorithmica 57 (2): 325–48. https://doi.org/10.1007/s00453-008-9213-z
- Aldwairi, Monther, and Yahya Flaifel. 2012. “Baeza-Yates and Navarro Approximate String Matching for Spam Filtering.” In Second International Conference on the Innovative Computing Technology (INTECH 2012). IEEE. https://doi.org/10.1109/intech.2012.6457802
- alves Da Silva, E., and J. J. Figueira. 2015. “Unique Device Identifier System: The Impact of the Portuguese Experience.” Value in Health 18 (7): A373. https://doi.org/10.1016/j.jval.2015.09.767
- Alwitt, Linda F. 1973. “Relationship of Visual and Name Similarity of Visually Presented Letters.” Memory & Cognition 1 (3): 209–12. https://doi.org/10.3758/bf03198097
- Amir, Amihood, Yonatan Aumann, Oren Kapah, Avivit Levy, and Ely Porat. n.d. “Approximate String Matching with Address Bit Errors.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-69068-9_13
- Amir, Amihood, Estrella Eisenberg, Orgad Keller, Avivit Levy, and Ely Porat. 2010. “Approximate String Matching with Stuck Address Bits.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-16321-0_41
- Anderson, James G., Rangaraj Ramanujam, Devon J. Hensel, and Carl A. Sirio. 2009. “Reporting Trends in a Regional Medication Error Data-Sharing System.” Health Care Management Science 13 (1): 74–83. https://doi.org/10.1007/s10729-009-9111-1
- andNa. 1995. “Pharmacists Have a Major Role in ADR and Medication Error Monitoring and Reporting.” Drugs & Therapy Perspectives 5 (1): 10–12. https://doi.org/10.2165/00042310-199505010-00004
- andNa. 1996. “Concern over Drug Name Confusion.” Inpharma Weekly &NA; (1039): 6. https://doi.org/10.2165/00128413-199610390-00008
- andNa. 1997. “Computer-Based Prediction of Medication Name Confusion.” Reactions Weekly &NA; (657): 2. https://doi.org/10.2165/00128415-199706570-00001
- andNa. 2004a. “Improving Systems Should Help to Reduce Errors Due to Look-Alike and Sound-Alike Drug Names.” Drugs & Therapy Perspectives 20 (4): 23–26. https://doi.org/10.2165/00042310-200420040-00008
- andNa. 2004b. “Three Reports of Serious Medication Errors Due to Confusion between Mercaptamine and Mercaptopurine,.” Reactions Weekly &NA; (1000): 3. https://doi.org/10.2165/00128415-200410000-00005
- andNa. 2005b. “Confusion between Reminyl and Amaryl Causes Medication Errors.” Reactions Weekly &NA; (1034): 3. https://doi.org/10.2165/00128415-200510340-00003
- andNa. 2006. “Several Cases Where Confusion between the Brand Name Salagen and the Generic Drug Name Selegiline Resulted in a Medication Error.” Reactions Weekly &NA; (1088): 2. https://doi.org/10.2165/00128415-200610880-00005
- Andrews, Sally. 1997. “The Effect of Orthographic Similarity on Lexical Retrieval: Resolving Neighborhood Conflicts.” Psychonomic Bulletin & Review 4 (4): 439–61. https://doi.org/10.3758/bf03214334
- Aratsu, Taku, Kouichi Hirata, and Tetsuji Kuboyama. 2009. “Approximating Tree Edit Distance through String Edit Distance for Binary Tree Codes.” In SOFSEM 2009: Theory and Practice of Computer Science. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-95891-8_12
- Aronson, Jeffrey K. 1995. “Confusion over Similar Drug Names Problems and Solutions.” Drug Safety 12 (3): 155–60. https://doi.org/10.2165/00002018-199512030-00001
- Arslan, Abdullah. 2006. “An Algorithm for String Edit Distance Allowing Substring Reversals.” In Sixth IEEE Symposium on BioInformatics and BioEngineering (BIBE’06). IEEE. https://doi.org/10.1109/bibe.2006.253338
- Assaker, Joseph, Abdallah Makhoul, Julien Bourgeois, and Jacques Demerjian. 2020. “A Unique Identifier Assignment Method for Distributed Modular Robots.” In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE. https://doi.org/10.1109/iros45743.2020.9341515
- Atallah, M. J., F. Chyzak, and P. Dumas. 2001. “A Randomized Algorithm for Approximate String Matching.” Algorithmica 29 (3): 468–86. https://doi.org/10.1007/s004530010062
- Audhkhasi, Kartik, and Ashish Verma. 2007. “Keyword Search Using Modified Minimum Edit Distance Measure.” In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP ‘07. IEEE. https://doi.org/10.1109/icassp.2007.367223
- “Author Name Processing at Chemical Abstracts Service: Name Matching Using Nonunique Bibliographic Identifiers.” 1983. World Patent Information 5 (1): 47. https://doi.org/10.1016/0172-2190(83)90220-x
- Ayad, Lorraine A. K., Solon P. Pissis, and Ahmad Retha. 2016. “libFLASM: A Software Library for Fixed-Length Approximate String Matching.” BMC Bioinformatics 17 (1): 454. https://doi.org/10.1186/s12859-016-1320-2
- Aygun, Ramazan S. 2017. “Using Maximum Subarrays for Approximate String Matching.” Annals of Data Science 4 (4): 503–31. https://doi.org/10.1007/s40745-017-0117-0
- Baeza-Yates, Ricardo, and Gonzalo Navarro. 1996. “A Faster Algorithm for Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-61258-0_1
- Baeza-Yates, Ricardo, and Gonzalo Navarro. 1997. “Multiple Approximate String Matching.” In Algorithms and Data Structures. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-63307-3_57
- Baeza-Yates, Ricardo A., and Chris H. Perleberg. 1992. “Fast and Practical Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-56024-6_15
- Baeza-Yates, Ricardo A., and Chris H. Perleberg. 1996. “Fast and Practical Approximate String Matching.” Information Processing Letters 59 (1): 21–27. https://doi.org/10.1016/0020-0190(96)00083-x
- Baeza-Yates and G. Navarro, R. 1999. “Faster Approximate String Matching.” Algorithmica 23 (2): 127–58. https://doi.org/10.1007/pl00009253
- Baghcheghi, Nayereh, and Hamid Reza Koohestani. 2025. “Evaluating a Medication Error Prevention Training for Nursing Students Using Kirkpatrick’s Model.” BMC Medical Education 26 (1): 31. https://doi.org/10.1186/s12909-025-08350-w
- Bakar, Zainab Abu, Tengku Mohd T. Sembok, and Mohammed Yusoff. 2000. “An Evaluation of Retrieval Effectiveness Using Spelling-Correction and String-Similarity Matching Methods on Malay Texts.” Journal of the American Society for Information Science 51 (8): 691–706. https://doi.org/10.1002/(sici)1097-4571(2000)51:8<691::aid-asi20>3.0.co;2-u
- Balabanis, George, and Samantha Craven. 1997. “Consumer Confusion from Own Brand Lookalikes: An Exploratory Investigation.” Journal of Marketing Management 13 (4): 299–313. https://doi.org/10.1080/0267257x.1997.9964474
- Balashov, Vadim S., and Andrei Nikiforov. 2019. “How Much Do Investors Trade Because of Name/ticker Confusion?” Journal of Financial Markets 46: 100499. https://doi.org/10.1016/j.finmar.2019.06.002
- Balocco, Raffaella, Jeffrey K. Aronson, Sarel F. Malan, and Albert Figueras. 2025. “Strengthening Signal Detection in Pharmacovigilance by Using International Nonproprietary Name (INN) Stems.” Drug Safety 49 (4): 381–87. https://doi.org/10.1007/s40264-025-01620-y
- Baloi, Aurel, Bogdan Belean, Flaviu Turcu, and Daniel Peptenatu. 2023. “GPU-Based Similarity Metrics Computation and Machine Learning Approaches for String Similarity Evaluation in Large Datasets.” Soft Computing 28 (4): 3465–77. https://doi.org/10.1007/s00500-023-08687-8
- Barnard, P., P. Wright, and P. Wilcox. 1978. “The Effects of Spatial Constraints on the Legibility of Handwritten Alphanumeric Codes.” Ergonomics 21 (1): 73–78. https://doi.org/10.1080/00140137808931695
- Bartolini, Ilaria, Paolo Ciaccia, and Marco Patella. 2002. “String Matching with Metric Trees Using an Approximate Distance.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-45735-6_24
- Barton, Carl, Costas S. Iliopoulos, and Solon P. Pissis. 2014. “Fast Algorithms for Approximate Circular String Matching.” Algorithms for Molecular Biology 9 (1): 9. https://doi.org/10.1186/1748-7188-9-9
- Basco, William T., Myla Ebeling, Thomas C. Hulsey, and Kit Simpson. 2010. “Using Pharmacy Data to Screen for Look-Alike, Sound-Alike Substitution Errors in Pediatric Prescriptions.” Academic Pediatrics 10 (4): 233–37. https://doi.org/10.1016/j.acap.2010.04.024
- Basco, William T., Sandra S. Garner, Myla Ebeling, Katherine D. Freeland, Thomas C. Hulsey, and Kit Simpson. 2016. “Evaluating the Potential Severity of Look-Alike, Sound-Alike Drug Substitution Errors in Children.” Academic Pediatrics 16 (2): 183–91. https://doi.org/10.1016/j.acap.2015.06.014
- Beck, Martin, and Florian Kerschbaum. 2013. “Approximate Two-Party Privacy-Preserving String Matching with Linear Complexity.” In 2013 IEEE International Congress on Big Data. IEEE. https://doi.org/10.1109/bigdata.congress.2013.14
- Beebe, Barton, Roy Germano, and Joel Steckel. 2026a. “Can Disclaimers of Affiliation Dispel Trademark Confusion? Evidence from Two Randomized Experiments.” Journal of Empirical Legal Studies 23 (2): 205–23. https://doi.org/10.1111/jels.70029
- Belazzougui, Djamal, and Rossano Venturini. 2012. “Compressed String Dictionary Look-Up with Edit Distance One.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-31265-6_23
- Belazzougui, Djamal, and Rossano Venturini. 2015. “Compressed String Dictionary Search with Edit Distance One.” Algorithmica 74 (3): 1099–1122. https://doi.org/10.1007/s00453-015-9990-0
- Ben Cheikha, I., M. Meftah, F. Sellami, N. Ben Fatma, and A. Abbassi. 2024. “Médicaments look-alike et médicaments sound-alike: détection des incidents et mesures correctives au sein d’un service pharmacie.” Le Pharmacien Clinicien 59 (2): e79-e80. https://doi.org/10.1016/j.phacli.2024.04.119
- Bessho, Masahiro, Shinsuke Kobayashi, Noboru Koshizuka, and Ken Sakamura. 2007. “A Pedestrian Navigation System Using Multiple Space-Identifying Devices Based on a Unique Identifier Framework.” In 2007 International Conference on Machine Learning and Cybernetics. IEEE. https://doi.org/10.1109/icmlc.2007.4370491
- Beyea, Suzanne C. 2007. “Confusing, Look-Alike, and Sound-Alike Medications.” AORN Journal 86 (5): 861–63. https://doi.org/10.1016/j.aorn.2007.10.008
- Bhat, K. Raghav, and Robert S. Gutzwiller. 2026. “Tall Man Lettering as a Solution for Look-Alike Sound-Alike Errors: A Systematic Literature Review.” Human Factors in Healthcare 9: 100123. https://doi.org/10.1016/j.hfh.2026.100123
- Bille, Philip. 2011. “Faster Approximate String Matching for Short Patterns.” Theory of Computing Systems 50 (3): 492–515. https://doi.org/10.1007/s00224-011-9322-y
- Bille, Philip, Rolf Fagerberg, and Inge Li Gørtz. n.d. “Improved Approximate String Matching and Regular Expression Matching on Ziv-Lempel Compressed Texts.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-73437-6_8
- Bille, Philip, Rolf Fagerberg, and Inge Li Gørtz. 2009. “Improved Approximate String Matching and Regular Expression Matching on Ziv-Lempel Compressed Texts.” ACM Transactions on Algorithms 6 (1): 1–14. https://doi.org/10.1145/1644015.1644018
- Blair, Philip, Carmel Eliav, Fiona Hasanaj, and Kfir Bar. 2021. “Balancing Speed and Accuracy in Neural-Enhanced Phonetic Name Matching.” In Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. Springer International Publishing. https://doi.org/10.1007/978-3-030-86517-7_17
- Blatt, Alexander, Martin Kocour, Karel Vesely, Igor Szoke, and Dietrich Klakow. 2022. “Call-Sign Recognition and Understanding for Noisy Air-Traffic Transcripts Using Surveillance Information.” In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. https://doi.org/10.1109/icassp43922.2022.9746301
- Boitsov, L. M. 2002. “Using Signature Hashing for Approximate String Matching.” Computational Mathematics and Modeling 13 (3): 314–26. https://doi.org/10.1023/a:1016014301288
- Bolton, Shaun C., Solomon Mbua, and David Storey. 2026. “A Global Unique Identifier (GUID) Tool for Niemann-Pick Diseases.” Molecular Genetics and Metabolism 147 (2): 109345. https://doi.org/10.1016/j.ymgme.2025.109345
- Bonner, Loren. 2020. “Name Confusion Can Happen with Rapid-Acting Insulins.” Pharmacy Today 26 (10): 43. https://doi.org/10.1016/j.ptdy.2020.10.022
- Boring, Dan. 1997. “The Development and Adoption of Nonproprietary, Established, and Proprietary Names for Pharmaceuticals.” Drug Information Journal 31 (3): 621–34. https://doi.org/10.1177/009286159703100301
- Borowska, Anna P. 2025. “Towards Enhanced Efficiency of Radiotelephony Communication – the Case of Native English Speakers.” In 2025 Integrated Communications, Navigation and Surveillance Conference (ICNS). IEEE. https://doi.org/10.1109/icns65417.2025.10976906
- Boschen, A. C., and R. K. Jones. 2004. “Aviation Language Problem: Improving Pilot-Controller Communication.” In International Professional Communication Conference, 2004. IPCC 2004. Proceedings.. IEEE. https://doi.org/10.1109/ipcc.2004.1375313
- Brengman, Malaika, Maggie Geuens, and Patrick De Pelsmacker. 2001. “The Impact of Consumer Characteristics and Campaign Related Factors on Brand Confusion in Print Advertising.” Journal of Marketing Communications 7 (4): 231–43. https://doi.org/10.1080/13527260127415
- Brown, Jeffrey P. 2004. “Closing the Communication Loop: Using Readback/Hearback to Support Patient Safety.” Joint Commission Journal on Quality and Safety 30 (8): 460–64. https://doi.org/10.1016/s1549-3741(04)30053-5
- Bryan, Rachel, Jeffrey K. Aronson, Alison Williams, and Sue Jordan. 2020. “The Problem of Look-Alike, Sound-Alike Name Errors: Drivers and Solutions.” British Journal of Clinical Pharmacology 87 (2): 386–94. https://doi.org/10.1111/bcp.14285
- Bunke, H., and J. Csirik. 1995. “Parametric String Edit Distance and Its Application to Pattern Recognition.” IEEE Transactions on Systems, Man, and Cybernetics 25 (1): 202–6. https://doi.org/10.1109/21.362950
- Bunker, Matthew D. 2015. “Mired in Confusion: Nominative Fair Use in Trademark Law and Freedom of Expression.” Communication Law and Policy 20 (3): 191–212. https://doi.org/10.1080/10811680.2015.1051915
- Burt, Jennifer S., and Julie K. Porter. 2022. “How Does Orthographic or Phonological Similarity Produce Repetition Blindness?” Language, Cognition and Neuroscience 37 (6): 686–706. https://doi.org/10.1080/23273798.2021.2016872
- Byrne, Eamonn, and Gerard Bury. 2018. “Barriers to the Medication Error Reporting Process within the Irish National Ambulance Service, a Focus Group Study.” Irish Journal of Medical Science (1971 -) 187 (4): 867–71. https://doi.org/10.1007/s11845-018-1745-x
- Cai, Dengchuan. 2017. “Stroke Effect on Legibility of Japanese Characters.” Human Factors and Ergonomics in Manufacturing & Service Industries 27 (2): 87–95. https://doi.org/10.1002/hfm.20694
- Calvo-Zaragoza, Jorge, Colin de la Higuera, and Jose Oncina. 2016. “Computing the Expected Edit Distance from a String to a PFA.” In Implementation and Application of Automata. Springer International Publishing. https://doi.org/10.1007/978-3-319-40946-7_4
- Cantone, Domenico, Simone Faro, and Arianna Pavone. 2025. “Approximate String Matching with Non-Overlapping Adjacent Unbalanced Translocations.” Mathematics 13 (13): 2103. https://doi.org/10.3390/math13132103
- Carbonnel, S., and E. Anquetil. n.d. “Lexicon Organization and String Edit Distance Learning for Lexical Post-Processing in Handwriting Recognition.” In Ninth International Workshop on Frontiers in Handwriting Recognition. IEEE. https://doi.org/10.1109/iwfhr.2004.63
- Cardosi, Kim. 1986. “Some Determining Factors of the Alphanumeric Category Effect.” Perception & Psychophysics 40 (5): 317–30. https://doi.org/10.3758/bf03203023
- Carothers, Nancy B. 1999. “An Analysis of Medication Errors: Look Alike and Sound Alike Names.” International Journal of Trauma Nursing 5 (1): 22–24. https://doi.org/10.1016/s1075-4210(99)90080-9
- Celik, Fatih, and Erdogan Koc. 2026. “From Confusion to Clarity: A Multi-Stage Process Framework for Understanding Consumer Confusion.” Journal of Consumer Behaviour 25 (5): 2720–46. https://doi.org/10.1002/cb.70195
- Chalasani, Sh, and R. Madhan. 2017. “Establishing a Medication Error Reporting and Monitoring Programme in a Developing Country’s Tertiary Care Teaching Hospital.” Value in Health 20 (9): A514. https://doi.org/10.1016/j.jval.2017.08.654
- Chalasani, Sri Harsha, Madhan Ramesh, and Parthasarathi Gurumurthy. 2018. “Pharmacist-Initiated Medication Error-Reporting and Monitoring Programme in a Developing Country Scenario.” Pharmacy 6 (4): 133. https://doi.org/10.3390/pharmacy6040133
- Chang, William I., and Jordan Lampe. 1992. “Theoretical and Empirical Comparisons of Approximate String Matching Algorithms.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-56024-6_14
- Chang, W. I., and E. L. Lawler. 1994. “Sublinear Approximate String Matching and Biological Applications.” Algorithmica 12 (4–5): 327–44. https://doi.org/10.1007/bf01185431
- Chang, William I., and Thomas G. Marr. 1994. “Approximate String Matching and Local Similarity.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-58094-8_23
- Chanyagorn, Pornchai, Bundid Kungwannarongkun, and Worrawan Chanyagorn. 2016. “Design of Electronic Nursing Kardex System for Medication Error Prevention in IPD Patients.” In 2016 6th IEEE International Conference on Control System, Computing and Engineering (ICCSCE). IEEE. https://doi.org/10.1109/iccsce.2016.7893585
- Chastain, Garvin. 1982. “Confusability and Interference between Members of Parafoveal Letter Pairs.” Perception & Psychophysics 32 (6): 576–80. https://doi.org/10.3758/bf03204213
- Chaturvedi, Abhijat, A. S. Cheema, P. K. Srivastava, Astha Rai, and Siddharth Srivastava. 2020. “Study and Analysis of Unique Health Identifiers and Applicability of Aadhaar as a Unique Health Identifier.” In 2020 IEEE 17th India Council International Conference (INDICON). IEEE. https://doi.org/10.1109/indicon49873.2020.9342439
- Chen, Chun-You, Ya-Lin Chen, Jeremiah Scholl, Hsuan-Chia Yang, and Yu-Chuan (Jack) Li. 2024. “Ability of Machine-Learning Based Clinical Decision Support System to Reduce Alert Fatigue, Wrong-Drug Errors, and Alert Users about Look Alike, Sound Alike Medication.” Computer Methods and Programs in Biomedicine 243: 107869. https://doi.org/10.1016/j.cmpb.2023.107869
- Cheng, Fangyuan, Guimin Jia, Jinfeng Yang, and Dan Li. 2018a. “Readback Error Classification of Radiotelephony Communication Based on Convolutional Neural Network.” In Biometric Recognition. Springer International Publishing. https://doi.org/10.1007/978-3-319-97909-0_62
- Chi-Chien Pan, Kai-Hsiang Yang, and Tzao-Lin Lee. 2002. “Approximate String Matching in LDAP Based on Edit Distance.” In Proceedings 16th International Parallel and Distributed Processing Symposium. IEEE. https://doi.org/10.1109/ipdps.2002.1016638
- Chiche, L., G. Thomas, S. Canavese, S. Branger, R. Jean, and J. M. Durand. 2008. “Severe Hemorrhagic Syndrome Due to Similarity of Drug Names.” European Journal of Internal Medicine 19 (2): 135–36. https://doi.org/10.1016/j.ejim.2007.03.018
- Christen, Peter. 2006. “A Comparison of Personal Name Matching: Techniques and Practical Issues.” In Sixth IEEE International Conference on Data Mining - Workshops (ICDMW’06). IEEE. https://doi.org/10.1109/icdmw.2006.2
- Christen, Peter, and Ross W. Gayler. 2015. “Context-Aware Approximate String Matching for Large-Scale Real-Time Entity Resolution.” In 2015 IEEE International Conference on Data Mining Workshop (ICDMW). IEEE. https://doi.org/10.1109/icdmw.2015.152
- Chung, Raymond. 2026. “Towards Proactive Air Traffic Safety with Speech LLMs: Transcription, Attribute Tagging, and Readback Detection.” In 2026 IEEE 50th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE. https://doi.org/10.1109/compsac69091.2026.00315
- Chung, Jen-Ming, Fu-Yuan Hsu, Cheng-Yu Lu, Hahn-Ming Lee, and Jan-Ming Ho. 2011. “Automatic English-Chinese Name Translation by Using Web-Mining and Phonetic Similarity.” In 2011 IEEE International Conference on Information Reuse & Integration. IEEE. https://doi.org/10.1109/iri.2011.6009560
- Ciociano, Nestor, and Lucia Bagnasco. 2013. “Look Alike/sound Alike Drugs: A Literature Review on Causes and Solutions.” International Journal of Clinical Pharmacy 36 (2): 233–42. https://doi.org/10.1007/s11096-013-9885-6
- Cocoros, Noelle M., Kevin Haynes, Qoua Her, et al. 2019. “Identification of Potential Drug Name Confusion Errors in the Sentinel System.” Pharmacoepidemiology and Drug Safety 28 (10): 1405–10. https://doi.org/10.1002/pds.4891
- Cohen, Michael R., and Neil M. Davis. 1992. “Drug Name Suffixes Can Cause Confusion.” American Pharmacy 32 (4): 21–22. https://doi.org/10.1016/s0160-3450(15)31167-3
- “Computer Algorithm Targets Possible Drug Name Confusions.” 2017. Reactions Weekly 1647 (1): 2–2. https://doi.org/10.1007/s40278-017-28695-x
- Cormode, Graham, and S. Muthukrishnan. 2007. “The String Edit Distance Matching Problem with Moves.” ACM Transactions on Algorithms 3 (1): 1–19. https://doi.org/10.1145/1186810.1186812
- Cosma, Antonio. 2025. “Unique Gating Strategy Identifier Based on the Prime Population System and Gödel Numbers.” Frontiers in Immunology 16: 1481412. https://doi.org/10.3389/fimmu.2025.1481412
- Cui, Zhenxin, and Chunhao Liu. 2019. “Research on Information Quantity Measurement of Aviation Safety Report.” In 2019 IEEE 1st International Conference on Civil Aviation Safety and Information Technology (ICCASIT). IEEE. https://doi.org/10.1109/iccasit48058.2019.8973128
- Das, Debarati, Jacob Gilbert, MohammadTaghi Hajiaghayi, Tomasz Kociumaka, and Barna Saha. 2025. “Dynamic Dyck and Tree Edit Distance: Decompositions and Reductions to String Edit Distance.” In 2025 IEEE 66th Annual Symposium on Foundations of Computer Science (FOCS). IEEE. https://doi.org/10.1109/focs63196.2025.00041
- de la Higuera, Colin, and Luisa Micó. 2008. “A Contextual Normalised Edit Distance.” In First International Workshop on Similarity Search and Applications (sisap 2008). IEEE. https://doi.org/10.1109/sisap.2008.17
- Debbarma, Abhijit, Bs Purkayastha, and Paritosh Bhattacharya. 2014. “Stemmer for Resource Scarce Language Using String Similarity Measure.” In 2014 International Conference on Reliability Optimization and Information Technology (ICROIT). IEEE. https://doi.org/10.1109/icroit.2014.6798299
- DeHenau, Carly, Mark W. Becker, Nora M. Bello, Sichang Liu, and Laura Bix. 2016. “Tallman Lettering as a Strategy for Differentiation in Look-Alike, Sound-Alike Drug Names: The Role of Familiarity in Differentiating Drug Doppelgangers.” Applied Ergonomics 52: 77–84. https://doi.org/10.1016/j.apergo.2015.06.009
- Dickens, David S., Diane Sinsabaugh, and James B. Fahner. 2007. “Characteristics of Pediatric Chemotherapy Medication Errors in a National Error Reporting Database.” Cancer 112 (2): 445–46. https://doi.org/10.1002/cncr.23177
- Dinh, Xuan Truong. 2023. “Name2Vec: Name Matching Using Character-Based with Deep Learning.” Procedia Computer Science 230: 305–15. https://doi.org/10.1016/j.procs.2023.12.086
- “Dispensing Errors/drug Name Confusion for Four GSK Inhalers.” 2018. Reactions Weekly 1703 (1): 1–1. https://doi.org/10.1007/s40278-018-46376-y
- Dong Deng, Guoliang Li, Jianhua Feng, and Wen-Syan Li. 2013. “Top-k String Similarity Search with Edit-Distance Constraints.” In 2013 IEEE 29th International Conference on Data Engineering (ICDE). IEEE. https://doi.org/10.1109/icde.2013.6544886
- Dowling, Helen, Girish Swaminathan, Colin Curtain, and Lynne Emmerton. 2019. “Automated Screening of Look-Alike, Sound-Alike Medicine Names for Safety.” Research in Social and Administrative Pharmacy 15 (5): e10-e11. https://doi.org/10.1016/j.sapharm.2019.03.095
- Drayton, Jenny, and Averil Coxhead. 2023. “The Development, Evaluation and Application of an Aviation Radiotelephony Specialised Technical Vocabulary List.” English for Specific Purposes 69: 51–66. https://doi.org/10.1016/j.esp.2022.10.001
- Droppo, Jasha, and Alex Acero. 2010. “Context Dependent Phonetic String Edit Distance for Automatic Speech Recognition.” In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE. https://doi.org/10.1109/icassp.2010.5495652
- Duan, Ying, Hua Long, and Yu Quan Qu. 2020. “Application of Improved BM Algorithm in String Approximate Matching.” Procedia Computer Science 166: 576–81. https://doi.org/10.1016/j.procs.2020.02.017
- Duñabeitia, Jon Andoni, Manuel Perea, and Manuel Carreiras. 2007. “Do Transposed-Letter Similarity Effects Occur at a Morpheme Level? Evidence for Morpho-Orthographic Decomposition.” Cognition 105 (3): 691–703. https://doi.org/10.1016/j.cognition.2006.12.001
- Dyab, Eman Ali, Ramadan Mohamed Elkalmi, Siti Halimah Bux, and Shazia Qasim Jamshed. 2018. “Exploration of Nurses’ Knowledge, Attitudes, and Perceived Barriers towards Medication Error Reporting in a Tertiary Health Care Facility: A Qualitative Approach.” Pharmacy 6 (4): 120. https://doi.org/10.3390/pharmacy6040120
- E.J. 1918. “Proprietary Drug Names.” American Journal of Ophthalmology 1 (7): 529. https://doi.org/10.1016/s0002-9394(18)90921-9
- Eier, Dieter, and Wolfgang Kampichler. 2026. “Impact of VoIP Induced Latency on Controller–Pilot Communication Dynamics.” In 2026 Integrated Communications, Navigation and Surveillance Conference (ICNS). IEEE. https://doi.org/10.1109/icns69853.2026.11570626
- Eko, Lyombe. 1998. “Trademark Parody and the Mass Media: Going beyond Survey Evidence in the Determination of “a Likelihood of Confusion”.” Communication Law and Policy 3 (4): 589–608. https://doi.org/10.1080/10811689809368665
- El-Mabrouk, Nadia, and Maxime Crochemore. 1996. “Boyer-Moore Strategy to Efficient Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-61258-0_2
- ElLithy, May Hassan, Hager Salah, Lamyaa Samir Abdelghani, Walid Assar, and Martin Corbally. 2023. “Benchmarking of Medication Incidents Reporting and Medication Error Rates in a JCI Accredited University Teaching Hospital at a GCC Country.” Saudi Pharmaceutical Journal 31 (9): 101726. https://doi.org/10.1016/j.jsps.2023.101726
- Emmerton, Lynne, Colin Curtain, Girish Swaminathan, and Helen Dowling. 2020. “Development and Exploratory Analysis of Software to Detect Look-Alike, Sound-Alike Medicine Names.” International Journal of Medical Informatics 137: 104119. https://doi.org/10.1016/j.ijmedinf.2020.104119
- Emmerton, Lynne M., and Mariam F. S. Rizk. 2011. “Look-Alike and Sound-Alike Medicines: Risks and ‘Solutions’.” International Journal of Clinical Pharmacy 34 (1): 4–8. https://doi.org/10.1007/s11096-011-9595-x
- Essex, Aleksander. 2019. “Secure Approximate String Matching for Privacy-Preserving Record Linkage.” IEEE Transactions on Information Forensics and Security 14 (10): 2623–32. https://doi.org/10.1109/tifs.2019.2903651
- Fayaz-Bakhsh, Ahmad, and Sadun Khezri. 2014. “The Impact of Computerized Physician Order Entry on Medication Error Prevention.” International Journal of Clinical Pharmacy 36 (6): 1097–98. https://doi.org/10.1007/s11096-014-0027-6
- Fenna, Donald. 1984. “Phonetic Reduction of Names.” Computer Programs in Biomedicine 19 (1): 31–36. https://doi.org/10.1016/0010-468x(84)90035-7
- Ferri, Junior, Hegler Tissot, and Marcos Didonet Del Fabro. 2018. “Integrating Approximate String Matching with Phonetic String Similarity.” In Advances in Databases and Information Systems. Springer International Publishing. https://doi.org/10.1007/978-3-319-98398-1_12
- Fhima, Ilanah, and Catrina Denvir. 2015. “An Empirical Analysis of the Likelihood of Confusion Factors in European Trade Mark Law.” IIC - International Review of Intellectual Property and Competition Law 46 (3): 310–39. https://doi.org/10.1007/s40319-015-0311-6
- Filik, Ruth, Jessica Price, Iain Darker, David Gerrett, Kevin Purdy, and Alastair Gale. 2010. “The Influence of Tall Man Lettering on Drug Name Confusion: A Laboratory-Based Investigation in the UK Using Younger and Older Adults and Healthcare Practitioners.” Drug Safety 33 (8): 677–87. https://doi.org/10.2165/11532360-000000000-00000
- Filik, Ruth, Kevin Purdy, Alastair Gale, and David Gerrett. 2004. “Drug Name Confusion: Evaluating the Effectiveness of Capital (“Tall Man”) Letters Using Eye Movement Data.” Social Science & Medicine 59 (12): 2597–2601. https://doi.org/10.1016/j.socscimed.2004.04.008
- Foxman, Ellen R., Phil W. Berger, and Joseph A. Cote. 1992. “Consumer Brand Confusion: A Conceptual Framework.” Psychology & Marketing 9 (2): 123–41. https://doi.org/10.1002/mar.4220090204
- Foxman, Ellen R., Darrel D. Muehling, and Phil W. Berger. 1990. “An Investigation of Factors Contributing to Consumer Brand Confusion.” Journal of Consumer Affairs 24 (1): 170–89. https://doi.org/10.1111/j.1745-6606.1990.tb00264.x
- Frances, Candice, Eugenia Navarra-Barindelli, and Clara D. Martin. 2021. “Inhibitory and Facilitatory Effects of Phonological and Orthographic Similarity on L2 Word Recognition across Modalities in Bilinguals.” Scientific Reports 11 (1): 12812. https://doi.org/10.1038/s41598-021-92259-z
- Frances, Candice, Eugenia Navarra-Barindelli, and Clara D. Martin. 2022. “Speaker Accent Modulates the Effects of Orthographic and Phonological Similarity on Auditory Processing by Learners of English.” Frontiers in Psychology 13: 892822. https://doi.org/10.3389/fpsyg.2022.892822
- Francis, Lucy. 2013. “More than Just a Number: The ORCID Unique Identifier for Academics and Their Research Activities.” Editors’ Bulletin 9 (2): 42–44. https://doi.org/10.1080/17521742.2013.870719
- Fredriksson, Kimmo. 2003. “Row-Wise Tiling for the Myers’ Bit-Parallel Approximate String Matching Algorithm.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-39984-1_6
- Fredriksson, Kimmo. 2004. “Metric Indexes for Approximate String Matching in a Dictionary.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-30213-1_30
- Fredriksson, Kimmo, and Gonzalo Navarro. 2003. “Average-Optimal Multiple Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-44888-8_9
- Fredriksson, Kimmo, and Gonzalo Navarro. 2004a. “Average-Optimal Single and Multiple Approximate String Matching.” ACM Journal of Experimental Algorithmics 9. https://doi.org/10.1145/1005813.1041513
- Fredriksson, Kimmo, and Gonzalo Navarro. 2004b. “Improved Single and Multiple Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-27801-6_35
- Gali, Najlah, Radu Mariescu-Istodor, Damien Hostettler, and Pasi Fränti. 2019. “Framework for Syntactic String Similarity Measures.” Expert Systems with Applications 129: 169–85. https://doi.org/10.1016/j.eswa.2019.03.048
- Galil, Z., and R. Giancarlo. 1988. “Data Structures and Algorithms for Approximate String Matching.” Journal of Complexity 4 (1): 33–72. https://doi.org/10.1016/0885-064x(88)90008-8
- Gawrychowski, Paweł. 2012. “Faster Algorithm for Computing the Edit Distance between SLP-Compressed Strings.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-34109-0_24
- George, Doris, Amar-Singh Hss, and Azmi Hassali. 2018. “Medication Error Reporting: Underreporting and Acceptability of Smartphone Application for Reporting among Health Care Professionals in Perak, Malaysia.” Cureus. https://doi.org/10.7759/cureus.2746
- Godwin, H. J., Michael C. Hout, and Tamaryn Menneer. 2013. “Visual Similarity Is Stronger than Semantic Similarity in Guiding Visual Search for Numbers.” Psychonomic Bulletin & Review 21 (3): 689–95. https://doi.org/10.3758/s13423-013-0547-4
- Goedecke, Thomas, Kathryn Ord, Victoria Newbould, Sabine Brosch, and Peter Arlett. 2016. “Medication Errors: New EU Good Practice Guide on Risk Minimisation and Error Prevention.” Drug Safety 39 (6): 491–500. https://doi.org/10.1007/s40264-016-0410-4
- Goth, Greg. 2009. “Unique Identifier Quandary Exemplifies Health Net Obstacles.” IEEE Internet Computing 13 (4): 6–10. https://doi.org/10.1109/mic.2009.92
- Greene, Stephanie M. 2006. “Sorting out “Fair Use” and “Likelihood of Confusion” in Trademark Law.” American Business Law Journal 43 (1): 43–77. https://doi.org/10.1111/j.1744-1714.2006.00011.x
- Grigor’eva, A. N. 1983. “Complexity Measures of Words Based on String Matching and Edit Distance.” Journal of Soviet Mathematics 22 (3): 1290–93. https://doi.org/10.1007/bf01084391
- Guo, Hui, Qian Guo, Xiuping Wang, Yonghong Liu, and Ze Wang. 2025. “Exploring Multidimensional Determinants of Medication Error Reporting in China: A Qualitative Study Using the Theoretical Domains Framework.” Frontiers in Pharmacology 16: 1590794. https://doi.org/10.3389/fphar.2025.1590794
- Guo, Siming, Xichen Jiang, Troy Thornton, and Daniel Saunders. 2019. “Approximate String Matching of Power System Substation Names.” In 2019 IEEE Power and Energy Conference at Illinois (PECI). IEEE. https://doi.org/10.1109/peci.2019.8698905
- Gurtov, Andrei, Tatiana Polishchuk, and Max Wernberg. 2018. “Controller–Pilot Data Link Communication Security.” Sensors 18 (5): 1636. https://doi.org/10.3390/s18051636
- Gvasalia, Sophie, Mauro Pelucchi, and Simone Perego. 2025. “Hybrid Ontology Matching for Company Name Alignment: Combining Text Matching, String Similarity, SBERT, and Siamese Networks in Italian and German Job Market Data.” In Flexible Query Answering Systems. Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-05607-8_19
- Haertzen, Charles A., and Frances E. Ross. 1980. “Knowledge of Drug Names Determines Associations to Drug Names More than Habits for the Drugs.” Drug and Alcohol Dependence 6 (6): 391–413. https://doi.org/10.1016/0376-8716(80)90022-8
- Hall, Patrick A. V., and Geoff R. Dowling. 1980. “Approximate String Matching.” ACM Computing Surveys 12 (4): 381–402. https://doi.org/10.1145/356827.356830
- Han, Jeong-Im, and Sujin Oh. 2018. “The Role of Phonetic Similarity and Orthographic Information in Asymmetrical Lexical Encoding in Second Language.” Journal of Psycholinguistic Research 47 (5): 1015–33. https://doi.org/10.1007/s10936-018-9574-7
- Handler, Steven M., David A. Nace, Stephanie A. Studenski, and Douglas B. Fridsma. 2004. “Medication Error Reporting in Long Term Care.” American Journal of Geriatric Pharmacotherapy 2 (3): 190–96. https://doi.org/10.1016/j.amjopharm.2004.09.003
- Harris, Lara, Andrew Olson, and Glyn Humphreys. 2013. “Overcoming the Effect of Letter Confusability in Letter-by-Letter Reading: A Rehabilitation Study.” Neuropsychological Rehabilitation 23 (3): 429–62. https://doi.org/10.1080/09602011.2013.776500
- Hashem, Rabab. 2025. “A Similarity-Based Memory Retrieval Model to Orthographic Processing.” Developmental Review 78: 101232. https://doi.org/10.1016/j.dr.2025.101232
- Hauk, Lisa. 2018. “Medication Safety Resources Provide Key Information on Error Prevention.” AORN Journal 107 (3). https://doi.org/10.1002/aorn.12104
- Hema, V. 2024. “Simplifying String Similarity: A Modern Evaluation of Minimum Edit Distance and N-Gram Overlap Efficiency.” In 2024 13th International Conference on System Modeling & Advancement in Research Trends (SMART). IEEE. https://doi.org/10.1109/smart63812.2024.10882561
- Hisa, Tomoyuki. 1996. “Drug Name Confusion between Patients and Doctor.” International Journal of Dermatology 35 (4): 303–303. https://doi.org/10.1111/j.1365-4362.1996.tb03013.x
- Ho, ThienLuan, Seung-Rohk Oh, and HyunJin Kim. 2017. “New Algorithms for Fixed-Length Approximate String Matching and Approximate Circular String Matching under the Hamming Distance.” Journal of Supercomputing 74 (5): 1815–34. https://doi.org/10.1007/s11227-017-2192-6
- Hoffman, James M., and Susan M. Proulx. 2003. “Medication Errors Caused by Confusion of Drug Names.” Drug Safety 26 (7): 445–52. https://doi.org/10.2165/00002018-200326070-00001
- Holmström, Anna-Riia, Raisa Laaksonen, and Marja Airaksinen. 2015. “How to Make Medication Error Reporting Systems Work – Factors Associated with Their Successful Development and Implementation.” Health Policy 119 (8): 1046–54. https://doi.org/10.1016/j.healthpol.2015.03.002
- Holub, Jan, and Bořivoj Melichar. 2000. “Approximate String Matching Using Factor Automata.” Theoretical Computer Science 249 (2): 305–11. https://doi.org/10.1016/s0304-3975(00)00064-5
- Hon, Wing-Kai, Tak-Wah Lam, Rahul Shah, Siu-Lung Tam, and Jeffrey Scott Vitter. n.d. “Cache-Oblivious Index for Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-73437-6_7
- Horsham, P. A. 2015. “Medication Error Prevention Is a Shared Responsibility.” Pharmacy Today 21 (3): 93. https://doi.org/10.1016/s1042-0991(15)30474-6
- Hout, Michael C., Jose Montelongo, Bryan L. White, Anita Hernandez, and Francisco Serrano-Wall. 2023. “Orthographic Similarity Ratings for English-Spanish Cognates from the Academic Word List.” Frontiers in Education 8: 1225169. https://doi.org/10.3389/feduc.2023.1225169
- Hrbek, Lukas, and Jan Holub. 2016. “Approximate String Matching for Self-Indexes.” In 2016 Data Compression Conference (DCC). IEEE. https://doi.org/10.1109/dcc.2016.25
- Hsiao, Janet H., and Kit Cheung. 2015. “Visual Similarity of Words Alone Can Modulate Hemispheric Lateralization in Visual Word Recognition: Evidence from Modeling Chinese Character Recognition.” Cognitive Science 40 (2): 351–72. https://doi.org/10.1111/cogs.12233
- Hull, Audrey J. 1976. “Reducing Sources of Human Error in Transmission of Alphanumeric Codes.” Applied Ergonomics 7 (2): 75–78. https://doi.org/10.1016/0003-6870(76)90152-6
- Humphrey, P. P. A., and E. A. Barnard. 1998. “International Union of Pharmacology. XIX. the IUPHAR Receptor Code: A Proposal for an Alphanumeric Classification System.” Pharmacological Reviews 50 (2): 271–77. https://doi.org/10.1016/s0031-6997(24)01361-9
- Hung, Chang-Chiao, Tsui-Ping Chu, Bih-O. Lee, and Chia-Chi Hsiao. 2015. “Nurses’ Attitude and Intention of Medication Administration Error Reporting.” Journal of Clinical Nursing 25 (3–4): 445–53. https://doi.org/10.1111/jocn.13071
- Hung, Chang-Chiao, Bih-O. Lee, Hwey-Fang Liang, and Tsui-Ping Chu. 2016. “Factors Influencing Nurses’ Attitudes and Intentions toward Medication Administration Error Reporting.” Japan Journal of Nursing Science 13 (3): 345–54. https://doi.org/10.1111/jjns.12113
- Hutchinson, Alison M., Anne E. Sales, Vanessa Brotto, and Tracey K. Bucknall. 2015. “Implementation of an Audit with Feedback Knowledge Translation Intervention to Promote Medication Error Reporting in Health Care: A Protocol.” Implementation Science 10 (1): 70. https://doi.org/10.1186/s13012-015-0260-y
- Huynh, Trinh N. D., Wing-Kai Hon, Tak-Wah Lam, and Wing-Kin Sung. 2004. “Approximate String Matching Using Compressed Suffix Arrays.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-27801-6_33
- Hyyrö, Heikki. 2003. “Bit-Parallel Approximate String Matching Algorithms with Transposition.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-39984-1_8
- Hyyrö, Heikki. 2004. “An Improvement and an Extension on the Hybrid Index for Approximate String Matching.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-30213-1_28
- Hyyrö, Heikki. 2005a. “Bit-Parallel Approximate String Matching Algorithms with Transposition.” Journal of Discrete Algorithms 3 (2–4): 215–29. https://doi.org/10.1016/j.jda.2004.08.006
- Hyyrö, Heikki. 2005b. “Restricted Transposition Invariant Approximate String Matching under Edit Distance.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/11575832_29
- Hyyrö, Heikki. 2008. “An Efficient Linear Space Algorithm for Consecutive Suffix Alignment under Edit Distance (Short Preliminary Paper).” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-89097-3_16
- Hyyrö, Heikki, and Gonzalo Navarro. 2002. “Faster Bit-Parallel Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-45452-7_18
- Hyyrö, Heikki, and Gonzalo Navarro. 2004. “Bit-Parallel Witnesses and Their Applications to Approximate String Matching.” Algorithmica 41 (3): 203–31. https://doi.org/10.1007/s00453-004-1108-z
- Ifada, Noor, Fika Hastarita Rachman, and Sri Wahyuni. 2023. “Character-Based String Matching Similarity Algorithms for Madurese Spelling Correction: A Preliminary Study.” In 2023 International Conference on Electrical Engineering and Informatics (ICEEI). IEEE. https://doi.org/10.1109/iceei59426.2023.10346716
- Ishihara, Noriko, and Han Eul Lee. 2021. “Face and (Im)politeness in Aviation English: The Pragmatics of Radiotelephony Communications.” Journal of Pragmatics 180: 102–13. https://doi.org/10.1016/j.pragma.2021.04.030
- Jember, Abebaw, Mignote Hailu, Anteneh Messele, Tesfaye Demeke, and Mohammed Hassen. 2018. “Proportion of Medication Error Reporting and Associated Factors among Nurses: A Cross Sectional Study.” BMC Nursing 17 (1): 9. https://doi.org/10.1186/s12912-018-0280-4
- Jia, Guimin, Fangyuan Cheng, Jinfeng Yang, and Dan Li. 2018. “Intelligent Checking Model of Chinese Radiotelephony Read-Backs in Civil Aviation Air Traffic Control.” Chinese Journal of Aeronautics 31 (12): 2280–89. https://doi.org/10.1016/j.cja.2018.10.001
- Jia, Guimin, and Junxian Li. 2022. “A Novel Strategy for Fine-Grained Semantic Verification of Civil Aviation Radiotelephony Read-Backs.” Chinese Journal of Aeronautics 35 (12): 266–77. https://doi.org/10.1016/j.cja.2022.05.005
- Jin Hwan Park. n.d. “Reconfigurable Parallel Approximate String Matching on FPGAs.” In 8th Euromicro Conference on Digital System Design (DSD’05). IEEE. https://doi.org/10.1109/dsd.2005.66
- Johnson, Barry. 1994. “English in Maritime Radiotelephony.” World Englishes 13 (1): 83–91. https://doi.org/10.1111/j.1467-971x.1994.tb00285.x
- Jokisch, Oliver, and Horst-Udo Hain. 2017. “A Trainable Method for the Phonetic Similarity Search in German Proper Names.” In Speech and Computer. Springer International Publishing. https://doi.org/10.1007/978-3-319-66429-3_4
- Jumde, Amol S., and Ravindra B. Keskar. 2020. “Supporting Uncertain Predicates in DBMS Using Approximate String Matching and Probabilistic Databases.” IEEE Access 8: 169070–81. https://doi.org/10.1109/access.2020.3021945
- Jupin, Joseph, Justin Y. Shi, and Eduard C. Dragut. 2016. “PSH: A Probabilistic Signature Hash Method with Hash Neighborhood Candidate Generation for Fast Edit-Distance String Comparison on Big Data.” In 2016 IEEE International Conference on Big Data (Big Data). IEEE. https://doi.org/10.1109/bigdata.2016.7840596
- Jupin, Joseph, Justin Y. Shi, and Zoran Obradovic. 2012. “Understanding Cloud Data Using Approximate String Matching and Edit Distance.” In 2012 SC Companion: High Performance Computing, Networking Storage and Analysis. IEEE. https://doi.org/10.1109/sc.companion.2012.149
- Kaleem, Mohammed, James D. O’Shea, and Keeley A. Crockett. 2014. “Word Order Variation and String Similarity Algorithm to Reduce Pattern Scripting in Pattern Matching Conversational Agents.” In 2014 14th UK Workshop on Computational Intelligence (UKCI). IEEE. https://doi.org/10.1109/ukci.2014.6930180
- Karas, Claire. 2016. “US Food and Drug Administration Unique Device Identifier Rule: Perioperative Basics.” AORN Journal 103 (3): 329–32. https://doi.org/10.1016/j.aorn.2016.01.002
- Karet, Gail B. 2023. “Linguistic Analysis of Generic-Generic Drug Name Pairs Prone to Wrong-Drug Errors for Which Tall-Man Lettering Is Recommended.” Therapeutic Innovation & Regulatory Science 57 (4): 751–58. https://doi.org/10.1007/s43441-023-00526-0
- Kärkkäinen, Juha, Gonzalo Navarro, and Esko Ukkonen. 2000. “Approximate String Matching over Ziv—Lempel Compressed Text.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-45123-4_18
- Karpov, Nikolai, Haoyu Zhang, and Qin Zhang. 2023. “MinJoin++: A Fast Algorithm for String Similarity Joins under Edit Distance.” VLDB Journal 33 (2): 281–99. https://doi.org/10.1007/s00778-023-00806-z
- Kashyap, R. L., and B. J. Oommen. 1981. “An Effective Algorithm for String Correction Using Generalized Edit Distance—II. Computational Complexity of the Algorithm and Some Applications.” Information Sciences 23 (3): 201–17. https://doi.org/10.1016/0020-0255(81)90056-6
- Katsumata, Akifumi, and Takao Miura. 2009. “Spatial Approximate String Matching.” In 2009 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing. IEEE. https://doi.org/10.1109/pacrim.2009.5291387
- Katsumata, A., T. Miura, and I. Shioya. 2010. “Approximate String Matching Using Markovian Distance.” In 2010 3rd International Symposium on Parallel Architectures, Algorithms and Programming. IEEE. https://doi.org/10.1109/paap.2010.11
- Kelling, Sarah E. 2017. “Look-Alike/sound-Alike Dietary Supplements.” Journal of the American Pharmacists Association 57 (3): 300–301. https://doi.org/10.1016/j.japh.2017.03.001
- Kennedy, Amanda G., and Benjamin Littenberg. 2004. “Medication Error Reporting by Community Pharmacists in Vermont.” Journal of the American Pharmacists Association 44 (4): 434–38. https://doi.org/10.1331/1544345041475724
- Kessler, Brett. 2005. “Phonetic Comparison Algorithms.” Transactions of the Philological Society 103 (2): 243–60. https://doi.org/10.1111/j.1467-968x.2005.00153.x
- Khalid, Madiha, Muhammad Murtaza Yousaf, and Muhammad Umair Sadiq. 2022. “Toward Efficient Similarity Search under Edit Distance on Hybrid Architectures.” Information 13 (10): 452. https://doi.org/10.3390/info13100452
- Khan, Suleman, Andrei Gurtov, An Breaken, and Pardeep Kumar. 2021. “A Security Model for Controller-Pilot Data Communication Link.” In 2021 Integrated Communications Navigation and Surveillance Conference (ICNS). IEEE. https://doi.org/10.1109/icns52807.2021.9441637
- Kiawkaew, Tip-Aroon, Natsuda Kaothanthong, and Thanaruk Theeramunkong. 2023. “A Practical Technique for Thai-English Word Mapping Using Phonetic Rules: Person Name Matching Case Study.” In 2023 18th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). IEEE. https://doi.org/10.1109/isai-nlp60301.2023.10354663
- Kim, Youn-hee. 2023. “The Challenges of Radiotelephony Communication and Effective Training Approaches: A Study of Korean Pilots and Air Traffic Controllers.” English for Specific Purposes 72: 26–39. https://doi.org/10.1016/j.esp.2023.07.001
- Kim, Siin, Hyungtae Kim, and Hae Sun Suh. 2022. “Priorities in the Prevention Strategies for Medication Error Using the Analytical Hierarchy Process Method.” Healthcare 10 (3): 512. https://doi.org/10.3390/healthcare10030512
- Kim, Mina, and Mary Lynn McPherson. 2012. “Medication Error Reporting Practices in Hospice (750).” Journal of Pain and Symptom Management 43 (2): 449–50. https://doi.org/10.1016/j.jpainsymman.2011.12.228
- Kim, Jong Yong, and John Shawe-Taylor. 1992. “An Approximate String-Matching Algorithm.” Theoretical Computer Science 92 (1): 107–17. https://doi.org/10.1016/0304-3975(92)90138-6
- Kinoshita, Sachiko, Lili Yu, Rinus Gerardus Verdonschot, and Dennis Graham Norris. 2021. “Letter Identity and Visual Similarity in the Processing of Diacritic Letters.” Memory & Cognition 49 (4): 815–25. https://doi.org/10.3758/s13421-020-01125-2
- Kiwi, Marcos, Gonzalo Navarro, and Claudio Telha. n.d. “On-Line Approximate String Matching with Bounded Errors.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-69068-9_14
- Kiwi, Marcos, Gonzalo Navarro, and Claudio Telha. 2011. “On-Line Approximate String Matching with Bounded Errors.” Theoretical Computer Science 412 (45): 6359–70. https://doi.org/10.1016/j.tcs.2011.08.005
- Knox, Dean. 2019. “Ffgrep: Scalable Approximate String Matching.” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3528533
- Koehler, Linda, Lyle Lloyd, and Lori Swanson. 1994. “Visual Similarity between Manual and Printed Alphabet Letters.” Augmentative and Alternative Communication 10 (2): 87–95. https://doi.org/10.1080/07434619412331276790
- Komatsu, Tomoki, Ryosuke Okuta, Kazuyuki Narisawa, and Ayumi Shinohara. 2014. “Bounded Occurrence Edit Distance: A New Metric for String Similarity Joins with Edit Distance Constraints.” In SOFSEM 2014: Theory and Practice of Computer Science. Springer International Publishing. https://doi.org/10.1007/978-3-319-04298-5_32
- Kondrak, Grzegorz. 2003. “Phonetic Alignment and Similarity.” Computers and the Humanities 37 (3): 273–91. https://doi.org/10.1023/a:1025071200644
- Kondrak, Grzegorz. 2005. “N-Gram Similarity and Distance.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/11575832_13
- Kondrak, Grzegorz, and Bonnie Dorr. 2006. “Automatic Identification of Confusable Drug Names.” Artificial Intelligence in Medicine 36 (1): 29–42. https://doi.org/10.1016/j.artmed.2005.07.005
- Kontorovich, A., and A. Trachtenberg. 2012. “String Reconciliation with Unknown Edit Distance.” In 2012 IEEE International Symposium on Information Theory Proceedings. IEEE. https://doi.org/10.1109/isit.2012.6284024
- Krauthgamer, Robert. 2013. “Efficient Approximation of Edit Distance.” In String Processing and Information Retrieval. Springer International Publishing. https://doi.org/10.1007/978-3-319-02432-5_3
- Kronrod, Ann, and Tina M. Lowrey. 2016. “Tastlé-Nestlé, Toogle-Google: The Effects of Similarity to Familiar Brand Names in Brand Name Innovation.” Journal of Business Research 69 (3): 1182–89. https://doi.org/10.1016/j.jbusres.2015.09.015
- Kuboi, Satoshi, Kensuke Baba, Shigeru Takano, and Kazuaki Murakami. 2014. “Approximate String Matching for Large-Scale Event Processing.” In 2014 Makassar International Conference on Electrical Engineering and Informatics (MICEEI). IEEE. https://doi.org/10.1109/miceei.2014.7067327
- Kucherov, Gregory, Kamil Salikhov, and Dekel Tsur. 2014. “Approximate String Matching Using a Bidirectional Index.” In Combinatorial Pattern Matching. Springer International Publishing. https://doi.org/10.1007/978-3-319-07566-2_23
- Kucherov, Gregory, Kamil Salikhov, and Dekel Tsur. 2016. “Approximate String Matching Using a Bidirectional Index.” Theoretical Computer Science 638: 145–58. https://doi.org/10.1016/j.tcs.2015.10.043
- Kuitunen, Sini, Mari Saksa, Justiina Tuomisto, and Anna-Riia Holmström. 2023. “Medication Errors Related to High-Alert Medications in a Paediatric University Hospital – a Cross-Sectional Study Analysing Error Reporting System Data.” BMC Pediatrics 23 (1): 548. https://doi.org/10.1186/s12887-023-04333-2
- Kysela, Jiří. 2018. “A Comparison of Text String Similarity Algorithms for POI Name Harmonisation.” In Articulated Motion and Deformable Objects. Springer International Publishing. https://doi.org/10.1007/978-3-319-94544-6_12
- Laarni, J. 1999. “Allocating Attention in the Visual Field: The Effects of Cue Type and Target–distractor Confusability.” Acta Psychologica 103 (3): 281–94. https://doi.org/10.1016/s0001-6918(99)00045-1
- Lambert, Bruce L., Runa Bhaumik, Weihan Zhao, and Dulal K. Bhaumik. 2015a. “Detection and Prediction Limits for Identifying Highly Confusable Drug Names from Experimental Data.” Journal of Biopharmaceutical Statistics 26 (2): 365–85. https://doi.org/10.1080/10543406.2015.1052481
- Lambert, Bruce L., Ken-Yu Chang, and Prahlad Gupta. 2003a. “Effects of Frequency and Similarity Neighborhoods on Pharmacists’ Visual Perception of Drug Names.” Social Science & Medicine 57 (10): 1939–55. https://doi.org/10.1016/s0277-9536(03)00059-5
- Lambert, Bruce L., Ken-Yu Chang, and Swu-Jane Lin. 2001. “Effect of Orthographic and Phonological Similarity on False Recognition of Drug Names.” Social Science & Medicine 52 (12): 1843–57. https://doi.org/10.1016/s0277-9536(00)00301-4
- Lambert, Bruce L., Don Donderi, and John W. Senders. 2002. “Similarity of Drug Names: Comparison of Objective and Subjective Measures.” Psychology & Marketing 19 (7–8): 641–61. https://doi.org/10.1002/mar.10029
- Lambert, Bruce L., Swu-Jane Lin, and HiangKiat Tan. 2005. “Designing Safe Drug Names.” Drug Safety 28 (6): 495–512. https://doi.org/10.2165/00002018-200528060-00003
- Landau, Gad M., and Uzi Vishkin. 1989. “Fast Parallel and Serial Approximate String Matching.” Journal of Algorithms 10 (2): 157–69. https://doi.org/10.1016/0196-6774(89)90010-2
- Lee, Chang Hun, and Marcus Taft. 2010. “Subsyllabic Structure Reflected in Letter Confusability Effects in Korean Word Recognition.” Psychonomic Bulletin & Review 18 (1): 129–34. https://doi.org/10.3758/s13423-010-0028-y
- Lehto, Andre, Isak Sestorp, Suleman Khan, and Andrei Gurtov. 2021. “Controller Pilot Data Link Communication Security: A Practical Study.” In 2021 Integrated Communications Navigation and Surveillance Conference (ICNS). IEEE. https://doi.org/10.1109/icns52807.2021.9441649
- Lévesque, Hervé, Nicholas Moore, and Hubert Courtois. 1991. “Reporting Adverse Drug Reactions by Proprietary Name.” Lancet 338 (8763): 393. https://doi.org/10.1016/0140-6736(91)90537-y
- Levy, Joseph. 2018. “The Confusion of Trademark Territoriality.” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3310978
- Li, Guoliang, Dong Deng, and Jianhua Feng. 2013. “A Partition-Based Method for String Similarity Joins with Edit-Distance Constraints.” ACM Transactions on Database Systems 38 (2): 1–33. https://doi.org/10.1145/2487259.2487261
- Li, Peining, Yandong Zheng, Hui Zhu, Qi Xu, Zhe Liu, and Hui Li. 2023. “Efficient and Private Edit Distance Based Range Query over Encrypted String Sequences.” In GLOBECOM 2023 - 2023 IEEE Global Communications Conference. IEEE. https://doi.org/10.1109/globecom54140.2023.10437476
- Liang, Yuchen, Yanan Cheng, Zhaoxin Zhang, Tingting Chai, and Chao Li. 2023. “Illegal Domain Name Generation Algorithm Based on Character Similarity of Domain Name Structure.” Applied Sciences 13 (6): 4061. https://doi.org/10.3390/app13064061
- Lin, Yi-Chen, Hsiang-Yu Chen, Yvonne C. Lai, and Denise Hsien Wu. 2014b. “Phonological Similarity and Orthographic Similarity Affect Probed Serial Recall of Chinese Characters.” Memory & Cognition 43 (3): 538–54. https://doi.org/10.3758/s13421-014-0495-x
- Lin, Chen, Haiyang Yu, Wei Weng, and Xianmang He. 2014a. “Large-Scale Similarity Join with Edit-Distance Constraints.” In Database Systems for Advanced Applications. Springer International Publishing. https://doi.org/10.1007/978-3-319-05813-9_22
- Little, J. 1973. “Impact of the ASCII Code and Printing Devices on Conventions for Alphanumeric Display Terminals: Part 1.” Communications Society 10 (1): 7–10. https://doi.org/10.1109/mcomd.1973.1145826
- Liu, J. J., G. S. Huang, Y. L. Wang, and R. C. T. Lee. 2007. “Edit Distance for a Run-Length-Encoded String and an Uncompressed String.” Information Processing Letters 105 (1): 12–16. https://doi.org/10.1016/j.ipl.2007.07.006
- Liu, Kaifeng, Calvin K. L. Or, and Simon Y. W. Li. 2019. “Visual Differentiation and Recognition Memory of Look-Alike Drug Names: Effects of Disfluent Format, Text Enhancement and Exposure Time.” Ergonomics 62 (10): 1289–1300. https://doi.org/10.1080/00140139.2019.1629637
- Liu, Pin-Ling, Chih-Ling Tsai, Kang-Hung Liu, and Chien-Chi Chang. 2025a. “AR vs. Physical Displays: Pharmacists’ Performance in Identifying Look-Alike Drug Names.” International Journal of Industrial Ergonomics 109: 103794. https://doi.org/10.1016/j.ergon.2025.103794
- Liu, Kaifeng, Yingjun Wan, Jialin Wei, and Hailiang Wang. 2026. “Effects of Text Enhancement on Visual Differentiation Performance of Chinese Look-Alike Drug Names: An Event-Related Potential Study.” International Journal of Industrial Ergonomics 114: 103959. https://doi.org/10.1016/j.ergon.2026.103959
- Lomax, Wendy, Emma Sherski, and Sarah Todd. 1999. “Assessing the Risk of Consumer Confusion: Some Practical Test Results.” Journal of Brand Management 7 (2): 119–32. https://doi.org/10.1057/bm.1999.45
- Lombardi, Manuel, Giulio Di Gravio, Antonio Licu, and Riccardo Patriarca. 2024. “An Expert System to Manage Call Sign Similarity for Safer Air Traffic Operations.” In 2024 New Trends in Civil Aviation (NTCA). IEEE. https://doi.org/10.23919/ntca60572.2024.10517810
- “Look-Alike and Sound-Alike Medication Errors.” 1997. Journal of the American Dental Association 128 (8): 1076. https://doi.org/10.1016/s0002-8177(15)60418-4
- Lopresti, Daniel, and Andrew Tomkins. 1997. “Block Edit Models for Approximate String Matching.” Theoretical Computer Science 181 (1): 159–79. https://doi.org/10.1016/s0304-3975(96)00268-x
- Lu, Wei, Xiaoyong Du, Marios Hadjieleftheriou, and Beng Chin Ooi. 2014. “Efficiently Supporting Edit Distance Based String Similarity Search Using B +-Trees.” IEEE Transactions on Knowledge and Data Engineering 26 (12): 2983–96. https://doi.org/10.1109/tkde.2014.2309131
- Lu, Yujun, Yihua Shi, Guimin Jia, and Jinfeng Yang. 2016. “A New Method for Semantic Consistency Verification of Aviation Radiotelephony Communication Based on LSTM-RNN.” In 2016 IEEE International Conference on Digital Signal Processing (DSP). IEEE. https://doi.org/10.1109/icdsp.2016.7868592
- Luján-Mora, Sergio, and Manuel Palomar. 2001. “Comparing String Similarity Measures for Reducing Inconsistency in Integrating Data from Different Sources.” In Advances in Web-Age Information Management. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-47714-4_18
- Mamunuwa, N., S. Jayamanne, N. Wijekoon, et al. 2023. “Duplication Errors Due to Brand Name Confusion; It Is Not Always the Name—Short Case Series.” Clinical Case Reports 11 (9): e7795. https://doi.org/10.1002/ccr3.7795
- Man, Duhu, Koji Nakano, and Yasuaki Ito. 2013. “The Approximate String Matching on the Hierarchical Memory Machine, with Performance Evaluation.” In 2013 IEEE 7th International Symposium on Embedded Multicore Socs. IEEE. https://doi.org/10.1109/mcsoc.2013.22
- Manning, Carol, Cynthia Fox, Elaine Pfleiderer, Scott Mills, and Henry Mogilka. 2002. “The Relationship between Air Traffic Control Communication Events and Measures of Controller Taskload and Workload.” Air Traffic Control Quarterly 10 (2): 69–83. https://doi.org/10.2514/atcq.10.2.69
- Marappa, U., and U. Reha Mallika. 2020. “PDG54 Establishment and Implementation of Medication Error Reporting in Community Pharmacies in Southern India.” Value in Health 23: S528. https://doi.org/10.1016/j.jval.2020.08.737
- Martinek, Tomas, Otto Fucik, Patrik Beck, and Matej Lexa. 2007. “Automatic Generation of Circuits for Approximate String Matching.” In 2007 IEEE Design and Diagnostics of Electronic Circuits and Systems. IEEE. https://doi.org/10.1109/ddecs.2007.4295281
- McClanahan, Kylie, and Qinghua Li. 2024. “Towards Automatically Matching Security Advisories to CPEs: String Similarity-Based Vendor Matching.” In 2024 International Conference on Computing, Networking and Communications (ICNC). IEEE. https://doi.org/10.1109/icnc59896.2024.10556231
- McCoy, Linda K. 2005. “Look-Alike, Sound-Alike Drugs Review: Include Look-Alike Packaging as an Additional Safety Check.” Joint Commission Journal on Quality and Patient Safety 31 (1): 47–53. https://doi.org/10.1016/s1553-7250(05)31007-5
- McKaig, Donald, Christine Collins, and Khaled A. Elsaid. 2014. “Impact of a Reengineered Electronic Error-Reporting System on Medication Event Reporting and Care Process Improvements at an Urban Medical Center.” Joint Commission Journal on Quality and Patient Safety 40 (9): 398-AP3. https://doi.org/10.1016/s1553-7250(14)40052-7
- Meadows, Alice, and Vera Koester. 2015. “ORCID – Unique Author Identifier.” ChemViews. https://doi.org/10.1002/chemv.201500088
- “Medication Error Prevention.” 2017. AORN Journal 106 (1). https://doi.org/10.1016/s0001-2092(17)30545-8
- “Medication Error Reporting System at a Portuguese University Hospital: Results of the First Six Months.” 2008. Drug Safety 31 (10): 885–960. https://doi.org/10.2165/00002018-200831100-00118
- Melichar, Bořivoj. 1995. “Approximate String Matching by Finite Automata.” In Computer Analysis of Images and Patterns. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-60268-2_315
- Menouar, Hamid, Fethi Filali, and Adnan Abu-Dayya. 2011. “Efficient and Unique Identifier for V2X Events Aggregation in the Local Dynamic Map.” In 2011 11th International Conference on ITS Telecommunications. IEEE. https://doi.org/10.1109/itst.2011.6060084
- Mergen, Sérgio. 2022. “Extending the Bag Distance for String Similarity Search.” SN Computer Science 4 (2): 95. https://doi.org/10.1007/s42979-022-01502-5
- Mhiri, A., A. Babbou, R. Golli, N. Kalboussi, and B. Kacem. 2022. “Évaluation des connaissances des médicaments look-alike sound-alike par les professionnels de santé.” Le Pharmacien Clinicien 57 (4): e115-e116. https://doi.org/10.1016/j.phacli.2022.10.576
- Michailidis, P. D., and K. G. Margaritis. 2005. “A Programmable Array Processor Architecture for Flexible Approximate String Matching Algorithms.” In 2005 International Conference on Parallel Processing Workshops (ICPPW’05). IEEE. https://doi.org/10.1109/icppw.2005.15
- Miller, Marlene R. 2007. “Reply to Characteristics of Pediatric Chemotherapy Medication Errors in a National Error Reporting Database.” Cancer 112 (2): 446–446. https://doi.org/10.1002/cncr.23178
- Mittal, Ankush, Pooja Bhatt, and Padam Kumar. 2014. “Phonetic Matching and Syntactic Tree Similarity Based QA System for SMS Queries.” In 2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE). IEEE. https://doi.org/10.1109/icgccee.2014.6921412
- Mohd Anuar, Fatahiyah, Rossitza Setchi, and Yu-Kun Lai. 2014. “Trademark Retrieval Based on Phonetic Similarity.” In 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE. https://doi.org/10.1109/smc.2014.6974151
- Montalvo, Soto, Eduardo G. Pardo, Raquel Martinez, and Victor Fresno. 2012. “Automatic Cognate Identification Based on a Fuzzy Combination of String Similarity Measures.” In 2012 IEEE International Conference on Fuzzy Systems. IEEE. https://doi.org/10.1109/fuzz-ieee.2012.6250802
- Morgan, Byron J. T., S. M. Chambers, and John Morton. 1973. “Acoustic Confusion of Digits in Memory and Recognition.” Perception & Psychophysics 14 (2): 375–83. https://doi.org/10.3758/bf03212408
- Morris, Serena, Lamar Haye, Ian McGowan, Raheem Gordon, Giselle Smalling, and Justin Brown. 2026. “A Comparative Study of Jaccard Similarity, Exact String Matching, and SQL Pattern Search Methods.” In SoutheastCon 2026. IEEE. https://doi.org/10.1109/southeastcon63549.2026.11476105
- Morris, Alison L., and Mary Lynn Still. 2012. “Orthographic Similarity: The Case of “Reversed Anagrams”.” Memory & Cognition 40 (5): 779–90. https://doi.org/10.3758/s13421-012-0183-7
- Morrow, Daniel, Alfred Lee, and Michelle Rodvold. 1993. “Analysis of Problems in Routine Controller-Pilot Communication.” International Journal of Aviation Psychology 3 (4): 285–302. https://doi.org/10.1207/s15327108ijap0304_3
- Morrow, Daniel, Michelle Rodvold, and Alfred Lee. 1994. “Nonroutine Transactions in Controller-Pilot Communication.” Discourse Processes 17 (2): 235–58. https://doi.org/10.1080/01638539409544868
- Mutalib, Nor Syahidah Abdul, and Shahrul Azman Noah. 2011. “Phonetic Coding Methods for Malay Names Retrieval.” In 2011 International Conference on Semantic Technology and Information Retrieval. IEEE. https://doi.org/10.1109/stair.2011.5995776
- Muthukrishnan, S. n.d. “Detecting False Matches in String Matching Algorithms.” In Combinatorial Pattern Matching. Springer-Verlag. https://doi.org/10.1007/bfb0029804
- Myers, Gene. 1998. “A Fast Bit-Vector Algorithm for Approximate String Matching Based on Dynamic Programming.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/bfb0030777
- Nagata, Tomoyuki, Masaomi Kimura, and Fumito Tsuchiya. 2014. “Similarity Index for Sound-Alikeness of Drug Names with Pitch Accents.” Procedia Computer Science 35: 1519–28. https://doi.org/10.1016/j.procs.2014.08.235
- Nakagawa, Shunta, Tokio Sakamoto, Yoshimasa Takabatake, I. Tomohiro, Kilho Shin, and Hiroshi Sakamoto. 2018. “Privacy-Preserving String Edit Distance with Moves.” In Similarity Search and Applications. Springer International Publishing. https://doi.org/10.1007/978-3-030-02224-2_18
- Nakano, Koji. 2012. “Efficient Implementations of the Approximate String Matching on the Memory Machine Models.” In 2012 Third International Conference on Networking and Computing. IEEE. https://doi.org/10.1109/icnc.2012.43
- Nakano, Koji. 2013. “Optimal Implementations of the Approximate String Matching and the Approximate Discrete Signal Matching on the Memory Machine Models.” International Journal of Parallel, Emergent and Distributed Systems 29 (2): 104–18. https://doi.org/10.1080/17445760.2013.773330
- Narita, Kazuyo, Shinji Nakadai, and Takuya Araki. 2012. “Landmark-Join: Hash-Join Based String Similarity Joins with Edit Distance Constraints.” In Data Warehousing and Knowledge Discovery. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-32584-7_15
- Naunton, Mark, Greg Kyle, and Hayley Gardiner. 2015. “Look-Alike, Sound-Alike Medication Errors: A Novel Case Concerning a Slow-Na, Slow-K Prescribing Error.” International Medical Case Reports Journal: 51. https://doi.org/10.2147/imcrj.s78637
- Navarro, Gonzalo. 2001. “A Guided Tour to Approximate String Matching.” ACM Computing Surveys 33 (1): 31–88. https://doi.org/10.1145/375360.375365
- Navarro, Gonzalo, and Ricardo Baeza-Yates. 1999a. “A New Indexing Method for Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-48452-3_13
- Navarro, Gonzalo, and Ricardo Baeza-Yates. 1999b. “Very Fast and Simple Approximate String Matching.” Information Processing Letters 72 (1–2): 65–70. https://doi.org/10.1016/s0020-0190(99)00121-0
- Navarro, Gonzalo, and Edgar Chávez. 2006. “A Metric Index for Approximate String Matching.” Theoretical Computer Science 352 (1–3): 266–79. https://doi.org/10.1016/j.tcs.2005.11.037
- Navarro, Gonzalo, and Kimmo Fredriksson. 2004. “Average Complexity of Exact and Approximate Multiple String Matching.” Theoretical Computer Science 321 (2–3): 283–90. https://doi.org/10.1016/j.tcs.2004.03.058
- Neelakantan, Murali, Parth Sharma, and Ashish Kulkarni. 2024. “Look-Alike, Sound-Alike (LASA) Drugs in India.” Lancet Regional Health - Southeast Asia 26: 100425. https://doi.org/10.1016/j.lansea.2024.100425
- Nesbitt, Gerry C., and Patricia A. Murphy. 2022. “CRID: A Unique, Universal, Patient-Generated Identifier to Facilitate Collaborative Rare Disease Clinical Research.” Informatics in Medicine Unlocked 31: 100973. https://doi.org/10.1016/j.imu.2022.100973
- Nguyen, Thi Thuy Anh, and Stefan Conrad. 2015. “An Improved String Similarity Measure Based on Combining Information-Theoretic and Edit Distance Methods.” In Knowledge Discovery, Knowledge Engineering and Knowledge Management. Springer International Publishing. https://doi.org/10.1007/978-3-319-25840-9_15
- Ni, Jiaqi, Xinru Tang, and Li Chen. 2023. “Medication Overdose Data Analysis: A Review of Medication Error Reports in the FDA Adverse Event Reporting System (FAERS).” BMC Pharmacology and Toxicology 24 (1): 41. https://doi.org/10.1186/s40360-023-00681-y
- Nydert, Per, Antonia Kumlien, Mikael Norman, and Synnöve Lindemalm. 2020. “Cross-Sectional Study Identifying High-Alert Substances in Medication Error Reporting among Swedish Paediatric Inpatients.” Acta Paediatrica 109 (12): 2810–19. https://doi.org/10.1111/apa.15273
- Oerthel, Aurélie, Valérie Guerreiro, Vanessa Venon, Isabelle Bonnet, and Xavier Bohand. 2020. “Le problème des médicaments look alike/sound alike pendant la crise de Covid-19.” Oxymag 33 (175): 8–10. https://doi.org/10.1016/j.oxy.2020.10.004
- Olden, Matthias, Rolf Holle, Iris M. Heid, and Klaus Stark. 2016. “IDGenerator: Unique Identifier Generator for Epidemiologic or Clinical Studies.” BMC Medical Research Methodology 16 (1): 120. https://doi.org/10.1186/s12874-016-0222-3
- Oppolzer, Jan, and Robert Bestak. 2012a. “Distributed pHysical Cell Identifier Assignment Algorithm in Femtocell Networks.” In 2012 IFIP Wireless Days. IEEE. https://doi.org/10.1109/wd.2012.6402878
- Oppolzer, Jan, and Robert Bestak. 2012b. “Physical Cell Identifier Assignment in Dense Home Evolved NodeB Deployment.” In 2012 Sixth International Conference on Next Generation Mobile Applications, Services and Technologies. IEEE. https://doi.org/10.1109/ngmast.2012.48
- Oppolzer, Jan, and Robert Bestak. 2012c. “Physical Cell Identifier Assignment in LTE-Advanced Networks.” In 2012 5th Joint IFIP Wireless and Mobile Networking Conference (WMNC). IEEE. https://doi.org/10.1109/wmnc.2012.6416150
- Oppolzer, Jan, and Robert Bestak. 2013. “Cell Identifier Assignment in Two-Tier Femtocell Networks.” In 2013 IEEE 77th Vehicular Technology Conference (VTC Spring). IEEE. https://doi.org/10.1109/vtcspring.2013.6692470
- Owolabi, O., and J. D. Ferguson. 1988. “Approximate String Matching: Investigations with a Hardware String Comparator.” In Pattern Recognition. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-19036-8_54
- Owolabi, O., and D. R. McGregor. 1988. “Fast Approximate String Matching.” Software: Practice and Experience 18 (4): 387–93. https://doi.org/10.1002/spe.4380180407
- Pal, Kreeti, Bidanisa Shira, Bandana Moktan, and Sanjay Kumar. 2025. “A Study of Assessing the Knowledge and Attitude of Nurses Regarding Medication Administration and Barriers in Reporting Medication Error in a Tertiary Care Teaching Hospital in Gangtok.” Hospital Topics 104 (3): 291–97. https://doi.org/10.1080/00185868.2025.2474756
- Pan, Weijun, Boyuan Han, and Peiyuan Jiang. 2025. “Study on the Standardization Method of Radiotelephony Communication in Low-Altitude Airspace Based on BART.” Frontiers in Neurorobotics 19: 1482327. https://doi.org/10.3389/fnbot.2025.1482327
- Pang-Yen Hsu. 2006. “Implementation of a Knowledge-Based System for Automatic Part Numbering in a Logistics Information System.” In 2006 IEEE International Conference on Service Operations and Logistics, and Informatics. IEEE. https://doi.org/10.1109/soli.2006.236434
- Papamichail, Dimitris, and Georgios Papamichail. 2009. “Improved Algorithms for Approximate String Matching (Extended Abstract).” BMC Bioinformatics 10 (S1): S10. https://doi.org/10.1186/1471-2105-10-s1-s10
- Paparella, Susan. 2008. “Choosing the Right Strategy for Medication Error Prevention—Part II.” Journal of Emergency Nursing 34 (3): 238–40. https://doi.org/10.1016/j.jen.2008.01.011
- Paramonov, Viacheslav V., Alexey O. Shigarov, Gennagy M. Ruzhnikov, and Polina V. Belykh. 2016. “Polyphon: An Algorithm for Phonetic String Matching in Russian Language.” In Information and Software Technologies. Springer International Publishing. https://doi.org/10.1007/978-3-319-46254-7_46
- Pelamatti, G. M., C. Umiltà, E. Vivalda, and G. Castagneri. 1983. “Effects of Phonetic Similarity and Order of Report on the Right Ear Advantage.” Cortex 19 (3): 393–405. https://doi.org/10.1016/s0010-9452(83)80008-2
- Peressotti, Francesca, Roberto Cubelli, and Remo Job. 2003. “On Recognizing Proper Names: The Orthographic Cue Hypothesis.” Cognitive Psychology 47 (1): 87–116. https://doi.org/10.1016/s0010-0285(03)00004-5
- Perveen, Feroza. 2026. “CT-015: Assessment of Awareness Regarding Look-Alike, Sound-Alike Medications among Healthcare Professionals: A Real Thread to Ensure Safe Medication Practices.” Clinical Lymphoma Myeloma and Leukemia 26: S1213-S1214. https://doi.org/10.1016/s2152-2650(26)03106-x
- Petty, Taylor, Jan Hannig, Tunde I. Huszar, and Hari Iyer. 2022. “A New String Edit Distance and Applications.” Algorithms 15 (7): 242. https://doi.org/10.3390/a15070242
- Pevzner, Pavel A., and Michael S. Waterman. n.d. “A Fast Filtration Algorithm for the Substring Matching Problem.” In Combinatorial Pattern Matching. Springer-Verlag. https://doi.org/10.1007/bfb0029806
- “The Pharmacy Technician’s Role in Medication Error Prevention.” 2014. Pharmacy Today 20 (1): 76. https://doi.org/10.1016/s1042-0991(15)31035-5
- Phoophuangpairoj, Rong, Panrawe Boonsom, and Piyarat Pipattarasakul. 2024. “Thai-English Name Matching Using Google Translation and Thai Romanization.” In 2024 12th International Electrical Engineering Congress (iEECON). IEEE. https://doi.org/10.1109/ieecon60677.2024.10537980
- Phuduhudu, Kanegelo, Michael Moeti, Tlou Ramabu, and Dan Masethe. 2025. “Automatic Grading of Linux Commands Using String Similarity Measures.” In 2025 IST-Africa Conference (IST-Africa). IEEE. https://doi.org/10.23919/ist-africa67297.2025.11060501
- Piskorski, Jakub, Karol Wieloch, and Marcin Sydow. 2009. “On Knowledge-Poor Methods for Person Name Matching and Lemmatization for Highly Inflectional Languages.” Information Retrieval 12 (3): 275–99. https://doi.org/10.1007/s10791-008-9085-5
- Pissis, Solon, and Ahmad Retha. 2015. “Generalised Implementation for Fixed-Length Approximate String Matching under Hamming Distance and Applications.” In 2015 IEEE International Parallel and Distributed Processing Symposium Workshop. IEEE. https://doi.org/10.1109/ipdpsw.2015.106
- Podgorny, Peter, and Wendell R. Garner. 1979. “Reaction Time as a Measure of Inter- and Intraobject Visual Similarity: Letters of the Alphabet.” Perception & Psychophysics 26 (1): 37–52. https://doi.org/10.3758/bf03199860
- Policriti, Alberto, and Nicola Prezza. 2015. “Fast Randomized Approximate String Matching with Succinct Hash Data Structures.” BMC Bioinformatics 16 (S9): S4. https://doi.org/10.1186/1471-2105-16-s9-s4
- Post, Yolanda V., and Suzanne Carrecker. 2002. “Orthographic Similarity and Phonological Transparency in Spelling.” Reading and Writing 15 (3–4): 317–40. https://doi.org/10.1023/a:1015213005350
- Pouliquen, Bruno. 2008. “Similarity of Names across Scripts: Edit Distance Using Learned Costs of N-Grams.” In Advances in Natural Language Processing. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-85287-2_39
- “Predicting Drug Name Confusion.” 1997. Inpharma Weekly 1093 (1): 21–21. https://doi.org/10.1007/bf03315223
- Propp, Douglas A. 2000. “Sound-Alike and Look-Alike Drugs an Overdue Opportunity to Reduce Medical Errors.” Academic Emergency Medicine 7 (11): 1334–35. https://doi.org/10.1111/j.1553-2712.2000.tb00486.x
- Rani, Shama, and Jaiteg Singh. 2018. “Enhancing Levenshtein’s Edit Distance Algorithm for Evaluating Document Similarity.” In Computing, Analytics and Networks. Springer Singapore. https://doi.org/10.1007/978-981-13-0755-3_6
- Rankin, J. M., and P. R. Mattson. n.d. “Controller Interface for Controller-Pilot Data Link Communications.” In 16th DASC. AIAA/IEEE Digital Avionics Systems Conference. Reflections to the Future. Proceedings, vol. 2. IEEE. https://doi.org/10.1109/dasc.1997.637221
- Rice, S. V., H. Bunke, and T. A. Nartker. 1997. “Classes of Cost Functions for String Edit Distance.” Algorithmica 18 (2): 271–80. https://doi.org/10.1007/bf02526038
- Rico-Juan, Juan R., Jose J. Valero-Mas, and José M. Iñesta. 2020. “Bounding Edit Distance for Similarity-Based Sequence Classification on Structural Pattern Recognition.” Applied Soft Computing 97: 106778. https://doi.org/10.1016/j.asoc.2020.106778
- Rider, Briana B., Hina Mehta, and Lubna Merchant. 2019. “Special Considerations for Proprietary Name Review: Focus on Products That May Be Prescribed “as Directed”.” Therapeutic Innovation & Regulatory Science 53 (3): 381–86. https://doi.org/10.1177/2168479018782669
- Ristad, E. S., and P. N. Yianilos. 1998. “Learning String-Edit Distance.” IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (5): 522–32. https://doi.org/10.1109/34.682181
- Rosenshine, Matthew. 1968. “Communications Constraint in the Air Traffic Control System.” Journal of Aircraft 5 (4): 355–58. https://doi.org/10.2514/3.43950
- Russo, Luís M. S., Gonzalo Navarro, and Arlindo L. Oliveira. n.d. “Approximate String Matching with Lempel-Ziv Compressed Indexes.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-75530-2_24
- Russo, Luís M. S., Gonzalo Navarro, and Arlindo L. Oliveira. 2008. “Indexed Hierarchical Approximate String Matching.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-89097-3_15
- Russo, Luís M. S., Gonzalo Navarro, Arlindo L. Oliveira, and Pedro Morales. 2009. “Approximate String Matching with Compressed Indexes.” Algorithms 2 (3): 1105–36. https://doi.org/10.3390/a2031105
- Rutledge, Dana N., Tina Retrosi, and Gary Ostrowski. 2018. “Barriers to Medication Error Reporting among Hospital Nurses.” Journal of Clinical Nursing 27 (9–10): 1941–49. https://doi.org/10.1111/jocn.14335
- Salmela, Leena, and Jorma Tarhio. 2010. “Approximate String Matching with Reduced Alphabet.” In Algorithms and Applications. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-12476-1_15
- Salmela, Leena, Jorma Tarhio, and Petri Kalsi. 2009. “Approximate Boyer-Moore String Matching for Small Alphabets.” Algorithmica 58 (3): 591–609. https://doi.org/10.1007/s00453-009-9286-3
- Samsiah, A., Noordin Othman, Shazia Jamshed, Mohamed Azmi Hassali, and W. M. Wan-Mohaina. 2016a. “Medication Errors Reported to the National Medication Error Reporting System in Malaysia: A 4-Year Retrospective Review (2009 to 2012).” European Journal of Clinical Pharmacology 72 (12): 1515–24. https://doi.org/10.1007/s00228-016-2126-x
- Sanders, Stuart, and A. B. Shaw. 1991. “Drug Name Confusion.” Lancet 338 (8758): 56–57. https://doi.org/10.1016/0140-6736(91)90048-t
- Sandlin, Debbie. 2008. “Pediatric Medication Error Prevention.” Journal of PeriAnesthesia Nursing 23 (4): 279–81. https://doi.org/10.1016/j.jopan.2008.05.007
- Sangurai, Nuanprang, Soontaree Thumsuwan, and Chouvalit Khancome. 2024. “Backward Inverted Lists Approximate String Matching Algorithm.” In 2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE). IEEE. https://doi.org/10.1109/jcsse61278.2024.10613631
- Sarvadikar, Ajit, Gordon Prescott, and David Williams. 2010. “Attitudes to Reporting Medication Error among Differing Healthcare Professionals.” European Journal of Clinical Pharmacology 66 (8): 843–53. https://doi.org/10.1007/s00228-010-0838-x
- Sauleau, Erik A., Jean-Philippe Paumier, and Antoine Buemi. 2005. “Medical Record Linkage in Health Information Systems by Approximate String Matching and Clustering.” BMC Medical Informatics and Decision Making 5 (1): 32. https://doi.org/10.1186/1472-6947-5-32
- Schlosser, E., A. L. Hincapie, and E. Grube. 2025. “1113 Evaluating Perceptions of Medication Error Reporting and Patient Safety in a Large Physician’s Network.” Journal of the American Pharmacists Association 65 (5): 102598. https://doi.org/10.1016/j.japh.2025.102598
- Schraagen, Marijn. 2011. “Complete Coverage for Approximate String Matching in Record Linkage Using Bit Vectors.” In 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence. IEEE. https://doi.org/10.1109/ictai.2011.116
- Scott, Clifford D. 2013. “Trademark Strategy in the Internet Age: Customer Hijacking and the Doctrine of Initial Interest Confusion.” Journal of Retailing 89 (2): 176–89. https://doi.org/10.1016/j.jretai.2012.11.004
- Senft, Donna J. 2007. “Significant Medication Error Citations without an Observed Medication Pass.” Geriatric Nursing 28 (1): 25–26. https://doi.org/10.1016/j.gerinurse.2006.11.001
- Seoane-Vazquez, Enrique, Rosa Rodriguez-Monguio, Saad Alqahtani, and Gordon Schiff. 2017. “Exploring the Potential for Using Drug Indications to Prevent Look-Alike and Sound-Alike Drug Errors.” Expert Opinion on Drug Safety 16 (10): 1103–9. https://doi.org/10.1080/14740338.2017.1358361
- Shah, Millie B., Lubna Merchant, Irene Z. Chan, and Kellie Taylor. 2017. “Characteristics That May Help in the Identification of Potentially Confusing Proprietary Drug Names.” Therapeutic Innovation & Regulatory Science 51 (2): 232–36. https://doi.org/10.1177/2168479016667161
- Shaikh, Muniba, Nasrullah Memon, and Uffe Kock Wiil. 2011. “Extended Approximate String Matching Algorithms to Detect Name Aliases.” In Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics. IEEE. https://doi.org/10.1109/isi.2011.5984085
- Shang, H., and T. H. Merrettal. 1996. “Tries for Approximate String Matching.” IEEE Transactions on Knowledge and Data Engineering 8 (4): 540–47. https://doi.org/10.1109/69.536247
- Shapira, Dana, and James A. Storer. 2003. “Large Edit Distance with Multiple Block Operations.” In String Processing and Information Retrieval. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-39984-1_29
- Shen, Yuxi, and Guimin Jia. 2025. “A Standardization Check Model for Radiotelephony Communication Based on Graph Convolutional Networks and Feature Fusion.” In 2025 IEEE 7th International Conference on Communications, Information System and Computer Engineering (CISCE). IEEE. https://doi.org/10.1109/cisce65916.2025.11065004
- Shiu, Jerry Yuwen. 2021. “Risk-Reduction Strategies in Competitive Convenience Retail: How Brand Confusion Can Impact Choice among Existing Similar Alternatives.” Journal of Retailing and Consumer Services 61: 102547. https://doi.org/10.1016/j.jretconser.2021.102547
- Showman, Diana J. 1967. “The Relative Legibility of Leroy and Lincoln/Mitre Alphanumeric Symbols.” Information Display 4 (2): 31–34. https://doi.org/10.1002/j.2637-496x.1967.tb01533.x
- Siew, Cynthia S. Q. 2018. “The Orthographic Similarity Structure of English Words: Insights from Network Science.” Applied Network Science 3 (1): 13. https://doi.org/10.1007/s41109-018-0068-1
- Skaltsas, Gerasimos, Jasenka Rakas, and Matthew G. Karlaftis. 2013. “An Analysis of Air Traffic Controller-Pilot Miscommunication in the NextGen Environment.” Journal of Air Transport Management 27: 46–51. https://doi.org/10.1016/j.jairtraman.2012.11.010
- Smith, Elida C. 2008. “Analysis of Controller-Pilot Communication Performance in Area Navigation (RNAV) and Conventional Arrival Operations.” In 2008 IEEE/AIAA 27th Digital Avionics Systems Conference. IEEE. https://doi.org/10.1109/dasc.2008.4702825
- Smith, D., and E. Pierzchala. n.d. “An Algorithm and Architecture for Approximate String Matching.” In Proceedings of the 33rd Midwest Symposium on Circuits and Systems. IEEE. https://doi.org/10.1109/mwscas.1990.140825
- Soman, Sumit, Praveen Srivastava, and B. K. Murthy. 2015. “Unique Health Identifier for India: An Algorithm and Feasibility Analysis on Patient Data.” In 2015 17th International Conference on E-health Networking, Application & Services (HealthCom). IEEE. https://doi.org/10.1109/healthcom.2015.7454507
- “Some Factors Affecting Legibility of Printed Materials for Older Adults.” 1981. Applied Ergonomics 12 (4): 245. https://doi.org/10.1016/0003-6870(81)90057-0
- Sorathia, Vikram. 2015. “ProMusicDB ID: Beyond a Unique Identifier for Professional Music.” Music Reference Services Quarterly 18 (1): 39–43. https://doi.org/10.1080/10588167.2015.995555
- “Sound-Alike Drug Names Produce Risk of Medication Interchange Errors.” 2005. Journal Of Pain & Palliative Care Pharmacotherapy 19 (3): 47–53. https://doi.org/10.1300/j354v19n03_08
- Stahel, Philip F. 2008. “Learning from Aviation Safety: A Call for Formal ‘Readbacks’ in Surgery.” Patient Safety in Surgery 2 (1): 21. https://doi.org/10.1186/1754-9493-2-21
- Starrfelt, Randi, Martin Lindegaard, and Claus Bundesen. 2015. “Confusing Confusability: On the Problems of Using Psychophysical Measures of Letter Confusability in Neuropsychological Research.” Cognitive Neuropsychology 32 (5): 314–20. https://doi.org/10.1080/02643294.2015.1061488
- “Stiftung Für Patientensicherheit, Schweiz: Quick-Alert Nr. 14 ‘Sound-Alike & Look-Alike’.” 2010. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen 104 (6): 453. https://doi.org/10.1016/j.zefq.2010.07.022
- Stockbridge, Melissa D., and Kellie Taylor. 2015. “A Method of Addressing Proprietary Name Similarity for US Prescription Drugs.” Therapeutic Innovation & Regulatory Science 49 (4): 524–29. https://doi.org/10.1177/2168479015570331
- Sukharev, Jeffrey, Leonid Zhukov, and Alexandrin Popescul. 2014. “Parallel Corpus Approach for Name Matching in Record Linkage.” In 2014 IEEE International Conference on Data Mining. IEEE. https://doi.org/10.1109/icdm.2014.76
- Sun, Decai, and Xiaoxia Wang. 2018. “MLS-Join: An Efficient MapReduce-Based Algorithm for String Similarity Self-Joins with Edit Distance Constraint.” In Cloud Computing and Security. Springer International Publishing. https://doi.org/10.1007/978-3-030-00006-6_60
- Sung-Hwan Kim and Hwan-Gue Cho. 2017. “Position-Restricted Approximate String Matching with Metric Hamming Distance.” In 2017 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE. https://doi.org/10.1109/bigcomp.2017.7881724
- Sutinen, Erkki, and Jorma Tarhio. 1996. “Filtration with q-Samples in Approximate String Matching.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-61258-0_4
- Tai, Xiao Hui. 2018. “Record Linkage and Matching Problems in Forensics.” In 2018 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE. https://doi.org/10.1109/icdmw.2018.00081
- Takabatake, Yoshimasa, Kenta Nakashima, Tetsuji Kuboyama, Yasuo Tabei, and Hiroshi Sakamoto. 2016. “siEDM: An Efficient String Index and Search Algorithm for Edit Distance with Moves.” Algorithms 9 (2): 26. https://doi.org/10.3390/a9020026
- Takabatake, Yoshimasa, Yasuo Tabei, and Hiroshi Sakamoto. 2014. “Online Pattern Matching for String Edit Distance with Moves.” In String Processing and Information Retrieval. Springer International Publishing. https://doi.org/10.1007/978-3-319-11918-2_20
- Takeda, Masayuki. 2001. “String Resemblance Systems: A Unifying Framework for String Similarity with Applications to Literature and Music.” In Combinatorial Pattern Matching. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-48194-x_13
- Tarhio, Jorma, and Esko Ukkonen. 1990. “Boyer-Moore Approach to Approximate String Matching.” In SWAT 90. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-52846-6_103
- “Task Analysis for Error Identification: Towards a Methodology for Identifying Human Error.” 1992. Applied Ergonomics 23 (3): 211. https://doi.org/10.1016/0003-6870(92)90241-m
- Tea, Vui Huang. 2021. “Relationship Discovery Graph of EU COVID Unique Vaccination Certificate Identifier (UVCI).” In 2021 IEEE International Conference on Big Data (Big Data). IEEE. https://doi.org/10.1109/bigdata52589.2021.9671798
- Telsang, Supriya, Aditya Pund, Pranav Rajput, et al. 2025. “Phonetic and Transliteration Based Name Matching System,Using Fuzzy Algorithm and Machine Learning for Police Database.” In 2025 9th International Conference on Computing, Communication, Control and Automation (ICCCBEA). IEEE. https://doi.org/10.1109/iccubea65967.2025.11283693
- Teplitsky, Benjamin. 1979b. “Look-Alikeand Sound-Alike Drug Names.” Hospital Topics 57 (6): 33–33. https://doi.org/10.1080/00185868.1979.9954735
- Teplitsky, Benjamin. 1994. “Similarity of Generic Quinolonedrug Names.” Urology 43 (1): 131–32. https://doi.org/10.1016/s0090-4295(94)80290-4
- Ternikov, Andrei A. 2024. “Company Name Matching Using Job Market Data Enrichment.” IT Professional 26 (2): 76–82. https://doi.org/10.1109/mitp.2024.3371179
- Thabet, Rafika, Elyes Lamine, Marie-Helene Cleostrate, Marie-Noelle Cufi, and Herve Pingaud. 2022. “Towards a Novel Spontaneous Medication Error Reporting Tool for Enhancing Patient Safety.” In 2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA). IEEE. https://doi.org/10.1109/aiccsa56895.2022.10017700
- Thakkar, Karan B., and Gauri Billa. 2013. “The Concept Of: Generic Drugs and Patented Drugs vs. Brand Name Drugs and Non-Proprietary (Generic) Name Drugs.” Frontiers in Pharmacology 4. https://doi.org/10.3389/fphar.2013.00113
- Thumsuwan, Soontaree, Nuanprang Sangurai, and Chouvalit Khancome. 2024. “Approximate String Matching Algorithm Using Multiple-Character Inverted Lists.” In 2024 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C). IEEE. https://doi.org/10.1109/ri2c64012.2024.10784446
- Tissot, Hegler, and Richard Dobson. 2019. “Combining String and Phonetic Similarity Matching to Identify Misspelt Names of Drugs in Medical Records Written in Portuguese.” Journal of Biomedical Semantics 10 (S1): 17. https://doi.org/10.1186/s13326-019-0216-2
- Top, Philip, Farid Dowla, and Jim Gansemer. 2007. “A Dynamic Programming Algorithm for Name Matching.” In 2007 IEEE Symposium on Computational Intelligence and Data Mining. IEEE. https://doi.org/10.1109/cidm.2007.368923
- Tranchard, Frederic, Christophe Hein, Jean Lacombe, Hélène Villars, Jean-Louis Montastruc, and Fabien Despas. 2016. “Medication Errors and Look-Alike Tablets: The Splitting Issue: Iatrogenic Look-Alike Tablets.” Pharmacoepidemiology and Drug Safety 25 (9): 1002–3. https://doi.org/10.1002/pds.4063
- Tsur, Dekel. 2010. “Fast Index for Approximate String Matching.” Journal of Discrete Algorithms 8 (4): 339–45. https://doi.org/10.1016/j.jda.2010.08.002
- Tu, Chi-Ming. 2019. “Use of Proprietary Names by Prescribers When Prescribing over-the-Counter (OTC) Drug Products.” Therapeutic Innovation & Regulatory Science 53 (1): 132–37. https://doi.org/10.1177/2168479018762376
- Tuohy, Nancy, and Susan Paparella. 2005. “Look-Alike and Sound-Alike Drugs: Errors Just Waiting to Happen.” Journal of Emergency Nursing 31 (6): 569–71. https://doi.org/10.1016/j.jen.2005.07.012
- Ukkonen, Esko. n.d. “Approximate String-Matching over Suffix Trees.” In Combinatorial Pattern Matching. Springer-Verlag. https://doi.org/10.1007/bfb0029808
- Ukkonen, Esko. 1983. “On Approximate String Matching.” In Foundations of Computation Theory. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-12689-9_129
- Ukkonen, Esko. 1985. “Algorithms for Approximate String Matching.” Information and Control 64 (1–3): 100–118. https://doi.org/10.1016/s0019-9958(85)80046-2
- Ukkonen, Esko. 1992. “Approximate String-Matching with q-Grams and Maximal Matches.” Theoretical Computer Science 92 (1): 191–211. https://doi.org/10.1016/0304-3975(92)90143-4
- Ukkonen, Esko, and Derick Wood. 1993. “Approximate String Matching with Suffix Automata.” Algorithmica 10 (5): 353–64. https://doi.org/10.1007/bf01769703
- “Utilisation of Neonatal Medication Error Prevention Strategies: A Clinical Practice Survey of Australian and New Zealand Neonatal Units.” 2018. Journal of Paediatrics and Child Health 54 (S1): 88–89. https://doi.org/10.1111/jpc.13882_237
- Vaiwsri, Sirintra, Thilina Ranbaduge, and Peter Christen. 2024. “Encryption-Based Sub-String Matching for Privacy-Preserving Record Linkage.” Journal of Information Security and Applications 81: 103712. https://doi.org/10.1016/j.jisa.2024.103712
- Valarakos, Alexandros G., Georgios Paliouras, Vangelis Karkaletsis, and George Vouros. 2004. “A Name-Matching Algorithm for Supporting Ontology Enrichment.” In Methods and Applications of Artificial Intelligence. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-24674-9_40
- Van Court, T., and M. C. Herbordt. 2004. “Families of FPGA-Based Algorithms for Approximate String Matching.” In Proceedings. 15th IEEE International Conference on Application-Specific Systems, Architectures and Processors, 2004.. IEEE. https://doi.org/10.1109/asap.2004.1342484
- Van Court, Tom, and Martin C. Herbordt. 2007. “Families of FPGA-Based Accelerators for Approximate String Matching.” Microprocessors and Microsystems 31 (2): 135–45. https://doi.org/10.1016/j.micpro.2006.04.001
- Varol, Cihan, and John R. Talburt. 2011. “Pattern and Phonetic Based Street Name Misspelling Correction.” In 2011 Eighth International Conference on Information Technology: New Generations. IEEE. https://doi.org/10.1109/itng.2011.101
- Vartabedian, Allen. 1970. “Human Factors Evaluation of Several Cursor Forms for Use on Alphanumeric CRT Displays.” IEEE Transactions on Man Machine Systems 11 (2): 132–37. https://doi.org/10.1109/tmms.1970.299995
- Vilares, Manuel, Francisco J. Ribadas, and Jesús Vilares. 2004. “Phrase Similarity through the Edit Distance.” In Database and Expert Systems Applications. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-30075-5_30
- Wang, Ruixin. 2025. “Trademark Infringement and Confusion: A Perspective Based on Consumer Cognition.” In Proceedings of the 1st International Conference on Politics, Law, and Social Science. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0014374800004859
- Wang, Dongsheng, Yue Feng, Jiawei Li, et al. 2024. “CFNAM-PG: Bridging Phonetic and Glyphic Information for Chinese Full Name and Abbreviation Matching Based on Simbert and DenseNet.” International Journal of Computational Intelligence Systems 17 (1): 157. https://doi.org/10.1007/s44196-024-00549-x
- Wang, Jiannan, Guoliang Li, and Jianhua Fe. 2011. “Fast-Join: An Efficient Method for Fuzzy Token Matching Based String Similarity Join.” In 2011 IEEE 27th International Conference on Data Engineering. IEEE. https://doi.org/10.1109/icde.2011.5767865
- Wang, Jiannan, Guoliang Li, and Jianhua Feng. 2014. “Extending String Similarity Join to Tolerant Fuzzy Token Matching.” ACM Transactions on Database Systems 39 (1): 1–45. https://doi.org/10.1145/2535628
- Watcharapinchai, Nattachai, and Sitapa Rujikietgumjorn. 2017. “Approximate License Plate String Matching for Vehicle Re-Identification.” In 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). IEEE. https://doi.org/10.1109/avss.2017.8078538
- West, Leonard J. 1954. “Less Confusability in Shorthand Learning.” Journal of Education for Business 30 (2): 87–88. https://doi.org/10.1080/08832323.1954.10115718
- Wieling, Martijn, Eliza Margaretha, and John Nerbonne. 2012. “Inducing a Measure of Phonetic Similarity from Pronunciation Variation.” Journal of Phonetics 40 (2): 307–14. https://doi.org/10.1016/j.wocn.2011.12.004
- Winkler, William E. 2014. “Matching and Record Linkage.” WIREs Computational Statistics 6 (5): 313–25. https://doi.org/10.1002/wics.1317
- Witt, Jessica M., Lisa M. Cillessen, and Paul O. Gubbins. 2024. “Barriers to Medication Error Reporting in a Federally Qualified Health Center.” Journal of the American Pharmacists Association 64 (4): 102079. https://doi.org/10.1016/j.japh.2024.102079
- Wright, Alden H. 1994. “Approximate String Matching Using Withinword Parallelism.” Software: Practice and Experience 24 (4): 337–62. https://doi.org/10.1002/spe.4380240402
- Wysocki, V., Dw Grabe, and Pd Meek. 2022. “SA44 Trends in Medication Error Reporting during the COVID-19 Pandemic: An Analysis of Faers Data, 2016 to 2021.” Value in Health 25 (7): S612-S613. https://doi.org/10.1016/j.jval.2022.04.1710
- Yang, Jing, and Yufeng Chen. 2026. “Beyond Orthography: A Refined Perceptual Assimilation Task Paradigm for Measuring Cross-Linguistic Phonetic Similarity.” Frontiers in Psychology 17: 1859283. https://doi.org/10.3389/fpsyg.2026.1859283
- Yang, Zhong, Bolong Zheng, Xianzhi Wang, Guohui Li, and Xiaofang Zhou. 2022. “minIL: A Simple and Small Index for String Similarity Search with Edit Distance.” In 2022 IEEE 38th International Conference on Data Engineering (ICDE). IEEE. https://doi.org/10.1109/icde53745.2022.00047
- Yarkoni, Tal, David A. Balota, and Melvin Ju-min Yap. 2008. “Moving beyond Coltheart’s N: A New Measure of Orthographic Similarity.” Psychonomic Bulletin & Review 15 (5): 971–79. https://doi.org/10.3758/pbr.15.5.971
- Young, Lauren. 2000. “What[apos ]s in a Name? Lessening the Confusion over Drug Names.” Home Care Provider 5 (2): 0062–0066. https://doi.org/10.1067/mhc.2000.hc0050062
- Yu, Minghe, Jin Wang, Guoliang Li, Yong Zhang, Dong Deng, and Jianhua Feng. 2016. “A Unified Framework for String Similarity Search with Edit-Distance Constraint.” VLDB Journal 26 (2): 249–74. https://doi.org/10.1007/s00778-016-0449-y
- Yu, Guangxi, Xinghua Yang, Yan Zhang, Huajun Cui, Huiran Yang, and Yang Li. 2020. “Towards Homograph-Confusable Domain Name Detection Using Dual-Channel CNN.” In Information and Communications Security. Springer International Publishing. https://doi.org/10.1007/978-3-030-41579-2_32
- Zhang, Haining, and Lihong Cui. 2022. “Reexamine the Appropriate Role of “Trademark Use” in Trademark Infringement Judgement: An Empirical Study of Trademark Infringement Cases in China.” Asian Journal of Technology Innovation 31 (1): 212–32. https://doi.org/10.1080/19761597.2022.2042704
- Zhang, Shengnan, Yan Hu, and Guangrong Bian. 2017. “Research on String Similarity Algorithm Based on Levenshtein Distance.” In 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE. https://doi.org/10.1109/iaeac.2017.8054419
- Zhang, Lyulei, and Adam. F. Osth. 2024. “Modelling Orthographic Similarity Effects in Recognition Memory Reveals Support for Open Bigram Representations of Letter Coding.” Cognitive Psychology 148: 101619. https://doi.org/10.1016/j.cogpsych.2023.101619
- Zhao, Feng, Yaping Liu, and Baosheng Wang. 2014. “DROUND: Direct Routing on Unique Network-Layer Identifier.” In 2014 Sixth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE. https://doi.org/10.1109/icufn.2014.6876807
- Zhao, Yang, Zoie Shui-Yee Wong, and Kwok Leung Tsui. 2018. “A Framework of Rebalancing Imbalanced Healthcare Data for Rare Events’ Classification: A Case of Look-Alike Sound-Alike Mix-Up Incident Detection.” Journal of Healthcare Engineering 2018: 1–11. https://doi.org/10.1155/2018/6275435
- Zhou, Weidong, Baozong Yuan, Zhenjiang Miao, and Xiaofang Tang. 2006. “Error Correction via Phonetic Similarity-Based Processing for Chinese Spoken Dialogue System.” In 2006 8th international Conference on Signal Processing. IEEE. https://doi.org/10.1109/icosp.2006.345742
Primary Sources, Non-Peer-Reviewed
- “5Chapter Human Error Identification and Analysis Methods.” 2009. In Human Factors Methods and Sports Science. CRC Press. https://doi.org/10.1201/9781420072181-12
- A01 Committee. n.d. Practice for Numbering Metals and Alloys in the Unified Numbering System (UNS). ASTM International. https://doi.org/10.1520/e0527-07
- Abdulrouf, P., B. Thomas, W. Elkassem, and M. Alhail. 2019. “5PSQ-096 Key Stakeholders, Perspectives on Medication Safety Practices and Error Reporting in Qatar – an Exploratory Sequential Mixed-Method Study.” In Section 5: Patient Safety and Quality Assurance. British Medical Journal Publishing Group. https://doi.org/10.1136/ejhpharm-2019-eahpconf.529
- Aborot, Jeffrey A. 2017. “Quantum Approximate String Matching for Large Alphabets.” In Theory and Practice of Computation. WORLD SCIENTIFIC. https://doi.org/10.1142/9789813202818_0003
- ACCESS: Aircraft Call Sign Confusion Evaluation Safety Study. 2000. CAP 704. UK Civil Aviation Authority. https://www.caa.co.uk/our-work/publications/documents/content/cap-704/
- Active Aeroelastic Wing Flight Research. 2005. FS-2005-03-061 DFRC. NASA Dryden Flight Research Center. https://www.nasa.gov/wp-content/uploads/2021/09/120314main_fs-061-dfrc.pdf
- Adamson, A., and N. Williams. 2016. Requirements for NFSv4 Multi-Domain Namespace Deployment. RFC Editor. https://doi.org/10.17487/rfc8000
- “Addressing LASA Medication Errors Through Improved Drug Packaging and Labeling.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch004
- Adhe, Kartika Rinakit, Mustaji Mustaji, Nadi Suprapto, Suryanti Suryanti, and Yi-Ling Lai. 2023. “Difficulty of Visual Recognition: Identifying the Direction Confusion of Reading Letters in Young Children.” International Journal of Education in Mathematics Science and Technology 12 (2): 334–44. https://doi.org/10.46328/ijemst.3888
- Adiana, Sylvi adiana, Amalina Fakhriah, and Kamelia Zahro. 2026. “Analisis Pengelolaan Obat Look Alike Sound Alike (LASA) Terhadap Angka Kejadian Medication Error Di Rumah Sakit X.” Journal of Innovative and Creativity (Joecy) 6 (1): 521–25. https://doi.org/10.31004/joecy.v6i1.5333
- Aerospace. Part Numbering for Hose Assemblies. n.d. BSI British Standards. https://doi.org/10.3403/30173349u
- Afanasev, Ilia, and Olga Lyashevskaya. 2024. “String Similarity Measures for Evaluating the Lemmatisation in Old Church Slavonic.” In Structuring Lexical Data and Digitising Dictionaries. BRILL. https://doi.org/10.1163/9789004702660_003
- Agoglia, Mary, Kathleen Kelly, Glenda B. Kelman, and Rosemarie VanPatten. 2024. “Competency-Based Medication Administration and Error Reporting.” Journal of Nursing Education 63 (5): 320–27. https://doi.org/10.3928/01484834-20240305-07
- Aguasvivas, Jose Armando, Alberto Testolin, Marco Zorzi, and Manuel Carreiras. 2021. “Words in the CLOUD: How Orthographic Similarity and Bilingual Experience Facilitate Foreign Vocabulary Learning.” Preprint, . https://doi.org/10.31234/osf.io/8tx7p
- Ahuja, Annapurna, and Vipin Ahuja. 2024. “LASA (Look Alike Sound Alike) Medicament Errors: What a Dental Personnel Needs to Know?” Journal of Dental Panacea 6 (3): 113–14. https://doi.org/10.18231/j.jdp.2024.023
- Air Force Instruction 33-217 Communications and Information Voice Call Sign Program. 1997. Defense Technical Information Center. https://doi.org/10.21236/ada403713
- Air-Ground Communications Briefing Note: 2: Call Sign Confusion. n.d. Briefing Note 2. https://skybrary.aero/sites/default/files/bookshelf/110.pdf
- Aksoy, Bekir, Sinan UĞUz, and Okan Oral. 2019. “Comparison of the Data Matching Performances of String Similarity Algorithms in Big Data.” Mühendislik Bilimleri ve Tasarım Dergisi 7 (3): 608–18. https://doi.org/10.21923/jesd.467036
- Al-Bakry, Abbas, and Marwa Al-Rikaby. 2016. “Enhanced Levenshtein Edit Distance Method Functioning as a String-to-String Similarity Measure.” Iraqi Journal for Computers and Informatics 42 (1): 48–54. https://doi.org/10.25195/ijci.v42i1.83
- Alexeeva, Svetlana. 2023. “Parafoveal Letter Identification in Russian: Confusion Matrices Based on Error Rates.” Preprint, . https://doi.org/10.31234/osf.io/e2uwm
- AlJassmi, Maryam A., and Manuel Perea. 2024. “Visual Similarity Effects in the Identification of Arabic Letters: Evidence with Masked Priming.” Language and Cognition 16 (4): 1618–38. https://doi.org/10.1017/langcog.2024.20
- Aljedaani, Hind, Jana Farrash, Nehal Nasr, and Intessar Sultan. 2025. “Enhanced Medication Error Reporting: Progress Evaluation at a College Hospital in Jeddah.” International Journal of Medicine in Developing Countries: 1983–89. https://doi.org/10.24911/ijmdc.51-1735682222
- Allington, Richard L. 1977. “The Visual “Confusability” of High-Frequency Words.” Journal of Learning Disabilities 10 (7): 444–49. https://doi.org/10.1177/002221947701000709
- Allott, Nicholas. 2016. “24. Misunderstandings in Verbal Communication.” In Verbal Communication. De Gruyter. https://doi.org/10.1515/9783110255478-025
- Alsaif, Malak Abdulaziz. 2018. “Knowledge, Attitude and Practice on Medication Error Reporting among Health Practitioners in a Tertiary Care Setting in Saudi Arabia: A Cross-Sectional Study.” General Medicine Open Access 06. https://doi.org/10.4172/2327-5146-c1-003
- Alsalameen, Ahlam A., Ahmad M. Alsuliman, Haidar H. Alhashim, et al. 2024. “Patient View on Look-Alike, Sound-Alike (LASA) Medication Errors in a Saudi General Hospital: Responding, Experience and Contributing Factors.” Journal of Surgery Care 03 (03): 01–10. https://doi.org/10.33140/jsc.03.03.09
- Alshaikh, Mashael, Ahmed Mayet, and Hisham Aljadhey. 2013. “Medication Error Reporting in a University Teaching Hospital in Saudi Arabia.” Journal of Patient Safety 9 (3): 145–49. https://doi.org/10.1097/pts.0b013e3182845044
- Altbach, Philip. 2015. “What’s in a Name? How Universities Sow Confusion and Cheapen Academe.” International Higher Education, no. 40. https://doi.org/10.6017/ihe.2005.40.7483
- Anderson, D. H. 1970. “Numbering System for Moon Samples.” Science 167 (3918): 781–781. https://doi.org/10.1126/science.167.3918.781
- andNa. 1985. “MEDICATION ERROR.” Nursing 15 (12): 9–11. https://doi.org/10.1097/00152193-198512000-00002
- andNa. 1993. “MEDICATION ERROR.” Nursing 23 (3): 18–19. https://doi.org/10.1097/00152193-199303000-00012
- andNa. 1999. “USP Effort on Medication Error Reporting and Prevention.” Clinical Nurse Specialist 13 (2): 104. https://doi.org/10.1097/00002800-199903000-00017
- andNa. 2005a. “CE Test: Medication Safety: Look-Alike/Sound-Alike Drugs in Home Care.” Home Healthcare Nurse: The Journal for the Home Care and Hospice Professional 23 (4): 254–55. https://doi.org/10.1097/00004045-200504000-00012
- andNa. 2005c. “Medication Errors Due to Confusion.” Nurse Practitioner 30 (8): 70. https://doi.org/10.1097/00006205-200508000-00020
- andNa. 2011. “Medication Error Reporting in the Home Setting.” Journal of Hospice & Palliative Nursing 13 (5): 268–69. https://doi.org/10.1097/njh.0b013e31822a5b6e
- Andrade, Natalia. 2023. “The Performance of Brazilian Air Traffic Controllers in Radiotelephony Communications in English: The Controllers’ Perspective.” Applied Linguistics Papers 1/2023 (27): 79–90. https://doi.org/10.32612/uw.25449354.2023.1.pp.79-90
- Anggiratih, Endang. 2025. “Look Alike-Sound Alike Prediction as a Tool for Patient Safety.” IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 19 (1): 85. https://doi.org/10.22146/ijccs.103210
- Annisa Sihotang, Yola. 2024. “Implementasi Algoritma Approximate String Matching Pada Aplikasi Pengarsipan Dokumen Ekspor Barang.” Buletin Ilmiah Informatika Teknologi 2 (3): 109–14. https://doi.org/10.58369/biit.v2i3.57
- Antonow, Juli A., Anne B. Smith, and Michael P. Silver. 2000. “Medication Error Reporting: A Survey of Nursing Staff.” Journal of Nursing Care Quality 15 (1): 42–48. https://doi.org/10.1097/00001786-200010000-00006
- Apodaca, Richard. 2010. “The FDA Unique Ingredient Identifier (UNII).” Preprint, Front Matter. https://doi.org/10.59350/xg75q-5ec40
- “Appendix C. Numbering System Used for Coding Causes of Death.” 1974. In University of California Press eBook-Package Archive Pre-2000. University of California Press. https://doi.org/10.1525/9780520323971-016
- Appendix C: Numbering System for Protective Devices, Control and Indication Devices for Power Systems. 2003. Wiley. https://doi.org/10.1002/0470013893.app3
- “Approximate String Matching.” 1994. In Lecture Notes Series on Computing. WORLD SCIENTIFIC. https://doi.org/10.1142/9789814317368_0005
- Aragão, Beatriz Faria, and Matilde Virginia Ricardi Scaramucci. 2020. “A Brief Analysis of Language Tasks Used by Air Traffic Controllers in Radiotelephony Communications in Brazil.” ESPecialist 41 (4). https://doi.org/10.23925/2318-7115.2020v41i4a5
- Aratsu, Taku, Kouichi Hirata, and Tetsuji Kuboyama. 2010. “Approximating Tree Edit Distance through String Edit Distance for Binary Tree Codes.” Fundamenta Informaticae 101 (3): 157–71. https://doi.org/10.3233/fi-2010-282
- “Are Electronic Prescribing Systems Increasing the Risk of ‘Look-Alike Sound-Alike’ Medication Errors?” 2026. Pharmaceutical Journal. https://doi.org/10.1211/pj.2026.1.411793
- Arora, Sonia. 2020. “A Study to Examine the Medication Error, Causes and Reporting Behaviour as Perceived by Staff Nurses Working in the Selective Units of Dr. Ram Manohar Lohia Hospital, New Delhi.” Indian Journal of Surgical Nursing 9 (1): 9–15. https://doi.org/10.21088/ijsn.2277.467x.9120.1
- Arslan, A. N., and O. Egecioglu. n.d. “An Efficient Uniform-Cost Normalized Edit Distance Algorithm.” In 6th International Symposium on String Processing and Information Retrieval. 5th International Workshop on Groupware (Cat. No.PR00268). IEEE Comput. Soc. https://doi.org/10.1109/spire.1999.796572
- Arunachalam, Subbiah, and Muthu Madhan. 2021. “Adopting ORCID as a Unique Identifier Will Benefit All Involved in Scholarly Communication.” National Medical Journal of India 0 (0): 0. https://doi.org/10.4103/0970-258x.190480
- Aschenbrenner, Diane S. 2025a. “Look-Alike, Sound-Alike Errors While Restocking Automated Dispensing Cabinets.” AJN, American Journal of Nursing 125 (11): 19–19. https://doi.org/10.1097/ajn.0000000000000187b
- Aschenbrenner, Diane S. 2025b. “Neffy and Narcan Nasal Sprays: Potential for Look-Alike, Sound-Alike Medication Errors.” AJN, American Journal of Nursing 125 (9): 20–21. https://doi.org/10.1097/ajn.0000000000000141b
- Ashish, Naveen, Arihant Patawari, Simrat Singh Chhabra, and Arthur W. Toga. 2016. “Name Similarity for Composite Element Name Matching.” In Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM. https://doi.org/10.1145/2975167.2975203
- Asian Development Bank. 2018. Unique Health Identifier Assessment Tool Kit. Asian Development Bank. https://doi.org/10.22617/tim168320-2
- “Assessment of Look-Alike, Sound-Alike and Read-Alike (LASARA) Medicine – Errors in Pharmacy.” 2020. Journal of the College of Physicians and Surgeons Pakistan 30 (4): 425–28. https://doi.org/10.29271/jcpsp.2020.04.425
- “Assessment of the Risk of Confusion between Two Similar Marks.” 2022. GRUR International 72 (2): 174–79. https://doi.org/10.1093/grurint/ikac104
- “Assessment of the Similarity and the Risk of Confusion with a Well-Known Trade Mark.” 2023. GRUR International 72 (8): 786–90. https://doi.org/10.1093/grurint/ikad055
- Aten, Thomas R., Leo Gugerty, and Richard A. Tyrrell. 2002. “Legibility of Words Rendered Using Cleartype™.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46 (17): 1684–87. https://doi.org/10.1177/154193120204601733
- Austin, William M. 1957. “Criteria for Phonetic Similarity.” Language 33 (4-Part1): 538–44. https://doi.org/10.2307/411308
- Austin, Graeme W. 2008. “Tolerating Confusion about Confusion: Trademark Policies and Fair Use.” In Edward Elgar Publishing eBooks. Edward Elgar Publishing. https://doi.org/10.4337/9781848441316.00024
- Author, Unknown. 2026. “The Phenomenon of Phonetic Similarity and Its Implications in the Authentic Narrations on Trials in Two Authentic Collections.” Journal of Raparin University 13 (2). https://doi.org/10.26750/9nebyy46
- AydemİR, Azize, and Derya Esenkaya. 2023. “The Views of Nurses Working in Surgical Clinics and Surgical Intensive Care Units on Medication Administration Errors and Error Reporting.” International Journal of Health Services Research and Policy 8 (1): 3–16. https://doi.org/10.33457/ijhsrp.1193061
- Baddeley, Alan. 1971. “Language Habits, Acoustic Confusability, and Immediate Memory for Redundant Letter Sequences.” Psychonomic Science 22 (2): 120–21. https://doi.org/10.3758/bf03332525
- Baeza-Yates, R., and G. Navarro. n.d. “Fast Approximate String Matching in a Dictionary.” In Proceedings. String Processing and Information Retrieval: A South American Symposium (Cat. No.98EX207). IEEE Comput. Soc. https://doi.org/10.1109/spire.1998.712978
- Bailey, Carrie. n.d. “Investigating the Role of Labelling and Packaging on Medication Error.” PhD diss., Open Access Te Herenga Waka-Victoria University of Wellington. https://doi.org/10.26686/wgtn.17019833
- Baker, Danial E. 2002. “Sound-Alike and Look-Alike Drug Errors.” Hospital Pharmacy 37 (3): 225–225. https://doi.org/10.1177/001857870203700301
- Balan, Shamala, and Lyna Irawati. 2026. “From Knowledge to Practice: Strengthening Medication Error Reporting Practices among Community Pharmacists in Malaysia.” Asian Journal of Medicine & Health Sciences 9 (1): 1–3. https://doi.org/10.70672/dnkpby91
- Bánki, Olaf, Markus Döring, and Thomas Stjernegaard Jeppesen. 2023. “Name IDs and Name Matching for Catalogue of Life: Existing Services and Prospects.” Biodiversity Information Science and Standards 7. https://doi.org/10.3897/biss.7.111662
- Bansal, Nancy, Akash Ashok Kumar Khobragade, Aditya R. Bawne, Ajinkya Bavlecha, and Balbir Singh Kohli. 2026. “A Cross-Sectional Study to Assess the Knowledge, Attitude, and Practice of Look-Alike, Sound-Alike Drugs among Healthcare Providers at a Tertiary Care Hospital.” Journal of The Association of Physicians of India 74 (7): 20–23. https://doi.org/10.59556/japi.74.1593
- Bar Coding. Unique Identifier for Transport Units. n.d. BSI British Standards. https://doi.org/10.3403/01013878u
- Barbre, William E., and Dennis L. Price. 1983. “Effects of Alcohol and Error Criticality on Alphanumeric Target Acquisition.” Proceedings of the Human Factors Society Annual Meeting 27 (6): 468–71. https://doi.org/10.1177/154193128302700609
- Baroni, Marco, Johannes Matiasek, and Harald Trost. 2002. “Unsupervised Discovery of Morphologically Related Words Based on Orthographic and Semantic Similarity.” In Proceedings of the ACL-02 workshop on Morphological and phonological learning -, vol. 6. Association for Computational Linguistics. https://doi.org/10.3115/1118647.1118653
- “Barriers to Reporting Medication Errors.” 2009. Nursing 39 (3): 8. https://doi.org/10.1097/01.nurse.0000347045.91245.a4
- Bartholomew, Mark. 2025. “Navigating Trademark Law’s Empirical Turn.” Preprint, . https://doi.org/10.2139/ssrn.5041413
- Bartow, Ann. 2005. “Exporting Trademark Confusion.” In IGI Global eBooks. IGI Global. https://doi.org/10.4018/978-1-59140-576-4.ch005
- Basire, Yann, and Pauline Darnand. 2017. “Likelihood of Confusion and Marks with Weak Distinctive Character.” Journal of Intellectual Property Law & Practice 12 (9): 723–24. https://doi.org/10.1093/jiplp/jpx108
- Bassi, Suki, Oscar Jakubiel Smith, and Raliat Onatade. 2025. “Disparities in Medication Error Reporting: A Focus on Patients with Select Protected Characteristics.” BMJ Open Quality 14 (2): e003175. https://doi.org/10.1136/bmjoq-2024-003175
- Batty, Rob. 2025. “Post-Sale Similarity and a Likelihood of Confusion: Lessons for New Zealand.” Preprint, . https://doi.org/10.2139/ssrn.5396414
- Batu, Tuğkan, Funda Ergun, and Cenk Sahinalp. 2006. “Oblivious String Embeddings and Edit Distance Approximations.” In Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm - SODA ‘06. ACM Press. https://doi.org/10.1145/1109557.1109644
- Batykov, Ivan Vladimirovich. 2020. “Factors of Trademark Confusion: Sociological Analysis.” Теория и практика общественного развития, no. 10: 18–22. https://doi.org/10.24158/tipor.2020.10.2
- Bayrak, Polen. 2026. “Artificial Intelligence in EU Trademark Registration and the Assessment of Likelihood of Confusion in the Digital Era.” Jusletter IT, no. juli-2026. https://doi.org/10.38023/947bf44b-7f07-4b92-ad44-fe5fd82f3629
- Bc, Teoh, Alian A. Alrasheedy, and Mohamed Azmi Hassali. 2015. “Perceptions of Doctors and Pharmacists towards Medication Error Reporting and Prevention in Kedah, Malaysia: A Rasch Model Analysis.” Advances in Pharmacoepidemiology & Drug Safety 04 (05). https://doi.org/10.4172/2167-1052.1000192
- Beale, Nancy J., and Nur Rajwany. 2022. “Implementation of a Unique Nurse Identifier.” Nursing Management 53 (1): 6–9. https://doi.org/10.1097/01.numa.0000805040.87004.37
- Beebe, Barton. 2006. “An Empirical Study of the Multifactor Tests for Trademark Infringement.” California Law Review 94 (6): 1581. https://doi.org/10.2307/20439078
- Beebe, Barton, and Jeanne C. Fromer. 2020. “Fake Trademark Specimens: An Empirical Analysis.” Preprint, . https://doi.org/10.2139/ssrn.3556121
- Beebe, Barton, Jeanne C. Fromer, and David Stein. 2026b. “Trademark Law’s View of the Image: A Computational and Empirical Analysis.” Preprint, . https://doi.org/10.2139/ssrn.7268138
- Bell, Glennis L. 1967. “The Effects of Symbol Frequency in Legibility Testing.” Human Factors: The Journal of the Human Factors and Ergonomics Society 9 (5): 471–78. https://doi.org/10.1177/001872086700900511
- Benito Fernández, Mónica, Alejandro Laborda Cobos, Reyes Méndez Escribano, Ana Isabel Fernández Pérez, Beatriz Fernández De Miguel, and Virginia Saavedra Quirós. 2026. “Implantación de medidas de seguridad para la gestión de medicamentos Look Alike/Sound Alike en un Servicio de Farmacia Hospitalaria.” In Libro de comunicaciones 71 Congreso SEFH. Sociedad Española de Farmacia Hospitalaria. https://doi.org/10.62917/26.71.0620
- Berendsohn, Walter G. 2023. “Use Cases for Scientific Name Identifiers and Name Matching: Progress Report from the TETTRIs Project.” Biodiversity Information Science and Standards 7. https://doi.org/10.3897/biss.7.109666
- Bergeron, H. P. 1983. “Analysis of General Aviation Single-Pilot IFR Incident Data Obtained from the NASA Aviation Safety Reporting System.” In Controls, Displays and Inform. Transfer for Gen. Aviation IFR Operations. https://ntrs.nasa.gov/citations/19840003965
- Berghel, H., D. Roach, and J. Talburt. 1990. “Approximate String Matching and the Automation of Word Games.” In Proceedings of the 1990 Symposium on Applied Computing. IEEE Comput. Soc. https://doi.org/10.1109/soac.1990.82170
- Bernard, Ephraim, and A. Ifeyinwa Ajah. 2025. “Sautex: A Language-Specific Phonetic Matching Algorithm for Resolving Spelling Variations in Hausa Personal Names.” Journal of Computer, Software, and Program 2 (2): 25–33. https://doi.org/10.69739/jcsp.v2i2.1141
- Bernard, Michael, Chia Hui Liao, and Melissa Mills. 2001. “The Effects of Font Type and Size on the Legibility and Reading Time of Online Text by Older Adults.” In CHI ‘01 Extended Abstracts on Human Factors in Computing Systems. ACM. https://doi.org/10.1145/634067.634173
- Best, K., and N. Walsh. 2001a. A URN Namespace for OASIS. RFC Editor. https://doi.org/10.17487/rfc3121
- Best, K., and N. Walsh. 2001b. A URN Namespace for XML.org. RFC Editor. https://doi.org/10.17487/rfc3120
- Bhise, Vivek D., and Rashad W. Hammoudeh. 2004. “A PC Based Model for Prediction of Visibility and Legibility for a Human Factors Engineer’s Tool Box.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 48 (7): 1074–76. https://doi.org/10.1177/154193120404800715
- Birdwell, Stephen W., Donald L. Sullivan, Dennis W. Grauer, and Gerald L. Cable. 2003. “Pharmacy Students’ Knowledge of Medication-Error Reporting.” American Journal of Health-System Pharmacy 60 (10): 1054–55. https://doi.org/10.1093/ajhp/60.10.1054
- Bisson, Marie-Josee. 2024. “The Impact of Cross-Linguistic Orthographic Similarity in Different Learning Contexts: Incidental vs Intentional Learning.” Preprint, . https://doi.org/10.31219/osf.io/2mk7n
- Blum, Kathleen V., Steven R. Abel, Christopher J. Urbanski, and Jeanne M. Pierce. 1988. “Medication Error Prevention by Pharmacists.” American Journal of Health-System Pharmacy 45 (9): 1902–3. https://doi.org/10.1093/ajhp/45.9.1902
- Blum, Kevin, Ariel Fox, Christina J. Hayes, and James Hanjun Xu. 2009. “Consistency of Confusion? A Fifteen-Year Revisiting of Barton Beebe’s Empirical Analysis of Multifactor Tests for Trademark Infringement.” Preprint, . https://doi.org/10.2139/ssrn.1424142
- Bogunenko, Nicolay N., Victoria I. Gavrylenko, and Maryana G. Smolyak. 2010. “Controller Pilot Data Link Communication Implementation to Avoid Controller-Pilot Misunderstanding.” Proceedings of National Aviation University 44 (3). https://doi.org/10.18372/2306-1472.44.1909
- Bogush, Alla, and Olena Kovtun. 2019. “Discourse “Radiotelephony of Civil Aviation”: Psycholinguistic Aspect.” Psycholinguistics 25 (1): 11–32. https://doi.org/10.31470/2309-1797-2019-25-1-11-32
- Boling, Aleasha J. 2015. “Confusion or Mere Diversion? Rosetta Stone v. Google’s Impact on Expanding Initial Interest Confusion to Trademark Use in Search Engine Sponsored Ads.” Indiana Law Review: 279–300. https://doi.org/10.18060/18352
- Bone, Robert G. 2021. “Likelihood of Confusion and Trademark Infringement: A Constructively Critical Analysis.” In Edward Elgar Publishing eBooks. Edward Elgar Publishing. https://doi.org/10.4337/9781785366215.00018
- Boyer, Rachel, Mary Lynn McPherson, Guarav Deshpande, and Sheila Weiss Smith. 2009. “Improving Medication Error Reporting in Hospice Care.” American Journal of Hospice and Palliative Medicine® 26 (5): 361–67. https://doi.org/10.1177/1049909109335145
- Brabcová, Iva, Sylva Bártlová, Valérie Tóthová, and Radka Prokešová. 2014. “The Possibility of Patient Involvement in Prevention of Medication Error.” Kontakt 16 (2): e65-e70. https://doi.org/10.1016/j.kontakt.2014.05.003
- Brammer, Anthony. 2003. Development of a Laboratory for Improving Communication between Air Traffic Controllers and Pilots. Connecticut Univ. https://ntrs.nasa.gov/citations/20040015121
- Branting, L. Karl. 2003. “A Comparative Evaluation of Name-Matching Algorithms.” In Proceedings of the 9th international conference on Artificial intelligence and law - ICAIL ‘03. ACM Press. https://doi.org/10.1145/1047788.1047837
- Brauneis, Robert, and Paul J. Heald. 2010. “Trademark Infringement, Trademark Dilution, and the Decline in Sharing of Famous Brand Names: An Introduction and Empirical Study.” Preprint, . https://doi.org/10.2139/ssrn.1662623
- Brochhagen, Thomas, Xixian Liao, Jamie Wright, and Carmen Saldana. 2025. “The Interaction of Meaning Similarity and Confusability Explains Regularity in Form-Meaning Mappings at and below the Word Level.” Preprint, . https://doi.org/10.31234/osf.io/vh5td_v1
- Brodell, R. T. 1997. “Prescription Errors. Legibility and Drug Name Confusion.” Archives of Family Medicine 6 (3): 296–98. https://doi.org/10.1001/archfami.6.3.296
- Brown, S. L., and D. Goodman. 1983. “A Mathematical Model for Predicing Speed of Alphanumeric Data Entry on Small Keypads.” Proceedings of the Human Factors Society Annual Meeting 27 (6): 506–10. https://doi.org/10.1177/154193128302700621
- Bruder, Gail, and Wayne Silverman. 1972. “Effects of Semantic and Phonetic Similarity on Verbal Recognition and Discrimination.” Journal of Experimental Psychology 94 (3): 314–20. https://doi.org/10.1037/h0032772
- Bryan, Rachel. n.d. “Linguistic Latent Conditions in International Nonproprietary Names of Medicines: Linguistic Drivers of Look-Alike Sound-Alike Errors and Implications in Russian and Italian Drug Nomenclatures.” PhD diss., Swansea University. https://doi.org/10.23889/suthesis.69508
- Buckley, Edward G. 1980. “Similarity of Drug Names.” JAMA: The Journal of the American Medical Association 243 (18): 1808. https://doi.org/10.1001/jama.1980.03300440014012
- Buerke, Anja. 2016. “Consumer Confusion als Herausforderung am Point of Sale (POS).” In Nachhaltigkeit und Consumer Confusion am Point of Sale. Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-15201-7_1
- Burt, Jennifer S., Kimberley A. McFarlane, Sarah J. Kelly, Michael S. Humphreys, Kimberlee Weatherall, and Robert G. Burrell. 2017. “Brand Name Confusion: Subjective and Objective Measures of Orthographic Similarity.” Journal of Experimental Psychology: Applied 23 (3): 320–35. https://doi.org/10.1037/xap0000127
- Busch, Allen C., and Robert B. King. 1964. Human Factors Review of the AN/TSQ-47 Air Traffic Control/Communications System. Defense Technical Information Center. https://doi.org/10.21236/ad0606629
- Butterbaugh, Larry C. 1981. A Performance Based Evaluation of Keying Logics for Alphanumeric Keyboards. Defense Technical Information Center. https://doi.org/10.21236/ada108813
- Butterbaugh, Larry C. 1982. “Keying Logics for Alphanumeric Keyboards and Human Performance.” Proceedings of the Human Factors Society Annual Meeting 26 (7): 634–38. https://doi.org/10.1177/154193128202600711
- Butterbaugh, Larry C., and Thomas H. Rockwell. 1982. “Evaluation of Alternative Alphanumeric Keying Logics.” Human Factors: The Journal of the Human Factors and Ergonomics Society 24 (5): 521–33. https://doi.org/10.1177/001872088202400503
- Cai, Hongyi. 2011. “A Practical Legibility Index: From Definition to Measurement Technology.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 55 (1): 1215–19. https://doi.org/10.1177/1071181311551253
- Campbell, B., and H. Tschofenig. 2012. An IETF URN Sub-Namespace for OAuth. RFC Editor. https://doi.org/10.17487/rfc6755
- Carbon and Alloy Steels Committee. 1993. SAE Numbering System for Wrought or Rolled Steel. https://doi.org/10.4271/j402_199311
- Carney, Edward. 2008. “Sound-Alike Affixes.” In Routledge eBooks. Routledge. https://doi.org/10.4324/9780203138489-15
- Carney, Shane L., Madlen Gazarian, Justin Timothy Denholm, et al. 2011. “What’s in a Name? Brand Name Confusion and Generic Medicines.” Medical Journal of Australia 195 (11–12): 650–51. https://doi.org/10.5694/mja10.10968
- Carpenter, Daniel, and Steven Joffe. 2011. “A Unique Researcher Identifier for the Physician Payments Sunshine Act.” JAMA 305 (19). https://doi.org/10.1001/jama.2011.651
- Carraway, J. Christopher. 1994. “Color as a Trademark under the Lanham Act: Confusion in the Circuits and the Need for Uniformity.” Law and Contemporary Problems 57 (4): 243. https://doi.org/10.2307/1192064
- Cavell, Gillian F., Vanessa Burgess, C. Alice Oborne, Roma Williams, and Soma Colwill. 2001. “Attitudes of Community Pharmacists towards Medication Error Reporting.” International Journal of Pharmacy Practice 9 (Supplement_1): 64–64. https://doi.org/10.1111/j.2042-7174.2001.tb01124.x
- Cebrian, Juli, Angélica Carlet, Núria Gavaldà, and Celia Gorba. 2025. “Minimal Effects of L2 Phonetic Training on Non-Naïve Learners’ Perception of Cross-Linguistic Similarity: Minimal Effects of Training on Perceived Similarity.” Journal of Second Language Pronunciation 12 (1): 131–45. https://doi.org/10.1075/jslp.25055.ceb
- Celko, Joe. 2010. “Data Universal Numbering System.” In Joe Celko’s Data, Measurements and Standards in SQL. Elsevier. https://doi.org/10.1016/b978-0-12-374722-8.00027-x
- Cerf, V. G. 1990. IAB Recommended Policy on Distributing Internet Identifier Assignment and IAB Recommended Policy Change to Internet “Connected” Status. RFC Editor. https://doi.org/10.17487/rfc1174
- “Challenges in Drug Identification and LASA Errors.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch003
- Chan, Amelia S., Raymond J. Muller, and Carissa E. Mancuso. 2018. “Description of a Tall-Man Lettering Program for Look-Alike and Sound-Alike Antineoplastic Agents.” American Journal of Health-System Pharmacy 75 (8): 512–13. https://doi.org/10.2146/ajhp170671
- Chan, Jeffrey W., and Carol A. Simpson. 1990. Comparison of Speech Intelligibility in Cockpit Noise Using SPH-4 Flight Helmet with and without Active Noise Reduction. NASA-CR-177564. NASA. https://ntrs.nasa.gov/citations/19900019194
- Chanakit, Teeraporn. 2013. “The Survey of Look Alike/sound Alike (LASA) Drugs Available in Hospitals in Thailand.” African Journal of Pharmacy and Pharmacology 7 (6): 227–39. https://doi.org/10.5897/ajpp11.812
- Chandra, Subhash. 2011. “Adding the PubMed Unique Identifier to Journal Article References without Increasing the Bulkiness of the Journals.” Acta Medica Academica 40 (2): 194. https://doi.org/10.5644/ama2006-124.26
- Chang, W. I., and E. L. Lawler. 1990. “Approximate String Matching in Sublinear Expected Time.” In Proceedings [1990] 31st Annual Symposium on Foundations of Computer Science. IEEE Comput. Soc. Press. https://doi.org/10.1109/fscs.1990.89530
- Chapanis, Alphonse, Wendell R. Garner, and Clifford T. Morgan. n.d. “Instrument Dials and Legibility.” In Applied experimental psychology: Human factors in engineering design.. John Wiley & Sons Inc. https://doi.org/10.1037/11152-005
- Chaparro, Barbara S., A. Dawn Shaikh, and Alex Chaparro. 2006. “The Legibility of Cleartype Fonts.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 50 (17): 1829–32. https://doi.org/10.1177/154193120605001724
- Charness, Neil, and Katinka Dijkstra. 1999. “Age, Luminance, and Print Legibility in Homes, Offices, and Public Places.” Human Factors: The Journal of the Human Factors and Ergonomics Society 41 (2): 173–93. https://doi.org/10.1518/001872099779591204
- Chauhan, Shivani, and Ankit Gaur. 2025. “Improving Medication Error Reporting through Clinical Audit and Targeted Interventions in a Tertiary Care Hospital.” Indian Journal of Pharmacy Practice 19 (2): 213–19. https://doi.org/10.5530/ijopp.20260492
- Chaware, S. M., and S. Rao. 2010. “Phonetic Matching through Writing Style.” In Proceedings of the International Conference and Workshop on Emerging Trends in Technology. ACM. https://doi.org/10.1145/1741906.1742028
- Chaware, Sandeep M., and Srikantha Rao. 2011. “Rule-Based Phonetic Matching Approach for Hindi and Marathi.” Computer Science & Engineering An International Journal 1 (3): 13–24. https://doi.org/10.5121/cseij.2011.1302
- Chen, Wei. 2016. “A Cognitive Study of Preposition Ellipsis in Radiotelephony Communication.” Open Journal of Modern Linguistics 06 (05): 390–400. https://doi.org/10.4236/ojml.2016.65035
- Chen, Rain, and ITing Cheng. 2012. “The Image Confusion in Trademark Map.” INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 4 (20): 27–34. https://doi.org/10.4156/aiss.vol4.issue20.4
- Chen, E., and J. Yuan. 2011. Autonomous-System-Wide Unique BGP Identifier for BGP-4. RFC Editor. https://doi.org/10.17487/rfc6286
- Cheng, Lechang, Mabo R. Ito, and Norm Hutchinson. n.d. “Internet Topology Based Identifier Assignment for Tree-Based DHTs.” In New Technologies, Mobility and Security. Springer Netherlands. https://doi.org/10.1007/978-1-4020-6270-4_50
- Cheng, Christine M., Alejandra Salazar, Mary G. Amato, Bruce L. Lambert, Lynn A. Volk, and Gordon D. Schiff. 2018b. “Using Drug Knowledgebase Information to Distinguish between Look-Alike-Sound-Alike Drugs.” Journal of the American Medical Informatics Association 25 (7): 872–84. https://doi.org/10.1093/jamia/ocy043
- Chernyak, Ekaterina. 2017. “Comparison of String Similarity Measures for Obscenity Filtering.” In Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing. Association for Computational Linguistics. https://doi.org/10.18653/v1/w17-1415
- Chiampi Ohly, Diana D. 2024. “Trademark Protection versus Parodic Use in Commerce: A Comparative Analysis of the US Approach Post Jack Daniel’s Properties v. VIP Products and the German Likelihood of Confusion Analysis.” GRUR International 73 (3): 198–209. https://doi.org/10.1093/grurint/ikad129
- Choi, Minchul. 2026. “Improving the Trademark Coexistence Consent System through the Introduction of a Right to Demand Confusion-Prevention Measures.” Kangwon LAW Review 83: 373–99. https://doi.org/10.18215/kwlr.2026.83..373
- Chrétien, Basile. 2026. “The Name-Collision Burden of Name-Based Author Attribution Is Unequal across Name Origins: A Measurement in OpenAlex, and an Identifier-Based Remedy (SigmaCV).” Preprint, Research Square. https://doi.org/10.21203/rs.3.rs-10125006/v1
- Christopher Jaisunder, G., Israr Ahmed, and R. K. Mishra. 2017. “Need for Customized Soundex Based Algorithm on Indian Names for Phonetic Matching.” Global Journal of Enterprise Information System 8 (2): 30. https://doi.org/10.18311/gjeis/2016/7658
- Chrysler, Susan, Donna Tranchida, Stirling Stackhouse, and Erik Arthur. 2001. “Improving Street Name Sign Legibility for Older Drivers.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 45 (23): 1597–1601. https://doi.org/10.1177/154193120104502308
- Ciobanu, Alina Maria, and Liviu P. Dinu. 2014. “An Etymological Approach to Cross-Language Orthographic Similarity. Application on Romanian.” In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics. https://doi.org/10.3115/v1/d14-1112
- Clark, Lynn, and Gareth John Williams. 2020. “English Language Proficiency in Radiotelephony: A Survey about Its Effect on the Safety and Efficiency of Aviation.” ESPecialist 41 (4). https://doi.org/10.23925/2318-7115.2020v41i4a9
- Clarke, Robert, Michael J. Allen, Ryan P. Dibley, Joseph Gera, and John Hodgkinson. 2005. Flight Test of the F/A-18 Active Aeroelastic Wing Airplane. NASA Dryden Flight Research Center. https://ntrs.nasa.gov/citations/20050204120
- “Clinical Consequences of Look-Alike, Sound-Alike Medication Errors.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch007
- Clopper, Cynthia G., Janet B. Pierrehumbert, and Terrin N. Tamati. 2010. “Lexical Neighborhoods and Phonological Confusability in Cross-Dialect Word Recognition in Noise.” Laboratory Phonology 1 (1). https://doi.org/10.1515/labphon.2010.005
- Cloud, Phillip A. 1998a. “Document Numbering System.” In Engineering Procedures Handbook. Elsevier. https://doi.org/10.1016/b978-081551410-7.50016-7
- Cloud, Phillip A. 1998b. “Model Numbering System.” In Engineering Procedures Handbook. Elsevier. https://doi.org/10.1016/b978-081551410-7.50019-2
- Cloud, Phillip A. 1998c. “Part Numbering System.” In Engineering Procedures Handbook. Elsevier. https://doi.org/10.1016/b978-081551410-7.50020-9
- Cloud, Phillip A. 1998d. “Serial Numbering System.” In Engineering Procedures Handbook. Elsevier. https://doi.org/10.1016/b978-081551410-7.50022-2
- Coates, A., D. Allen, and D. Rivers-Moore. 2001. URN Namespace for NewsML Resources. RFC Editor. https://doi.org/10.17487/rfc3085
- “Coding of Adverse Events and Drug Names.” 2025. In Cobert’s Manual of Drug Safety and Pharmacovigilance. WORLD SCIENTIFIC. https://doi.org/10.1142/9789811297724_0016
- Cohen, Michael R. 1996. “Medication-Error Reporting: Banish a System That Blames.” Nursing 26 (1): 15. https://doi.org/10.1097/00152193-199601000-00007
- Cohen, Michael R. 2000a. “Misidentification of Alphanumeric Characters Confusion between Sufenta and Sublimaze Fortune 500 Company Benefit Plans Adopting Computerized Physician Order Entry Standards.” Hospital Pharmacy 35 (3): 234–36. https://doi.org/10.1177/001857870003500310
- Cohen, Michael R. 2000b. “Put a Stop to Problem-Prone Automatic Stop Order Policies/Pharmacists Should Review All Nonurgent Drug Orders before Administration/Be on Guard for Name Confusion with Two New Medications.” Hospital Pharmacy 35 (11): 1176–79. https://doi.org/10.1177/001857870003501101
- Cohen, Michael R. 2003. “Don’t Lose Track of Orders during Clarification Never Prescribe Leucovorin Calcium as “Folinic Acid” Confusion Mounting over Drug Name Suffixes Fellowship in Medication Safety.” Hospital Pharmacy 38 (12): 1120–22. https://doi.org/10.1177/001857870303801207
- Cohen, Michael R. 2004a. “Confusion between Various Acetylcysteine Dosage Forms: New Formulation of Cytoxan: Three-Way Name Mix-Up: Error despite Robotics?: Diabetes or Alzheimer Disease?” Hospital Pharmacy 39 (11): 1020–22. https://doi.org/10.1177/001857870403901102
- Cohen, Michael R. 2004b. “Metronidazole and Metformin: Prone to Mix-Ups: Soy Allergy?: Save Lives: Improve the Pneumococcal Vaccine Administration Rate: Inefficient Screening Process: Omitted Vaccine Administration: Flammability of Ethyl Chloride: Current Nonproprietary Drug Names under Consideration by United States Adopted Names Council.” Hospital Pharmacy 39 (12): 1140–46. https://doi.org/10.1177/001857870403901202
- Cohen, Michael R. 2005. “Symlin Insulin Adjunct Presents Safety Issues; Changed Ophthalmic Color-Code; Name Pair Confusion.” Hospital Pharmacy 40 (8): 643–48. https://doi.org/10.1177/001857870504000802
- Cohen, Michael R. 2006. “Confusion between Two Forms of EDTA; Identical Name Error Which Spans Three Continents; New Form and Strength.” Hospital Pharmacy 41 (5): 405–6. https://doi.org/10.1310/hpj4105-405
- Cohen, Michael R. 2008. “Cross Contamination with Insulin Pens; Look-Alike Vials; Kids and Medication Patches; New Look-Alike Name Pair; Preventing Dosing Errors with Methotrexate Injection.” Hospital Pharmacy 43 (6): 445–47. https://doi.org/10.1310/hpj4306-445
- Cohen, Michael R., and Judy L. Smetzer. 2010a. “Distribute Instructions for Oral Dispenser; Seasonal Vaccine “H1N1” Is Not 2009 Pandemic Strain; Same Name, Different Drug; Confusion between Organ Preservation Solutions and IV Containers; Enteral Nutrition Safety; LQ? LAR? DSC? Drug Name Suffixes and Their Meanings.” Hospital Pharmacy 45 (6): 441–47. https://doi.org/10.1310/hpj4506-441
- Cohen, Michael R., and Judy L. Smetzer. 2010b. “No Extraneous Information, Please: Adding Drug to Hanging IV Bag Poses Many Risks: Doribax-Zovirax Name Confusion: Ambiguous Directions, Wrong Assumption by Patient.” Hospital Pharmacy 45 (12): 898–905. https://doi.org/10.1310/hpj4512-898
- Cohen, Michael R., and Judy L. Smetzer. 2018. “Multifactorial Causes of Tacrolimus Errors: Confusion with Strength/Formulation, Look-Alike Names, Preparation Errors, and More Ensuring Safety of Recipes for Drug Compounding Please, No More Teaspoon Dosing.” Hospital Pharmacy 53 (3): 142–45. https://doi.org/10.1177/0018578718769757
- Colby, Grace. 1992. “Maintaining Legibility, Structure, and Style of Information Layout in Dynamic Display Environments.” In Posters and short talks of the 1992 SIGCHI conference on Human factors in computing systems - CHI ‘92. ACM Press. https://doi.org/10.1145/1125021.1125089
- Cole, Richard, and Ramesh Hariharan. 2002. “Approximate String Matching: A Simpler Faster Algorithm.” SIAM Journal on Computing 31 (6): 1761–82. https://doi.org/10.1137/s0097539700370527
- Colomer, Jordi. 2012. “Appendix 2: Name-Matching Algorithms.” In The Small Worlds of Corporate Governance. The MIT Press. https://doi.org/10.7551/mitpress/9115.003.0014
- Comer, Douglas. 2025. “A Syntactic Namespace.” In Operating System Design. Chapman and Hall/CRC. https://doi.org/10.1201/9781003597667-21
- “The Communicative Aspect in the English Aviation Phraseology of Radiotelephony between a Pilot and an Air Traffic Controller.” 2023. Issues of applied linguistics, no. 49. https://doi.org/10.25076/vpl.49.02
- “Confusing Drug Names.” 1985. Drug and Therapeutics Bulletin 23 (20): 77–79. https://doi.org/10.1136/dtb.23.20.77
- Connell, Linda J., and William D. Reynard. 1993. EMS Helicopter Incidents Reported to the NASA Aviation Safety Reporting System. NASA Ames Research Center. https://ntrs.nasa.gov/citations/19950063602
- Copper and Copper Alloys. European Numbering System. n.d. BSI British Standards. https://doi.org/10.3403/00818537
- Corps Of Engineers Washington Dc. 1986. Plant: Radio Frequency and Call Sign Assignments. Defense Technical Information Center. https://doi.org/10.21236/ada404085
- Corrie, Stephan, and Stephan Corrie. 1997. “The U.S. Aviation Safety Reporting System.” In 1997 World Aviation Congress. AIAA 1997-5562. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.1997-5562
- Corter, James E. 1987. “Similarity, Confusability, and the Density Hypothesis.” Journal of Experimental Psychology: General 116 (3): 238–49. https://doi.org/10.1037//0096-3445.116.3.238
- Costello, Jennifer L., Deborah Lloyd Torowicz, and Timothy S. Yeh. 2007. “Effects of a Pharmacist-Led Pediatrics Medication Safety Team on Medication-Error Reporting.” American Journal of Health-System Pharmacy 64 (13): 1422–26. https://doi.org/10.2146/ajhp060296
- Crochemore, Maxime, and Thierry Lecroq. n.d. “Alignments and Approximate String Matching.” In Studies in Computational Intelligence. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-78291-9_3
- Crossman, Mark. 2009. “Technical and Environmental Impact on Medication Error in Paramedic Practice: A Review of Causes, Consequences and Strategies for Prevention.” Australasian Journal of Paramedicine 7: 1–10. https://doi.org/10.33151/ajp.7.3.170
- Cunningham, Kelli J. 2012. “Analysis of Clinical Interventions and the Impact of Pediatric Pharmacists on Medication Error Prevention in a Teaching Hospital.” Journal of Pediatric Pharmacology and Therapeutics 17 (4): 365–73. https://doi.org/10.5863/1551-6776-17.4.365
- Cusano, Frances L., Carole R. Chambers, and D. Lee Summach. 2008. “A Medication Error Prevention Survey: Five Years of Results.” Journal of Oncology Pharmacy Practice 15 (2): 87–93. https://doi.org/10.1177/1078155208099284
- Cushing, Steven. 1989. An Error-Resistant Linguistic Protocol for Air Traffic Control. NASA-CR-196098. NASA. https://ntrs.nasa.gov/citations/19940032505
- Cutler, Anne. 2005. “The Lexical Statistics of Word Recognition Problems Caused by L2 Phonetic Confusion.” In Interspeech 2005. ISCA. https://doi.org/10.21437/interspeech.2005-275
- Dai, Lixin. 2022. “A Study on Radiotelephony English Test Design.” MATEC Web of Conferences 355: 03051. https://doi.org/10.1051/matecconf/202235503051
- Dai, Dongbo, and Gang Zhao. 2009. “Incremental Similarity Joins with Edit Distance Constraints.” In Proceedings of the 18th ACM conference on Information and knowledge management. ACM. https://doi.org/10.1145/1645953.1646142
- Daigle, L., D. Van, R. Iannella, and P. Falstrom. 1999. URN Namespace Definition Mechanisms. RFC Editor. https://doi.org/10.17487/rfc2611
- DanishAli, Syed, and Zuber Farooqui. 2013a. “Approximate Multiple Pattern String Matching Using Bit Parallelism: A Review.” International Journal of Computer Applications 74 (19): 47–51. https://doi.org/10.5120/13006-0312
- DanishAli, Syed, and Zuber Farooqui. 2013b. “Improved Approximate Multiple Pattern String Matching Using Consecutive Q Grams of Pattern.” International Journal of Computer Applications 76 (15): 1–6. https://doi.org/10.5120/13320-0451
- DaPolito, K. L., M. E. Jones, and S. B. Hottman. 1989. Operator Performance Measures for Assessing Voice Communication Effectiveness. Defense Technical Information Center. https://doi.org/10.21236/ada213934
- Dasopang, Eva Sartika, Adinda Utami, Fenny Hasanah, Desy Natalia Siahaan, and Niken Septriani Harefa. 2022. “Profil Penyimpanan Obat LASA (Look Alike Sound Alike) Pada Beberapa Apotek Di Kota Medan.” JFIOnline | Print ISSN 1412-1107 | e-ISSN 2355-696X 14 (2): 147–54. https://doi.org/10.35617/jfionline.v14i2.97
- Davis, Neil M. 1999. “Drug Names That Look and Sound Alike.” Hospital Pharmacy 34 (10): 1160–78. https://doi.org/10.1177/001857879903401006
- Davis, Neil M. 2000a. “A Medication Error Prevention Educational Retreat.” Hospital Pharmacy 35 (5): 466–68. https://doi.org/10.1177/001857870003500503
- Davis, Neil M. 2000b. “Medication Error Reporting: Persistence Will Pay Off.” Hospital Pharmacy 35 (2): 112–112. https://doi.org/10.1177/001857870003500204
- Davuth, Nhauo, and Sung-Ryul Kim. 2013. “A Better Edit Distance Measure Allowing for Block Swaps.” In Proceedings of the 2013 Research in Adaptive and Convergent Systems. ACM. https://doi.org/10.1145/2513228.2513282
- Dawodu, Isa Agaie, Francis Ifeanyi Okeke, Mubarak Umar Faruk, and Yusuf Ibrahin Kuriwa. 2023. “Developing a Unique Identifier of Smallest Possible Ballot Area That Create One-One-Match with Voting Unit Identifier for Efficient Election Management in Jos South LGA Plateau State, Nigeria.” Journal of Psychology and Political Science, no. 41: 1–9. https://doi.org/10.55529/jpps.41.1.9
- “Dealing With Look-Alike, Sound-Alike (LASA) Risks in Oncology Pharmacy.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch006
- Definition Identifier URNs in OGC Namespace. n.d. Open Geospatial Consortium, Inc. https://doi.org/10.62973/07-092r3
- Degroot, Morris H. 2004. Record Linkage and Matching Systems. Wiley. https://doi.org/10.1002/0471667196.ess2205
- Degroot, Morris H. 2014. Record Linkage and Matching Systems. Wiley. https://doi.org/10.1002/9781118445112.stat01783
- Dejos, Michael Claro. 2021. “Medication Safety and Medication Error Prevention.” In Remington. Elsevier. https://doi.org/10.1016/b978-0-12-820007-0.00039-8
- Dekker, Sidney W. A. 2017. “Human Error by Any Other Name.” In Routledge eBooks. Routledge. https://doi.org/10.4324/9781315202778-5
- Dembicki, Eugene L. 1967. “Look-Alike and Sound-Alike Drugs.” Journal of Psychosocial Nursing and Mental Health Services 5 (6): 604–8. https://doi.org/10.3928/0279-3695-19671101-11
- “Design of the Teaching and Simulation System for Radiotelephony Communication Course.” 2024. Journal of Digital Innovation for Humanity 5: 1–12. https://doi.org/10.31355/148
- Development of a 14-Digit Hydrologic Unit Code Numbering System for South Carolina. 1999. US Geological Survey. https://doi.org/10.3133/wri994015
- Devine, Jennifer. 2012. “Medication Error Reporting.” In Routledge eBooks. Routledge. https://doi.org/10.4324/9780203049327-31
- Dhande, Priti Pravin, Akshay V. Mule, and Akshay Chaudhari. 2021. “Retrospective Analysis of Look-Alike and Sound-Alike Drug Incidents in a Tertiary Care Hospital.” Indian Journal of Pharmacy Practice 14 (2): 114–17. https://doi.org/10.5530/ijopp.14.2.21
- Dhiman, Anil Kumar. 2015. “Digital Object Identifier: A Unique Identifier for Scholarly Assets.” Pearl: A Journal of Library and Information Science 9 (4). https://doi.org/10.5958/0975-6922.2015.00032.7
- Digital Token Identifier (DTI). Registration, Assignment and Structure: Method for Registration and Assignment. n.d. BSI British Standards. https://doi.org/10.3403/30412556
- “Digital Voice Communication Systems for UK Air Traffic Control Operations.” 2008. Aircraft Engineering and Aerospace Technology 80 (4). https://doi.org/10.1108/aeat.2008.12780dab.018
- Dimov, Dimo T. 1994. “An Approximate String Matching Method for Handwriting Recognition Post-Processing Using a Dictionary.” In Fundamentals in Handwriting Recognition. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-78646-4_19
- Ding, Guoyao, Tianrui Li, and Weili Zou. 2009. “A Novel Calculation Model of Approximate String Matching Based on Characteristic Parameters.” In Intelligent Decision Making Systems. WORLD SCIENTIFIC. https://doi.org/10.1142/9789814295062_0086
- Dixit, Sanjaya Mani. 2014. “Look-Alike and Sound-Alike Medicines: Let Us All Be Aware.” Journal of Kathmandu Medical College 2 (2): 75–83. https://doi.org/10.3126/jkmc.v2i2.10630
- Document Management. Portable Document Format: PDF 1.7 and 2.0 Structure Namespace Inclusion in ISO 32000-2. n.d. BSI British Standards. https://doi.org/10.3403/30436126
- Dodek, Peter, Kimberley Louie, Amanda Wilmer, Hubert Wong, Maja Grubisić, and Najib Ayas. 2010. “Medication Error Reporting Systems: A Survey of Canadian Intensive Care Units.” Canadian Journal of Hospital Pharmacy 63 (1): 20–4. https://doi.org/10.4212/cjhp.v63i1.864
- Dolle, Tobias, and Yury Rovnov. 2017. “What’s in a Name? The US Food and Drug Administration Issues a Guidance on the Non-Proprietary Naming of Biological Products.” European Journal of Risk Regulation 8 (3): 559–64. https://doi.org/10.1017/err.2017.46
- Dornis, Tim W. 2017. “Behind the Steele Curtain: An Empirical Study of Trademark Conflicts Law, 1952-2016.” Preprint, . https://doi.org/10.2139/ssrn.2995688
- Dorris, Nathan T., and Jerry Davis. 2003. “Testing the Effects of Label Deterioration on the Legibility and Comprehensibility of Warnings.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 47 (14): 1726–29. https://doi.org/10.1177/154193120304701402
- Dosunmu, Oyebode Oluwaseyi, and Rasaq Adisa. 2025. “Intervention on Look-Alike Sound-Alike Medication Errors for Patient Safety in Healthcare Institutions: A Systematic Review.” Preprint, . https://doi.org/10.22541/au.175674618.88225511/v1
- Drayton, Jennifer. n.d. “The Vocabulary of Aviation Radiotelephony Communication in Simulator Emergencies and the Contradictions in Air Traffic Controller Beliefs about Language Use.” PhD diss., Open Access Te Herenga Waka-Victoria University of Wellington. https://doi.org/10.26686/wgtn.17152022
- “DRUG NAMES.” 1964. JAMA 190 (6): 542. https://doi.org/10.1001/jama.1964.03070190062016
- “Drug Names That Look or Sound Alike.” 1979. BMJ 2 (6197): 1073.2-1073. https://doi.org/10.1136/bmj.2.6197.1073-a
- Duncan, Jerry, and Stephan Konz. 1974. “Effect of Ambient Illumination on Legibility of Displays of Liquid-Crystals and Light-Emitting Diodes.” Proceedings of the Human Factors Society Annual Meeting 18 (1): 102–8. https://doi.org/10.1177/154193127401800124
- Dunn-Rankin, Peter, Donald A. Leton, and Velma F. Shelton. 1968. “Congruency Factors Related to Visual Confusion of English Letters.” Perceptual and Motor Skills 26 (2): 659–66. https://doi.org/10.2466/pms.1968.26.2.659
- Earth-Moving Machinery. Product Identification Numbering System. n.d. BSI British Standards. https://doi.org/10.3403/00556567u
- Edgar, Todd A., Doris S. Lee, and Diane D. Cousins. 1994. “Experience with a National Medication Error Reporting Program.” American Journal of Health-System Pharmacy 51 (10): 1335–38. https://doi.org/10.1093/ajhp/51.10.1335
- “Effects of Perceptual Similarity on Name Selection.” 2005. In Psychology Press eBooks. https://doi.org/10.4324/9780203990292-12
- Eggemeier, F. Thomas, Andrea B. Granitz, Timothy E. Rogus, and Eric E. Geiselman. 1990. “Development of Automatic Processing with Alphanumeric Materials.” Proceedings of the Human Factors Society Annual Meeting 34 (18): 1357–61. https://doi.org/10.1177/154193129003401812
- Elmzughi, Rima F., Aya Abuhasina, and Omaymah Abdulsalam. 2025. “Impact of Illegible Handwritten Prescriptions on Dispensing Errors: A Focus on Look-Alike Sound-Alike Medications in Libyan Community Pharmacies.” EAS Journal of Pharmacy and Pharmacology 7 (03): 73–82. https://doi.org/10.36349/easjpp.2025.v07i03.004
- Elnour, Asim Ahmed, Nagy H. Ellahham, and Huria I. Al Qassas. 2007. “Implementation of Medication Error Reporting through Med Safe Tool: The Clinical Pharmacists and the Inpatient Nursing Staff Collaborative Approach.” Journal of Patient Safety 3 (4): 177–83. https://doi.org/10.1097/pts.0b01e31815a6110
- Elsmore, B. 1986. “The IAU Numbering System of Radio Sources.” In Astrometric Techniques. Springer Netherlands. https://doi.org/10.1007/978-94-009-4676-7_92
- Elvretta, Jesica Jane, Jultuti Arni Lase, Yuhelmita Sakerebau, Juniarta Juniarta, and Fransiska Ompusunggu. 2021. “Gambaran Sikap Perawat Dalam Melaporkan Insiden Medication Error [Description of Nurses’ Attitude in Reporting Incidents of Medication Error].” Nursing Current Jurnal Keperawatan 8 (2): 127. https://doi.org/10.19166/nc.v8i2.3097
- Embossed Credit Cards. Specifications, Numbering System and Registration Procedure. n.d. BSI British Standards. https://doi.org/10.3403/30309373
- “Empirical Studies of Trademark Law.” 2019. In Edward Elgar Publishing eBooks. Edward Elgar Publishing. https://doi.org/10.4337/9781789903997.00073
- Erdmann, Robert L., and Alan S. Neal. 1968. “Character Legibility and Digital Facsimile Resolution.” Human Factors: The Journal of the Human Factors and Ergonomics Society 10 (5): 465–73. https://doi.org/10.1177/001872086801000502
- F02 Committee. n.d. Practice to Enhance Identification of Drug Names on Labels. ASTM International. https://doi.org/10.1520/d6398
- Falzon, Paul A. 2009. “Discourse Segmentation and the Management of Multiple Tasks in Single Episodes of Air Traffic Controller-Pilot Spoken Radio Communication.” Discours 4. https://doi.org/10.4000/discours.7241
- Faure, Pascaline. 2018. “Natesto®. What Else? New Trends in Drug Naming.” Names 66 (2): 65–74. https://doi.org/10.1080/00277738.2017.1415532
- Fell, James C., and Kenneth R. Laughery. 1969. “Short-Term Memory: Mode of Presentation for Alphanumeric Information.” Human Factors: The Journal of the Human Factors and Ergonomics Society 11 (4): 401–5. https://doi.org/10.1177/001872086901100412
- Fenner, Martin. 2010a. “ORCID as Unique Author Identifier: What Is It Good for and Should We Worry or Be Happy?” Preprint, Front Matter. https://doi.org/10.53731/tr1wp-0wn11
- Fenner, Martin H. 2010b. ORCID or How to Build a Unique Identifier for Scientists in 10 Easy Steps. https://doi.org/10.53731/r294649-6f79289-8cw3k
- Fenner, Martin H. 2010c. Survey Asks for Feedback about ORCID Unique Researcher Identifier. https://doi.org/10.53731/r294649-6f79289-8cw8c
- Ferber, Robert, and Joseph Weitz. 1960. “The FORUM: A Study of Trade Name Confusion.” Journal of Marketing 25 (2): 54–56. https://doi.org/10.1177/002224296002500210
- Fered, Nigusu Yitayal, Haymanot Matebie Yigzaw, and Ayenew Kassie Adimas. 2026. “Addressing Name Variation in Low-Resource Amharic Corpora: A Phonetic Normalization Strategy for Information Retrieval.” Preprint, . https://doi.org/10.2139/ssrn.6811521
- Festa, Giuseppe, Sergio Chirico, Jamel Chouaibi, and Renato Civitillo. 2021. “Cultural Approach to Healthcare Risk Management: An Italian Experience with Look-Alike, Sound-Alike Drugs.” International Journal of Managerial and Financial Accounting 13 (1): 64. https://doi.org/10.1504/ijmfa.2021.116220
- Fhima, Ilanah. 2026. “Initial Interest Confusion (Relative Grounds for Refusal of Trademark Registration).” In Elgar Encyclopedia of Intellectual Property Law. Edward Elgar Publishing. https://doi.org/10.4337/9781800886926.initial.interest.confusion
- Fhima, Ilanah, and Dev S. Gangjee. 2019a. “Assessing Likelihood of Confusion.” In The Confusion Test in European Trade Mark Law. Oxford University Press. https://doi.org/10.1093/oso/9780199674336.003.0006
- Fhima, Ilanah, and Dev S. Gangjee. 2019b. “Introduction: The Likelihood of Confusion.” In The Confusion Test in European Trade Mark Law. Oxford University Press. https://doi.org/10.1093/oso/9780199674336.003.0001
- Fhima, Ilanah, and Dev S. Gangjee. 2019c. “Non-Traditional Marks and the Likelihood of Confusion.” In The Confusion Test in European Trade Mark Law. Oxford University Press. https://doi.org/10.1093/oso/9780199674336.003.0008
- Filik, Ruth, Kevin Purdy, Alastair Gale, and David Gerrett. 2006. “Labeling of Medicines and Patient Safety: Evaluating Methods of Reducing Drug Name Confusion.” Human Factors: The Journal of the Human Factors and Ergonomics Society 48 (1): 39–47. https://doi.org/10.1518/001872006776412199
- Filik, Ruth, Kevin J. Purdy, Alastair G. Gale, and David Gerrett. 2019. “Investigating Medication Errors Caused by Confusable Drug Names.” In Routledge eBooks. Routledge. https://doi.org/10.4324/9781315782362-86
- Financial Services � Natural Person Identifier (NPI) � Natural Person Identifier Lifecycle Operation and Management. n.d. BSI British Standards. https://doi.org/10.3403/30478791u
- Financial Services � Unique Product Identifier (UPI). n.d. BSI British Standards. https://doi.org/10.3403/30419364
- Financial Services. Legal Entity Identifier (LEI): Assignment. n.d. BSI British Standards. https://doi.org/10.3403/30403751
- Financial Services. Unique Transaction Identifier (UTI). n.d. BSI British Standards. https://doi.org/10.3403/30394050u
- Fiori, Fernando J., Waltteri Pakalén, and Jorma Tarhio. 2021. “Approximate String Matching with SIMD.” Computer Journal 65 (6): 1472–88. https://doi.org/10.1093/comjnl/bxaa193
- Fischer, Rudolf-Josef. 1982. “A Threshold Method of Approximate String Matching.” In Lecture Notes in Medical Informatics. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-93201-4_150
- Folli, Hugo L., Robert L. Poole, William E. Benitz, and Janita C. Russo. 1987. “Medication Error Prevention by Clinical Pharmacists in Two Children’s Hospitals.” Pediatrics 79 (5): 718–22. https://doi.org/10.1542/peds.79.5.718
- Fox, Doug, Barbara S. Chaparro, and Ed Merkle. 2008. “Examining the Onscreen Legibility of the Number ‘0’ and Number ‘1’.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 52 (6): 547–51. https://doi.org/10.1177/154193120805200608
- Frances, Candice, Eugenia Navarra-Barindelli, and Clara Martin. 2020. “Inhibitory and Facilitatory Effects of Phonological and Orthographic Similarity on Bilingual Word Recognition.” Preprint, Research Square. https://doi.org/10.21203/rs.3.rs-119578/v1
- Fraser, Neil C. 1980. “Drug Names That Look or Sound Alike.” BMJ 280 (6208): 185.3-185. https://doi.org/10.1136/bmj.280.6208.185-b
- Fredriksson, Kimmo. 2006. “On-Line Approximate String Matching in Natural Language.” Fundamenta Informaticae 72 (4): 453–66. https://doi.org/10.3233/fun-2006-72402
- Friedman, Mary McGoldrick. 2005. “MEDICATION SAFETY: Look-Alike/Sound-Alike Drugs in Home Care.” Home Healthcare Nurse: The Journal for the Home Care and Hospice Professional 23 (4): 243–53. https://doi.org/10.1097/00004045-200504000-00011
- Fritch, David M. 2006. “Searching for Initial Interest Confusion Im Trademark Protection in Cyberspace.” Pittsburgh Journal of Technology Law and Policy 6. https://doi.org/10.5195/tlp.2006.24
- Furukawa, Hiroyuki, Hisashi Bunko, Fumito Tsuchiya, and Ken-ichi Miyamoto. 2003. “Voluntary Medication Error Reporting Program in a Japanese National University Hospital.” Annals of Pharmacotherapy 37 (11): 1716–22. https://doi.org/10.1345/aph.1c330
- “A Fused Situational Awareness Model of Air Traffic Controller andPilot by Radiotelephony.” 2025. In Proceedings of 2025 the 15th International Workshop on Computer Science and Engineering. WCSE. https://doi.org/10.18178/wcse.2025.06.047
- G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies. 2004. Recommended Part Numbering Guidelines for Fluid System Components Inch System of Measurements. https://doi.org/10.4271/arp1590
- Gadd, T. N. 1988. “‘Fisching Fore Werds’: Phonetic Retrieval of Written Text in Information Systems.” Program 22 (3): 222–37. https://doi.org/10.1108/eb046999
- Gahrns, M., and C. Newman. 1998. IMAP4 Namespace. RFC Editor. https://doi.org/10.17487/rfc2342
- Galanter, William L., Michelle L. Bryson, Suzanne Falck, et al. 2014. “Indication Alerts Intercept Drug Name Confusion Errors during Computerized Entry of Medication Orders.” PLoS ONE 9 (7): e101977. https://doi.org/10.1371/journal.pone.0101977
- Galil, Zvi, and Kunsoo Park. 1990. “An Improved Algorithm for Approximate String Matching.” SIAM Journal on Computing 19 (6): 989–99. https://doi.org/10.1137/0219067
- Gao, Guilin, and Tianyi Wang. 2018. “An Analysis of the Reverse Confusion of Trademark Rights.” In Proceedings of the 2018 2nd International Conference on Education Science and Economic Management (ICESEM 2018). Atlantis Press. https://doi.org/10.2991/icesem-18.2018.135
- Garvey, Philip M., Abdulilah Z. Zineddin, and Martin T. Pietrucha. 2001. “Letter Legibility for Signs and Other Large Format Applications.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 45 (18): 1443–47. https://doi.org/10.1177/154193120104501828
- “Generalized String Matching.” 2015. In Analytic Pattern Matching. Cambridge University Press. https://doi.org/10.1017/cbo9780511843204.007
- Geographic Information. Place Identifier (PI) Architecture: Place Identifier (PI) Linking. n.d. BSI British Standards. https://doi.org/10.3403/30284322u
- George, Jacob. 2023. “Adding to the Confusion in More than Just the Name.” Clinical and Molecular Hepatology 29 (4): 973–76. https://doi.org/10.3350/cmh.2023.0367
- Gewurz, Daniele A., and Andrea Vietri. 2007. “A combinatorial approach to the phonetic similarity of language.” Mathématiques et sciences humaines 179: 21–44. https://doi.org/10.4000/msh.6803
- Giannino, Michele. 2022. “The Italian Court of Cassation Confirms Likelihood of Confusion Is Not a Requisite for Additional Protection of a Trade Mark with a Reputation.” Preprint, . https://doi.org/10.2139/ssrn.4005339
- Giegerich, Robert, Stefan Kurtz, Frank Hischke, and Enno Ohlebusch. 1997. “A General Technique to Improve Filter Algorithms for Approximate String Matching.” In Fourth South American Workshop on String Processing (WSP 1997). McGill-Queen’s University Press. https://doi.org/10.1515/9780773591400-006
- Giolas, Thomas G., Harry S. Cooker, and Joseph R. Duffy. 1971. Studies of Voice Communication in the Navy: Sentence Predictability. Defense Technical Information Center. https://doi.org/10.21236/ad0734121
- Giolas, Thomas G., Joseph R. Duffy, Robert J. Duffy, Harry S. Cooker, and Russell L. Sergeant. 1973. Equivalency of Sentence Intelligibility Lists for Audiological Assessment of Naval Personnel and Navy Voice Communication Systems. Defense Technical Information Center. https://doi.org/10.21236/ad0775684
- Giordani, Lorenza. 2025. “Consumer Attention in the Digital Era: Modernizing the Likelihood of Confusion Standard.” GRUR International 74 (8): 724–35. https://doi.org/10.1093/grurint/ikaf084
- Glushanytsia, Nataliia. 2020. “Radiotelephony Discourse Analysis: The Case of Aviation English.” Humanities science current issues 1 (27): 98–105. https://doi.org/10.24919/2308-4863.1/27.203373
- Gong, Jun, Lidan Wang, and Douglas W. Oard. 2009. “Personal Name-Matching through Name Transformation.” In Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries. ACM. https://doi.org/10.1145/1555400.1555476
- Gonzales, Janine Mae, Christina Marie Moneda, Martin Angelo Semilla, and Keneth Sedilla. 2018. “Factors Affecting Legibility and Readability of Philippine Metropolitan Bus Signage.” In Advances in Intelligent Systems and Computing. Springer International Publishing. https://doi.org/10.1007/978-3-319-93888-2_15
- Grant, Matthew. 2017. “Prescribing Generic Drugs Will Reduce Patient Confusion and Medication Errors.” Preprint, . https://doi.org/10.64628/aa.jj7gh756t
- Greco, M., N. Stucchi, D. Zavagno, and B. Marino. 2008. “On the Portability of Computer-Generated Presentations: The Effect of Text-Background Color Combinations on Text Legibility.” Human Factors: The Journal of the Human Factors and Ergonomics Society 50 (5): 821–33. https://doi.org/10.1518/001872008x354156
- Greene, Kevin J. 2003. “Abusive Trademark Litigation and the Shrinking Doctrine of Consumer Confusion: Trademark Abuse in the Context of Entertainment Media and Cyberspace.” Preprint, . https://doi.org/10.2139/ssrn.446100
- Greene, Frances A., R. Dale Huchingson, and Rodger J. Koppa. 1995. “Comparison of Simulation and Field Legibility Distances for Symbol Highway Signs.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 39 (17): 1147–51. https://doi.org/10.1177/154193129503901717
- Greene, Frances A., Rodger J. Koppa, Ronald D. Zellner, and Jerome J. Congleton. 1994. “Determining Legibility Distance for Highway Signs: Is the within Subject Variability Being Overlooked?” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38 (14): 907–11. https://doi.org/10.1177/154193129403801424
- Grindrod, Kelly Anne, Carole R. Chambers, and Jolene Hicks. 2002. “Updating a Survey for Medication Error Prevention.” Journal of Oncology Pharmacy Practice 8 (4): 105–17. https://doi.org/10.1191/1078155202jp098oa
- Grissinger, Matthew, Michael Gaunt, and Alexander Shilman. 2019. “Allergy-Related Medication Error Reports Submitted to a Large Patient Safety Reporting System.” Patient Safety: 18–27. https://doi.org/10.33940/medical/2019.9.3
- Gschneider, K., Jr. 1976. Commercial Rare Earth Metals and Alloys Covered by the Unified Numbering System (UNS). Office of Scientific and Technical Information (OSTI). https://doi.org/10.2172/7251906
- Guclu, Orhan Ertugrul. 2017. “New Approach to the ATC-Pilot Radio Communication Phraseology Phonetic Confusion.” In Advances in Sustainable Aviation. Springer International Publishing. https://doi.org/10.1007/978-3-319-67134-5_20
- Gunderson, Jon, George Gruetzmacher, and Naomi Swanson. 1991. “Legibility of Seven Segment Numeric LED Displays: Comparisons of Two Fonts at Various Distances.” Proceedings of the Human Factors Society Annual Meeting 35 (6): 491–95. https://doi.org/10.1518/107118191786754941
- Guvenkaya, Hilal. 2026. “Can AI Be Confused: AI and the Concepts of Average Consumer and Likelihood of Confusion.” Preprint, . https://doi.org/10.2139/ssrn.6333658
- Hachemi, Khalid, Anas Mouattah, and Souad Moufok. 2024. “K-Means and DBSCAN for Look Alike-Sound Alike Medicines Issue.” International Journal of Data Mining, Modelling and Management 16 (1): 10057242. https://doi.org/10.1504/ijdmmm.2024.10057242
- Hacquard, Valentine, and Mary Ann Walter. 2003. “Consonant Confusability: An MEG Study.” Proceedings of the Annual Meeting of the Berkeley Linguistics Society 29 (1): 535. https://doi.org/10.3765/bls.v29i1.977
- Hajibabaee, F., S. Joolaee, H. Peyravi, H. Alijany-Renany, N. Bahrani, and H. Haghani. 2014. “Medication Error Reporting in Tehran: A Survey.” Journal of Nursing Management 22 (3): 304–10. https://doi.org/10.1111/jonm.12226
- Hall, Kathleen C., and Elizabeth V. Hume. 2013. “Perceptual Confusability of French Vowels.” In Proceedings of Meetings on Acoustics. ASA. https://doi.org/10.1121/1.4800615
- Hamad Abdelaziz, Ibrahim, Manal Salah Hassan, and Zeinab Hussien Bakr. 2024. “Nurses Performance Regarding Safety Infusion of Look-Alike Sound-Alike Medication in Intensive Care Units.” Egyptian Journal of Health Care 15 (3): 708–16. https://doi.org/10.21608/ejhc.2024.379509
- Hampton, Tracy. 2011. “Drug Name Confusion.” JAMA 306 (4): 366. https://doi.org/10.1001/jama.2011.1012
- Hamzah, Haryani, Pramela Krish, and Afendi Hamat. 2022. “Communication Competence in Pilot-Controller Interactions: Repair and Accommodation Strategies.” GEMA Online® Journal of Language Studies 22 (3). https://doi.org/10.17576/gema-2022-2203-10
- Hancox, Peter, and Nikolaos Polatidis. 2013. “An Evaluation of Keyword, String Similarity and Very Shallow Syntactic Matching for a University Admissions Processing Infobot.” Computer Science and Information Systems 10 (4): 1703–26. https://doi.org/10.2298/csis121202065h
- Hanmei, E., Yunqing Yu, Kensuke Baba, and Kazuaki Murakami. 2019. “Approximate String Matching Based on Bit Operations.” In Recent Progress in Computational Sciences and Engineering. CRC Press. https://doi.org/10.1201/9780429070655-48
- Harrison, Randal Sean. 2013. “The Problematic of Privacy in the Namespace.” PhD diss.. https://doi.org/10.37099/mtu.dc.etds/666
- Hartmann, William, and Eric Fosler-Lussier. 2009. “Investigating Phonetic Information Reduction and Lexical Confusability.” In Interspeech 2009. ISCA. https://doi.org/10.21437/interspeech.2009-503
- Hartnell, Nicole, Neil MacKinnon, Ingrid Sketris, and Mark Fleming. 2012. “Identifying, Understanding and Overcoming Barriers to Medication Error Reporting in Hospitals: A Focus Group Study.” BMJ Quality & Safety 21 (5): 361–68. https://doi.org/10.1136/bmjqs-2011-000299
- Hartwig, Steven C., Sharon D. Denger, and Philip J. Schneider. 1991. “Severity-Indexed, Incident Report-Based Medication Error-Reporting Program.” American Journal of Health-System Pharmacy 48 (12): 2611–16. https://doi.org/10.1093/ajhp/48.12.2611
- Hayati, Hadi, and Majid Piramoon. 2023. “Preventive Risk Assessment of Medication in Intensive Wards.” International Journal of Preventive Medicine 14 (1): 117. https://doi.org/10.4103/ijpvm.ijpvm_290_22
- Health Informatics. Health Cards. Numbering System and Registration Procedure for Issuer Identifiers. n.d. BSI British Standards. https://doi.org/10.3403/30084399
- Heggarty, Paul, April McMahon, and Robert McMahon. 2005. “From Phonetic Similarity to Dialect Classification: A Principled Approach.” In Perspectives on Variation. DE GRUYTER MOUTON. https://doi.org/10.1515/9783110909579.43
- Hemingway, John C., and Ronald A. Erickson. 1969. “Relative Effects of Raster Scan Lines and Image Subtense on Symbol Legibility on Television.” Human Factors: The Journal of the Human Factors and Ergonomics Society 11 (4): 331–38. https://doi.org/10.1177/001872086901100404
- Her, Qoua L., and Sengwee Toh. 2019. “Sound-Alike Look-Alike Confusion and Matching Medication Product Attributes: Simulated Case-Control Studies.” Annals of Pharmacotherapy 53 (10): 973–80. https://doi.org/10.1177/1060028019838239
- Hershenson, Maurice, and Joan M. Ryder. 1982. “Perceived Symmetry and Name Matching.” Bulletin of the Psychonomic Society 19 (1): 19–22. https://doi.org/10.3758/bf03330028
- Herzog, Thomas N., Fritz J. Scheuren, and William E. Winkler. n.d.-a. “Phonetic Coding Systems for Names.” In Data Quality and Record Linkage Techniques. Springer New York. https://doi.org/10.1007/0-387-69505-2_11
- Herzog, Thomas N., Fritz J. Scheuren, and William E. Winkler. n.d.-b. “String Comparator Metrics for Typographical Error.” In Data Quality and Record Linkage Techniques. Springer New York. https://doi.org/10.1007/0-387-69505-2_13
- Hicks, Rodney W., and Shawn C. Becker. 2006. “An Overview of Intravenous-Related Medication Administration Errors as Reported to MEDMARX®, a National Medication Error-Reporting Program.” Journal of Infusion Nursing 29 (1): 20–27. https://doi.org/10.1097/00129804-200601000-00005
- Hilton, D. 1980. “Points: Drug Names That Look or Sound Alike.” BMJ 280 (6209): 257.6-257. https://doi.org/10.1136/bmj.280.6209.257-e
- Ho, Anson, Catherine Maritan, Jeffery Sullivan, Eric Cheng, and Shi Cao. 2016. “Measuring Glance Legibility of Wearable Heads-Up Display Interfaces Using an Adaptive Staircase Procedure: A Study with Google Glass.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60 (1): 2073–77. https://doi.org/10.1177/1541931213601470
- Holmström, Anna-Riia, Marja Airaksinen, Marjorie Weiss, Tana Wuliji, Xuan Hao Chan, and Raisa Laaksonen. 2012. “National and Local Medication Error Reporting Systems—a Survey of Practices in 16 Countries.” Journal of Patient Safety 8 (4): 165–76. https://doi.org/10.1097/pts.0b013e3182676cf3
- Howard, Daniel J., Roger A. Kerin, and Charles Gengler. 2000. “The Effects of Brand Name Similarity on Brand Source Confusion: Implications for Trademark Infringement.” Journal of Public Policy & Marketing 19 (2): 250–64. https://doi.org/10.1509/jppm.19.2.250.17131
- Howard, James P., II. 2018. “Phonetic Algorithms in R.” Journal of Open Source Software 3 (22): 480. https://doi.org/10.21105/joss.00480
- Howard, James P., II. 2020. “Phonetic Spelling Algorithm Implementations for R.” Journal of Statistical Software 95 (8). https://doi.org/10.18637/jss.v095.i08
- Hristina Viktorova Lebanova. 2012. “Descriptive Study for Look-Alike and Sound-Alike Medicines Based on Local Language Peculiarities.” African Journal of Pharmacy and Pharmacology 6 (28). https://doi.org/10.5897/ajpp12.496
- Hritz, Richard W., Jill L. Everly, and Sandra A. Care. 2002. “Medication Error Identification Is a Key to Prevention: A Performance Improvement Approach.” Journal For Healthcare Quality 24 (2): 10–17. https://doi.org/10.1111/j.1945-1474.2002.tb00413.x
- Htun Htet Htet and Sornlertlamvanich Virach. 2018. “SNOMED CT Primitive Concept Similarity Measure by Concept Name Text Similarity Approach.” In Frontiers in Artificial Intelligence and Applications. IOS Press. https://doi.org/10.3233/978-1-61499-834-1-373
- Huang, Jun Xiang, and Hong Yong Wang. 2015. “Relationship of Traffic Complexity and Pilot-Controller Voice Communication Load.” Applied Mechanics and Materials 744-746: 1980–84. https://doi.org/10.4028/www.scientific.net/amm.744-746.1980
- Huerta, Juan M. 2010. “A Stack Decoder Approach to Approximate String Matching.” In Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval. ACM. https://doi.org/10.1145/1835449.1835634
- “Human Error Identification and Accident Analysis Methods.” 2017. In Human Factors Methods. CRC Press. https://doi.org/10.1201/9781315587394-6
- “Human Error Identification and Analysis Methods.” 2009. In Human Factors Methods and Sports Science. CRC Press. https://doi.org/10.1201/9781420072181-c5
- “Human Error in Medication.” 2003. In Series on Industrial and Systems Engineering. WORLD SCIENTIFIC. https://doi.org/10.1142/9789812795236_0006
- “Human-Error Identification in Human-Computer Interaction.” 2007. In The Human-Computer Interaction Handbook. CRC Press. https://doi.org/10.1201/9781410615862-17
- “Human-Error Identification in Human–Computer Interaction.” 2009. In Human-Computer Interaction Fundamentals. CRC Press. https://doi.org/10.1201/b10368-14
- Hussey, Hugh H. 1974. “Name Confusion.” JAMA: The Journal of the American Medical Association 228 (10): 1273. https://doi.org/10.1001/jama.1974.03230350045030
- “Identical or Confusingly Similar Domain Names.” 2014. In Hart Publishing eBooks. https://doi.org/10.5040/9781472564184.ch-005
- “Improved Air-Traffic Control Voice-Communications Systems for UK.” 2005. Aircraft Engineering and Aerospace Technology 77 (6). https://doi.org/10.1108/aeat.2005.12777fab.009
- Inecik, Kemal, Erkmen Erken, and Fabian J. Theis. 2026. “IDTrack: Time- and Namespace-Aware Identifier Harmonization for Reproducible Workflows.” Preprint, bioRxiv. https://doi.org/10.64898/2026.02.05.703984
- Information Technology. Unique Identifiers: Unique Identifier for Product Groupings. n.d. BSI British Standards. https://doi.org/10.3403/30151784
- “Integrated Strategies for Preventing Look-Alike Sound-Alike (LASA) Medication Errors.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch002
- “Introduction to Look-Alike, Sound-Alike Medication Errors.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch001
- Ishikawa, C. 2012. A URN Namespace for Ucode. RFC Editor. https://doi.org/10.17487/rfc6588
- Ivory, Catherine H., and Nancy Beale. 2025. “Economic Implications of Adopting a Unique Nurse Identifier.” Nursing Economic$ 43 (1): 33. https://doi.org/10.62116/nec.2025.43.1.33
- J-P. Evain. 2008. A Uniform Resource Name (URN) Namespace for the European Broadcasting Union (EBU). RFC Editor. https://doi.org/10.17487/rfc5174
- Jacobson, Daniel R. 2018. “Unique Device Identifier Database Integration for Clinical Engineers.” Journal of Clinical Engineering 43 (2): 71–74. https://doi.org/10.1097/jce.0000000000000264
- Jacoby, Jacob. 2000. “The Psychological Foundations of Trademark Law: Secondary Meaning, Acquired Distinctiveness, Genericism, Fame, Confusion and Dilution.” Preprint, . https://doi.org/10.2139/ssrn.229325
- Jae Jeong, Heon. 2017. “A Strategy to Overcome under-Reporting Issues of Voluntary Medication Error Reporting System, Part II: Changes in Number of Reports by a Counter-Error Measure—Computerized Prescriber Order Entry.” Biometrics & Biostatistics International Journal 5 (5). https://doi.org/10.15406/bbij.2017.05.00146
- Jae-Yun, Ho, and Jin-Kook Choi. 2023. “A Study on Non-Compliance with Standard Phraseology and Communication Errors in Pilot-Controller Communication.” Korean Journal of Aerospace and Environmental Medicine 33 (3): 65–70. https://doi.org/10.46246/kjasem.230011
- Jani, Mátyás, Catia Cucchiarini, Roeland van Hout, and Helmer Strik. 2015. “Confusability in L2 Vowels: Analyzing the Role of Different Features.” In Interspeech 2015. ISCA. https://doi.org/10.21437/interspeech.2015-394
- Jeong, Byung-Hui, Jin-Tak Choi, Reeyan Kyoo Ho Lee, Dong Ha Park, and Chang Il Kim. 2014. “Study of the Private Information Similarity and the Distinguishing Module Development Improvement of Korean Name String Similarity Algorithm.” In Advanced Science and Technology Letters. Science & Engineering Research Support soCiety. https://doi.org/10.14257/astl.2014.63.29
- Jethanandani, M. 2016. URN Namespace for MEF Documents. RFC Editor. https://doi.org/10.17487/rfc7818
- Jethanandani, M., and M. A. Reina Ortega. 2019. URN Namespace for ETSI Documents. RFC Editor. https://doi.org/10.17487/rfc8515
- Jia, Guimin, Yujun Lu, Weibing Lu, Yihua Shi, and Jinfeng Yang. 2017. “Verification Method for Chinese Aviation Radiotelephony Readbacks Based on LSTM-RNN.” Electronics Letters 53 (6): 401–3. https://doi.org/10.1049/el.2016.2877
- Jiang, Anqi. 2024. “Revisiting the Issue of Regulatory Measures for Trademark Reverse Confusion.” Beijing Law Review 15 (01): 249–70. https://doi.org/10.4236/blr.2024.151016
- Jiang, Yu, Dong Deng, Jiannan Wang, Guoliang Li, and Jianhua Feng. 2013. “Efficient Parallel Partition-Based Algorithms for Similarity Search and Join with Edit Distance Constraints.” In Proceedings of the Joint EDBT/ICDT 2013 Workshops. ACM. https://doi.org/10.1145/2457317.2457382
- Jiang, Yu, Guoliang Li, Jianhua Feng, and Wen-Syan Li. 2014. “String Similarity Joins: An Experimental Evaluation.” Proceedings of the VLDB Endowment 7 (8): 625–36. https://doi.org/10.14778/2732296.2732299
- Jintcharadze, Nukri. 2024. “Understanding Trademark Likelihood of Confusion: Unfair Competition in a Digital Era.” European Scientific Journal, ESJ 20 (14): 1. https://doi.org/10.19044/esj.2024.v20n14p1
- Joiner, Gayle A. 1994. “Developing a Proactive Approach to Medication Error Prevention.” Journal For Healthcare Quality 16 (2): 35–40. https://doi.org/10.1111/j.1945-1474.1994.tb00697.x
- Jongprasithporn, Manutchanok, Wichai Sunkarat, Thanakorn Homsai, Teppakorn Sittiwanchai, and Nantakrit Yodpijit. 2018. “The Performance Improvement of Look-Alike Sound-Alike Drug Pre-Dispensing.” MATEC Web of Conferences 192: 01051. https://doi.org/10.1051/matecconf/201819201051
- Joshi, M. C., H. S. Joshi, K. Tariq, A. Ejaj, S. Prayag, and A. Raju. 2007. “A Prospective Study of Medication Errors Arising out of Look-Alike and Sound-Alike Brand Names Confusion.” International Journal of Risk & Safety in Medicine 19 (4): 195–201. https://doi.org/10.3233/jrs-2007-416
- Judson, Dean H. 2005. “Computerized Record Linkage and Statistical Matching.” In Encyclopedia of Social Measurement. Elsevier. https://doi.org/10.1016/b0-12-369398-5/00190-0
- Kaeding, Patricia J. 1992. “Clearly Erroneous Review of Mixed Questions of Law and Fact: The Likelihood of Confusion Determination in Trademark Law.” University of Chicago Law Review 59 (3): 1291. https://doi.org/10.2307/1599865
- Kalin, T., and M. Molina. 2007. A URN Namespace for GEANT. RFC Editor. https://doi.org/10.17487/rfc4926
- Kamali, Omar. 2026. “Sawtone: A Universal Framework for Phonetic Similarity and Alignment across Languages and Scripts.” Lingua Posnaniensis 67 (1): 165–200. https://doi.org/10.14746/linpo.2025.67.1.8
- Kang, Seung-Shik. 2015. “Word Similarity Calculation by Using the Edit Distance Metrics with Consonant Normalization.” Journal of Information Processing Systems. https://doi.org/10.3745/jips.04.0018
- Kang, Shinae, and Clara Cohen. 2016. “Relationships between Functional Load and Auditory Confusability under Different Speech Environments.” In Interspeech 2016. ISCA. https://doi.org/10.21437/interspeech.2016-906
- Kant, Tapan, Shailesh Kumar Shrivastava, Niraj Kumar Tiwary, and Nagma Parween. 2020. “SoundexHindi: A Phonetic Matching Algorithm for Hindi Written in English.” Preprint, . https://doi.org/10.2139/ssrn.3579322
- Karakoyun, Ömer Faruk, Cem Abacı, Halil Emre Koyuncuoğlu, and Yalcin Golcuk. 2024. “Phonetic Ambiguities: Risks of Drug Name Confusion in Elderly Patient.” Journal of Emergency Medicine Case Reports 15 (3): 84–86. https://doi.org/10.33706/jemcr.1495028
- Kärkkäinen, Juha, and Joong Chae Na. 2007. “Faster Filters for Approximate String Matching.” In 2007 Proceedings of the Ninth Workshop on Algorithm Engineering and Experiments (ALENEX). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611972870.8
- Kaur, Arshpreet. 2026. “The Likelihood of Confusion: An Enduring Trademark Doctrine under Digital Strain.” Preprint, . https://doi.org/10.2139/ssrn.6445258
- Kavros, Antrei, and Yannis Tzitzikas. 2022. “SoundexGR: An Algorithm for Phonetic Matching for the Greek Language.” Natural Language Engineering 29 (5): 1305–40. https://doi.org/10.1017/s1351324922000018
- Kearny, Ide, and Vincent-Wayne Mitchell. 2001. “Measuring Consumer Brand Confusion to Comply with Legal Guidelines.” International Journal of Market Research 43 (1): 1–7. https://doi.org/10.1177/147078530104300103
- Keefer, Patricia, Kelley Kidwell, Candice Lengyel, Kavita Warrier, and Deborah Wagner. 2017. “Variability in Threshold for Medication Error Reporting between Physicians, Nurses, Pharmacists, and Families.” Current Drug Safety 12 (3). https://doi.org/10.2174/1574886312666170724163439
- Kelso, Barbara J. 1965. “Legibility Study of Selected Scale Characteristics for Moving-Tape Instruments.” Human Factors: The Journal of the Human Factors and Ergonomics Society 7 (6): 545–55. https://doi.org/10.1177/001872086500700606
- Kerpatenko, Yu. V., A. V. Shcherbyna, S. S. Kovalenko, and A. S. Ivanytska. 2024. “The ICAO Alphabet Retrospective as a Tool for Providing Unambiguous Radiotelephony Communication in Airspace: Historical and Linguistic Aspects.” Тrаnscarpathian Philological Studies 1 (33): 88–93. https://doi.org/10.32782/tps2663-4880/2024.33.1.15
- Keshtkar, Narges, Iravan Masoudi Asl, Somayeh Hessam, and Soad Mahfoozpour. 2023. “Management of Medication Error Reporting in HIV/AIDS Patients.” Evidence Based Health Policy, Management and Economics. https://doi.org/10.18502/jebhpme.v7i2.13138
- Khan, Sameer ud Dowla. 2013. “Consonant Confusability and Its Relation to Phonological Dissimilarity.” In Proceedings of Meetings on Acoustics. ASA. https://doi.org/10.1121/1.4801011
- Khan, Ahmad. 2021. “Medication Error Overview and Prevention Strategies.” American International Journal of Social Science Research: 19–24. https://doi.org/10.46281/aijssr.v8i1.1313
- Khan, Shahidul Islam, Rakib Hosen, and Iqbal Hossain. 2022. “Secure Approximate String Matching Using Homomorphic Encryption for Privacy-Preserving Record Linkage.” Preprint, . https://doi.org/10.20944/preprints202210.0064.v1
- Kianfar, Kiavash, Christopher Pockrandt, Bahman Torkamandi, Haochen Luo, and Knut Reinert. 2018. “Optimum Search Schemes for Approximate String Matching Using Bidirectional FM-Index.” Preprint, bioRxiv. https://doi.org/10.1101/301085
- Kim, Myoung Soo. 2012. “Medication Error Management Climate and Perception for System Use According to Construction of Medication Error Prevention System.” Journal of Korean Academy of Nursing 42 (4): 568. https://doi.org/10.4040/jkan.2012.42.4.568
- Kim, Hyejeong. 2013a. “Exploring the Construct of Radiotelephony Communication: A Critique of the ICAO English Testing Policy from the Perspective of Korean Aviation Experts.” Studies in Language Assessment: 103–10. https://doi.org/10.58379/ywll7105
- Kim, Myoung Soo. 2013b. “Role of Transformational-Leadership in the Relationship between Medication Error Management Climate and Error Reporting Intention of Nurse.” Korean Journal of Adult Nursing 25 (6): 633–43. https://doi.org/10.7475/kjan.2013.25.6.633
- Kim, Myoung Soo. 2016. “Discriminating Power of Organization Related Variables on Intention to Medication Error Reporting.” Journal of Health Informatics and Statistics 41 (2): 155–64. https://doi.org/10.21032/jhis.2016.41.2.155
- Kim, HyunJin. 2021. “A k-Mismatch String Matching for Generalized Edit Distance Using Diagonal Skipping Method.” PLOS ONE 16 (5): e0251047. https://doi.org/10.1371/journal.pone.0251047
- Kim, Jinkyung Jenny. 2024. “Brand Portfolio Extension of International Hotel Chains: A Perspective on Consumer Confusion and Consumer Decision-Making Process.” International Journal of Contemporary Hospitality Management 36 (9): 3093–3111. https://doi.org/10.1108/ijchm-02-2023-0245
- Kim, Sangho, Sungho Chang, Wookgee Lee, Kimok Shin, and Keunbae Lee. 2000. “The Influence of Crt Characteristics on Perception of Character Legibility.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44 (32): 6-35-6-38. https://doi.org/10.1177/154193120004403210
- Kim, Jeahong, JeYoung Jung, and Kichun Nam. 2021. “Neural Correlates of Confusability in Recognition of Morphologically Complex Korean Words.” PLOS ONE 16 (4): e0249111. https://doi.org/10.1371/journal.pone.0249111
- Kim, Jeong Eun, and Sung Cil Lim. 2019. “A Study on Correlations between Medication Error and Prescription by Trade Name.” Yakhak Hoeji 63 (4): 238–46. https://doi.org/10.17480/psk.2019.63.4.238
- Kimura, Kenji, Kenji Marunaka, and Seiichi Sugiura. 2020. “Human Factors Considerations for Automotive Navigation Systems— Legibility, Comprehension, and Voice Guidance.” In Ergonomics and Safety of Intelligent Driver Interfaces. CRC Press. https://doi.org/10.1201/9781003064107-8
- Kinney, Glenn C., Marion Marsetta, and Diana J. Showman. 1966. Studies of Display Symbol Legibility. Part 12. the Legibility of Alphanumeric Symbols for Digitalized Television. Defense Technical Information Center. https://doi.org/10.21236/ad0646660
- Kinoshita, Sachiko, and Stephen J. Lupker. 2004. “Transposed-Letter Confusability Effects in Masked Form Priming.” In Psychology Press eBooks. https://doi.org/10.4324/9780203502846-13
- Kirubakaran, Anusuya, and M. Aramudhan. 2018. “A Watchdog Approach: Name-Matching Algorithm for Big Data Risk Intelligence.” International Journal of Data Analysis Techniques and Strategies 10 (3): 273. https://doi.org/10.1504/ijdats.2018.094128
- Klassen, Kimberly. 2022. “Orthographic Processing of Proper Names: A Proposal to Investigate the Orthographic Cue for Second Language Readers.” Vocabulary Learning and Instruction 11 (2): 94–100. https://doi.org/10.7820/vli.v11.2.klassen
- Klensin, J., and J. Hakala. 2017. Uniform Resource Name (URN) Namespace Registration Transition. RFC Editor. https://doi.org/10.17487/rfc8254
- Klensin, J., T. Wolf, and G. Oglesby. 1998. Domain Names and Company Name Retrieval. RFC Editor. https://doi.org/10.17487/rfc2345
- Kocour, Martin, Karel Veselý, Alexander Blatt, et al. 2021. “Boosting of Contextual Information in ASR for Air-Traffic Call-Sign Recognition.” In Interspeech 2021. ISCA. https://doi.org/10.21437/interspeech.2021-1619
- Kondrak, Grzegorz, and Bonnie Dorr. 2004. “Identification of Confusable Drug Names: A New Approach and Evaluation Methodology.” In Proceedings of the 20th international conference on Computational Linguistics - COLING ‘04. Association for Computational Linguistics. https://doi.org/10.3115/1220355.1220492
- Kondrak, Grzegorz, and Tarek Sherif. 2006. “Evaluation of Several Phonetic Similarity Algorithms on the Task of Cognate Identification.” In Proceedings of the Workshop on Linguistic Distances - LD ‘06. Association for Computational Linguistics. https://doi.org/10.3115/1641976.1641983
- Koneru, Keerthi, Venkata Sai Venkatesh Pulla, and Cihan Varol. 2016. Performance Evaluation of Phonetic Matching Algorithms on English Words and Street Names: Comparison and Correlation. https://doi.org/10.5220/0005926300570064
- Koo, Bon-Ki. 2012. “Patient Safety Management in the Medication Use Process: Prevention and Management of Medication Error.” Journal of Korean Medical Association 55 (9): 835. https://doi.org/10.5124/jkma.2012.55.9.835
- Korotkov, Alexander. 2010. “Database Index for Approximate String Matching.” In Proceedings of the Spring/Summer Young Researchers’ Colloquium on Software Engineering. Institute for System Programming of the Russian Academy of Sciences. https://doi.org/10.15514/syrcose-2010-4-27
- Kovacic, Laurel, and Carole Chambers. 2010. “Look-Alike, Sound-Alike Drugs in Oncology.” Journal of Oncology Pharmacy Practice 17 (2): 104–18. https://doi.org/10.1177/1078155209354135
- Kovesdi, Casey R. 2022. “A Simple Tool to Evaluate Color for Legibility and Distinguishability When Designing Digital Displays.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66 (1): 1519–23. https://doi.org/10.1177/1071181322661209
- Kristanto, Andri, and Toto Indriyanto. 2024. “Development of Communication System for UAV Ground Control Station with ATC Based on Controller Pilot Data Link Communication.” Warta Penelitian Perhubungan 35 (2): 243–56. https://doi.org/10.25104/warlit.v35i2.2308
- Kumari, W. 2014. A Method for Mitigating Namespace Collisions. RFC Editor. https://doi.org/10.17487/rfc7304
- Kuncheria, Johnson. 2008. “Trademark Law: Determining a Likelihood of Confusion: The Southern District of New York Improperly Denies Preliminary Injunction Due to Its Misconstruction of the Relevant Standard and Misapplication of the Polaroid Factors.” Journal of Air Law and Commerce 73 (1): 97. https://doi.org/10.25172/jalc.73.1.6
- Kunchukuttan, Anoop, and Pushpak Bhattacharyya. 2021. “Utilizing Orthographic Similarity for Unsupervised Transliteration.” In Machine Translation and Transliteration Involving Related and Low-resource Languages. Chapman and Hall/CRC. https://doi.org/10.1201/9781003096771-9
- Kunchukuttan, Anoop, Mitesh Khapra, Gurneet Singh, and Pushpak Bhattacharyya. 2018. “Leveraging Orthographic Similarity for Multilingual Neural Transliteration.” Transactions of the Association for Computational Linguistics 6: 303–16. https://doi.org/10.1162/tacl_a_00022
- Kundig, François. 2011. “[b]Médicaments[/b] [i]look-alike[/i], [i]sound-alike[/i]: un enjeu important dans le domaine de l’infectiologie.” JMIG 7 (312): 1955–61. https://doi.org/10.53738/revmed.2011.7.312.1955
- Ladefoged, Peter. 1969. “The Measurement of Phonetic Similarity.” In Proceedings of the 1969 conference on Computational linguistics -. Association for Computational Linguistics. https://doi.org/10.3115/990403.990460
- Lakoan, Milda Rianty, Ahmad Ardiansyah, and Anna Uswatun Hasanah Rochjana. 2024. “Gambaran pengelolaan obat Look Alike Sound Alike (LASA) di instalasi farmasi rawat jalan eksekutif Rumah Sakit Hermina Tangerang Bulan Desember Tahun 2023.” Indonesian Journal of Health Science 4 (6s): 848–56. https://doi.org/10.54957/ijhs.v4i6s.1209
- Lambert, Bruce L. 1997. “Predicting Look-Alike and Sound-Alike Medication Errors.” American Journal of Health-System Pharmacy 54 (10): 1161–71. https://doi.org/10.1093/ajhp/54.10.1161
- Lambert, Bruce L., Ken-Yu Chang, and Swu-Jane Lin. 2003b. “Immediate Free Recall of Drug Names: Effects of Similarity and Availability.” American Journal of Health-System Pharmacy 60 (2): 156–68. https://doi.org/10.1093/ajhp/60.2.156
- Lambert, Bruce L., Swu-Jane Lin, Ken-Yu Chang, and Sanjay K. Gandhi. 1999. “Similarity as a Risk Factor in Drug-Name Confusion Errors: The Look-Alike (Orthographic) and Sound-Alike (Phonetic) Model.” Medical Care 37 (12): 1214–25. https://doi.org/10.1097/00005650-199912000-00005
- Lambert, Bruce L., Scott R. Schroeder, and William L. Galanter. 2015b. “Does Tall Man Lettering Prevent Drug Name Confusion Errors? Incomplete and Conflicting Evidence Suggest Need for Definitive Study.” BMJ Quality & Safety 25 (4): 213–17. https://doi.org/10.1136/bmjqs-2015-004929
- LaMonica, Clelia R. 2014. “Using Acoustic String-Edit Distance to Evaluate US Pronunciation Variation.” Journal of the Acoustical Society of America 135 (4_Supplement): 2422–2422. https://doi.org/10.1121/1.4878047
- Lau, Jeanette. 2001. “A Study of Potential Medication Errors Related to Look-Alike or Sound-Alike Drugs (LASAD) in a Prescription Benfit Management Setting.” Journal of Managed Pharmaceutical Care 1 (2): 39–47. https://doi.org/10.1300/j234v01n02_06
- Laustsen, Rasmus Dalgaard. 2019a. “The Dynamics of the European Trademark Law.” In The Average Consumer in Confusion-based Disputes in European Trademark Law and Similar Fictions. Springer International Publishing. https://doi.org/10.1007/978-3-030-26350-8_4
- Laustsen, Rasmus Dalgaard. 2019b. “Likelihood of Confusion: Legislative Harmonisation?” In The Average Consumer in Confusion-based Disputes in European Trademark Law and Similar Fictions. Springer International Publishing. https://doi.org/10.1007/978-3-030-26350-8_9
- Laustsen, Rasmus Dalgaard. 2019c. “The UCPD and Trademark Average Consumers: Two of a Kind?” In The Average Consumer in Confusion-based Disputes in European Trademark Law and Similar Fictions. Springer International Publishing. https://doi.org/10.1007/978-3-030-26350-8_7
- Leach, P., M. Mealling, and R. Salz. 2005. A Universally Unique IDentifier (UUID) URN Namespace. RFC Editor. https://doi.org/10.17487/rfc4122
- Lee, Thomas R. 2008. “Abercrombie Unveiled: A Theoretical and Empirical Analysis of Trademark Distinctiveness.” Preprint, . https://doi.org/10.2139/ssrn.1319409
- Lee, Eunjoo. 2016. “Safety Climate and Attitude toward Medication Error Reporting after Hospital Accreditation in South Korea.” International Journal for Quality in Health Care 28 (4): 508–14. https://doi.org/10.1093/intqhc/mzw058
- Leek, Sheena, and Dai Kun. 2006. “Consumer Confusion in the Chinese Personal Computer Market.” Journal of Product & Brand Management 15 (3): 184–93. https://doi.org/10.1108/10610420610668621
- Lees, Graham, and William Williamson. 2013a. International Call Sign Series. https://doi.org/10.4324/9781842145807-31
- Lees, Graham, and William Williamson. 2013b. RADIOTELEPHONY (RT). https://doi.org/10.4324/9781842145807-15
- Lees, Graham D., and William G. Williamson. 2020. Radiotelephony (RT). https://doi.org/10.4324/9781315766393-7
- Lees, G. D., and W. G. Williamson. 2022. Radiotelephony (RT). https://doi.org/10.4324/9781003171294-7
- “Legibility of Colored Print.” 2006. In International Encyclopedia of Ergonomics and Human Factors - 3 Volume Set. CRC Press. https://doi.org/10.1201/9780849375477-305
- Lehnert, Kerstin, Jens Klump, Lesley Wyborn, and Sarah Ramdeen. 2019. “Persistent, Global, Unique: The Three Key Requirements for a Trusted Identifier System for Physical Samples.” Biodiversity Information Science and Standards 3: e37334. https://doi.org/10.3897/biss.3.37334
- Lemieux, P. 2014. Entertainment Identifier Registry (EIDR) URN Namespace Definition. RFC Editor. https://doi.org/10.17487/rfc7302
- Lemieux, P. 2016. Entertainment Identifier Registry (EIDR) URN Namespace Definition. RFC Editor. https://doi.org/10.17487/rfc7972
- Lemley, Mark A., and Mark P. McKenna. 2026. “Trademarks without Confusion: Can Brand Rights Rescue Trademark Law?” Preprint, . https://doi.org/10.2139/ssrn.6122326
- Leslie, Mitch. 2026. “Protein Name Confusion Led to Antibody Mix-up.” Science 392 (6803): 1104–1104. https://doi.org/10.1126/science.aej5919
- Levien, Terri L. 2006. “International Drug Name Confusion.” Hospital Pharmacy 41 (7): 697–710. https://doi.org/10.1310/hpj4107-697
- Lewis, Benjamin P. 1979. “Potential Confusion Resulting from Trade Name Similarities.” American Journal of Health-System Pharmacy 36 (11): 1477–1477. https://doi.org/10.1093/ajhp/36.11.1477a
- Lewis, Benjamin P., and Marilyn Blackstone. 1982. “Potential Confusion Resulting from Trade-Name Similarities.” American Journal of Health-System Pharmacy 39 (7): 1148–56. https://doi.org/10.1093/ajhp/39.7.1148
- Li, Ling. 2018. “A Study on Chinese Legal Regulation of Trademark Reverse Confusion.” International Law Review 10 (1): 205–19. https://doi.org/10.36727/jjilr.10.1.201805.009
- Li, Xuan, and Siyun Liu. 2013. “The Effects of Phonological Similarity and Visual Similarity in Immediate Serial Recall of Chinese Characters.” Acta Psychologica Sinica 44 (12): 1571–82. https://doi.org/10.3724/sp.j.1041.2012.01571
- Libovický, Jindřich, and Alexander Fraser. 2022. “Neural String Edit Distance.” In Proceedings of the Sixth Workshop on Structured Prediction for NLP. Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.spnlp-1.6
- “Likelihood of Confusion between a Trade Mark and a Domain Name.” 2022. GRUR International 71 (10): 1002–7. https://doi.org/10.1093/grurint/ikac062
- “Likelihood of Confusion of Essential Parts of a Complex Trade Mark.” 2020. GRUR International 69 (3): 301–7. https://doi.org/10.1093/grurint/ikaa008
- Lilley, Linda L., and Robert Guanci. 1997a. “Look-Alike Abbreviations: Prescriptions for Confusion.” American Journal of Nursing 97 (11): 12. https://doi.org/10.1097/00000446-199711000-00006
- Lilley, Linda L., and Robert Guanci. 1997b. “Med Errors: Look-Alike Abbreviations: Prescriptions for Confusion.” American Journal of Nursing 97 (11): 12. https://doi.org/10.2307/3465239
- Lilley, Linda L., and Robert Guanci. 1997c. “When ‘Look-Alikes’ and ‘Sound-Alikes’ Don’t Act Alike.” American Journal of Nursing 97 (9): 12–14. https://doi.org/10.1097/00000446-199709000-00007
- Lin, Wei-Hao, and Hsin-Hsi Chen. 2002. “Backward Machine Transliteration by Learning Phonetic Similarity.” In proceeding of the 6th conference on Natural language learning - COLING-02, vol. 20. Association for Computational Linguistics. https://doi.org/10.3115/1118853.1118870
- Lin, Xuemin, and Wei Wang. 2011. “Set and String Similarity Queries: A Survey.” Chinese Journal of Computers 34 (10): 1853–62. https://doi.org/10.3724/sp.j.1016.2011.01853
- Lippert, S. 1963. “Dynamic Vision—the Legibility of Equally Spaced Alphanumeric Symbols.” Human Factors: The Journal of the Human Factors and Ergonomics Society 5 (2): 129–38. https://doi.org/10.1177/001872086300500203
- Lippert, S., and D. M. Lee. 1965. “Dynamic Vision: The Legibility of Moderately Spaced Alphanumeric Symbols.” Human Factors: The Journal of the Human Factors and Ergonomics Society 7 (6): 555–60. https://doi.org/10.1177/001872086500700607
- Lisbach, Bertrand. 2011a. “G3 Name Matching und Identity Matching.” In Linguistisches Identity Matching. Vieweg+Teubner. https://doi.org/10.1007/978-3-8348-9791-6_13
- Lisbach, Bertrand. 2011b. “Name-Matching-Verfahren der 1. Generation.” In Linguistisches Identity Matching. Vieweg+Teubner. https://doi.org/10.1007/978-3-8348-9791-6_9
- Lisbach, Bertrand. 2011c. “Name-Matching-Verfahren der 2. Generation.” In Linguistisches Identity Matching. Vieweg+Teubner. https://doi.org/10.1007/978-3-8348-9791-6_10
- Lisbach, Bertrand. 2011d. “Name-Matching-Verfahren der 3. Generation.” In Linguistisches Identity Matching. Vieweg+Teubner. https://doi.org/10.1007/978-3-8348-9791-6_11
- Lisbach, Bertrand, and Victoria Meyer. 2013a. “Name Matching and Identity Matching.” In Linguistic Identity Matching. Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-8348-2095-2_12
- Lisbach, Bertrand, and Victoria Meyer. 2013b. “Name Matching Methods of the First Generation.” In Linguistic Identity Matching. Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-8348-2095-2_8
- Lisbach, Bertrand, and Victoria Meyer. 2013c. “Second Generation Name Matching Methods.” In Linguistic Identity Matching. Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-8348-2095-2_9
- Lisbach, Bertrand, and Victoria Meyer. 2013d. “Third Generation Name Matching Methods.” In Linguistic Identity Matching. Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-8348-2095-2_10
- Liu, Kung-Chung, and Fa-Chang Cheng. 2019. “Taiwan IP Court Decisions Tend to Treat Likelihood of Confusion and Likelihood of Dilution as Mutually Interchangeable.” In Routledge eBooks. Routledge. https://doi.org/10.4324/9780429316395-22
- Liu, Bing, Dan Han, and Shuang Zhang. 2014. “Approximate Chinese String Matching Techniques Based on Pinyin Input Method.” Applied Mechanics and Materials 513-517: 1017–20. https://doi.org/10.4028/www.scientific.net/amm.513-517.1017
- Liu, Xijuan, Haobo Wei, Peilun Yang, and haiyang Hu. 2025b. “Charformer: Character-Oriented Attention Network for String Edit Distance.” Preprint, . https://doi.org/10.2139/ssrn.5095777
- Lizotte, Andrew M., and Michael J. Allen. 2007. “Twist Model Development and Results from the Active Aeroelastic Wing F/A-18 Aircraft.” In International Forum on Aeroelasticity and Structural Dynamics (IFASD). https://ntrs.nasa.gov/citations/20070022496
- Loken, Barbara, Ivan Ross, and Ronald L. Hinkle. 1986. “Consumer “Confusion” of Origin and Brand Similarity Perceptions.” Journal of Public Policy & Marketing 5 (1): 195–211. https://doi.org/10.1177/074391568600500114
- Loo, Mark,P. J.,van,der. 2014. “The Stringdist Package for Approximate String Matching.” R Journal 6 (1): 111. https://doi.org/10.32614/rj-2014-011
- “Look-Alike and Sound-Alike Drugs.” 1976. Journal of Drug Issues 6 (3): 305–6. https://doi.org/10.1177/002204267600600308
- “Look-Alike, Sound-Alike in Dietary Supplements.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch008
- “Look-Alike, Sound-Alike Medication Errors Caused by Drug Names.” 2026a. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch005
- “Look-Alike, Sound-Alike Medication Errors in Injectable Drugs.” 2026b. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch012
- “Look-Alike, Sound-Alike Medication Errors in Vaccines.” 2026c. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch011
- Lopresti, D., and G. Wilfong. n.d. “Cross-Domain Approximate String Matching.” In 6th International Symposium on String Processing and Information Retrieval. 5th International Workshop on Groupware (Cat. No.PR00268). IEEE Comput. Soc. https://doi.org/10.1109/spire.1999.796586
- Lou, Qiqi. 2024. “Consumer Confusion: The Sole Focus of Trademark Law.” Lecture Notes in Education Psychology and Public Media 69 (1): 45–49. https://doi.org/10.54254/2753-7048/69/20240157
- Loucks, Roger B. 1944. Legibility of Aircraft Instrument Dials: The Relative Legibility of Techometer Dials. Defense Technical Information Center. https://doi.org/10.21236/ad0038561
- Lu, Jiaheng, Chunbin Lin, Wei Wang, Chen Li, and Haiyong Wang. 2013. “String Similarity Measures and Joins with Synonyms.” In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. ACM. https://doi.org/10.1145/2463676.2465313
- Lunsford, Julius R. 1949. “Trademark Infringement and Confusion of Source: Need for Supreme Court Action.” Virginia Law Review 35 (2): 214. https://doi.org/10.2307/1069224
- Lupker, Stephen J. 1982. “The Role of Phonetic and Orthographic Similarity in Picture–word Interference.” Canadian Journal of Psychology / Revue canadienne de psychologie 36 (3): 349–67. https://doi.org/10.1037/h0080652
- Lutzker, Arnold P. 2002. “Likelihood of Confusion: The Acid Test.” In Content Rights for Creative Professionals. Elsevier. https://doi.org/10.1016/b978-0-240-80484-2.50018-6
- Lutzker, Arnold P. 2013. “Likelihood of Confusion: The Acid Test.” In Routledge eBooks. Routledge. https://doi.org/10.4324/9780080503028-22
- Lynn, Amy Louise. n.d. “The Effects of Readback on a Spatial Navigation Task.” PhD diss., San Jose State University. https://doi.org/10.31979/etd.rrmb-f3h4
- Machine Readable Cards. Health Care Applications. Numbering System and Registration Procedure for Issuer Identifiers. n.d. BSI British Standards. https://doi.org/10.3403/01234750u
- Mackintosh, Margaret-Anne, Sandra Lozito, Alison McGann, and Elizabeth Waller Logsdon. 1999. “Designing Procedures for Controller-Pilot Data Link Communication: Effects of Textual Data Link on Information Transfer.” SAE technical papers on CD-ROM/SAE technical paper series 1. https://doi.org/10.4271/1999-01-5507
- Maidment, Ian D., and Angie Thorn. 2005. “A Medication Error Reporting Scheme: Analysis of the First 12 Months.” Psychiatric Bulletin 29 (8): 298–301. https://doi.org/10.1192/pb.29.8.298
- Maksurov, Alexey Anatolievich. 2021. “Trademark Definitions: Problems of Coordination in British Law.” In THEORETICAL AND EMPIRICAL SCIENTIFIC RESEARCH: CONCEPT AND TRENDS VOLUME1. https://doi.org/10.36074/logos-10.12.2021.v1.34
- Manik, Audina. 2020. “Pengetahuan Perawat Di Rumah Sakit Mengenai Medication Safety Terhadap Medication Error.” Preprint, . https://doi.org/10.31219/osf.io/w8gy5
- Manning, Susan Karp, and Elizabeth Shofner. 1991. “Similarity Ratings and Confusability of Lipread Consonants Compared with Similarity Ratings of Auditory and Orthographic Stimuli.” American Journal of Psychology 104 (4): 587. https://doi.org/10.2307/1422942
- Mansour, Magda M., and Latifah AL-Gethami. 2013. “Nurse Perceptions about the Culture of Reporting Medication Error in Taif- Hospital.” Assiut Scientific Nursing Journal 1 (1): 124–29. https://doi.org/10.21608/asnj.2013.57391
- Marovino, Edoardo, Amelia Morgillo, Naomi Mancino, Veronica Di Feo, and Emanuela Genito. 2022. “Therapeutic Error: Types and Prevention Strategies and Focus about ‘Look Alike/Sound Alike’ and ‘High Risk’ Drugs.” Journal of Pharmaceutical Research International: 9–16. https://doi.org/10.9734/jpri/2022/v34i48a36409
- Marzal, Andrés, Ramón Mollineda, Guillermo Penis, and Enrique Vidal. 2003. “Cyclic String Matching: Efficient Exact and Approximate Algorithms.” In Combinatorial Optimization. Springer US. https://doi.org/10.1007/978-1-4613-0231-5_19
- Masmali, Khalid, Hussain Maashi, Mohammed Ayyashi, Ibrahim Alnami, Abualqasim Masmali, and Sultan MusaThubab. 2020. “Pharmacist-Initiated Medication Error Reporting and Monitoring Program.” International Journal of Medicine in Developing Countries: 1092–96. https://doi.org/10.24911/ijmdc.51-1577306617
- Massah, laleh, Rouhangiz Mohammadi, and Mahboobeh Namnabati. 2021. “Improvement of Medication Error Reporting: An Applied Motivation Program in Pediatric Units.” Journal of Education and Health Promotion 10 (1): 189. https://doi.org/10.4103/jehp.jehp_1025_20
- Mathew, Binu, Anjali Thomas, and Doddayya Hiremath. 2021. “Assessment of Knowledge Attitude and Practice on Medication Error Reporting among Clinical Pharmacists.” Asian Journal of Pharmaceutical and Health Sciences 11 (2): 2462–67. https://doi.org/10.5530/ajphs.2021.11.8
- Matsumoto, T., T. Kida, M. Takeda, A. Shinohara, and S. Arikawa. 2000. “Bit-Parallel Approach to Approximate String Matching in Compressed Texts.” In Proceedings Seventh International Symposium on String Processing and Information Retrieval. SPIRE 2000. IEEE Comput. Soc. https://doi.org/10.1109/spire.2000.878198
- Mattox, A. S. 1990. “Pilot-Controller Communication: A Line Pilot’s Perspective.” SAE technical papers on CD-ROM/SAE technical paper series 1. https://doi.org/10.4271/902354
- Matveev, Daniil. 2024. “Edit Distance Patterns andEfcient Similarity JoinAlgorithms.” PhD diss.. https://doi.org/10.46569/8w32rf845
- McAlpin, Ingrid. 2003. “Overview of the New South Wales Health Unique Patient Identifier Project.” Health Information Management 31 (3): 17–20. https://doi.org/10.1177/183335830303100311
- McArdle, D., N. Burns, and A. Ireland. 2003. “Attitudes and Beliefs of Doctors towards Medication Error Reporting.” International Journal of Health Care Quality Assurance 16 (7): 326–33. https://doi.org/10.1108/09526860310499981
- McCallum, Andrew, Kedar Bellare, and Fernando Pereira. 2005. A Conditional Random Field for Discriminatively-Trained Finite-State String Edit Distance. Defense Technical Information Center. https://doi.org/10.21236/ada440386
- McCarley, J. Scott. 2009. “Cross Language Name Matching.” In Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval. ACM. https://doi.org/10.1145/1571941.1572065
- McCutcheon, Jani. 2023. “Character Confusion: Literary Characters as Unregistered Trade Marks.” In Edward Elgar Publishing eBooks. Edward Elgar Publishing. https://doi.org/10.4337/9781788114325.00012
- McGlannan, Frances, and Gary Thorson. 1976. “Reading — Confusability of Letters: An Alternative for Judging Confusability of Visual Letters.” Journal of Learning Disabilities 9 (9): 577–78. https://doi.org/10.1177/002221947600900905
- McLean, Michael V. 1965. “Brightness Contrast, Color Contrast, and Legibility.” Human Factors: The Journal of the Human Factors and Ergonomics Society 7 (6): 521–27. https://doi.org/10.1177/001872086500700603
- McNally, Karen M., and V. Bruce Sunderland. 1998. “No-Blame Medication Administration Error Reporting by Nursing Staff at a Teaching Hospital in Australia.” International Journal of Pharmacy Practice 6 (2): 67–71. https://doi.org/10.1111/j.2042-7174.1998.tb00918.x
- McTyre, John H. 1982. “Legibility Comparison of 7 by 7 and 7 by 9 CRT Character Dot Matrices.” Proceedings of the Human Factors Society Annual Meeting 26 (8): 710–14. https://doi.org/10.1177/154193128202600808
- McTyre, John H., and W. David Frommer. 1985. “Effects of Character/Background Color Combinations on CRT Character Legibility.” Proceedings of the Human Factors Society Annual Meeting 29 (8): 779–81. https://doi.org/10.1177/154193128502900811
- Mealling, M. 2000. A URN Namespace of Object Identifiers. RFC Editor. https://doi.org/10.17487/rfc3001
- Mealling, M. 2001. A URN Namespace of Object Identifiers. RFC Editor. https://doi.org/10.17487/rfc3061
- Mealling, M. 2004. A Uniform Resource Name (URN) Namespace for the Liberty Alliance Project. RFC Editor. https://doi.org/10.17487/rfc3622
- “Medication Error Prevention: Progress of Initiatives.” 2004. JONA’s Healthcare Law, Ethics, and Regulation 6 (1): 13–14. https://doi.org/10.1097/00128488-200403000-00003
- Medication Safety and Error Reduction. 2020. SAGE Publications Ltd. https://doi.org/10.4135/9781529728569
- Mednis, Martins, and Maike K. Aurich. 2012. “Application of String Similarity Ratio and Edit Distance in Automatic Metabolite Reconciliation Comparing Reconstructions and Models.” Biosystems and Information technology 1 (1): 14–18. https://doi.org/10.11592/bit.121102
- Mehanna, Diala, Najwa El Gerges, Marianne Chalhoub, and Remy Daou. 2024. “Barriers to Medication Administration Error Reporting in a Tertiary Hospital in Lebanon.” BMJ Open Quality 13 (4): e002994. https://doi.org/10.1136/bmjoq-2024-002994
- Menneer, T., H. J. Godwin, and M. C. Hout. 2014. “Visual Similarity Is Stronger than Semantic Similarity in Guiding Visual Search for Numbers.” Journal of Vision 14 (10): 1201–1201. https://doi.org/10.1167/14.10.1201
- Metals Technical Committee. 2000. Numbering System for Designating Grades of Cast Ferrous Materials. https://doi.org/10.4271/j859_200007
- “MHRA: Confusion over Drug Names.” 2018. Drug and Therapeutics Bulletin 56 (3): 26.1-26. https://doi.org/10.1136/dtb.2018.3.0592
- Miaoulis, George, and Nancy D’Amato. 1978. “Consumer Confusion & Trademark Infringement.” Journal of Marketing 42 (2): 48. https://doi.org/10.2307/1249885
- Michelet-Huot, E., Jb Bacouillard, P. Quillet, M. Bonnet, C. Mongaret, and D. Hettler. 2017. “PS-106 Look-Alike and Sound-Alike Drug Incidents in a Hospital: A Retrospective Analysis.” In Patient safety and risk management. British Medical Journal Publishing Group. https://doi.org/10.1136/ejhpharm-2017-000640.612
- Micrographics. Alphanumeric Computer Output Microforms. Quality Control. n.d. BSI British Standards. https://doi.org/10.3403/bsiso8514
- Miftahurrozik, Fariz. 2023. “Gambaran Pengelolaan Obat Lasa (Look- Alike Sound-Alike) Di Apotek Goge Farma.” Malahayati Nursing Journal 5 (2): 461–68. https://doi.org/10.33024/mnj.v5i2.7966
- Millán-Hernández, Christian Eduardo, René Arnulfo García-Hernández, Yulia Ledeneva, and Ángel Hernández-Castañeda. 2020. “An Orthographic and Phonetic Knowledge-Based Measure for Confused Drug Names.” Journal of Intelligent & Fuzzy Systems 39 (2): 2003–13. https://doi.org/10.3233/jifs-179867
- Miller, M. R. 2006. “Computer Based Medication Error Reporting: Insights and Implications.” Quality and Safety in Health Care 15 (3): 208–13. https://doi.org/10.1136/qshc.2005.016733
- Milton, Robin M., Nicole B. Washington, and Nancy Brahm. 2015. “Hypoglycemia from a Look-Alike, Sound-Alike Medication Error.” Mental Health Clinician 5 (4): 174–79. https://doi.org/10.9740/mhc.2015.07.174
- Mishra, Shashwat, Tejas Gandhi, Akhil Arora, and Arnab Bhattacharya. 2013. “Efficient Edit Distance Based String Similarity Search Using Deletion Neighborhoods.” In Proceedings of the Joint EDBT/ICDT 2013 Workshops. ACM. https://doi.org/10.1145/2457317.2457387
- Mishra, Aditi, R. Isiri, Sonali Shinde, Shruti Kothari, and Sakshi Iyer. 2026. “Perceptions of Consumers on Trademark Disparagement in Comparative Advertising: An Empirical Study.” Preprint, . https://doi.org/10.2139/ssrn.6989939
- Mitchell, Vincent-Wayne, and Íde Kearney. 2002. “A Critique of Legal Measures of Brand Confusion.” Journal of Product & Brand Management 11 (6): 357–79. https://doi.org/10.1108/10610420210445497
- Mitchell, Vincent-Wayne, and Vassilios Papavassiliou. 1999. “Marketing Causes and Implications of Consumer Confusion.” Journal of Product & Brand Management 8 (4): 319–42. https://doi.org/10.1108/10610429910284300
- “Mixed Messages: Marketing and Consumer Confusion.” 2024. In Seeing Red. The MIT Press. https://doi.org/10.7551/mitpress/11213.003.0009
- Moats, R. 1999. A URN Namespace for IETF Documents. RFC Editor. https://doi.org/10.17487/rfc2648
- Moe, Albert F. 1970. “Phonetic Alphabet: Names of the Letters.” Names 18 (4): 247–85. https://doi.org/10.1179/nam.1970.18.4.247
- Mohammed, Zaid Rajih, and Ahmed H. Aliwy. 2024. “Review of Current Trends in Information Technology Concerning Phonetic Similarity”.” Al-Bahir Journal for Engineering and Pure Sciences 5 (2). https://doi.org/10.55810/2313-0083.1077
- Mohanty, Sailabala. 2016. “Awareness of Medication Error, Medication Management and Prevention among Staff Nurses in IMS &Sum Hospital, Odisha.” Journal of Health and Allied Sciences NU 06 (04): 18–22. https://doi.org/10.1055/s-0040-1708670
- Moini, Jahangir. 2025. “Drug Classifications, Drug Names, and Drug Sources.” In Principles of Pharmacology. CRC Press. https://doi.org/10.1201/9781003461913-2
- Mollineda, R. A., E. Vidal, and F. Casacuberta. n.d. “A Windowed Weighted Approach for Approximate Cyclic String Matching.” In Object recognition supported by user interaction for service robots, vol. 4. IEEE Comput. Soc. https://doi.org/10.1109/icpr.2002.1047429
- Monan, W. P. 1983. Addressee Errors in ATC Communications: The Call Sign Problem. NASA-CR-166462. NASA. https://ntrs.nasa.gov/citations/19840012433
- “Monograph of Look-Alike, Sound-Alike (LASA) Drugs Reported in Thailand (Oral Liquid Preparations).” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch010
- Montalyo, Michael L., and J. Victor Lebacqz. 1994. Pre-Departure Clearance (PDC): An Analysis of Aviation Safety Reporting System Reports Concerning PDC Related Errors. NASA Ames Research Center. https://ntrs.nasa.gov/citations/20020005889
- Monteiro, Ana Lúcia Tavares. 2022. “The Assessment of English in Aeronautical Radiotelephony Communications: A Mixed Methods Study.” In Bookerfield Editora. https://doi.org/10.53268/bkf22080512
- Moody, Jeanne Christensen. n.d. “Some Typographic Factors Influencing the Legibility of Permuted-Title Indexes.” PhD diss., Drexel University. https://doi.org/10.17918/00003782
- Moon, Suemi. 2018. “A Study on the Criteria for Likelihood of Confusion under the Trademark Law on ‘the Goods Marked as Counterfeit’.” Journal of Intellectual Property 13 (4): 63–96. https://doi.org/10.34122/jip.2018.12.13.4.63
- “More on Drug-Name Confusion.” 1995. New England Journal of Medicine 332 (11): 754–55. https://doi.org/10.1056/nejm199503163321118
- Moreau, Erwan, François Yvon, and Olivier Cappé. 2008. “Robust Similarity Measures for Named Entities Matching.” In Proceedings of the 22nd International Conference on Computational Linguistics - COLING ‘08, vol. 1. Association for Computational Linguistics. https://doi.org/10.3115/1599081.1599156
- Morrin, Maureen, and Jacob Jacoby. 2000. “Trademark Dilution: Empirical Measures for an Elusive Concept.” Preprint, . https://doi.org/10.2139/ssrn.231023
- Morrison, Robert E., and Keith Rayner. 1985. “Legibility of Telephone Directories: Reductions Due to Compressed Print and Disproportionate Effects for the Aged.” Proceedings of the Human Factors Society Annual Meeting 29 (3): 231–34. https://doi.org/10.1177/154193128502900306
- Morrow, Daniel, and J. Victor Lebacqz. 1994. Collaboration in Controller-Pilot Communication. Decision Systems, Inc. https://ntrs.nasa.gov/citations/20020003930
- Morrow, Daniel G., Alfred Lee, and Michelle Rodvold. 1990. “Analysis of Routine Pilot-Controller Communication.” In SAE. https://ntrs.nasa.gov/citations/19910065238
- Moser, Henry M., John F. Michel, and Wallace C. Fotheringham. 1961. Intelligibility and Confusability of Vowels and Diphthongs under Various Conditions of Quiet and Noise. Defense Technical Information Center. https://doi.org/10.21236/ad0260556
- Mostafa, Khaled Elnouby, Zeinab Hussein Ali, and Naglaa Gamal Eldine Abd Hafez. 2021. “Nurses’ Performance Regarding Intravenous Infusion of Look-Alike Sound Alike Medications at Sohag University Hospital.” International Journal of Advance Research in Nursing 4 (2): 286–91. https://doi.org/10.33545/nursing.2021.v4.i2e.217
- Motor Vehicle Council. 1990a. Numbering System for Reamers. https://doi.org/10.4271/j2124_199011
- Motor Vehicle Council. 1990b. Numbering System for Standard Drills. https://doi.org/10.4271/j2122_199011
- Motor Vehicle Council. 1990c. Numbering System for Standard Taps. https://doi.org/10.4271/j2123_199011
- Motor Vehicle Council. 1998a. Numbering System for Multiple Diameter Cutting Tools. https://doi.org/10.4271/j2276_199810
- Motor Vehicle Council. 1998b. Numbering System for Single Diameter Drills. https://doi.org/10.4271/j2122_199810
- Motor Vehicle Council. 1998c. Numbering System for Taps. https://doi.org/10.4271/j2123_199810
- Motor Vehicle Council. 2019. Numbering System for Single Diameter and Taper Reamers. https://doi.org/10.4271/j2124_201910
- Moureaud, Charlotte, John B. Hertig, and Robert J. Weber. 2020. “Guidelines for Leading a Safe Medication Error Reporting Culture.” Hospital Pharmacy 56 (5): 604–9. https://doi.org/10.1177/0018578720931752
- Mtc1, Earthmoving Machinery. 1987. Product Identification Numbering System of off-Road Work Machines. https://doi.org/10.4271/j1360_198709
- Muchu, Prathyusha. 2024. “Look Alike Sound Alike Drugs in Adults.” International Journal of Health Care and Biological Sciences: 18–23. https://doi.org/10.46795/ijhcbs.v5i1.609
- Muhlis, Muhammad, Resa Andyani, Tika Wulandari, and Aulisa A. Sahir. 2019. “Pengetahuan Apoteker Tentang Obat-Obat Look-Alike Sound-Alike Dan Pengelolaannya Di Apotek Kota Yogyakarta.” Indonesian Journal of Clinical Pharmacy 8 (2): 107. https://doi.org/10.15416/ijcp.2019.8.2.107
- Mukherjee, Shatavisa, Rudra Paul, Biswajit Biswas, and Swarup Mondal. 2025. “Knowledge, Attitude, and Practice Regarding Look-Alike, Sound-Alike Drugs among Healthcare Professionals in Eastern India.” Amrita Journal of Medicine 22 (3): 118–24. https://doi.org/10.4103/amjm.amjm_86_25
- Mukriani, Mukriani. 2026. “The Role of Pharmacists in Medication Prevention Error in Hospital.” International Journal of Health Sciences 4 (1): 14–21. https://doi.org/10.59585/ijhs.v4i1.1037
- Munshi, Renuka P., Ganesh D. Tople, and Sonali R. Munot. 2019. “Assessment of the Degree of Awareness among Post-Graduate Medical Physicians and Pharmacists about Look-Alike, Sound-Alike Drug and Potential Medication Errors.” International Journal of Basic & Clinical Pharmacology 8 (8): 1771. https://doi.org/10.18203/2319-2003.ijbcp20193176
- Mupangavanhu, Yeukai, and Kawake Sipelo Vuke. 2023. “The Risk of Confusion in Trademark Infringement in South Africa and Kenya: Lessons from Singapore?” Journal of Comparative Law in Africa 10 (2): 174–203. https://doi.org/10.47348/jcla/v10/i2a6
- Murray, D. J. 1968. “Articulation and Acoustic Confusability in Short-Term Memory.” Journal of Experimental Psychology 78 (4, Pt.1): 679–84. https://doi.org/10.1037/h0026641
- Murry, Thomas. 1970. Problems of Voice Communication in the Navy. Regulation of Vocal Intensity at Low Fundamental Frequencies. Defense Technical Information Center. https://doi.org/10.21236/ad0718857
- Mursiti, Handri, Galau Menanti Embri Baskara Putra Mesias, and Peni Indrayudha. 2022. “Implementation of Drug Administration with High Awareness (LASA/ Look Alike Sound Alike and High Alert) for Patient Safety at Pharmacies in Surakarta.” Pharmacon: Jurnal Farmasi Indonesia 19 (2): 197–202. https://doi.org/10.23917/pharmacon.v19i2.20019
- Mustonen, Terhi, Maria Olkkonen, and Jukka Hakkinen. 2004. “Examining Mobile Phone Text Legibility While Walking.” In CHI ‘04 Extended Abstracts on Human Factors in Computing Systems. ACM. https://doi.org/10.1145/985921.986034
- Nabeta, Keita, Hirotsugu Ishida, Masaomi Kimura, Michiko Ohkura, and Fumito Tsuchiya. 2011. “A Proposed Method for Generating Question Tests Based on Prescription Drug Name Similarity.” In International Conference on Computer Supported Education. https://doi.org/10.5220/0003401404490452
- Nadeau, Herbert L. 1937. “Trade-Marks: Registration: Likelihood of Confusion.” Michigan Law Review 36 (1): 170. https://doi.org/10.2307/1281772
- Nagamotoo, Y., K. Lai, and G. Cavell. 2022. “Measuring Drug Name Similarity to Prioritise the Application of Tall-Man Lettering in a Computerised Pharmacy Dispensing System.” International Journal of Pharmacy Practice 30 (Supplement_2): ii35-ii36. https://doi.org/10.1093/ijpp/riac089.041
- Naif H. Helman, Badr I. Alrufaiq, and Ahmed G. Alsahli. 2020. “Pharmacists’ Experiences with Medication Error Reporting Systems: Examining Attitudes, Experiences, and Challenges in Hospitals.” International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 8 (3). https://doi.org/10.37082/ijirmps.v8.i3.230809
- Naik, Nagappa Anantha, Wal Pranay, Puja Kumari, and Wal Ankita. 2009. “Look Alike and Sound Alike Names of Branded Medicines in Indian Pharmaceutical Market.” Journal of Pharmaceutical Research 8 (3): 134. https://doi.org/10.18579/jpcrkc/2009/8/3/79732
- Narten, T., and J. Johnson. 2011. Definition of the UUID-Based DHCPv6 Unique Identifier (DUID-UUID). RFC Editor. https://doi.org/10.17487/rfc6355
- NASA Aviation Safety Reporting System. 1978. NASA-TM-78476. NASA. https://ntrs.nasa.gov/citations/19780017128
- NASA Aviation Safety Reporting System. 1980. NASA-TM-81197. NASA. https://ntrs.nasa.gov/citations/19800023844
- Natalia, Debora, Waynhena Sarawa Nesia, Dewi Sri Surya Wuisan, and Ferdi Antonio. 2026. “The Digital Path toward Perceived Medication Error Prevention from the Physician Perspective in Private Clinics in Eastern Indonesia: A Mixed Methods Study.” Preprint, Research Square. https://doi.org/10.21203/rs.3.rs-9609691/v1
- Naval Material Command Washington DC. 1980. Standard Technical Manual Identification Numbering System (TMINS). M0000-00-IDX-000 TMINS. Defense Technical Information Center. https://doi.org/10.21236/ada100663
- Navarro, Gonzalo. 2008. “Sequential Approximate String Matching: 2003; Crochemore, Landau, Ziv-Ukelson 2004; Fredriksson, Navarro.” In Encyclopedia of Algorithms. Springer US. https://doi.org/10.1007/978-0-387-30162-4_363
- Navarro, Gonzalo. 2016. “Approximate String Matching.” In Encyclopedia of Algorithms. Springer New York. https://doi.org/10.1007/978-1-4939-2864-4_363
- Navarro, G., T. Kida, M. Takeda, A. Shinohara, and S. Arikawa. 2001. “Faster Approximate String Matching over Compressed Text.” In Proceedings DCC 2001. Data Compression Conference. IEEE Comput. Soc. https://doi.org/10.1109/dcc.2001.917177
- Navarro¹², Gonzalo. 1997a. “Multiple Approximate String Matching by Counting.” In Fourth South American Workshop on String Processing (WSP 1997). McGill-Queen’s University Press. https://doi.org/10.1515/9780773591400-012
- Navarro¹², Gonzalo. 1997b. “A Partial Deterministic Automaton for Approximate String Matching.” In Fourth South American Workshop on String Processing (WSP 1997). McGill-Queen’s University Press. https://doi.org/10.1515/9780773591400-011
- Nchinech, Naoual, Omar Benhasna, Sanae Achour, et al. 2023. “Medication Errors Related to Look Alike and Sound Alike Medications: About a Moroccan City University Hospital and Community Pharmacies Experience.” Scholars Academic Journal of Pharmacy 12 (12): 271–77. https://doi.org/10.36347/sajp.2023.v12i12.003
- Neely, Keith K. 1956. “Study of MAYDAY and S.O.S. as Radiotelephony Distress Signals.” Journal of the Acoustical Society of America 28 (4): 554–55. https://doi.org/10.1121/1.1908391
- Nelson, Douglas L., and Richard C. Borden. 1973. “Interference Produced by Phonetic Similarities: Stimulus Recognition, Associative Retrieval, or Both?” Journal of Experimental Psychology 97 (2): 167–69. https://doi.org/10.1037/h0033901
- Nguyen, Thi Thuy Anh, and Stefan Conrad. 2014. “Applying Information-Theoretic and Edit Distance Approaches to Flexibly Measure Lexical Similarity.” In International Conference on Knowledge Discovery and Information Retrieval. https://doi.org/10.5220/0005170005050511
- Nilsson, Thomy, and Murray Kaiserman. 2004. “Legibility of Warnings in Color.” In Handbook of Human Factors in Litigation. CRC Press. https://doi.org/10.1201/9780203490297.ch32
- Nitayaphorn, Paneeta. n.d. “A Reference Grammar of Radiotelephony in Air-Ground Communication.” PhD diss., Chulalongkorn University. https://doi.org/10.58837/chula.the.2009.2062
- “No Cumulative Protection against Likelihood of Confusion under Trade Mark and Unfair Competition Law.” 2023. GRUR International 73 (1): 63–64. https://doi.org/10.1093/grurint/ikad125
- “No Likelihood of Confusion between Signs Featuring Geometric Shapes.” 2025. GRUR International 74 (5): 459–63. https://doi.org/10.1093/grurint/ikae159
- Nomenclature, Aircraft Hydraulic and Pneumatic Systems. 1956. https://doi.org/10.4271/arp243a
- Nomenclature, Aircraft Oxygen Equipment. 1944. https://doi.org/10.4271/arp171
- None, None. 2021. Unique Building Identifier (UBID): Public Sector Implementation Guide. Office of Scientific and Technical Information (OSTI). https://doi.org/10.2172/1764638
- Novi Yulianti, Hema Malini, and Sri Muharni. 2019. “Analisis Faktor Yang Mempengaruhi Peran Perawat Dalam Pencegahan Medication Error Diruang Rawat Inap Rumah Sakit Awal Bros Batam: Analysis of Factors Influencing the Role of Nurses in Prevention Medication Error in the Inpatient Room of Awal Bros Batam Hospital.” NERS Jurnal Keperawatan 15 (2): 130–39. https://doi.org/10.25077/njk.v15i2.178
- Novitra, Aria. 2023. “Penerapan Algoritma Approximate String Matching Untuk Pencarian Teks Pada Aplikasi Ensiklopedia Teknologi Komputer.” Journal Global Technology Computer 2 (2): 61–66. https://doi.org/10.47065/jogtc.v2i2.3341
- Nowak-Gruca, Aleksandra. 2018. “Consumer Protection against Confusion in the Trademark Law.” European Journal of Economics, Law and Politics 05 (01). https://doi.org/10.19044/elp.v5no1a1
- Nozawa, Takeshi, and Ratree Wayland. 2025. “Phoneme Confusability Meets Lexical Factors: Japanese Listeners’ Recognition of English Words.” Journal of the Acoustical Society of America 158 (4_Supplement): A407-A407. https://doi.org/10.1121/10.0041332
- “Numbering System for Food Additives.” 2001. In Food Science and Technology. CRC Press. https://doi.org/10.1201/9780824741709.ax2
- O’Leary, Jeffrey, and Alok Srivastava. 2012. “FAA’s Controller Pilot Automatic Data Communication (Data Comm) System Software Development.” ACM SIGAda Ada Letters 32 (3): 71–72. https://doi.org/10.1145/2402709.2402700
- Ogamba, Ikedinachi, Caleb Ndukwe, and Isaac Sarkodie Obeng. 2023. “Use of Web-Based Medication Error Reporting and Management Systems in Improving Medication Safety in Assisted Living Facilities: A Systematic Review.” International Journal of Electronic Healthcare 13 (1): 1. https://doi.org/10.1504/ijeh.2023.128599
- Ögeyik, Muhlise Coşgun. 2022. “Measuring Phonological and Orthographic Similarity.” In IGI Global eBooks. IGI Global. https://doi.org/10.4018/978-1-6684-5682-8.ch045
- Ohtake, Kiyonori, Youichi Sekiguchi, and Kazuhide Yamamoto. 2004. “Detecting Transliterated Orthographic Variants via Two Similarity Metrics.” In Proceedings of the 20th international conference on Computational Linguistics - COLING ‘04. Association for Computational Linguistics. https://doi.org/10.3115/1220355.1220457
- Ohtani, Hisakazu, Masayuki Takeda, Yuki Imada, and Yasufumi Sawada. 2006. “Development of the Measures to Evaluate the Similarity of Drug Brand Names.” Yakugaku Zasshi 126 (5): 349–56. https://doi.org/10.1248/yakushi.126.349
- Ohunyon, Glory, Prisca U. Ojukwu, and Moshood Ayinde. 2026. “Medication Safety and Error Prevention in Acute Care Nursing.” International Journal of Multidisciplinary Research and Growth Evaluation 2 (6): 792–805. https://doi.org/10.54660/.ijmrge.2021.2.6.792-805
- Olson, Paul L., and Arthur Bernstein. 1979. “The Nighttime Legibility of Highway Signs as a Function of Their Luminance Characteristics.” Human Factors: The Journal of the Human Factors and Ergonomics Society 21 (2): 145–60. https://doi.org/10.1177/001872087902100202
- Omoro, Gonza O., Maureen Awuor, and Amos Omamo. 2018. “National Unique Patient Identifier in HIV/AIDS Healthcare in Kenya.” International Journal of Research Publications 15 (1): 3. https://doi.org/10.47119/ijrp100151102018396
- Oppolzer, Jan, and Robert Bešťák. 2014. “Physical Cell Identifier Assignment in Dense Femtocell Deployment.” In Advances in wireless technologies and telecommunication book series. IGI Global. https://doi.org/10.4018/978-1-4666-4888-3.ch019
- “Oral Liquid Medications and LASA Errors.” 2026. In IGI Global eBooks. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1.ch009
- Ortolani, C. 2009. “The Function of Phonetic Similarity in Analysis of the Likelihood of Confusion.” Journal of Intellectual Property Law & Practice 4 (5): 312–14. https://doi.org/10.1093/jiplp/jpp031
- Orye, Erwin, Gabor Visky, and Olaf Maennel. 2023. “Analysing the Actual Use of Controller–Pilot Data Link Communications.” In OpenSky 2022. MDPI. https://doi.org/10.3390/engproc2022028018
- Osipova, Olga A. 2016. “PROSODIC CHARACTERISTICS OF THE DISCOURSE OF RADIOTELEPHONY IN CIVIL AVIATION.” Bulletin of the Moscow State Regional University (Linguistics), no. 6: 35–42. https://doi.org/10.18384/2310-712x-2016-6-35-42
- Ostini, Remo, Elizabeth E. Roughead, Carl M. J. Kirkpatrick, Greg R. Monteith, and Susan E. Tett. 2012. “Quality Use of Medicines – Medication Safety Issues in Naming; Look-Alike, Sound-Alike Medicine Names.” International Journal of Pharmacy Practice 20 (6): 349–57. https://doi.org/10.1111/j.2042-7174.2012.00210.x
- Page, Roderic. 2008. “When DOIs Collide and Then Disappear: When Is a Unique, Resolvable Identifier a Bad Idea?” Preprint, Front Matter. https://doi.org/10.59350/xaevz-82m80
- Palanivelrajan, P., and P. Alli. 2018. “Unique Patient Identifier for National Ehealthcare Service Delivery the Indian Approach.” International Journal of Computer Sciences and Engineering 6 (11): 807–10. https://doi.org/10.26438/ijcse/v6i11.807810
- Panca, Arvidareyna, Nikma Fitriasari, and Wiwik Supartiwi. 2018. “Medication Error Factors, Safety Guideline System, Flow of Drug Usage, and Code of Conduct to Prevent Medication Error.” Bioinformatics and Biomedical Research Journal 1 (2): 28–32. https://doi.org/10.11594/bbrj.01.02.01
- Paramathma, Chilukuri. 2015. “Potential Hazards of Illegible Prescription: Look Alike Sound Alike Trade and Generic Names.” Journal of Pharmaceutical Research 14 (4): 98. https://doi.org/10.18579/jpcrkc/2015/14/4/89470
- Pastoor, Siegmund. 1990. “Legibility and Subjective Preference for Color Combinations in Text.” Human Factors: The Journal of the Human Factors and Ergonomics Society 32 (2): 157–71. https://doi.org/10.1177/001872089003200204
- Patel, Kaushikkumar. 2023. “Revolutionizing Consumer Data Analysis: The Development and Impact of a Unique Customer Identifier.” International Journal of Computer Trends and Technology 71 (12): 61–74. https://doi.org/10.14445/22312803/ijctt-v71i12p111
- Patrician, Patricia A., and Laura R. Brosch. 2009. “Medication Error Reporting and the Work Environment in a Military Setting.” Journal of Nursing Care Quality 24 (4): 277–86. https://doi.org/10.1097/ncq.0b013e3181afa4cb
- Pebrianto, Juri. 2022. “Perbandingan Kecepatan Baca Dan Tulis Data Pada Mysql Menggunakan Primary Key Auto Increment Dengan Universally Unique Identifier (UUID).” Media Jurnal Informatika 14 (2): 86. https://doi.org/10.35194/mji.v14i2.2681
- Pellegrini, Thomas, Jérôme Farinas, Estelle Delpech, and François Lancelot. 2019. “The Airbus Air Traffic Control Speech Recognition 2018 Challenge: Towards ATC Automatic Transcription and Call Sign Detection.” In Interspeech 2019. ISCA. https://doi.org/10.21437/interspeech.2019-1962
- Peng, Taoxin, and Calum Mackay. 2014. “Approximate String Matching Techniques.” In International Conference on Enterprise Information Systems. https://doi.org/10.5220/0004892802170224
- “Perbandingan Algoritma Edit Distance, Levenshtein Distance, Hamming Distance, Jaccard Similarity Dalam Mendeteksi String Matching.” 2014. JURNAL SISTEM INFORMASI UNIVERSITAS SURYADARMA 10 (1). https://doi.org/10.35968/jsi.v10i1.1009
- Perez, Tyandra. 2026. “Promoting Just Culture: Implementing a Medication Error Reporting Process in Nursing Education.” Journal of Nursing Education: 1–4. https://doi.org/10.3928/01484834-20260403-04
- Peshek, Stephanie C., and Kathleen Cubera. 2004. “Nonpunitive, Voice-Mail-Based Medication Error Reporting System.” Hospital Pharmacy 39 (9): 857–63. https://doi.org/10.1177/001857870403900907
- Peterson, Jeffrey A., Isabella Cunningham, and Robert Peterson. 2024. “Measuring Source, Affiliation, and Permission Likelihood of Consumer Confusion in Trademark Infringement Litigation.” International Journal of Applied Decision Sciences 1 (1): 1. https://doi.org/10.1504/ijads.2024.10051848
- Petrun, Craig J., William Hernon, and Marian MacDonald. 1985. “An Examination of the Relative Legibility of Text on One Line Vacuum Florescent and Liquid Crystal Displays.” Proceedings of the Human Factors Society Annual Meeting 29 (12): 1122–24. https://doi.org/10.1177/154193128502901210
- Phillips, Marjorie A. Shaw. 2001. “National Program for Medication Error Reporting and Benchmarking: Experience with MedMARx.” Hospital Pharmacy 36 (5): 509–13. https://doi.org/10.1177/001857870103600507
- Phillips, Marjorie Shaw. 2014. “Chapter 9: Medication Error Reporting and Analysis.” In ASHP eBooks. https://doi.org/10.37573/9781585283583.009
- Phipps, Denham L. 2025. “Addressing the Risk of Look-Alike, Sound-Alike Medication Errors: Bending Metal or Twisting Arms?” BMJ Quality & Safety 34 (11): 714–16. https://doi.org/10.1136/bmjqs-2025-018648
- Phonetic features. 2019. “7.10 Phonetic Features, Vocalisation and Graphic Confusion.” In The Greek and Latin Inscriptions of Ankara (Ancyra), edited by Stephen Mitchell, David French. Verlag C.H.BECK oHG. https://doi.org/10.17104/9783406736254-340
- Pidlubna, O. 2019. “Functional Peculiarities of Modal Verbs Usage in the Aviation English Radiotelephony Discourse.” International Humanitarian University Herald. Philology 40 (2): 61–64. https://doi.org/10.32841/2409-1154.2019.40.2.15
- “Pilot-Controller Communication Problems and an Initial Exploration of Language-Engineering Technologies as a Potential Solution.” 2016. In Industrial and Systems Engineering Series. CRC Press. https://doi.org/10.1201/9781315370460-23
- “Pilot-Controller Communication: A Multidimensional Analysis.” 2020. In Bloomsbury Academic eBooks. https://doi.org/10.5040/9781350059344.ch-006
- Plaisant, Catherine, and Andrew Sears. 1992. “Touchscreen Interfaces for Alphanumeric Data Entry.” Proceedings of the Human Factors Society Annual Meeting 36 (4): 293–97. https://doi.org/10.1177/154193129203600407
- Polk, J. 2014. Registering a SIP Resource Priority Header Field Namespace for Local Emergency Communications. RFC Editor. https://doi.org/10.17487/rfc7135
- Polychronakos, Constantin. 2012. “Unique Author Identifier; What Are We Waiting For?” Journal of Medical Genetics 49 (2): 75–75. https://doi.org/10.1136/jmedgenet-2012-100736
- Poornima, Penumarthi, Pasala Reshma, Ramakrishnan Tv, et al. 2015. “Medication Reconciliation and Medication Error Prevention in an Emergency Department of a Tertiary Care Hospital.” Journal of Young Pharmacists 7 (3): 241–49. https://doi.org/10.5530/jyp.2015.3.15
- Post, Olaf, and Godfried Toussaint. 2011. “The Edit Distance as a Measure of Perceived Rhythmic Similarity.” Empirical Musicology Review 6 (3): 164–79. https://doi.org/10.18061/1811/52811
- Prakash, Bhanu. 2010. “Sad Confusion of Look-Alike Tablets.” Indian Dermatology Online Journal 1 (1): 50. https://doi.org/10.4103/2229-5178.73266
- Pranoto, Dani Chandra Yudho, and Fajar Susanto. 2024. “The Challenges in Learning ICAO Radiotelephony: Students’ Perspective.” Langit Biru Jurnal Ilmiah Aviasi 17 (01): 40–48. https://doi.org/10.54147/langitbiru.v17i01.1119
- Preczewski, Stanley C., and Donald L. Fisher. 1990. “The Selection of Alphanumeric Code Sequences.” Proceedings of the Human Factors Society Annual Meeting 34 (3): 224–28. https://doi.org/10.1177/154193129003400310
- The Prescription and Drug Names. 2020. Wiley. https://doi.org/10.1002/9781119539384.ch2
- Prokhozhay, Irina Nikolayevna. 2011. “Radiotelephony as a Special Type of Institutional Discourse.” Izvestiya of Saratov University. New Series. Series: Philology. Journalism 11 (3): 52–59. https://doi.org/10.18500/1817-7115-2011-11-3-52-59
- “Pronunciation of Drug Names.” 1970. Drug and Therapeutics Bulletin 8 (8): 32.1-32. https://doi.org/10.1136/dtb.8.8.32
- “public access.” n.d. Accessed October 24, 2026. https://poca-public.fda.gov/
- R. G. D. 1926. “Trade Name—Similarity of Name—Injunction.” Cambridge Law Journal 2 (3): 396–97. https://doi.org/10.1017/s0008197300111766
- Rached, Stephanie. n.d. “Barriers to the Implementation of a Unique Identifier and a Track and Trace System in the Lebanese Pharmaceutical Sector. (c2022).” PhD diss., LAU. https://doi.org/10.26756/th.2022.427
- Radack, David V. 2002. “Likelihood of Confusion — The Basis for Trademark Infringement.” JOM 54 (12): 80–80. https://doi.org/10.1007/bf02709194
- Radul, Serhii. 2025. Barriers to verbal communication in aviation safety. https://doi.org/10.36059/978-966-397-502-3-92
- Rahman, Zaida, and Rukhsana Parvin. 2015. “Medication Errors Associated with Look-alike/Sound-Alike Drugs: A Brief Review.” Journal of Enam Medical College 5 (2): 110–17. https://doi.org/10.3329/jemc.v5i2.23385
- Rakas, Jasenka, Matthew Alvarado, Kezhi He, Drew Kim, and Della Qu. 2022. “Analysis of Controller-Pilot Communication Messages with Natural Language Processing.” In AIAA AVIATION 2022 Forum. AIAA 2022-3832. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2022-3832
- Rakas, Jasenka, Sungmin Sohn, Lee Keslerwest, and Jimmy Krozel. 2023. “Deep Speech Pattern Analysis of Controller-Pilot Voice Communications for Enhancing Future Aviation Systems Safety.” In AIAA AVIATION 2023 Forum. AIAA 2023-4410. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2023-4410
- Rakas, Jasenka, Vishali Kirthi Vallioor, Jimmy Krozel, Peter F. Kostiuk, and Michael T. Mohen. 2024. “Controller-Pilot Voice Communication and Intent Monitoring for Future Aviation Systems Safety.” In AIAA Aviation Forum and Ascend 2024. AIAA 2024-3942. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2024-3942
- Rakas, Jasenka, and Huifang Yin. 2005. “Analysis and Modeling of Controller-Pilot Miscommunication Messages.” In AIAA 5th ATIO and16th Lighter-Than-Air Sys Tech. and Balloon Systems Conferences. AIAA 2005-7430. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2005-7430
- Rama, Taraka, and Lars Borin. 2015. “Comparative Evaluation of String Similarity Measures for Automatic Language Classification.” In Sequences in Language and Text. DE GRUYTER. https://doi.org/10.1515/9783110362879-012
- Rash-Foanio, Christine, William Galanter, Michelle Bryson, et al. 2017. “Automated Detection of Look-Alike/sound-Alike Medication Errors.” American Journal of Health-System Pharmacy 74 (7): 521–27. https://doi.org/10.2146/ajhp150690
- Rask, Kimberly, Jonathan Hawley, Anne Davis, Dorothy ‘Vi’ Naylor, and Kenneth Thorpe. 2006. “Impact of a Statewide Reporting System on Medication Error Reduction.” Journal of Patient Safety 2 (3): 116–23. https://doi.org/10.1097/01.jps.0000226323.37963.19
- Rasmussen, P. G., B. P. Chesterfield, and D. L. Lowrey. 1980. “Legibility of Smoke-Obscured Emergency Exit Signs.” Proceedings of the Human Factors Society Annual Meeting 24 (1): 476–79. https://doi.org/10.1177/1071181380024001124
- Rastogi, Shantanu. 2015. “Look Alike Sound Alike Drugs: From Hospitals to Homes.” Journal of Pediatric Intensive Care 01 (03): 125–26. https://doi.org/10.3233/pic-2012-021
- Rataboli, Padmanabh, Akshay Khandeparkar, Suvidha Khandolkar, and Lokesh Chawla. 2015. “Confusing Brand Names: Algorithms to Assess the Confusability to Dispensers and Risk to Patients.” International Journal of Scientific Reports 1 (1): 52. https://doi.org/10.18203/issn.2454-2156.intjscirep20150201
- Rawat, Neeta. 2008. “Medication Error and Their Prevention.” Journal of Neonatology 22 (2): 115–17. https://doi.org/10.1177/0973217920080209
- Reichert, Thomas. 2025. “Confusingly Similar, Quantifiably Different a Machine-Learning Framework for Assessing Likelihood of Confusion.” Preprint, . https://doi.org/10.2139/ssrn.5508738
- Reichert, Thomas. 2026a. “Decoding DuPont: A Large-Scale Empirical Study of Trademark Confusion at the TTAB.” Preprint, . https://doi.org/10.2139/ssrn.6222839
- Reichert, Thomas. 2026b. “FACTORS AND FICTIONS: The Empirical Collapse of the Likelihood-of-Confusion Test across the Federal Courts.” Preprint, . https://doi.org/10.2139/ssrn.6329638
- Reichert, Thomas. 2026c. “The Missing Jury: Fact, Law, and Who Actually Decides Trademark Confusion.” Preprint, . https://doi.org/10.2139/ssrn.7045278
- Reichert, Thomas. 2026d. “On Confusion: A Restatement of Trademark’s Likelihood-of-Confusion Test.” Preprint, . https://doi.org/10.2139/ssrn.7045119
- Reichert, Thomas. 2026e. “Summary Judgment and Jury Rates in Likelihood-of-Confusion Cases, by Circuit.” Preprint, . https://doi.org/10.2139/ssrn.7248286
- Reines, Scott A. 2005. “Look-Alike, Sound-Alike Drug Errors with Reminyl and Amaryl.” American Journal of Health-System Pharmacy 62 (1): 35–36. https://doi.org/10.1093/ajhp/62.1.35
- Revesz, Peter Zsolt. 2021. “A Tiling Algorithm-Based String Similarity Measure.” WSEAS TRANSACTIONS ON COMPUTER RESEARCH 9: 109–12. https://doi.org/10.37394/232018.2021.9.13
- Ribeiro, Davyson, Paulo V. A. Fabrício, Rafael Pereira, et al. 2025. “Handling Inconsistent Government Data: From Acquisition to Entity Name Matching and Address Standardization.” In International Conference on Enterprise Information Systems. https://doi.org/10.5220/0013294200003929
- Richmond, Sandra L. 2011. “Medication Error Prevention in the School Setting: A Closer Look.” NASN School Nurse 26 (5): 304–8. https://doi.org/10.1177/1942602x11416369
- Rigan Ramadhani, Muhammad, and Veny Usviany. 2024. “Evaluasi Penyimpanan Obat Lasa (Look-Alike Sound- Alike) Di Instalasi Farmasi Rumah Sakit Sariningsih.” Prepotif: Jurnal Kesehatan Masyarakat 8 (3): 4855–61. https://doi.org/10.31004/prepotif.v8i3.33661
- Riley, Daniel D., and Floyd A. Glenn. 1996. “Alphanumeric Data Entry and Editing on a Telephone-Type Keypad.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40 (19): 1012–16. https://doi.org/10.1177/154193129604001912
- Ringseis, E. L., and J. K. Caird. 1995. “The Comprehensibility and Legibility of Twenty Pharmaceutical Warning Pictograms.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 39 (15): 974–78. https://doi.org/10.1177/154193129503901502
- Rinke, Michael L., David G. Bundy, Andrew D. Shore, Elizabeth Colantuoni, Laura L. Morlock, and Marlene R. Miller. 2010. “Pediatric Antidepressant Medication Errors in a National Error Reporting Database.” Journal of Developmental & Behavioral Pediatrics 31 (2): 129–36. https://doi.org/10.1097/dbp.0b013e3181ce6509
- Ritchie, Lorelei D. 2026. “Likelihood of Confusion as a Relative Ground for Refusal.” In Elgar Encyclopedia of Intellectual Property Law. Edward Elgar Publishing. https://doi.org/10.4337/9781800886926.likelihood.of.confusion
- Riva, Alberto, and Graziano Pesole. 2009. “A Unique, Consistent Identifier for Alternatively Spliced Transcript Variants.” PLoS ONE 4 (10): e7631. https://doi.org/10.1371/journal.pone.0007631
- Robins, Rebecca. 2001. “Pharmaceutical Brand Name Development.” In Brand Medicine. Palgrave Macmillan UK. https://doi.org/10.1057/9780230522510_11
- Roca, Javier, Beatriz Insa, and Pilar Tejero. 2018. “Legibility of Text and Pictograms in Variable Message Signs: Can Single-Word Messages Outperform Pictograms?” Human Factors: The Journal of the Human Factors and Ergonomics Society 60 (3): 384–96. https://doi.org/10.1177/0018720817751623
- Rochmawati, Yeny, and Retno Kusumaningrum. 2016. “Studi Perbandingan Algoritma Pencarian String Dalam Metode Approximate String Matching Untuk Identifikasi Kesalahan Pengetikan Teks.” Jurnal Buana Informatika 7 (2). https://doi.org/10.24002/jbi.v7i2.491
- “The Role of Orthographic and Phonetic Distances in Mutual Intelligibility between Montenegrin and Bulgarian.” 2019. Logos et Littera: 50–66. https://doi.org/10.31902/ll.2019.6.1.3
- “The Role of Typography in Differentiating Look-Alike/Sound-Alike Drug Names.” 2006. Healthcare Quarterly 9 (sp): 88–95. https://doi.org/10.12927/hcq.2013.18465
- Rose, F. C., and D. Y. Cornog. 1964. Legibility of Alphanumeric Characters and Other Symbols I. a Permuted Title Index and Bibiography/. National Institute of Standards and Technology. https://doi.org/10.6028/nbs.mp.262-1
- Rose, F. C., and D. Y. Cornog. 1967. Legibility of Alphanumeric Characters and Other Symbols II. a Reference Handbook/. National Institute of Standards and Technology. https://doi.org/10.6028/nbs.mp.262-2
- Rosmayanti, Lina, Djoko Jatmoko, Sri Rahayu Surtiningtyas, et al. 2024. “Radiotelephony Untuk Personel Pangkalan TNI AU Atang Sendjaja.” Jurnal Pengabdian Kepada Masyarakat (JPKM) Langit Biru 5 (02): 82–87. https://doi.org/10.54147/jpkm.v5i02.1254
- Ruutiainen, Henna Karoliina, Miia Marjukka Kallio, and Sini Karoliina Kuitunen. 2021. “Identification and Safe Storage of Look-Alike, Sound-Alike Medicines in Automated Dispensing Cabinets.” European Journal of Hospital Pharmacy 28 (e1): e151-e156. https://doi.org/10.1136/ejhpharm-2020-002531
- Ryan, Alexandra N., Kelvin L. Robertson, and Beverley D. Glass. 2025. “Look-Alike, Sound-Alike Medication Perioperative Incidents in a Regional Australian Hospital: Assessment Using a Novel Medication Safety Culture Assessment Tool.” International Journal for Quality in Health Care 37 (1): mzaf018. https://doi.org/10.1093/intqhc/mzaf018
- Saad, Aline H., Rehab Bondok, Farah Sayeg, et al. 2025. “Enhancing Medication Error Reporting through Interprofessional Education: Analysis of MedWatch Reporting Accuracy and Completion Rates between Teams and Individuals.” Preprint, Research Square. https://doi.org/10.21203/rs.3.rs-5687396/v1
- Saada, Mohammad. 2023. “Healthcare Professional’s Knowledge and Awareness of the Medication Error Reporting Systems in the Kuwaiti Hospitals.” Current Issues in Pharmacy and Medical Sciences 36 (2): 87–93. https://doi.org/10.2478/cipms-2023-0015
- Saada, Mohammed, Hana Morrissey, and Patrick Ball. 2023. “Importance of Healthcare Professional Training on Medication Safety, Medication Error Prevention, and Reporting.” Journal Of Advanced Pharmacy Education And Research 13 (3): 1–7. https://doi.org/10.51847/nsvledyp4z
- Sadeh, I. n.d. “On Approximate String Matching.” In [Proceedings] DCC `93: Data Compression Conference. IEEE Comput. Soc. Press. https://doi.org/10.1109/dcc.1993.253135
- Sadler, Garrett, Meghan Chandarana, and Jillian Keeler. 2023. “Effects of Communication Modality on Pilot-Controller Coordination during a Simulated m:N Operation.” In AIAA AVIATION 2023 Forum. AIAA 2023-3265. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2023-3265
- Sagawa, Haruka, Hayato Kizaki, Kodai Yoshikawa, et al. 2024. “Analyzing the Impact of Drug Name Similarity on Dispensing Errors: An Examination Using a Drug Name Similarity Index.” Biological and Pharmaceutical Bulletin 47 (8): 1460–66. https://doi.org/10.1248/bpb.b24-00365
- Saikrishna, Vidya, and Sid Ray. 2013. “Improved Approximate Multiple-Pattern String Matching Using Consecutive N-Grams.” International Journal of Computer Applications 81 (2): 26–31. https://doi.org/10.5120/13986-1996
- Saint-Andre, P. 2013. A Uniform Resource Name (URN) Namespace for Examples. RFC Editor. https://doi.org/10.17487/rfc6963
- Salim, Suriyati. 2026. “Reforming Aural Similarity in Malaysian Trademark Law: Structuring Judicial Discretion through Mandatory Phonetic Particularisation.” Jurnal Undang-Undang DAN Masyarakat 36 (1): 127–44. https://doi.org/10.17576/juum-2026-3601-08
- Samaei, Seyed Ehsan, Mohammad Amrollahi, Narges Khanjani, Mehdi Raadabadi, MajidBagheri Hosseinabadi, and Maryam Mostafaee. 2017. “Nurses’ Perspectives on the Reasons behind Medication Errors and the Barriers to Error Reporting.” Nursing and Midwifery Studies 6 (3): 132. https://doi.org/10.4103/nms.nms_31_17
- Samsiah, A., Noordin Othman, Shazia Jamshed, and Mohamed Azmi Hassali. 2016b. “Perceptions and Attitudes towards Medication Error Reporting in Primary Care Clinics: A Qualitative Study in Malaysia.” PLOS ONE 11 (12): e0166114. https://doi.org/10.1371/journal.pone.0166114
- Samudra, Agung giri, Bella Friska, and Mita Kurnia. 2022. “Pengetahuan Tenaga Teknis Kefarmasian Tentang Obat-Obat Look-Alike Sound-Alike (LASA) Di Apotek Kota Bengkulu.” Bencoolen Journal of Pharmacy 2 (1). https://doi.org/10.33369/bjp.v2i1.23484
- Samundeeswari, A. 2018. “Nurses Knowledge on Prevention of Medication Error.” Journal of Medical Science And clinical Research 6 (3). https://doi.org/10.18535/jmscr/v6i3.45
- Sankaran, Sathya, and R. Rajkumar. 2016. “Unique Barcode Identifier for Patient Record Using Geographical, Calendar, Time Barcodes with Error Detection.” Indian Journal of Science and Technology 9 (38). https://doi.org/10.17485/ijst/2016/v9i38/97189
- Santos, Karina. 2020. “Exploring Nurses’ Knowledge of Medication Error Reporting.” Preprint, Rhode Island College. https://doi.org/10.28971/532020sa57
- Sardana, Kabir, and Sinu Rose Mathachan. 2023. “Iatrogenic Irritant Contact Dermatitis to Podophyllin and the Perils of Look-Alike, Sound-Alike Trade Names in Dermatology.” Indian Journal of Dermatology, Venereology and Leprology 90: 110–12. https://doi.org/10.25259/ijdvl_72_2023
- Sariyar, Murat. 2027. “Record Linkage and Entity Matching Using Statistical, Machine Learning and LLM Based Models.” In Encyclopedia of Measurement in Social Sciences. Elsevier. https://doi.org/10.1016/b978-0-443-26629-4.00057-5
- Sastry, R., and N. Ranganathan. 1993. “A Systolic Array for Approximate String Matching.” In Proceedings of 1993 IEEE International Conference on Computer Design ICCD’93. IEEE Comput. Soc. Press. https://doi.org/10.1109/iccd.1993.393344
- Savage, Scott W., Philip J. Schneider, and Craig A. Pedersen. 2005. “Utility of an Online Medication-Error-Reporting System.” American Journal of Health-System Pharmacy 62 (21): 2265–70. https://doi.org/10.2146/ajhp040622
- Sawyer, Ben D., Jonathan Dobres, Nadine Chahine, and Bryan Reimer. 2017. “The Cost of Cool: Typographic Style Legibility in Reading at a Glance.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61 (1): 833–37. https://doi.org/10.1177/1541931213601698
- Scarborough, Rebecca Anne. 2003a. “Lexical Confusability and Degree of Coarticulation.” Proceedings of the Annual Meeting of the Berkeley Linguistics Society 29 (1): 367. https://doi.org/10.3765/bls.v29i1.990
- Scarborough, Rebecca. 2003b. “The Specificity of Lexical Confusability Effects on Coarticulation.” Journal of the Acoustical Society of America 114 (4_Supplement): 2393–2393. https://doi.org/10.1121/1.4777975
- Scheirman, Katherine. 2001. An Analysis of Medication Errors at the Military Medical Center: Implications for a Systems Approach for Error Reduction. Defense Technical Information Center. https://doi.org/10.21236/ada420601
- Schieber, Frank. 1994. “Using the “Blur Tolerance” Technique to Predict and Optimize the Legibility Distance of Symbol Highway Signs.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38 (14): 912–15. https://doi.org/10.1177/154193129403801425
- Schieber, Frank. 1998. “Design-By-Blur: An Integrated Software Environment for Optimizing the Legibility of Graphical Symbol Signs.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42 (16): 1150–1150. https://doi.org/10.1177/154193129804201610
- Schieber, Frank. 2005. “Effects of Driving Speed and Sign Reflectance on Nighttime Highway Sign Legibility Distance and Reading Time Requirements.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49 (22): 1927–30. https://doi.org/10.1177/154193120504902209
- Schieber, Frank, and Donald W. Kline. 1994. “Age Differences in the Legibility of Symbol Highway Signs as a Function of Luminance and Glare Level: A Preliminary Report.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38 (2): 133–36. https://doi.org/10.1177/154193129403800201
- Schnell, Thomas, and Helmut T. Zwahlen. 1999. “Legibility Threshold Contrast of Uppercase Text Seen against a Dark Background.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 43 (23): 1338–42. https://doi.org/10.1177/154193129904302316
- Schulmeister, Lisa. 2006. “Look-Alike, Sound-Alike Oncology Medications.” Clinical Journal of Oncology Nursing 10 (1): 35–41. https://doi.org/10.1188/06.cjon.35-41
- Schumacher, Elliot, James Mayfield, and Mark Dredze. 2023. “On the Surprising Effectiveness of Name Matching Alone in Autoregressive Entity Linking.” In Proceedings of the First Workshop on Matching From Unstructured and Structured Data (MATCHING 2023). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.matching-1.6
- Schweizer, Markus. 2005b. “Consumer Confusion: Eine begriffliche Explikation.” In Consumer Confusion im Handel. Deutscher Universitätsverlag. https://doi.org/10.1007/978-3-322-81977-2_2
- Schweizer, Markus. 2005c. “Empirische Untersuchung von Consumer Confusion.” In Consumer Confusion im Handel. Deutscher Universitätsverlag. https://doi.org/10.1007/978-3-322-81977-2_4
- Schweizer, Markus. 2005d. “Modelltheoretische Konzeption von Consumer Confusion.” In Consumer Confusion im Handel. Deutscher Universitätsverlag. https://doi.org/10.1007/978-3-322-81977-2_3
- Schweizer, Markus. 2005e. “Positionierung und Profilierung unter Berücksichtigung von Consumer Confusion.” In Consumer Confusion im Handel. Deutscher Universitätsverlag. https://doi.org/10.1007/978-3-322-81977-2_5
- Scott, Denise, and Alan Baddeley. 1969. “Acoustic Confusability Values for 1172 CCC Trigrams.” Psychonomic Science 14 (4): 189–90. https://doi.org/10.3758/bf03332782
- Sears, Erin L., and Joyce A. Generali. 2005. “Adverse Drug Reaction and Medication Error Reporting by Pharmacy Students.” Annals of Pharmacotherapy 39 (3): 452–59. https://doi.org/10.1345/aph.1e369
- Securities and Related Financial Instruments. International Securities Identification Numbering System (ISIN). n.d. BSI British Standards. https://doi.org/10.3403/30181185
- Sensmeier, Joyce, and Whende M. Carroll. 2021. “Improving Patient Outcomes through Sharable, Comparable Nursing Data Using a Unique Nurse Identifier.” CIN: Computers, Informatics, Nursing 39 (2): 61–62. https://doi.org/10.1097/cin.0000000000000706
- Sergent, Justine. 1983. “Hemispheric Competence and Perceptual Confusability.” Quarterly Journal of Experimental Psychology Section A 35 (4): 589–96. https://doi.org/10.1080/14640748308402148
- Serrano, Marcos, Anne Roudaut, and Pourang Irani. 2016. “Investigating Text Legibility on Non-Rectangular Displays.” In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM. https://doi.org/10.1145/2858036.2858057
- ShabnamHasan, Syeda, Fareal Ahmed, and Rosina Surovi Khan. 2015. “Approximate String Matching Algorithms: A Brief Survey and Comparison.” International Journal of Computer Applications 120 (8): 26–31. https://doi.org/10.5120/21247-4048
- Shah, Rima, and Dheeraj Kumar Singh. 2014a. “Analysis and Comparative Study on Phonetic Matching Techniques.” International Journal of Computer Applications 87 (9): 14–17. https://doi.org/10.5120/15236-3771
- Shah, Rima, and Dheeraj Kumar Singh. 2014b. “Improvement of Soundex Algorithm for Indian Language Based on Phonetic Matching.” International Journal of Computer Science Engineering and Applications 4 (3): 31–39. https://doi.org/10.5121/ijcsea.2014.4303
- Shanty, Joyce A. n.d. “The Influence of Perceived Safety Culture and Nurses’ Work Environment on Medication Error Occurrence and Reporting.” PhD diss., West Virginia University Libraries. https://doi.org/10.33915/etd.4787
- Shastay, Ann. 2023. “Look-Alike Packaging.” Home Healthcare Now 41 (3): 168–69. https://doi.org/10.1097/nhh.0000000000001170
- Sheedy, James E., Manoj V. Subbaram, Aaron B. Zimmerman, and John R. Hayes. 2005. “Text Legibility and the Letter Superiority Effect.” Human Factors: The Journal of the Human Factors and Ergonomics Society 47 (4): 797–815. https://doi.org/10.1518/001872005775570998
- Sheff, Jeremy N. 2024. “An Empirical Evaluation of the Trademark Modernization Act.” Preprint, . https://doi.org/10.2139/ssrn.4903190
- Shelake, Vijay Maruti, and Narendra M. Shekokar. 2022. “Different Similarity Measures for Secure Name Matching in Record Linkage.” In Cyber Security Threats and Challenges Facing Human Life. Chapman and Hall/CRC. https://doi.org/10.1201/9781003218555-18
- Shetty, Shruthi H., Hartmut Helmke, Matthias Kleinert, and Oliver Ohneiser. 2022. “Early Callsign Highlighting Using Automatic Speech Recognition to Reduce Air Traffic Controller Workload.” AHFE international. https://doi.org/10.54941/ahfe1002493
- Shiima, Yuko, Muzaffar Malik, and Michael Okorie. 2022. “Medication without Harm: Developing Optimal Medication Error Reporting Systems.” Current Drug Safety 17 (1): 7–12. https://doi.org/10.2174/1574886316666210423115029
- Shivanand H Honakeri, Hemanth C K, and Latha Venkatesh. 2026. “Medication Administration Safety and Error Prevention System Using Intelligent Nursing Support Technology.” Journal of Nursing Future Care: AI and Innovation: 21–30. https://doi.org/10.65900/jnfcai.2026.v01i02.003
- Shurtleff, D. 1966. Design Problems in Visual Displays. Part 1. Classical Factors in the Legibility of Numerals and Capital Letters. Defense Technical Information Center. https://doi.org/10.21236/ad0636414
- Shurtleff, D., and W. Wuersch. 1979. “Legibility Criteria in Design and Selection of Data Displays for Group Viewing.” Proceedings of the Human Factors Society Annual Meeting 23 (1): 411–14. https://doi.org/10.1177/1071181379023001103
- Siddiqui, Durr-e-Shahwar. 2020. “Minimizing Medication Errors by Triangle Check of Look-Alike Sound-Alike Medications from Crash Cart of Gynecology and Obstetrics in Emergency.” INNOVATIONS in pharmacy 11 (4): 18. https://doi.org/10.24926/iip.v11i4.3480
- Sihotang, Yola Annisa. 2023. “Implementasi Algoritma Approximate String Matching Pada Aplikasi Pengarsipan Dokumen Ekspor Barang.” Management of Information System Journal. 2 (1): 14–18. https://doi.org/10.47065/mis.v2i1.1025
- “Similar Drug Names a Risky Prescription.” 2004. JAMA 291 (16): 1948. https://doi.org/10.1001/jama.291.16.1948
- Simpson, F. V. 1979. “Points: Drug Names That Look or Sound Alike.” BMJ 2 (6200): 1297.5-1297. https://doi.org/10.1136/bmj.2.6200.1297-d
- Simpson, Heather, Stephanie Strassel, Robert Parker, and Paul McNamee. 2010. “Wikipedia and the Web of Confusable Entities: Experience from Entity Linking Query Creation for TAC 2009 Knowledge Base Population.” In Proceedings of the Language Resources and Evaluation Conference. European Language Resources Association (ELRA). https://doi.org/10.63317/4hxrwhom8hus
- Singh, Sunil, and Angel Rajan Singh. 2017. “Policies and Procedures for Sound-Alike and Look-Alike Medications.” International Journal of Research Foundation of Hospital and Healthcare Administration 5 (1): 15–20. https://doi.org/10.5005/jp-journals-10035-1071
- Sitbon, Laurianne, Patrice Bellot, and Philippe Blache. 2007. “Phonetic Based Sentence Level Rewriting of Questions Typed by Dyslexic Spellers in an Information Retrieval Context.” In Interspeech 2007. ISCA. https://doi.org/10.21437/interspeech.2007-676
- Siti Fitriani, Rani. 2021. “IMPLIKASI FENOMENA ALAM DAN MISKOMUNIKASI RADIOTELEPHONY PADA KECELAKAAN PENERBANGAN: KAJIAN AEROLINGUISTIK: Implications of Natural Phenomenas and Radiotelephony Miscommunications in Flight Accidents: Aerolinguistic Study.” Prosiding Balai Arkeologi Jawa Barat: 183–92. https://doi.org/10.24164/prosiding.v4i1.17
- Sivak, Michael, Paul L. Olson, and Leon A. Pastalan. 1981. “Effect of Driver’s Age on Nighttime Legibility of Highway Signs.” Human Factors: The Journal of the Human Factors and Ergonomics Society 23 (1): 59–64. https://doi.org/10.1177/001872088102300106
- Skaltsas, Gerasimos, Jasenka Rakas, Jasenka Rakas, Gerasimos Skaltsas, Matthew Karlaftis, and Matthew Karlaftis. 2011. “An Analysis of Controller-Pilot Miscommunication in the NextGen Environment.” In 11th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference. AIAA 2011-6897. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2011-6897
- Smetzer, Judy. 2001. “Medication Error Prevention Techniques for the Bedside Nurse.” Hospital Pharmacy 36 (6): 588–89. https://doi.org/10.1177/001857870103600602
- Smetzer, Judy L., and Michael R. Cohen. 2007. “Chapter 19. Medication Error Reporting Systems.” In Medication Errors, 2nd Edition. The American Pharmacists Association. https://doi.org/10.21019/9781582120928.ch19
- Smith, Sidney L. 1979. “Letter Size and Legibility.” Human Factors: The Journal of the Human Factors and Ergonomics Society 21 (6): 661–70. https://doi.org/10.1177/001872087912210604
- Smith, Kelly M., Philip J. Trapskin, Philip E. Empey, Keith A. Hecht, and John A. Armitstead. 2006. “Internally-Developed Online Adverse Drug Reaction and Medication Error Reporting Systems.” Hospital Pharmacy 41 (5): 428–36. https://doi.org/10.1310/hpj4105-428
- Snae, Chakkrit, and Michael Brueckner. 2009. “Novel Phonetic Name Matching Algorithm with a Statistical Ontology for Analysing Names Given in Accordance with Thai Astrology.” In InSITE Conference. Informing Science Institute. https://doi.org/10.28945/3347
- Snyder, Harry L. 1979. “The Sensitivity of Response Measures of Alphanumeric Legibility to Variations in Dot Matrix Display Parameters.” Human Factors: The Journal of the Human Factors and Ergonomics Society 21 (4): 457–71. https://doi.org/10.1177/001872087902100408
- Sohn, Minjoon, San Hong, Namhee Kim, Sungwoo Jeong, and Woojin Park. 2024. “Effects of Glass Transmittance, Font Brightness and Font Size on Text Legibility in LCD Home Appliance Interface.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 68 (1): 734–37. https://doi.org/10.1177/10711813241275517
- Soukup, Kathryn M., and Silas E. Hammond. 1982. “Author Name Processing at Chemical Abstracts Service: Name Matching by Using Nonunique Bibliographic Identifiers.” Journal of Chemical Information and Computer Sciences 22 (3): 172–76. https://doi.org/10.1021/ci00035a008
- Specification for International Securities Identification Numbering System (ISIN). n.d. BSI British Standards. https://doi.org/10.3403/00137461u
- Specification for Key Numbering System and Layout Charts for Keyboards on Office Machines. n.d. BSI British Standards. https://doi.org/10.3403/00116414u
- Spiker, Alan, and Steven P. Rogers. 1984. “Relative Legibility of Random-Scan and Raster-Scan CRT Displays in High Ambient Illumination.” Proceedings of the Human Factors Society Annual Meeting 28 (10): 931–34. https://doi.org/10.1177/154193128402801021
- Spoto, Cheryl G., and A. J. G. Babu. 1989. “Highlighting in Alphanumeric Displays: The Efficacy of Monochrome Methods.” Proceedings of the Human Factors Society Annual Meeting 33 (5): 370–74. https://doi.org/10.1177/154193128903300530
- Stanchev, Peter, Weiyue Wang, and Hermann Ney. 2019. “EED: Extended Edit Distance Measure for Machine Translation.” In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1). Association for Computational Linguistics. https://doi.org/10.18653/v1/w19-5359
- Stanford, LaMarr, and Willem Homan. 1990. “A Model of “Applied Ethics” in Aviation Safety: The Aviation Safety Reporting System.” Journal of Aviation/Aerospace Education and Research. https://doi.org/10.15394/jaaer.1999.1235
- “Statutory Protection for Medication-Error Reporting (1505).” 2019. In ASHP eBooks. https://doi.org/10.37573/9781585286560.167
- Stewart, Ian. 2005. “Beware of Look-Alike and Sound-Alike Drugs.” Canadian Pharmacists Journal / Revue des Pharmaciens du Canada 138 (2): 45–45. https://doi.org/10.1177/171516350513800209
- Strauch, Bruce. 2006. “Cases of Note – Copyright – the Attrezzi of Trademark Violations – Reverse Confusion.” Against the Grain 18 (2). https://doi.org/10.7771/2380-176x.4655
- “Study of Deviant Use of International Non-Proprietary Name of Medicines in India.” 2020. Journal of Preventive Medicine and Holistic Health 4 (1): 16–19. https://doi.org/10.18231/2454-6712.2018.0005
- Stump, Lisa S. 2000. “Re-Engineering the Medication Error-Reporting Process: Removing the Blame and Improving the System.” American Journal of Health-System Pharmacy 57 (suppl_4): S10-S17. https://doi.org/10.1093/ajhp/57.suppl_4.s10
- Stuntz, Stephen E. 1963. Speech-Intelligibility and Talker-Recognition Tests of Air Force Voice Communication Systems. Defense Technical Information Center. https://doi.org/10.21236/ad0402989
- Subalakshmi, K. 2025. “Enhancing Aviation Safety through Secure Controller-Pilot Data Link Communication Protocols.” International Journal of Science, Engineering and Technology 13 (2): 1–12. https://doi.org/10.61463/ijset.vol.13.issue2.203
- Sulastri, Ainul Yaqin Salam, and Zainal Abidin. 2023. “Blaming Culture Perceptions and Nurses’ Attitudes in Reporting Medication Error Incidents in Hospital.” Jurnal Kesehatan Komunitas Indonesia 3 (3): 281–95. https://doi.org/10.58545/jkki.v3i3.211
- Sung, Wing-Kin. 2008. “Indexed Approximate String Matching: 2006; Chan, Lam, Sung, Tam, Wong.” In Encyclopedia of Algorithms. Springer US. https://doi.org/10.1007/978-0-387-30162-4_188
- Sung, Wing-Kin. 2016. “Indexed Approximate String Matching.” In Encyclopedia of Algorithms. Springer New York. https://doi.org/10.1007/978-1-4939-2864-4_188
- Supapaan, Teeraporn Sadira, Jirawat Kamnuek, Chanawat Khakaew, et al. 2024a. “Assessment of Look-Alike, Sound-Alike Similarities among BrandNames of Tablets and Capsules: A Cross-Sectional Survey inThailand.” Pharmacy Practice 22 (3): 1–9. https://doi.org/10.18549/pharmpract.2024.3.2955
- Supapaan, Teeraporn Sadira, Ananya Songmuang, Jintana Napaporn, et al. 2024b. “Look-Alike/sound-Alike Medication Errors: An in-Depth Examination through a Hospital Case Study.” Pharmacy Practice 22 (2): 1–13. https://doi.org/10.18549/pharmpract.2024.2.2959
- Susik, Robert. 2017. “Applying a q-Gram Based Multiple String Matching Algorithm for Approximate Matching.” Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska 7 (3): 47–50. https://doi.org/10.5604/01.3001.0010.5214
- Suzuki, M. 2001. The Assignment of the Information Field and Protocol Identifier in the Q.2941 Generic Identifier and Q.2957 User-to-User Signaling for the Internet Protocol. RFC Editor. https://doi.org/10.17487/rfc3033
- Svahn, David S. 1978. “Similarity of Drug Names.” JAMA: The Journal of the American Medical Association 240 (22): 2433. https://doi.org/10.1001/jama.1978.03290220045010
- “A Syntactic Namespace.” 2011. In Operating System Design. Chapman and Hall/CRC. https://doi.org/10.1201/9781439881118-25
- Systems, E-25 General Standards for Aerospace and Propulsion. 1959. Position Terms and Numbering System for Aircraft Gas Turbine Engines. https://doi.org/10.4271/arp246a
- Tagliacozzo, Renata, Manfred Kochen, and Lawrence Rosenberg. 1970. “Orthographic Error Patterns of Author Names in Catalog Searches.” Information Technology and Libraries 3 (2): 93–101. https://doi.org/10.6017/ital.v3i2.5245
- Takasu, A. n.d. “Document Filtering for Fast Approximate String Matching of Erroneous Text.” In Proceedings of Sixth International Conference on Document Analysis and Recognition. IEEE Comput. Soc. https://doi.org/10.1109/icdar.2001.953919
- Tamaki, Hirofumi, Hiroki Satoh, Satoko Hori, and Yasufumi Sawada. 2012. “Evaluation and Improvement of a Measure of Drug Name Similarity, Vwhtfrag, in Relation to Subjective Similarities and Experimental Error Rates.” Yakugaku Zasshi 132 (4): 525–29. https://doi.org/10.1248/yakushi.132.525
- Tan, Kevin, and Wee-Sen Choo. 2023. “Hemolysis during Cell Salvage from Look-Alike, Sound-Alike Wash Solutions: A Case Report.” Preprint, . https://doi.org/10.2139/ssrn.4593510
- Tarhio, Jorma, and Esko Ukkonen. 1993. “Approximate Boyer–Moore String Matching.” SIAM Journal on Computing 22 (2): 243–60. https://doi.org/10.1137/0222018
- Tavares Monteiro, Ana. n.d. “Reconsidering the Measurement of Proficiency in Pilot and Air Traffic Controller Radiotelephony Communication: From Construct Definition to Task Design.” PhD diss., Carleton University. https://doi.org/10.22215/etd/2019-13660
- Teakel, Julie. 1999. “What’s in a Name? Plenty of Confusion, Actually.” Nursing Standard 14 (5): 31–31. https://doi.org/10.7748/ns.14.5.31.s47
- Teplitsky, Benjamin. 1977. “Look-Alike and Sound-Alike Drugs.” Journal of Drug Issues 7 (1): 87–88. https://doi.org/10.1177/002204267700700108
- Teplitsky, Benjamin. 1978. “Look-Alike and Sound-Alike Drugs.” Journal of Drug Issues 8 (4): 443–45. https://doi.org/10.1177/002204267800800407
- Teplitsky, Benjamin. 1979a. “Look-Alike and Sound-Alike Drugs.” Journal of Drug Issues 9 (1): 105–6. https://doi.org/10.1177/002204267900900110
- Teplitsky, Benjamin. 1980. “Look-Alike and Sound-Alike Drugs.” Journal of Drug Issues 10 (3): 371–72. https://doi.org/10.1177/002204268001000308
- Teplitsky, Benjamin. 1981. “Look-Alike and Sound-Alike Drugs.” Journal of Drug Issues 11 (1): 141–42. https://doi.org/10.1177/002204268101100109
- Teplitsky, Benjamin. 1982. “Look-Alike and Sound-Alike Drugs.” Journal of Drug Issues 12 (4): 457–58. https://doi.org/10.1177/002204268201200411
- Teplitsky, Benjamin. 1984. “Look-Alike and Sound-Alike Drugs.” Journal of Drug Issues 14 (3): 593–94. https://doi.org/10.1177/002204268401400311
- Teplitsky, Benjamin. 1992. “Avoiding the Hazards of Look-Alike Drug Names.” NURSING 22 (1): 60–61. https://doi.org/10.1097/00152193-199201000-00017
- Teplitsky, Benjamin. 2001. “Avoiding the Hazards of Look-Alike Drug Names.” Nursing 31 (9): 56–57. https://doi.org/10.1097/00152193-200131090-00026
- Tesink, K., and R. Fox. 2005. A Uniform Resource Name (URN) Namespace for the Common Language Equipment Identifier (CLEI) Code. RFC Editor. https://doi.org/10.17487/rfc4152
- Tessman, D. 2005. A Uniform Resource Name (URN) Namespace for Federated Content. RFC Editor. https://doi.org/10.17487/rfc4198
- Tfeplitsky, Benjamin. 1986. “Look-Alike and Sound-Alike Drug Names.” Journal of Drug Issues 16 (3): 463–463. https://doi.org/10.1177/002204268601600311
- Thomas, A. 2017. URN Namespace for IEEE. RFC Editor. https://doi.org/10.17487/rfc8069
- Thouvenin, Florent, Daniel Gerber, and Tilmann Altwicker. 2025. “Trademark Opposition Proceedings in Switzerland: An Empirical Study of Legal Reasoning.” Preprint, . https://doi.org/10.2139/ssrn.5282554
- Tidman, Melanie M. 2022. “Causesof Medication Error in Nursing.” Research Review. https://doi.org/10.52845/jmrhs/2022-5-1-7
- Tisdale, Jim E. 1986. “Justifying a Pediatric Critical-Care Satellite Pharmacy by Medication-Error Reporting.” American Journal of Health-System Pharmacy 43 (2): 368–71. https://doi.org/10.1093/ajhp/43.2.368
- Tracked Changes. Earth-Moving Machinery. Product Identification Numbering System. n.d. BSI British Standards. https://doi.org/10.3403/30432432
- “Trade-Mark Registration. Similarity of Sound. Possibility of Confusion in Radio Advertising.” 1938. Virginia Law Review 24 (8): 930. https://doi.org/10.2307/1068099
- “Tradename. Company. Similarity of Name. Right of Individual to Trade in His Own Name. Transfer to Company of Use of Individual Name.” 1912. Virginia Law Register 18 (4): 308. https://doi.org/10.2307/1104893
- Trbovich, P. L., and Sylvia Hyland. 2016. “Responding to the Challenge of Look-Alike, Sound-Alike Drug Names.” BMJ Quality & Safety 26 (5): 357–59. https://doi.org/10.1136/bmjqs-2016-005629
- Treeratpituk, Pucktada, and C. Lee Giles. 2021. “Name-Ethnicity Classification and Ethnicity-Sensitive Name Matching.” Proceedings of the AAAI Conference on Artificial Intelligence 26 (1): 1141–47. https://doi.org/10.1609/aaai.v26i1.8324
- Trpkoska, Dragica, and Natasha Vukikjevikj. 2022. “Practical Examples of Implementation of the Unique Device Identifier (UDI) Requirements for Medical Devices.” Macedonian Pharmaceutical Bulletin 68 (03): 79–80. https://doi.org/10.33320/maced.pharm.bull.2022.68.03.035
- Tseng, Chun-Hsiung, and Yung-Hui Chen. 2016. “Evaluate the Performance of K-Means Distance Functions with String Edit Distance and the Open Directory Project.” In Applied System Innovation. CRC Press. https://doi.org/10.1201/b21811-36
- Tseng, Hsiang-Yi, Chen-Fan Wen, Ya-Lun Lee, Kee-Ching Jeng, and Pei-Liang Chen. 2016. “Dispensing Errors from Look-Alike Drug Trade Names.” European Journal of Hospital Pharmacy 25 (2): 96–99. https://doi.org/10.1136/ejhpharm-2016-001019
- Tsuruoka, Yoshimasa, John McNaught, Jun’i;chi Tsujii, and Sophia Ananiadou. 2007. “Learning String Similarity Measures for Gene/protein Name Dictionary Look-up Using Logistic Regression.” Bioinformatics 23 (20): 2768–74. https://doi.org/10.1093/bioinformatics/btm393
- Tullis, Thomas S. 1981. “An Evaluation of Alphanumeric, Graphic, and Color Information Displays.” Human Factors: The Journal of the Human Factors and Ergonomics Society 23 (5): 541–50. https://doi.org/10.1177/001872088102300504
- Tullis, Thomas S. 1983. “The Formatting of Alphanumeric Displays: A Review and Analysis.” Human Factors: The Journal of the Human Factors and Ergonomics Society 25 (6): 657–82. https://doi.org/10.1177/001872088302500604
- Tumuhaise, Alex, and Jane Frances Namukwaya. 2024. “Attitude and Practices of Health Workers towards Medication Error Reporting at Kampala Hospital, Kampala District. a Cross –Sectional Study.” Journal of Pharmacology and Drug Safety Africa 1 (8): 12. https://doi.org/10.51168/s6cnvm69
- Tumuhaise, Alex, and Jane Frances Namukwaya. 2026. “Knowledge of Health Workers towards Medication Error Reporting at Kampala Hospital, Kampala District. a Cross–sectional Study.” Journal of Pharmacology and Drug Safety Africa 3 (2): 7. https://doi.org/10.51168/vqh17x37
- Tuncal, Arif. 2026. “Cognitive and Linguistic Challenges in Controller–Pilot Communication.” Human Factors in Aviation and Aerospace 3 (1): 17–33. https://doi.org/10.26650/hfaa.2026.1867276
- U.S. Department of the Air Force and U.S. Department of the Navy. 1994. Designating and Naming Defense Military Aerospace Vehicles. Joint Instruction 16-401; NAVAIRINST 8800.3A. U.S. Department of the Air Force. https://irp.fas.org/doddir/usaf/16-401.htm
- U.S. Food and Drug Administration. n.d. “Phonetic and Orthographic Computer Analysis (POCA) Program.” U.S. Food and Drug Administration. Accessed October 24, 2026. https://www.fda.gov/drugs/resources-drugs/phonetic-and-orthographic-computer-analysis-poca-program
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER). 2020. Best Practices in Developing Proprietary Names for Human Prescription Drug Products: Guidance for Industry. U.S. Department of Health and Human Services, Food and Drug Administration. https://www.fda.gov/media/88496/download
- Ukkonen, Esko. 1993. “Approximate String-Matching and the q-Gram Distance.” In Sequences II. Springer New York. https://doi.org/10.1007/978-1-4613-9323-8_22
- “The Unified Numbering System (UNS) for Metals and Alloys.” 2010. In The History of Stainless Steel. ASM International. https://doi.org/10.31399/asm.tb.hss.t52790235
- Uniform Dash Numbering System for O-Rings. 1970. https://doi.org/10.4271/arp568b
- Unique Digital Media Identifier (C4 ID). 2017. https://doi.org/10.5594/smpte.st2114.2017
- Unique Material Identifier (UMID). 2011. https://doi.org/10.5594/smpte.st330.2011
- Uryupina, Olga. 2004. “Evaluating Name-Matching for Coreference Resolution.” In Proceedings of the Language Resources and Evaluation Conference. European Language Resources Association (ELRA). https://doi.org/10.63317/4ewz8ao8chxi
- Vallabhaneni, Pramodh, Aamina Ahmad, Rachel Issac, Nicola Fitchett, and Bhavee Patel. 2023. “28 Paediatric Medication Error Prevention (PMEP) a Tripartite Alliance Working Together.” Archives of Disease in Childhood 108 (6): A9.3-A10. https://doi.org/10.1136/archdischild-2023-esdppp.28
- Vallioor, Vishali Kirthi, Jasenka Rakas, Jimmy Krozel, Peter F. Kostiuk, and Michael T. Mohen. 2025. “Air Traffic Controller-Pilot Speech Analysis: A Bayesian Statistical Framework for Future Aviation Systems Safety.” In AIAA Aviation Forum and Ascend 2025. AIAA 2025-3672. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2025-3672
- van Nes, Floris L. 1988. “The Legibility of Visual Display Texts.” In Human-Computer Interaction. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-73402-1_2
- Van Nes, Floris L., and Herman Bouma. 1980. “On the Legibility of Segmented Numerals.” Human Factors: The Journal of the Human Factors and Ergonomics Society 22 (4): 463–74. https://doi.org/10.1177/001872088002200407
- Vaughan, W. S., Robert A. Glass, and Jerome Williams. 1982. “Determinants Display Legibility in Dark, Turbid Waters.” Human Factors: The Journal of the Human Factors and Ergonomics Society 24 (2): 193–201. https://doi.org/10.1177/001872088202400205
- Vázquez, Eder Vázquez, Yulia Ledeneva, and René Arnulfo García-Hernández. 2020. “Combination of Similarity Measures Based on Symbolic Regression for Confusing Drug Names Identification.” Journal of Intelligent & Fuzzy Systems 39 (2): 2093–2103. https://doi.org/10.3233/jifs-179875
- Vicory, Arthur C. 1968. A Brief History of Aircraft Identification Training. Defense Technical Information Center. https://doi.org/10.21236/ad0676791
- Vinod-prasad, P. 2016. “A Novel Algorithm for String Matching with Mismatches.” In International Conference on Pattern Recognition Applications and Methods. https://doi.org/10.5220/0005752006380644
- Wackerow, J. 2024. A URN Namespace for the Data Documentation Initiative (DDI). RFC Editor. https://doi.org/10.17487/rfc9517
- Walsh, Johnny. 2023. “Confusion Mélange: A Call to Revise the Law on Trademark Infringement, Initial Interest Confusion, and Digital Marketing.” Indiana Law Review 57 (1): 281–311. https://doi.org/10.18060/27650
- Wang, Hailiang. 2016. “Effects of Task- and Environment-Related Interventions on the Performance in Differentiation and Visual Search of Look-Alike Drug Names Using Simulation and Eye-Tracking Techniques.” PhD diss.. https://doi.org/10.5353/th_991026390029703414
- Wang, Xiaoren. 2024. “Should We Worry about Color Depletion? An Empirical Study of USPTO Single-Color Trademark Registrations.” Preprint, . https://doi.org/10.2139/ssrn.5032804
- Wang, Hailiang, Da Tao, and Mian Yan. 2021. “Effects of Text Enhancement on Reduction of Look-Alike Drug Name Confusion: A Systematic Review and Meta-Analysis.” Quality Management in Health Care 30 (4): 233–43. https://doi.org/10.1097/qmh.0000000000000303
- Ward, Nicholas J., Andrew Parkes, and Peter R. Crone. 1995. “Effect of Background Scene Complexity and Field Dependence on the Legibility of Head-Up Displays for Automotive Applications.” Human Factors: The Journal of the Human Factors and Ergonomics Society 37 (4): 735–45. https://doi.org/10.1518/001872095778995625
- Weant, Kyle A., Aaron M. Cook, and John A. Armitstead. 2007. “Medication-Error Reporting and Pharmacy Resident Experience during Implementation of Computerized Prescriber Order Entry.” American Journal of Health-System Pharmacy 64 (5): 526–30. https://doi.org/10.2146/ajhp060001
- Weant, Kyle A., Roger L. Humphries, Kimberly Hite, and John A. Armitstead. 2010. “Effect of Emergency Medicine Pharmacists on Medication-Error Reporting in an Emergency Department.” American Journal of Health-System Pharmacy 67 (21): 1851–55. https://doi.org/10.2146/090579
- Weisenberger, Janet M. 1996. “Stimulus Factors in Perceptual Confusability of Tactile Speech Stimuli.” Journal of the Acoustical Society of America 100 (4_Supplement): 2772–2772. https://doi.org/10.1121/1.416399
- Weitz, Joseph. 1960. “A Study of Trade Name Confusion.” Journal of Marketing 25 (2): 54. https://doi.org/10.2307/1248612
- Wertheimer, Albert. 2014. “Medication Error Prevention.” Journal of Pharmaceutical Health Services Research 5 (3): 147–48. https://doi.org/10.1111/jphs.12064
- Westbury, Chris, and Michelle Yang. 2024. “Orthographic Uncertainty: An Entropy-Based Measure of Word Form Typicality.” Mental Lexicon 19 (3): 439–95. https://doi.org/10.1075/ml.24006.wes
- Wetzel, Jake, and Angie Hernandez. 2010. “Effects of Display Media Type, Ambient Lighting, Viewing Distance, Viewing Offset, Object Type, and Object Size on Large-Screen Display Legibility.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 54 (25): 2155–59. https://doi.org/10.1177/154193121005402507
- Williams, Charles M. 1967. “Legibility of Numbers as a Function of Contrast and Illumination.” Human Factors: The Journal of the Human Factors and Ergonomics Society 9 (5): 455–60. https://doi.org/10.1177/001872086700900509
- Williamson, Sheena. 2009. “Reporting Medication Errors and near Misses.” In Medication Safety. Cambridge University Press. https://doi.org/10.1017/cbo9780511642272.011
- Winter, Felix, Nysret Musliu, and Peter Stuckey. 2020. “Explaining Propagators for String Edit Distance Constraints.” Proceedings of the AAAI Conference on Artificial Intelligence 34 (02): 1676–83. https://doi.org/10.1609/aaai.v34i02.5530
- Wold, J. 2017. Advertising Digital Identifier (Ad-ID) URN Namespace Definition. RFC Editor. https://doi.org/10.17487/rfc8107
- Wolf, Catherine G. 1982. “Effects of Color on Legibility of Displayed Text.” Proceedings of the Human Factors Society Annual Meeting 26 (6): 595–595. https://doi.org/10.1177/154193128202600625
- Wolff, Peter. 1971. “Mirror-Image Confusability in Adults.” Journal of Experimental Psychology 91 (2): 268–72. https://doi.org/10.1037/h0031796
- Wong, Zoie Shui Yee. 2014. “Statistical Classification of Drug Incidents Due to Look-Alike Sound-Alike Mix-Ups.” Health Informatics Journal 22 (2): 276–92. https://doi.org/10.1177/1460458214555040
- Xiang, Zheng, Wei Jun Pan, and Yu Tang. 2012. “Application of Controller Pilot Data Link Communication in the Training for Air Traffic Controller.” Advanced materials research 616-618: 2162–65. https://doi.org/10.4028/www.scientific.net/amr.616-618.2162
- Yan, Ding, Paolo Mairano, and Séverine Casalis. 2026. “Towards a Quantifiable Measure of Orthographic Congruence between Two Languages.” Behavior Research Methods 58 (6): 152. https://doi.org/10.3758/s13428-026-02981-7
- Yanqing, wan, Xiaolei Zhang, Siyu Wu, and Jingrui Ren. 2025. “Impacts of Radiotelephony Language on Auditory Attentional Blink in Approach Controllers: An EEG Experiment for Mitigating ‘Errors-Omissions-Deviations’ Safety Threats in Aviation.” Preprint, . https://doi.org/10.2139/ssrn.5607163
- Yash, K. 2020. “Similarity of Trademarks and Confusion of the Customer.” “International Humanitarian University Herald. Jurisprudence”, no. 46: 129–33. https://doi.org/10.32841/2307-1745.2020.46.27
- Yencken, Lars, and Timothy Baldwin. 2008. “Measuring and Predicting Orthographic Associations: Modelling the Similarity of Japanese Kanji.” In Proceedings of the 22nd International Conference on Computational Linguistics - COLING ‘08, vol. 1. Association for Computational Linguistics. https://doi.org/10.3115/1599081.1599212
- Yencken Lars and Baldwin Timothy. 2008. “Orthographic Similarity Search for Dictionary Lookup of Japanese Words.” In Frontiers in Artificial Intelligence and Applications. IOS Press. https://doi.org/10.3233/978-1-58603-891-5-343
- Yoneyama, Kiyoko. 2001. “Phonological Neighborhoods and Phonetic Similarity in Spoken Word Recognition.” Journal of the Acoustical Society of America 110 (5_Supplement): 2739–2739. https://doi.org/10.1121/1.4777515
- Yoo, Keat Jiu, and Fazlollah Keshavarzi. 2020. “Barriers and Enhancers of Medication Error Reporting among Hospital Pharmacists, a Qualitative Exploration.” Current Trends in Biotechnology and Pharmacy 14 (5): 64–71. https://doi.org/10.5530/ctbp.2020.4s.7
- Yoshikawa, Kodai, Hayato Kizaki, Shungo Imai, and Satoko Hori. 2023. “Influence of Voiced and Semi-Voiced Sounds on the Subjective Similarity of Different Drug Names: A Cognitive Psychological Experiment.” Biological and Pharmaceutical Bulletin 46 (11): 1630–34. https://doi.org/10.1248/bpb.b23-00396
- Young, Stephen L., Kenneth R. Laughery, and Marilyn Bell. 1992. “Effects of Two Type Density Characteristics on the Legibility of Print.” Proceedings of the Human Factors Society Annual Meeting 36 (5): 504–8. https://doi.org/10.1177/154193129203600507
- Yuan, Jiahong, and Chilin Shih. 2004. “Confusability of Chinese Intonation.” In Speech Prosody 2004. ISCA. https://doi.org/10.21437/speechprosody.2004-31
- Yuan, Peisen, Haoyun Wang, Jianghua Che, Shougang Ren, Huanliang Xu, and Dechang Pi. 2014. “Approximate String Similarity Join Using Hashing Techniques under Edit Distance Constraints.” Journal of Software 9 (10). https://doi.org/10.4304/jsw.9.10.2721-2731
- Yuniar, Dwi Candra, Herlina Febiyanti, Minulya Eska Nugraha, and Shabrina Ramadhani. 2024. “Design of Android-Based Interactive E-Module Teaching Media for Aviation Radiotelephony Course.” Didaktika: Jurnal Kependidikan 13 (001 Desemb): 293–304. https://doi.org/10.58230/27454312.1295
- Zacher, Jessica M., Francesca E. Cunningham, Xinhua Zhao, et al. 2018. “Detection of Potential Look-Alike/sound-Alike Medication Errors Using Veterans Affairs Administrative Databases.” American Journal of Health-System Pharmacy 75 (19): 1460–66. https://doi.org/10.2146/ajhp170703
- Zaijul, Ummu, Mirfaidah Nadjamuddin, and Miftahul Jannah. 2026. “Implementasi Penyimpanan Obat High Alert Kategori Lasa (Look Alike Sound Alike).” JOURNAL OF Qualitative Health Research & Case Studies Reports 6 (1): 243–51. https://doi.org/10.56922/quilt.v6i1.2215
- Zaini, Muhammad, Nazhipah Isnani, Siti Nur Hikmah, and Muliyani Muliyani. 2026. “Penanganan Obat Look Alike Sound Alike (LASA) Dalam Praktik Kefarmasian: Tinjauan Literatur Naratif.” Jurnal Kajian Ilmiah Kesehatan dan Teknologi 7 (2): 276–84. https://doi.org/10.52674/jkikt.v7i2.304
- Zeisel, Hans, and David Kaye. 1997. “Trademark Surveys: Confusion.” In Prove It with Figures. Springer New York. https://doi.org/10.1007/978-1-4612-1824-1_11
- Zellmer, William A. 1993. “Medication Error versus Medication Misadventure—What’s in a Name?” American Journal of Health-System Pharmacy 50 (2): 315–18. https://doi.org/10.1093/ajhp/50.2.315
- Žgank, Andrej, and Z. Kacic. 2012. “Predicting the Acoustic Confusability between Words for a Speech Recognition System Using Levenshtein Distance.” Elektronika ir Elektrotechnika 18 (8): 81–84. https://doi.org/10.5755/j01.eee.18.8.2628
- Zhang, Huihui, Zhengtao Yu, Longhua Shen, Jianyi Guo, and Xudong Hong. 2014. “Naxi Sentence Similarity Calculation Based on Improved Chunking Edit-Distance.” International Journal of Wireless and Mobile Computing 7 (1): 48. https://doi.org/10.1504/ijwmc.2014.058872
- Zhang, Haoyu, and Qin Zhang. 2020. “MinSearch: An Efficient Algorithm for Similarity Search under Edit Distance.” In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. ACM. https://doi.org/10.1145/3394486.3403099
- Zhou, Xueqing. 2024a. “Determination of Infringement of Trademark Confusion.” Journal of Economics and Law 1 (6): 116–24. https://doi.org/10.62517/jel.202414616
- Zhou, Yizi. 2024b. “Identification of Likelihood of Confusion in Trademark Infringement Cases.” Journal of Economics and Law 1 (5): 49–58. https://doi.org/10.62517/jel.202414507
- Zhou, Jason, Adam F. Osth, and Philip L. Smith. 2023. “Intrusion Errors in Source Memory Are Affected by Orthographic but Not Semantic Similarity.” Preprint, . https://doi.org/10.31234/osf.io/6tfmc
- Zhu, Shouxi, and Wenlai Ma. 2015. “A Countermeasures Study on Level Bust Caused by Radiotelephony Communication.” Journal of Traffic and Logistics Engineering 3 (1). https://doi.org/10.12720/jtle.3.1.41-44
- Zhu, Eliza, Patrick Gary Rose, Robert Seabury, et al. 2025. “Assessment of Erroneous Allergy Documentation of Amoxapine with Look Alike Sound Alike Drugs.” Hospital Pharmacy 61 (3): 217–19. https://doi.org/10.1177/00185787251390790
- Zineddin, Abdulilah Z., Philip M. Garvey, Richard A. Carlson, and Martin T. Pietrucha. 2003. “Effects of Practice on Font Legibility.” Proceedings of the Human Factors and Ergonomics Society Annual Meeting 47 (13): 1717–20. https://doi.org/10.1177/154193120304701326
- Zobel, Justin, and Philip Dart. 1996. “Phonetic String Matching: Lessons from Information Retrieval.” In Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR ‘96. ACM Press. https://doi.org/10.1145/243199.243258
- Zuluaga-Gomez, Juan, Karel Veselý, Alexander Blatt, et al. 2020. “Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications.” In 8th OpenSky Symposium 2020. MDPI. https://doi.org/10.3390/proceedings2020059014
- Zwaga, Harm J. 1979. “Legibility of Public Information Symbols.” Proceedings of the Human Factors Society Annual Meeting 23 (1): 448–448. https://doi.org/10.1177/1071181379023001112
- 김민정 and SeongSook Jun. 2016. “Impact Factors of Safety Climate and Work Environment Influencing Barrier to Medication Administration Error Reporting.” Global Health and Nursing (글로벌 건강과 간호) 6 (1): 1–10. https://doi.org/10.35144/ghn.2016.6.1.1
Secondary Sources
- Ams, Astm A01 / Sae. 2025. Metals & Alloys in the Unified Numbering System, 15th Edition. SAE International eBooks. https://doi.org/10.4271/9781468609493
- Bowker, Geoffrey C., Susan Leigh Star, and Sorting things out. 1999. Sorting Things Out: Classification and Its Consequences. MIT Press. https://openlibrary.org/works/OL20989007W
- Cushing, Steven, and Fatal words. 1994. Fatal Words: Communication Clashes and Aircraft Crashes. University of Chicago Press. https://openlibrary.org/works/OL3931281W
- Fhima, Ilanah Simon. 2024. Likelihood of Confusion. Edward Elgar Publishing. https://doi.org/10.4337/9781800886933.likelihood.of.confusion
- Identity Crisis: An Examination of the Costs and Benefits of a Unique Patient Identifier for the U.S. Health Care System. 2008. RAND Corporation. https://doi.org/10.7249/mg753
- Laustsen, Rasmus Dalgaard. 2020. The Average Consumer in Confusion-Based Disputes in European Trademark Law and Similar Fictions. Springer International Publishing. https://doi.org/10.1007/978-3-030-26350-8
- Metals and Alloys in the Unified Numbering System, 13th Edition. 2017. SAE International eBooks. https://doi.org/10.4271/0768084210
- Norman, Donald A., and The psychology of everyday things. 1988. The Psychology of Everyday Things. Basic Books. https://openlibrary.org/works/OL1879162W
- Reason, James. 1990. Human Error. Cambridge University Press. https://openlibrary.org/works/OL9006915W
- Room, Adrian. 2013. Dictionary of Confusable Words. Routledge. https://doi.org/10.4324/9780203058756
- Schweizer, Markus. 2005a. Consumer Confusion im Handel. Deutscher Universitätsverlag. https://doi.org/10.1007/978-3-322-81977-2
- ST 330:2004: Unique Material Identifier (UMID). 2004. The Society of Motion Picture and Television Engineers eBooks. https://doi.org/10.5594/s9781614824695
- Supapaan, Teeraporn Sadira. 2026. Medication Safety in Look-Alike Sound-Alike (LASA) Drugs. IGI Global. https://doi.org/10.4018/979-8-3373-5478-1
- World Bank Group. 2016. Implementing a Unique Business Identifier in Government: Guidance Note for Practitioners and Nine Country Case Studies. World Bank, Washington, DC. https://doi.org/10.1596/k8618
Commercial Sources
- Active Aeroelastic Wing flight research vehicle receives X-53 designation. 2006. “Air Force Research Laboratory, 11 December.” https://web.archive.org/web/20110605105552/http://www.wpafb.af.mil/news/story.asp?id=123035661
- Gelzer, Christian. 2018. “F/A-18 Active Aeroelastic Wing.” National Aeronautics and Space Administration, August 17. https://www.nasa.gov/aeronautics/x-53/
Tertiary Sources
- “1962 United States Tri-Service Aircraft Designation System.” 2026. Wikipedia. Last modified July 14, at 18:40 (UTC). https://en.wikipedia.org/w/index.php?title=1962_United_States_Tri-Service_aircraft_designation_system&oldid=1364134610
- “Air Force Research Laboratory.” 2026. Wikipedia. Last modified August 11, at 10:22 (UTC). https://en.wikipedia.org/w/index.php?title=Air_Force_Research_Laboratory&oldid=1368835347
- “Bell XV-15.” 2026. Wikipedia. Last modified June 24, at 15:16 (UTC). https://en.wikipedia.org/w/index.php?title=Bell_XV-15&oldid=1360932163
- “Boeing B-52 Stratofortress.” 2026. Wikipedia. Last modified August 29, at 01:06 (UTC). https://en.wikipedia.org/w/index.php?title=Boeing_B-52_Stratofortress&oldid=1371872296
- “Boeing C-17 Globemaster III.” 2026. Wikipedia. Last modified September 1, at 19:35 (UTC). https://en.wikipedia.org/w/index.php?title=Boeing_C-17_Globemaster_III&oldid=1372678410
- “Boeing X-53 Active Aeroelastic Wing.” 2026. Wikipedia. Last modified August 27, at 11:23 (UTC). https://en.wikipedia.org/w/index.php?title=Boeing_X-53_Active_Aeroelastic_Wing&oldid=1371611911
- “General Dynamics F-16 Fighting Falcon.” 2026. Wikipedia. Last modified September 1, at 23:46 (UTC). https://en.wikipedia.org/w/index.php?title=General_Dynamics_F-16_Fighting_Falcon&oldid=1372719234
- “Levenshtein Distance.” 2026. Wikipedia. Last modified August 30, at 12:24 (UTC). https://en.wikipedia.org/w/index.php?title=Levenshtein_distance&oldid=1372120590
- “List of X-Planes.” 2026. Wikipedia. Last modified June 16, at 19:44 (UTC). https://en.wikipedia.org/w/index.php?title=List_of_X-planes&oldid=1359712029
- “Lockheed Martin F-35 Lightning II.” 2026. Wikipedia. Last modified September 4, at 08:29 (UTC). https://en.wikipedia.org/w/index.php?title=Lockheed_Martin_F-35_Lightning_II&oldid=1373151795
- “Lockheed Martin X-35.” 2026. Wikipedia. Last modified July 25, at 06:18 (UTC). https://en.wikipedia.org/w/index.php?title=Lockheed_Martin_X-35&oldid=1365924511
- “NATO Phonetic Alphabet.” 2026. Wikipedia. Last modified August 27, at 00:09 (UTC). https://en.wikipedia.org/w/index.php?title=NATO_phonetic_alphabet&oldid=1371526304
- “Northrop F-20 Tigershark.” 2026. Wikipedia. Last modified August 19, at 03:53 (UTC). https://en.wikipedia.org/w/index.php?title=Northrop_F-20_Tigershark&oldid=1370106485
- Parsch, Andreas. 2000. “Allocation of Official Aerospace Vehicle MDS Designations.” Designation-Systems.Net. https://www.designation-systems.net/usmilav/mdsallocation.html
- Parsch, Andreas. 2002a. “Non-Standard DOD Aircraft Designations.” Designation-Systems.Net. https://www.designation-systems.net/usmilav/nonstandard-mds.html
- Parsch, Andreas. 2002b. ““Missing” USAF/DOD Aircraft Designations.” Designation-Systems.Net. https://www.designation-systems.net/usmilav/missing-mds.html
- U.S. Department of the Air Force, U.S. Department of the Army, and U.S. Department of the Navy. 1997. Designating and Naming Defense Military Aerospace Vehicles. AFJI 16-401, AR 70-50, NAVAIRINST 8800.3A. U.S. Department of the Air Force. https://www.designation-systems.net/usmilav/afji16-401(1997).pdf
- U.S. Department of the Air Force, U.S. Department of the Army, and U.S. Department of the Navy. 2005. Designating and Naming Defense Military Aerospace Vehicles. AFI 16-401(I), AR 70-50, NAVAIRINST 13100.16. U.S. Department of the Air Force. https://www.designation-systems.net/usmilav/afi16-401(i).pdf
- U.S. Department of the Air Force, U.S. Department of the Army, and U.S. Department of the Navy. 2014. Designating and Naming Defense Military Aerospace Vehicles. AFI 16-401, AR 70-50, NAVAIRINST 13100.16. U.S. Department of the Air Force. https://www.designation-systems.net/usmilav/afi16-401(2014).pdf
- U.S. Department of the Air Force, U.S. Department of the Army, and U.S. Department of the Navy. 2020. Designating and Naming Defense Military Aerospace Vehicles. DAFI 16-401, AR 70-50, NAVAIRINST 13100.16. U.S. Department of the Air Force. https://www.designation-systems.net/usmilav/afi16-401.pdf
- “United States Department of Defense Aerospace Vehicle Designation.” 2025. Wikipedia. Last modified December 28, at 09:20 (UTC). https://en.wikipedia.org/w/index.php?title=United_States_Department_of_Defense_aerospace_vehicle_designation&oldid=1329864644
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- Sechter, Brendan. 2025. “X-Planes: Ryan X-13 Vertijet.” Brendan A R Sechter’s Development Blog, October 19. https://sgeos.github.io/aerospace/history/engineering/2025/10/19/x_planes_ryan_x13.html
- Sechter, Brendan. 2025. “X-Planes: Bell X-14.” Brendan A R Sechter’s Development Blog, October 20. https://sgeos.github.io/aerospace/history/engineering/2025/10/20/x_planes_bell_x14.html
- Sechter, Brendan. 2025. “X-Planes: North American X-15.” Brendan A R Sechter’s Development Blog, October 21. https://sgeos.github.io/aerospace/history/engineering/2025/10/21/x_planes_north_american_x15.html
- Sechter, Brendan. 2025. “X-Planes: Bell X-16.” Brendan A R Sechter’s Development Blog, October 22. https://sgeos.github.io/aerospace/history/engineering/2025/10/22/x_planes_bell_x16.html
- Sechter, Brendan. 2025. “X-Planes: Lockheed X-17.” Brendan A R Sechter’s Development Blog, October 23. https://sgeos.github.io/aerospace/history/engineering/2025/10/23/x_planes_lockheed_x17.html
- Sechter, Brendan. 2025. “X-Planes: Hiller X-18.” Brendan A R Sechter’s Development Blog, October 24. https://sgeos.github.io/aerospace/history/engineering/2025/10/24/x_planes_hiller_x18.html
- Sechter, Brendan. 2025. “X-Planes: Curtiss-Wright X-19.” Brendan A R Sechter’s Development Blog, October 25. https://sgeos.github.io/aerospace/history/engineering/2025/10/25/x_planes_curtiss_wright_x19.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-20 Dyna-Soar.” Brendan A R Sechter’s Development Blog, October 26. https://sgeos.github.io/aerospace/history/engineering/2025/10/26/x_planes_boeing_x20.html
- Sechter, Brendan. 2025. “X-Planes: Northrop X-21.” Brendan A R Sechter’s Development Blog, October 27. https://sgeos.github.io/aerospace/history/engineering/2025/10/27/x_planes_northrop_x21.html
- Sechter, Brendan. 2025. “X-Planes: Bell X-22.” Brendan A R Sechter’s Development Blog, October 28. https://sgeos.github.io/aerospace/history/engineering/2025/10/28/x_planes_bell_x22.html
- Sechter, Brendan. 2025. “X-Planes: Martin Marietta X-23 PRIME and a Contested Assignment.” Brendan A R Sechter’s Development Blog, October 29. https://sgeos.github.io/aerospace/history/engineering/2025/10/29/x_planes_martin_marietta_x23.html
- Sechter, Brendan. 2025. “X-Planes: Martin Marietta X-24.” Brendan A R Sechter’s Development Blog, October 30. https://sgeos.github.io/aerospace/history/engineering/2025/10/30/x_planes_martin_marietta_x24.html
- Sechter, Brendan. 2025. “X-Planes: Bensen X-25.” Brendan A R Sechter’s Development Blog, October 31. https://sgeos.github.io/aerospace/history/engineering/2025/10/31/x_planes_bensen_x25.html
- Sechter, Brendan. 2025. “X-Planes: Schweizer X-26 Frigate.” Brendan A R Sechter’s Development Blog, November 1. https://sgeos.github.io/aerospace/history/engineering/2025/11/01/x_planes_schweizer_x26.html
- Sechter, Brendan. 2025. “X-Planes: Lockheed X-27.” Brendan A R Sechter’s Development Blog, November 2. https://sgeos.github.io/aerospace/history/engineering/2025/11/02/x_planes_lockheed_x27.html
- Sechter, Brendan. 2025. “X-Planes: Osprey X-28 Sea Skimmer.” Brendan A R Sechter’s Development Blog, November 3. https://sgeos.github.io/aerospace/history/engineering/2025/11/03/x_planes_osprey_x28.html
- Sechter, Brendan. 2025. “X-Planes: Grumman X-29.” Brendan A R Sechter’s Development Blog, November 4. https://sgeos.github.io/aerospace/history/engineering/2025/11/04/x_planes_grumman_x29.html
- Sechter, Brendan. 2025. “X-Planes: Rockwell X-30 and the National Aero-Space Plane.” Brendan A R Sechter’s Development Blog, November 5. https://sgeos.github.io/aerospace/history/engineering/2025/11/05/x_planes_rockwell_x30.html
- Sechter, Brendan. 2025. “X-Planes: Rockwell-MBB X-31.” Brendan A R Sechter’s Development Blog, November 6. https://sgeos.github.io/aerospace/history/engineering/2025/11/06/x_planes_rockwell_mbb_x31.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-32.” Brendan A R Sechter’s Development Blog, November 7. https://sgeos.github.io/aerospace/history/engineering/2025/11/07/x_planes_boeing_x32.html
- Sechter, Brendan. 2025. “X-Planes: Lockheed Martin X-33.” Brendan A R Sechter’s Development Blog, November 8. https://sgeos.github.io/aerospace/history/engineering/2025/11/08/x_planes_lockheed_martin_x33.html
- Sechter, Brendan. 2025. “X-Planes: Orbital Sciences X-34.” Brendan A R Sechter’s Development Blog, November 9. https://sgeos.github.io/aerospace/history/engineering/2025/11/09/x_planes_orbital_sciences_x34.html
- Sechter, Brendan. 2025. “X-Planes: Lockheed Martin X-35.” Brendan A R Sechter’s Development Blog, November 10. https://sgeos.github.io/aerospace/history/engineering/2025/11/10/x_planes_lockheed_martin_x35.html
- Sechter, Brendan. 2025. “X-Planes: McDonnell Douglas X-36.” Brendan A R Sechter’s Development Blog, November 11. https://sgeos.github.io/aerospace/history/engineering/2025/11/11/x_planes_mcdonnell_douglas_x36.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-37.” Brendan A R Sechter’s Development Blog, November 12. https://sgeos.github.io/aerospace/history/engineering/2025/11/12/x_planes_boeing_x37.html
- Sechter, Brendan. 2025. “X-Planes: Scaled Composites X-38.” Brendan A R Sechter’s Development Blog, November 13. https://sgeos.github.io/aerospace/history/engineering/2025/11/13/x_planes_scaled_composites_x38.html
- Sechter, Brendan. 2025. “X-Planes: X-39, Reserved but Never Assigned.” Brendan A R Sechter’s Development Blog, November 14. https://sgeos.github.io/aerospace/history/engineering/2025/11/14/x_planes_x39_reserved_never_assigned.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-40.” Brendan A R Sechter’s Development Blog, November 15. https://sgeos.github.io/aerospace/history/engineering/2025/11/15/x_planes_boeing_x40.html
- Sechter, Brendan. 2025. “X-Planes: X-41 Common Aero Vehicle.” Brendan A R Sechter’s Development Blog, November 16. https://sgeos.github.io/aerospace/history/engineering/2025/11/16/x_planes_x41_common_aero_vehicle.html
- Sechter, Brendan. 2025. “X-Planes: Orbital Sciences X-42.” Brendan A R Sechter’s Development Blog, November 17. https://sgeos.github.io/aerospace/history/engineering/2025/11/17/x_planes_orbital_sciences_x42.html
- Sechter, Brendan. 2025. “X-Planes: Micro-Craft X-43 Hyper-X.” Brendan A R Sechter’s Development Blog, November 18. https://sgeos.github.io/aerospace/history/engineering/2025/11/18/x_planes_micro_craft_x43_hyper_x.html
- Sechter, Brendan. 2025. “X-Planes: X-44, One Designation and Two Aircraft.” Brendan A R Sechter’s Development Blog, November 19. https://sgeos.github.io/aerospace/history/engineering/2025/11/19/x_planes_x44_one_designation_two_aircraft.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-45.” Brendan A R Sechter’s Development Blog, November 20. https://sgeos.github.io/aerospace/history/engineering/2025/11/20/x_planes_boeing_x45.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-46.” Brendan A R Sechter’s Development Blog, November 21. https://sgeos.github.io/aerospace/history/engineering/2025/11/21/x_planes_boeing_x46.html
- Sechter, Brendan. 2025. “X-Planes: Northrop Grumman X-47.” Brendan A R Sechter’s Development Blog, November 22. https://sgeos.github.io/aerospace/history/engineering/2025/11/22/x_planes_northrop_grumman_x47.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-48.” Brendan A R Sechter’s Development Blog, November 23. https://sgeos.github.io/aerospace/history/engineering/2025/11/23/x_planes_boeing_x48.html
- Sechter, Brendan. 2025. “X-Planes: Piasecki X-49 SpeedHawk.” Brendan A R Sechter’s Development Blog, November 24. https://sgeos.github.io/aerospace/history/engineering/2025/11/24/x_planes_piasecki_x49.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-50 Dragonfly.” Brendan A R Sechter’s Development Blog, November 25. https://sgeos.github.io/aerospace/history/engineering/2025/11/25/x_planes_boeing_x50.html
- Sechter, Brendan. 2025. “X-Planes: Boeing X-51 Waverider.” Brendan A R Sechter’s Development Blog, November 26. https://sgeos.github.io/aerospace/history/engineering/2025/11/26/x_planes_boeing_x51.html
Referenced by
- X-Planes: Synthesis and What the Designation Became 2025-12-16
- X-Planes: Bell Textron X-76 SPRINT 2025-12-15
- X-Planes: X-69 through X-75, the Leapfrogged Block 2025-12-14
- X-Planes: General Atomics X-68 LongShot 2025-12-13
- X-Planes: X-67, the Slot Taken by XQ-67A 2025-12-12
- X-Planes: Boeing X-66 2025-12-11
- X-Planes: Aurora Flight Sciences X-65 CRANE 2025-12-10
- X-Planes: Invocon X-64 2025-12-09
- X-Planes: ABL Space Systems X-63 2025-12-08
- X-Planes: Lockheed Martin X-62 VISTA 2025-12-07
- X-Planes: Dynetics X-61 Gremlins 2025-12-06
- X-Planes: Generation Orbit X-60 2025-12-05
- X-Planes: Lockheed Martin X-59 Quesst 2025-12-04
- X-Planes: X-58, the Slot Taken by XQ-58 2025-12-03
- X-Planes: ESAero X-57 Maxwell 2025-12-02
- X-Planes: Lockheed Martin X-56 2025-12-01
- X-Planes: Lockheed Martin X-55 ACCA 2025-11-30
- X-Planes: Gulfstream X-54 2025-11-29
- X-Planes: Boeing X-53 Active Aeroelastic Wing 2025-11-28