Hasil untuk "Comparative grammar"

Yuanjie Song, Ke Deng

Arthur Bouffandeau, Sabine Bensamoun, Robert Schleip et al.

Background: Palpation is the most widely used approach to empirically assess the mechanical properties of superficial tissues. While elastography is used for volume measurements, it remains difficult to assess skin properties with non-invasive methods. This study aimed to compare the performances of an impact-based analysis method (IBAM) consisting in studying the dynamic response of a punch in contact with the tissue with other approaches available on the market. Materials and Methods: IBAM consists in analyzing the time dependent force signal induced when a hammer instrumented with a force sensor impacts a cylindrical punch placed in contact with soft tissue. Sensitivities to stiffness changes and to spatial variations were compared between IBAM and four other mechanical surface characterization techniques: IndentoPro (macroindentation), Cutometer (suction), MyotonPro (damped oscillation) and Shore Durometer (durometry) using soft tissue phantoms based on polyurethane gel. Results: For stiffness discrimination in homogeneous phantoms, IBAM was slightly better than IndentoPro and MyotonPro (by 20 % and 35 % respectively), and outperformed the Shore Durometer and Cutometer by a factor of 2 to 4. Furthermore, for stiffness and thickness variations in bilayer phantoms, the axial sensitivity of IBAM was between 2.5 and 4.5 times better than that of MyotonPro and IndentoPro. In addition, the Cutometer appeared to be severely limited by its measurement depth. Conclusion: IBAM seems to be a promising technique for characterizing the mechanical properties of soft tissue phantoms at relatively low depth after future ex vivo and in vivo validation studies with biological tissues (with both animal and in human experiments). This work could pave the way to the development of a decision support system in the field of dermatology and cosmetics.

Areen Khalaila, Dylan Cashman

Tactile graphics are often adapted from visual chart designs, yet many of these encodings do not translate effectively to non-visual exploration. Blind and low-vision (BLV) people employ a variety of physical strategies such as measuring lengths with fingers or scanning for texture differences to interpret tactile charts. These observations suggest an opportunity to move beyond direct visual translation and toward a tactile-first design approach. We outline a speculative tactile design framework that explores how data analysis tasks may align with tactile strategies and encoding choices. While this framework is not yet validated, it offers a lens for generating tactile-first chart designs and sets the stage for future empirical exploration. We present speculative mockups to illustrate how the Tactile Perceptual Grammar might guide the design of an accessible COVID-19 dashboard. This scenario illustrates how the grammar can guide encoding choices that better support comparison, trend detection, and proportion estimation in tactile formats. We conclude with design implications and a discussion of future validation through co-design and task-based evaluation.

Lars Vogt, Barend Mons

The FAIR Principles aim to make data and knowledge Findable, Accessible, Interoperable, and Reusable, yet current digital infrastructures often lack a unifying semantic framework that bridges human cognition and machine-actionability. In this paper, we introduce the Grammar of FAIR: a granular and modular architecture for FAIR semantics built on the concept of semantic units. Semantic units, comprising atomic statement units and composite compound units, implement the principle of semantic modularisation, decomposing data and knowledge into independently identifiable, semantically meaningful, and machine-actionable units. A central metaphor guiding our approach is the analogy between the hierarchy of level of organisation in biological systems and the hierarchy of levels of organisation in information systems: both are structured by granular building blocks that mediate across multiple perspectives while preserving functional unity. Drawing further inspiration from concept formation and natural language grammar, we show how these building blocks map to FAIR Digitial Objects (FDOs), enabling format-agnostic semantic transitivity from natural language token models to schema-based representations. This dual biological-linguistic analogy provides a semantics-first foundation for evolving cross-ecosystem infrastructures, paving the way for the Internet of FAIR Data and Services (IFDS) and a future of modular, AI-ready, and citation-granular scholarly communication.

Christoph Wernhard, Zsolt Zombori

Viewing formal mathematical proofs as logical terms provides a powerful and elegant basis for analyzing how human experts tend to structure proofs and how proofs can be structured by automated methods. We pursue this approach by (1) combining proof structuring and grammar-based tree compression, where we show how they are inherently related, and (2) exploring ways to combine human and automated proof structuring. Our source of human-structured proofs is Metamath, which, based on condensed detachment, naturally provides a view of proofs as terms. A knowledge base is then just a grammar that compresses a set of gigantic proof trees. We present a formal account of this view, an implemented practical toolkit as well as experimental results.

Amy Fitriani Siregar, Ananda Zalfa Firdaus, Agung Setiyawan et al.

Difficulties in learning Shorof for students are frequently found but the innovation of learning media utilization in this subject is quite rare. The article analyzed about how effective the use of flashcards media on Shorof subjects to support the quality of learning for junior high school students. The research was conducted with experimental quantitative methods, and the research design was a true experiment. The experimental class and the control class were chosen randomly in order to that students' abilities were equal. The samples of learning outcomes were obtained from 15 students who were randomly selected from the experimental and control classes with a total sample of 30 students. In collecting data, the tests and documentation were used, whereas data analysis was carried out with SPSS 26 through the Mann-Whitney non-parametric test because the data were normally distributed and not homogeneous. From this research, it was concluded that there were differences in the learning outcomes of the experimental and control classes after the treatment, which the experimental class got higher score than the control class with an average score of 93.3327:62.0520, which means that there was a positive impact of using flashcards on student learning outcomes evidenced by the Mann Whitney test of 0.000 < 0.05. Based on the valid test results, it was suggested that Shorof flashcards can be used in various institutions as Shorof learning subject in general to increase the learning methods more creative and innovative.

Marco Antonio Almeida Ruiz, Lígia Mara Boin Menossi de Araújo

Apresentamos uma análise representativa da relação entre a norma da língua e a norma do corpo feminino em rede social. Observamos o perfil da empresária Cíntia Chagas no Instagram, relacionando, por um lado, a língua, no âmbito profissional, a um modelo de sucesso e, por outro, seu corpo, na vida pessoal, a um padrão de beleza estigmatizado. Analisamos as cenografias criadas dessa relação com o digital e seus (d)efeitos diante das movências de sentidos quando atreladas às condições de sua emergência. Nossos pressupostos teórico-metodológicos inscrevem-se na análise do discurso francesa, sobretudo na noção de cenas da enunciação de Dominique Maingueneau.

Alma-Pierre Bonnet

Extensive academic literature has been devoted to the way “Brexit narratives” were used during the 2016 referendum campaign. Both camps dwelt on this rhetorical tool to create stories about the advantages of leaving or staying in the European Union (EU). Overall, studies have revealed the construction of broadly similar stories, in particular within the “populist narratives” of the Leave campaign, which depicted the EU as a “failure”, an “oppressor”, and an object of anti-establishment “fury”. Within the field of narratology, cognitive linguistics and conspiratorial studies, this paper proposes a discursive analysis focused on one particular narrative which, we argue, has received relatively little attention but which might constitute an example of “Brexit conspiracy”: what we call “the Turkey story”. Indeed, one key element in the Brexit narratives elaborated by the official pro-Brexit campaign, Vote Leave, was the fact that Turkey, and other poorer – and predominantly Muslim – countries, were “in the pipeline” to join the EU. At first marginal, this story soon took centre-stage to justify the necessity to leave the supra-national organization before “hordes” of illegal immigrants from those countries, and from neighbouring Iraq and Syria, decided to emigrate en masse to Britain. Thanks to the narrative analysis of speeches and declarations by leading Vote Leave members, this paper sets to examine whether “the Turkey story” amounts to a conspiracy theory and how it was used to defend the anti-EU agenda, which will lead to the introduction of the concept of “strategic conspiracy”.

Xiaodong Jia, Gang Tan

Accurate description of program inputs remains a critical challenge in the field of programming languages. Active learning, as a well-established field, achieves exact learning for regular languages. We offer an innovative grammar inference tool, V-Star, based on the active learning of visibly pushdown automata. V-Star deduces nesting structures of program input languages from sample inputs, employing a novel inference mechanism based on nested patterns. This mechanism identifies token boundaries and converts languages such as XML documents into VPLs. We then adapted Angluin's L-Star, an exact learning algorithm, for VPA learning, which improves the precision of our tool. Our evaluation demonstrates that V-Star effectively and efficiently learns a variety of practical grammars, including S-Expressions, JSON, and XML, and outperforms other state-of-the-art tools.

Eva Portelance, Siva Reddy, Timothy J. O'Donnell

Semantic and syntactic bootstrapping posit that children use their prior knowledge of one linguistic domain, say syntactic relations, to help later acquire another, such as the meanings of new words. Empirical results supporting both theories may tempt us to believe that these are different learning strategies, where one may precede the other. Here, we argue that they are instead both contingent on a more general learning strategy for language acquisition: joint learning. Using a series of neural visually-grounded grammar induction models, we demonstrate that both syntactic and semantic bootstrapping effects are strongest when syntax and semantics are learnt simultaneously. Joint learning results in better grammar induction, realistic lexical category learning, and better interpretations of novel sentence and verb meanings. Joint learning makes language acquisition easier for learners by mutually constraining the hypotheses spaces for both syntax and semantics. Studying the dynamics of joint inference over many input sources and modalities represents an important new direction for language modeling and learning research in both cognitive sciences and AI, as it may help us explain how language can be acquired in more constrained learning settings.

Shangtong Gui, Chenze Shao, Zhengrui Ma et al.

Non-autoregressive Transformer(NAT) significantly accelerates the inference of neural machine translation. However, conventional NAT models suffer from limited expression power and performance degradation compared to autoregressive (AT) models due to the assumption of conditional independence among target tokens. To address these limitations, we propose a novel approach called PCFG-NAT, which leverages a specially designed Probabilistic Context-Free Grammar (PCFG) to enhance the ability of NAT models to capture complex dependencies among output tokens. Experimental results on major machine translation benchmarks demonstrate that PCFG-NAT further narrows the gap in translation quality between NAT and AT models. Moreover, PCFG-NAT facilitates a deeper understanding of the generated sentences, addressing the lack of satisfactory explainability in neural machine translation.Code is publicly available at https://github.com/ictnlp/PCFG-NAT.

Daria Stetsenko, Inez Okulska

This paper provides an overview of a text mining tool the StyloMetrix developed initially for the Polish language and further extended for English and recently for Ukrainian. The StyloMetrix is built upon various metrics crafted manually by computational linguists and researchers from literary studies to analyze grammatical, stylistic, and syntactic patterns. The idea of constructing the statistical evaluation of syntactic and grammar features is straightforward and familiar for the languages like English, Spanish, German, and others; it is yet to be developed for low-resource languages like Ukrainian. We describe the StyloMetrix pipeline and provide some experiments with this tool for the text classification task. We also describe our package's main limitations and the metrics' evaluation procedure.

Ewa Komorowska

The article presents partial results from an online survey conducted with a group of expatriates living and working in Poland. The main aim of the study was to examine the attitude of the target group towards learning Polish, and to find the most important motivations for learning it or the reasons for not doing so. This problem has not been thoroughly researched before because expatriates previously were not treated as a separate research group. The results show, however, that they are an interesting object of study; they differ from other types of learners (e.g. academic learners) mostly because of their different motivations and attitudes towards learning Polish. The language profile of the expatriates is particularly noteworthy, especially their multilingualism, although not all are learning Polish. Their motivations to start learning the language, and the reasons for stopping to do so or for not even starting at all despite living in Poland for long time, are also worth exploring.

Imran Ali, Muhammad Ijaz Tabassum

<span style="font-size: 14.0pt; line-height: 115%; font-family: &quot;Calibri&quot;,&quot;sans-serif&quot;; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: Arial; mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">The Oriental College is first educational institution of Governemnt of Punjab, where Oriental Languages are taught. Oriental College was established in 1870, basically this Institution was established to acquaint the people with modern field of knowledge in Oriental Languages. At that time Arabic, Persian, Sanskrit, Hindi, Urdu, Punjabi (Grumukhi) and Peshto, including modern subjects of knowledge, like Engineering, Mathematic, Geography, Economic, Philosophy, Muslim Law, Dharam Shaster, Medicine, Economic, Tibb Unani, Vedak and History were taught in this College.&nbsp;</span><span style="font-size: 14.0pt; line-height: 115%; font-family: &quot;Calibri&quot;,&quot;sans-serif&quot;; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: Arial; mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">M.A. classes were started at Oriental College beginning with Arabic, M.A. Sanskrit 1888, Persian 1921, Urdu 1948, Punjabi 1970 and Kashmir Studies 1987.</span>

Hossep Dolatian

Cross-linguistically, it is rare to find cases of phonologically-conditioned allomorphy where the trigger morpheme lies external or outside the target morpheme. At first sight, the Armenian definite suffix seems to be such a case. The definite suffix uses various surface forms. The choice of surface form is conditioned by the preceding segment, the following clitic, and/or the following word. However, we argue that this outward sensitivity is epiphenomenal and not actual allomorphy. We derive the surface forms by using an abstract underlying representation that uses floating segments or ghost segments. These segments go through rigid cycles of spell-out and phonological strata. Constraint re-rankings of autosegmental docking, phrasal resyllabification, and cluster avoidance explain a range of dialectal variation. In sum, the Armenian definite suffix is one apparent case of outwardly-sensitive allomorphy that is reducible to latent segments.

Hyeok Kim, Ryan Rossi, Fan Du et al.

Designing responsive visualizations can be cast as applying transformations to a source view to render it suitable for a different screen size. However, designing responsive visualizations is often tedious as authors must manually apply and reason about candidate transformations. We present Cicero, a declarative grammar for concisely specifying responsive visualization transformations which paves the way for more intelligent responsive visualization authoring tools. Cicero's flexible specifier syntax allows authors to select visualization elements to transform, independent of the source view's structure. Cicero encodes a concise set of actions to encode a diverse set of transformations in both desktop-first and mobile-first design processes. Authors can ultimately reuse design-agnostic transformations across different visualizations. To demonstrate the utility of Cicero, we develop a compiler to an extended version of Vega-Lite, and provide principles for our compiler. We further discuss the incorporation of Cicero into responsive visualization authoring tools, such as a design recommender.

Michele Mannoni

This study addresses the different types and implications of linguistic indeterminacy in Chinese law. It firstly draws on the studies of scholars of different disciplines, such as linguistics and philosophy of language, to provide a taxonomy of indeterminacy in language. It then provides examples of each type, highlighting the implications in law and legal interpretation. It uses linguistic data from various texts, such as statutory laws and judgements, and analyse them with various methods, including discourse analysis and corpus linguistics. This study argues that when the language of the law is indeterminate, the legal outcomes may be particularly uncertain. It suggests that although it is difficult to ascertain whether the degree of indeterminacy is higher in some languages more than in others, some linguistic mechanisms at the word-formation level in Chinese are remarkably ambiguous. When uncertain terms are in key parts of the law, the consequences may be more serious. The study of linguistic indeterminacy in Chinese has implications for the study of forensic linguistics, and Chinese studies in general.

Anthony Peruma, Emily Hu, Jiajun Chen et al.

It is good practice to name test methods such that they are comprehensible to developers; they must be written in such a way that their purpose and functionality are clear to those who will maintain them. Unfortunately, there is little automated support for writing or maintaining the names of test methods. This can lead to inconsistent and low-quality test names and increase the maintenance cost of supporting these methods. Due to this risk, it is essential to help developers in maintaining their test method names over time. In this paper, we use grammar patterns, and how they relate to test method behavior, to understand test naming practices. This data will be used to support an automated tool for maintaining test names.

Vignav Ramesh, Anton Kolonin

Many current artificial general intelligence (AGI) and natural language processing (NLP) architectures do not possess general conversational intelligence--that is, they either do not deal with language or are unable to convey knowledge in a form similar to the human language without manual, labor-intensive methods such as template-based customization. In this paper, we propose a new technique to automatically generate grammatically valid sentences using the Link Grammar database. This natural language generation method far outperforms current state-of-the-art baselines and may serve as the final component in a proto-AGI question answering pipeline that understandably handles natural language material.

Christopher W. Tindale

Early in The New Rhetoric, Perelman and Olbrechts-Tyteca raise the spectre of the fanatic who “adheres to a disputed thesis for which no unquestionable proof can be furnished,” refuses to submit it for free discussion, and thereby “rejects the preliminary conditions which would make it possible to engage in argumentation” (1970: 62). One of the many interesting suggestions here is that there may be preliminary conditions that should be in place before argumentation can be engaged. In this paper, I pursue that suggestion and consider what such preliminary conditions should be, in order to address problems of dialogue between people or groups who seem to subscribe to different conceptions of rationality. I draw from some examples of confrontations between peoples for the first time (encounter rhetorics), where those involved had first to come to understand each other before argumentation between them could develop.