Uniform Word Research Articles

Minimum length word-representants of graph products

A graph G=(V,E) is said to be word-representable if a word w can be formed using the letters of the alphabet V such that for every pair of vertices x and y, x≠y, xy∈E if and only if x and y alternate in w. Gaetz and Ji have recently introduced the notion of minimum length word-representants for word-representable graphs. They have also determined the minimum possible length of the word-representants for certain classes of graphs, such as trees and cycles. It is known that Cartesian and rooted products preserve word-representability. Moreover, using occurrence-based functions, Broere constructed a uniform word representing the Cartesian product of G and Kn.In this paper, we study the minimum length of word-representants for Cartesian and rooted products using morphism and occurrence-based functions, respectively. Also, we solve an open problem posed by Broere in his master thesis. This problem asks to construct a word for the Cartesian product of two arbitrary word-representable graphs.

An explicit algorithm for normal forms in small overlap monoids

We describe a practical algorithm for computing normal forms for semigroups and monoids with finite presentations satisfying so-called small overlap conditions. Small overlap conditions are natural conditions on the relations in a presentation, which were introduced by J. H. Remmers and subsequently studied extensively by M. Kambites. Presentations satisfying these conditions are ubiquitous; Kambites showed that a randomly chosen finite presentation satisfies the C(4) condition with probability tending to 1 as the sum of the lengths of relation words tends to infinity. Kambites also showed that several key problems for finitely presented semigroups and monoids are tractable in C(4) monoids: the word problem is solvable in O(min⁡{|u|,|v|}) time in the size of the input words u and v; the uniform word problem for 〈A|R〉 is solvable in O(N2min⁡{|u|,|v|}) where N is the sum of the lengths of the words in R; and a normal form for any given word u can be found in O(|u|) time. Although Kambites' algorithm for solving the word problem in C(4) monoids is highly practical, it appears that the coefficients in the linear time algorithm for computing normal forms are too large in practice.In this paper, we present an algorithm for computing normal forms in C(4) monoids that has time complexity O(|u|2) for input word u, but where the coefficients are sufficiently small to allow for practical computation. Additionally, we show that the uniform word problem for small overlap monoids can be solved in O(Nmin⁡{|u|,|v|}) time.

Less is more in language production: an information-theoretic analysis of agrammatism in primary progressive aphasia.

Agrammatism is a disorder of language production characterized by short, simplified sentences, the omission of function words, an increased use of nouns over verbs and a higher use of heavy verbs. Despite observing these phenomena for decades, the accounts of agrammatism have not converged. Here, we propose and test the hypothesis that the lexical profile of agrammatism results from a process that opts for words with a lower frequency of occurrence to increase lexical information. Furthermore, we hypothesize that this process is a compensatory response to patients' core deficit in producing long, complex sentences. In this cross-sectional study, we analysed speech samples of patients with primary progressive aphasia (n = 100) and healthy speakers (n = 65) as they described a picture. The patient cohort included 34 individuals with the non-fluent variant, 41 with the logopenic variant and 25 with the semantic variant of primary progressive aphasia. We first analysed a large corpus of spoken language and found that the word types preferred by patients with agrammatism tend to have lower frequencies of occurrence than less preferred words. We then conducted a computational simulation to examine the impact of word frequency on lexical information as measured by entropy. We found that strings of words that exclude highly frequent words have a more uniform word distribution, thereby increasing lexical entropy. To test whether the lexical profile of agrammatism results from their inability to produce long sentences, we asked healthy speakers to produce short sentences during the picture description task. We found that, under this constrained condition, a similar lexical profile of agrammatism emerged in the short sentences of healthy individuals, including fewer function words, more nouns than verbs and more heavy verbs than light verbs. This lexical profile of short sentences resulted in their lower average word frequency than unconstrained sentences. We extended this finding by showing that, in general, shorter sentences get packaged with lower-frequency words as a basic property of efficient language production, evident in the language of healthy speakers and all primary progressive aphasia variants.

Generalizations of Sturmian sequences associated with N-continued fraction algorithms

Given a positive integer N and x∈[0,1]∖Q, an N-continued fraction expansion of x is defined analogously to the classical continued fraction expansion, but with the numerators being all equal to N. Inspired by Sturmian sequences, we introduce the N-continued fraction sequencesω(x,N) and ωˆ(x,N), which are related to the N-continued fraction expansion of x. They are infinite words over a two letter alphabet obtained as the limit of a directive sequence of certain substitutions, hence they are S-adic sequences. When N=1, we are in the case of the classical continued fraction algorithm, and obtain the well-known Sturmian sequences. We show that ω(x,N) and ωˆ(x,N) are C-balanced for some explicit values of C and compute their factor complexity function. We also obtain uniform word frequencies and deduce unique ergodicity of the associated subshifts. Finally, we provide a Farey-like map for N-continued fraction expansions, which provides an additive version of N-continued fractions, for which we prove ergodicity and give the invariant measure explicitly.

Representability of matroids by c-arrangements is undecidable

For a natural number c, a c-arrangement is an arrangement of dimension c subspaces satisfying the following condition: the sum of any subset of the subspaces has dimension a multiple of c. Matroids arising as normalized rank functions of c-arrangements are also known as multilinear matroids. We prove that it is algorithmically undecidable whether there exists a c such that a given matroid has a c-arrangement representation, or equivalently whether the matroid is multilinear. It follows that certain problems on network coding and secret sharing schemes are also undecidable. In the proof, we encode group presentations in frame matroids of rank three which we call generalized Dowling geometries: the construction is inspired by Dowling geometries of finite groups and by the von Staudt construction. The idea is to construct a reduction from the uniform word problem for finite groups to multilinear representability of matroids. The c-arrangement condition gives rise to some difficulties and their resolution is the main part of the paper.

Loop-checking and the uniform word problem for join-semilattices with an inflationary endomorphism

We solve in polynomial time two decision problems that occur in type checking when typings depend on universe level constraints.

NCERT CLASS 1 ENGLISH MARIGOLD: WORD LIST BY FREQUENCY

Studies in psycholinguistics, memory and psychological assessment of vocabulary and related measures may be greatly facilitated in our country through a uniform word list by frequency based on common textbook used across the country. Present study has used NCERT Class 1 English Textbook Marigold to analyse the word frequencies and prepare an academic word list for the researchers. Findings are discussed in terms of size of vocabulary, word length, word frequencies, word types, word tokens, and PoS tags unit wise and on the whole.

Sentiment analysis with covariate-assisted word embeddings

Sentiment analysis measures inclination of textual documents, aiming to extract and quantify their subjective sentiment polarity. In literature, most sentiment analysis methods first numericalize textual documents through certain word embeddings framework, and then formulate sentiment analysis as an ordinal regression or classification task. Yet it is often ignored that different people may have different preference of wording, and thus a uniform word embeddings often leads to suboptimal performance. In this article, to accommodate the heterogeneity among individual persons, we propose a covariate-assisted word embeddings in a margin-based ordinal regression framework, where covariates are incorporated through scaling factors to adjust the word embeddings. Moreover, we employ a block-wise coordinate descent scheme to tackle the resultant large-scale optimization task, and establish theoretical results to quantify the asymptotic behavior of the proposed method, guaranteeing its fast convergence rate in terms of prediction accuracy. Finally, we demonstrate the advantages of the proposed method over its competitors in both the Yelp Challenge dataset and synthetic datasets.

Disrupting uniformity: Feature contrasts that reduce crowding interfere with peripheral word recognition

Peripheral word recognition is impaired by crowding, the harmful influence of surrounding objects (flankers) on target identification. Crowding is usually weaker when the target and the flankers differ (for example in color). Here, we investigated whether reducing crowding at syllable boundaries improved peripheral word recognition. In Experiment 1, a target letter was flanked by single letters to the left and right and presented at 8° in the lower visual field. Target and flankers were either the same or different in regard to contrast polarity, color, luminance, and combined color/luminance. Crowding was reduced when the target differed from the flankers in contrast polarity, but not in any of the other conditions. Using the same color and luminance values as in Experiment 1, we measured recognition performance (speed and accuracy) for uniform (e.g., all letters black), congruent (e.g., alternating black and white syllables), and incongruent (e.g., alternating black and white non-syllables) words in Experiment 2. Participants verbally reported the target word, briefly displayed at 8° in the lower visual field. Congruent and incongruent words were recognized slower compared to uniform words in the opposite contrast polarity condition, but not in the other conditions. Our results show that the same feature contrast between the target and the flankers that yielded reduced crowding, deteriorated peripheral word recognition when applied to syllables and non-syllabic word parts. We suggest that a potential advantage of reduced crowding at syllable boundaries in word recognition is counteracted by the disruption of word uniformity.

Reading sentences of uniform word length \u2013 II: Very rapid adaptation of the preferred saccade length

In the current study we investigated whether readers adjust their preferred saccade length (PSL) during reading on a trial-by-trial basis. The PSL refers to the distance between a saccade launch site and saccade target (i.e., the word center during reading) when participants neither undershoot nor overshoot this target (McConkie, Kerr, Reddix, & Zola in Vision Research, 28, 1107-1118, 1988). The tendency for saccades longer or shorter than the PSL to under or overshoot their target is referred to as the range error. Recent research by Cutter, Drieghe, and Liversedge (Journal of Experimental Psychology: Human Perception and Performance, 2017) has shown that the PSL changes to be shorter when readers are presented with 30 consecutive sentences exclusively made of three-letter words, and longer when presented with 30 consecutive sentences exclusively made of five-letter words. We replicated and extended this work by this time presenting participants with these uniform sentences in an unblocked design. We found that adaptation still occurred across different sentence types despite participants only having one trial to adapt. Our analyses suggested that this effect was driven by the length of the words readers were making saccades away from, rather than the length of the words in the rest of the sentence. We propose an account of the range error in which readers use parafoveal word length information to estimate the length of a saccade between the center of two parafoveal words (termed the Centre-Based Saccade Length) prior to landing on the first of these words.

Reading sentences of uniform word length: Evidence for the adaptation of the preferred saccade length during reading.

In the current study, the effect of removing word length variability within sentences on spatial aspects of eye movements during reading was investigated. Participants read sentences that were uniform in terms of word length, with each sentence consisting entirely of three-, four-, or five-letter words, or a combination of these word lengths. Several interesting findings emerged. Adaptation of the preferred saccade length occurred for sentences with different uniform word length; participants would be more accurate at making short saccades while reading uniform sentences of three-letter words, while they would be more accurate at making long saccades while reading uniform sentences of five-letter words. Furthermore, word skipping was affected such that three- and four-letter words were more likely, and five-letter words less likely, to be directly fixated in uniform compared to non-uniform sentences. It is argued that saccadic targeting during reading is highly adaptable and flexible toward the characteristics of the text currently being read, as opposed to the idea implemented in most current models of eye movement control during reading that readers develop a preference for making saccades of a certain length across a lifetime of experience with a given language. (PsycINFO Database Record

On the complexity of the word problem for automaton semigroups and automaton groups

In this paper, we study the word problem for automaton semigroups and automaton groups from a complexity point of view. As an intermediate concept between automaton semigroups and automaton groups, we introduce automaton-inverse semigroups, which are generated by partial, yet invertible automata. We show that there is an automaton-inverse semigroup and, thus, an automaton semigroup with a PSpace-complete word problem. We also show that there is an automaton group for which the word problem with a single rational constraint is PSpace-complete. Additionally, we provide simpler constructions for the uniform word problems of these classes. For the uniform word problem for automaton groups (without rational constraints), we show NL-hardness. Finally, we investigate a question asked by Cain about a better upper bound for the length of a word on which two distinct elements of an automaton semigroup must act differently.A detailed listing of the contributions of this paper can be found at the end of this paper.

Decision problems for word-hyperbolic semigroups

This paper studies decision problems for semigroups that are word-hyperbolic in the sense of Duncan and Gilman. A fundamental investigation reveals that the natural definition of a ‘word-hyperbolic structure’ has to be strengthened slightly in order to define a unique semigroup up to isomorphism. (This does not alter the class of word-hyperbolic semigroups.) The isomorphism problem is proven to be undecidable for word-hyperbolic semigroups (in contrast to the situation for word-hyperbolic groups). It is proved that it is undecidable whether a word-hyperbolic semigroup is automatic, asynchronously automatic, biautomatic, or asynchronously biautomatic. (These properties do not hold in general for word-hyperbolic semigroups.) It is proved that the uniform word problem for word-hyperbolic semigroups is solvable in polynomial time (improving on the previous exponential-time algorithm). Algorithms are presented for deciding whether a word-hyperbolic semigroup is a monoid, a group, a completely simple semigroup, a Clifford semigroup, or a free semigroup.

Provision of Economic Security by Creating Innovation Network of Transnational Cluster Initiatives

1. Introduction Modern linguistics has gained a wealth of experience (OR: a great deal of) experience studying phenomena related to the description of human's occupation and his professional discourse, as well as professional term-system description. But nowadays scholars note modern shift to study languages not only in itself and for itself' but to studying it close connection with human consciousness, his cognition, culture and professional practice, i.e. shift toward closely connected to cognitive language study anthropological and civilizational linguistics (see such scholars as E.S. Kubryakova, L.V. Ivina, I.G. Ruzin, G. Lakoff, M. Johnson, A.G. Shaikhulov, Z.R. Pal'utina). So, the problem of a new approach to terminology study appears very important nowadays. The purpose of this article is to outline our experience of professional terminology study and description according to these modern science trends. Thus, for example, linguists state that scientific phenomena should be studied first and foremost according to their role for a human being, their assignment for human personality development and improvement (1, c. 212). Basing on this message we suppose that oil and gas sector terminology system should reflect true and clear understanding of the level of human knowledge of oil and gas industry.. Being constantly subjected to human purposeful activity, it constantly keeps being shaped and altered under the influence of the serving its needs science development level. The term system under study enables us to ascertain specific oil and gas field terminology characteristics every new term unit of which is to acquire similar structural and semantic characteristics. The study investigated the hypothesis that the methodology of cognitive-ideographic description is applicable for modern terminology systems and allows scholars and subject specialists to systematize terminology, identify structural, semantic, nominative, motivational and functional characteristics of composing them terms. 2. Method We can justify our idea of oil and gas term unification into a separate investigation object by our observation that the elements of this term-system represent structurally and communicatively interacting term units. Term units of the term system under study have common logical, structural and semantic features, uniform word form building and derivational characteristics stating logical and semantic relations between them and affecting term system formation. Studies modern lexicology stress the idea that full and thorough study of a language lexical system is possible only by compiling its thesaurus, where it is possible not only to outline paradigmatic relations but also show typical combination models of lexical units (Moskvin (1997), Shaikhulov (2001), Tabanakova (2001) and others). In their ideographic studies these scholars point out that not any single study of a language lexical system can fully depict its dividedness. This task can only be solved by compiling ideographic dictionaries the very core of which is based on the principle of studying the full volume of language lexical system, concurrently reflecting the basic principles of its formation--integrity, continuity, hierarchical pattern and inclusiveness. Ideographic dictionaries, as the scholars' state, make it possible to represent the whole aggregate of semantic fields, lexical-semantic groups and other lexeme amalgamations their co-relation and hierarchical organization (3, p. 43-57; 4, p. 5-22; 5, p. 234; 6, p. 20 and others). In line with the above we propose our holistic and systematic approach to building ideographic oil and gas business term unit's paradigm. Scholars believe ideographic dictionaries alongside with other types of dictionaries (analogical, associative, synonymic, semantic, subject-thematic and others) to be a means of a particular terminological systems term units description and at the same time enable us to represent the term system as a set of concepts each having own specific structure and comprising lexemes of relatively equal semantics. …

Zipfian frequency distributions facilitate word segmentation in context

Word frequencies in natural language follow a highly skewed Zipfian distribution, but the consequences of this distribution for language acquisition are only beginning to be understood. Typically, learning experiments that are meant to simulate language acquisition use uniform word frequency distributions. We examine the effects of Zipfian distributions using two artificial language paradigms—a standard forced-choice task and a new orthographic segmentation task in which participants click on the boundaries between words in contexts. Our data show that learners can identify word forms robustly across widely varying frequency distributions. In addition, although performance in recognizing individual words is predicted best by their frequency, a Zipfian distribution facilitates word segmentation in context: The presence of high-frequency words creates more chances for learners to apply their knowledge in processing new sentences. We find that computational models that implement “chunking” are more effective than “transition finding” models at reproducing this pattern of performance.

Selection of preeminent list in word recognition score test for adult with normal hearing

Introduction: Speech audiometry is one of the most essential components of the current audiologic test battery. It provides information regarding hearing sensitivity and speech intelligibility at supra threshold levels. Considering the importance of the word recognition score (WRS) test and due to the lack of a uniform word recognition list to accomplish that test in Iran, we decided to evaluate people with normal hearing with the four most common lists used for clinical practice in order to select the preeminent one. Materials and Methods: In this non randomized descriptive-analytic study, thirty normal-hearing adults aged 18 to 40 years were evaluated. Test-retest reliability was achieved within a 2-week interval for the subjects. Results: The subjects’ scores ranged from %92 to %100 when the four lists were considered altogether. The mean scores of word recognition test for each individual list were as follows: list 2: %99/65, list 4: %94/13, list 5: %98, and list 9: %98/53. List 9 was the most reliable one in adults with normal hearing. Conclusion: All the four lists evaluated possess both phonetic and word reliability and the subtle differences between their reliability scores are not statistically significant. Keywords: Word recognition score (WRS), Preeminent list, Validity, Reliability

Generic Complexity of Finitely Presented Monoids and Semigroups

We study the generic properties of finitely presented monoids and semigroups, and the generic-case complexity of decision problems for them. We show that for a finite alphabet A of size at least 2 and positive integers k and m, the generic A-generated k-relation monoid and semigroup (defined using any of several stratifications) satisfies the small overlap condition C(m). It follows that the generic finitely presented monoid has a number of interesting semigroup-theoretic properties and, by a recent result of the author, admits a linear time solution to its word problem and a regular language of unique normal forms for its elements. Moreover, the uniform word problem for finitely presented monoids is generically solvable in polynomial time.

On the equational theory of projection lattices of finite von neumann factors

AbstractFor a finite von Neumann algebra factor M, the projections form a modular ortholattice L(M). We show that the equational theory of L(M) coincides with that of some resp. all L(ℂn×n ) and is decidable. In contrast, the uniform word problem for the variety generated by all L(ℂn×n) is shown to be undecidable.

A solution of the uniform word problem for ortholattices

The uniform word problem for finitely presented ortholattices is shown to be solvable through a method of terminating proof search. The axioms of ortholattices are all Harrop formulas, and thus can be expressed in natural deduction style as single succedent rules. A system of natural deduction style rules for orthologic is given as an extension of the system for lattices presented by Negri and von Plato. By considering formal derivations of atomic formulas from a finite number of given atomic formulas, it is shown that proof search is bounded, and thus that the question of derivability of any atomic formula from any finite set of given atomic formulas is decidable.

Undecidable problems for completely 0-simple semigroups

The decidability of the uniform word problem in a pseudovariety V of groups is known to be equivalent to the decidability of a number of embedding problems for finite semigroups in classes related to completely 0-simple semigroups with subgroups from V . Unfortunately the existing proof of some of these equivalences turns out to contain an error. We provide an update on these types of properties, correcting the error and amending results accordingly. Several new undecidability properties are exhibited, some superceding previous results. A theme of many of the new contributions is problems that are solvable in polynomial time but become undecidable when a facet of their description is restricted by some finiteness condition.