Categorical Dimensions Research Articles

Beyond Vision Impairments: Redefining the Scope of Accessible Data Representations.

The increasing ubiquity of data in everyday life has elevated the importance of data literacy and accessible data representations, particularly for individuals with disabilities. While prior research predominantly focuses on the needs of the visually impaired, our survey aims to broaden this scope by investigating accessible data representations across a more inclusive spectrum of disabilities. After conducting a systematic review of 152 accessible data representation papers from ACM and IEEE databases, we found that roughly 78% of existing articles center on vision impairments. In this article, we conduct a comprehensive review of the remaining 22% of papers focused on underrepresented disability communities. We developed categorical dimensions based on accessibility, visualization, and human-computer interaction to classify the papers. These dimensions include the community of focus, issues addressed, contribution type, study methods, participants involved, data type, visualization type, and data domain. Our work redefines accessible data representations by illustrating their application for disabilities beyond those related to vision. Building on our literature review, we identify and discuss opportunities for future research in accessible data representations.

"Urgency" and "emergency" in the system of law-making proccess: conceptual and categorical dimension

It is indicated that the course of events at the global and regional levels of social development during recent years is difficult to characterize unambiguously from the standpoint of purely positive or negative aspects. However, it can be unequivocally noted that modern socio-political processes at the global and regional levels have a particularly sensitive effect on legal phenomena and processes. In the article, the author focuses on the relevance of the study of the conceptual and categorical foundations of the categories «urgency» and «emergency» and the peculiarities of their manifestation within the framework of law­making process. According to the author of the article, the achievement of the above is due to the need to carry out a comprehensive and conceptual analysis through the prism of scientific views and approaches of scientists. Attention was drawn to the fact that in connection with numerous factors of a subjective and objective nature, in particular, the duration of the war on the territory of Ukraine, the spread of the SARS- CoV-2 virus, the development of technologies, especially in the information field, the issues of new mechanisms for the development and adoption of the system are being updated normative legal acts taking into account the existing requirements and realities of the modern state of development of society, law and the state. Analysis of doctrinal approaches to this issue will provide clarification of the conceptual and categorical aspects of the relevant legal categories. It is substantiated that in cognitive terms it is expedient to analyze these legal categories through the prism of scientific views and concepts, which will allow generalizing their properties and improving their definitions. The content of the work includes a doctrinal analysis of the concepts of «urgency» and «emergency» as special legal categories. It was concluded that the categories «emergency» and «urgency» within the framework of law-making have a high level of relevance; require thorough, comprehensive scientific research within the framework of legal theory; are characterized by the presence of a common purpose, essential differences.

Conceptual masking disrupts change-detection performance.

The present study investigated the effects of long-term knowledge on backward masking interference in visual working memory (VWM) by varying the similarity of mask stimuli along categorical dimensions. To-be-remembered items and masks were taken from categories controlled for perceptual distinctiveness and distinctiveness in kinds (e.g., there are many kinds of cars and few kinds of coffee mugs). Participants completed a change-detection task in which the memory array consisted of exemplars from either a similar or distinctive category, followed by a mask array of items from the same category (conceptually similar versus conceptually distinct categories), a different category, or no mask. The results over two experiments showed greater interference from conceptually similar masks as compared with the other conditions across stimulus onset asynchrony (SOA) conditions, suggesting masking with conceptually similar categories leads to more interference even when masks are shown well after the stimulus. These results have important implications for both the nature and time course of long-term conceptual knowledge influencing VWM, particularly when using complex real-world objects.

The ontic-epistemic debates of explanation revisited: The three-dimensional approach

After Wesley Salmon’s causal-mechanical stance on explanation in the 1980s, the ontic-epistemic debate of scientific explanations appeared to be resolved in the philosophy of science. However, since the twenty-first century, this debate has been rekindled among philosophers who focus on mechanistic explanations. Nevertheless, its issues have evolved, necessitating scrutiny of the new trends in this debate and a comparison with the original controversy between Carl Hempel and Salmon. The primary objective of this paper is to elucidate three categorical dimensions in the ontic-epistemic debates, spanning from the original to the recent controversies. Subsequently, it will explore why the conception of explanation is linked to representations, what conditions are necessary for linguistic expressions to be explanatory, and what roles norms play in explanation. Consequently, contrary to the common stereotype, it will be argued that mechanistic explanations are more likely to be epistemic rather than ontic.

On straightening for Segal spaces

The straightening–unstraightening correspondence of Grothendieck–Lurie provides an equivalence between cocartesian fibrations between $(\infty, 1)$-categories and diagrams of $(\infty, 1)$-categories. We provide an alternative proof of this correspondence, as well as an extension of straightening–unstraightening to all higher categorical dimensions. This is based on an explicit combinatorial result relating two types of fibrations between double categories, which can be applied inductively to construct the straightening of a cocartesian fibration between higher categories.

Multiplicities and Dimensions in Enveloping Tensor Categories

Abstract In a previous paper, semisimple tensor categories were constructed from certain regular Mal’cev categories. In this paper, we calculate the tensor product multiplicities and the categorical dimensions of the simple objects. This yields also the Grothendieck ring. The main tool is the subquotient decomposition of the generating objects.

TEXT IN THE MODERN PARADIGM OF SCIENTIFIC KNOWLEDGE: CATEGORIZATION AND PRAGMATICS

The article analyzes the text in the modern paradigm of scientific knowledge from the perspective of categorization and pragmatics. A look at the text in a categorical dimension attests to a change in definitions, an expansion of the interpretation of the concept. It is noted that linguists differentiate text and discourse, study the text in semantic, grammatical, pragmatic- communicative and structural planes, study the categorical organization of the text. Focused on what, in addition to written texts, oral texts also attract the attention of scholars. The analysis of the text as an object of linguistic research in a pragmatic dimension is presented on the material of an oral text – a football television report. Football live television reporting appears as a process and product of oral communication addressed to a multi-million audience of game fans. The features of the football television report as a text are explained through a system of text categories with units of a lower hierarchy (according to the concept of A. Yeshchenko) in three dimensions: from the perspective of semantics, from the perspective of communicativeness, at the level of pragmatics. Summarized that, the correlation of text categories of different dimensions serves as a text-constitutive factor.

Signs of intellectual property as a value-legal phenomenon

In the work, the author focused attention on the relevance of studying the properties of intellectual property. It was noted that the relevance of intellectual property research through the prism of its conceptual and categorical dimension is determined by: firstly, the presence of various, sometimes doctrinally opposing theories of intellectual property; secondly, the doctrinal disputability of the characteristic of the functional purpose of the methodological toolkit developed by both legal science and general theoretical methodological research. It has been proven that the basis of defining any concept of legal science, improving its terminological consolidation in the provisions of the legislation of Ukraine are defined properties of the corresponding phenomenon or process, which are generalized and characterized within the limits of the corresponding system of features. Examining intellectual property from the point of view of a value-legal methodological approach, the expediency of revealing the signs of the specified concept, which from the point of view of methodology can be laid as a basis for the further definition of intellectual property as an independent concept of legal science and a term of domestic legislation, has been ascertained.In the content of the article, the author clarified the system and content of signs of intellectual property as a value-legal phenomenon based on the established and analyzed properties of intellectual property. It is noted that the independence of intellectual property in the system of doctrinal concepts and categories is proven by its ability to accumulate and formalize the valuable aspects of intellectual property as such, which by its essence reflects its spiritual value, and by its results, its acquisition of economic and material value.It is summarized that the concept of «intellectual property» is complex and multifaceted, which makes possible its conceptual dimension and corresponding conceptual understanding both within different sciences (economic, sociological, technical, legal, etc.) and within different methodological approaches and methods of scientific knowledge , the result of which is the possibility of providing appropriate definitions of the specified concept. This is confirmed by various definitions of the concept of «intellectual property» presented in encyclopedic literature (legal, economic, technical dictionaries), as well as in literary scientific sources.Therefore, it is summarized that the definition of the concept of «intellectual property» as a special value-legal phenomenon will contribute to the unification of such recognition, as well as strengthen its methodological importance for the development of the conceptual and categorical apparatus of other legal sciences, as well as any other social sciences in general.

Towards Natural Language Interfaces for Data Visualization: A Survey.

Utilizing Visualization-oriented Natural Language Interfaces (V-NLI) as a complementary input modality to direct manipulation for visual analytics can provide an engaging user experience. It enables users to focus on their tasks rather than having to worry about how to operate visualization tools on the interface. In the past two decades, leveraging advanced natural language processing technologies, numerous V-NLI systems have been developed in academic research and commercial software, especially in recent years. In this article, we conduct a comprehensive review of the existing V-NLIs. In order to classify each article, we develop categorical dimensions based on a classic information visualization pipeline with the extension of a V-NLI layer. The following seven stages are used: query interpretation, data transformation, visual mapping, view transformation, human interaction, dialogue management, and presentation. Finally, we also shed light on several promising directions for future work in the V-NLI community.

Motivated Categories: Social Structures Shape the Construction of Social Categories Through Attentional Mechanisms

Social categorization is often framed as the antecedent to stereotyping, with perceivers rationally sorting the social world on the basis of perceptually salient categories before applying biased or motivated beliefs about those categories. Here, we instead suggest that the construction of social categories by individuals is itself subject to motivational influences, such that perceivers will attend to a given dimension of social categorization (e.g., race or gender) insofar as doing so fits within their motivations. Drawing from classic conceptualizations of social structure as the interplay of schemas and resources, we focus on how the motivations for shared schemas and for material benefits or resources may shape attention to social category dimensions. We outline the potential cognitive mechanisms through which these motivations may act on attention, before discussing the implications of this model for individual differences, conceptualizations of social categorization as rational information reduction, and prejudice reduction. Public Social categories like race and gender often give rise to stereotypes and prejudice, and a great deal of research has focused on how motivations influence these biased beliefs. Here, we focus on potential biases in how these categories are even formed in the first place, suggesting that motivations can influence the very categories people use to group others. We propose that motivations to share schemas with other people and to gain resources shape people’s attention to dimensions like race, gender, and age in different contexts. Specifically, people will pay attention to dimensions to the degree that the conclusions produced from using those dimensions align with their motivations. Overall, we suggest that simply examining the downstream effects of social categorization like stereotyping and prejudice is not enough, and that research should look earlier in the process at how and when we form the categories on which those stereotypes are based.

SEMANTIC CONTENT OF CONCEPT HELP CATEGORIZED AS PROPERTY IN CONTEMPORARY ENGLISH

The article deals with the analysis of the semantic structure of nominative units contributing to the establishment of deep patterns of interaction between the structures of human consciousness and linguistic forms. A person's interpretation of the surrounding reality is the result of cognitive activity and is represented in mental structures that are mediators between the real or imagined environment and the language that objectifies them. Nominative possibilities of the linguistic picture of the world are realized by lexical units, which undergo the conceptual analysis to achieve the goal of linguistic-cognitive research for the reconstruction of the content of the HELP concept in particular. The object of the study is the language means for marking help as a property and its components in the modern English language. Notional aspect with its cognitive features of the concept and categorical dimension of property are interrelated in the organization of knowledge about characteristics of help. Language has proved to be effective for accessing the structures of data about the surrounding world which is the area of human physical and mental activity, as well as for exchanging knowledge and experience. As a part of cognitive process, the nominative act presupposes indulgence into the semantic content of language units which involves the analysis of meaningful connections between the lexemes. Conceptual analysis of verbalized segments of knowledge about characteristics of help promotes restoring the notional conceptual content related to understanding of the helping process in terms of its properties. The semantic content of the concept HELP is constructed due to the meaning of attributes to denote properties of help which make up the lexical-semantic group with the integral seme ²helpful². The lexeme ‘helpful’ comprises two notional segments with differentiating semes ²useful² and ²beneficial². Lexical units to designate the property of help constitute semantic subgroups in relation to the kind of help differentiated from the definitions of the lexemes.

Computer crime motives: Do we have it right?

AbstractAcademic, legal and practitioner responses to cyber threats have been predominantly reactive, punitive, and deterrence‐based, with limited attention given to the motives underlying computer criminals' behaviors. This paper reasons that new and better theoretical perspectives are needed to explain computer criminals' motives. Following a review of the computer crime behavioral literature, a summary review of core philosophies and theories used to explain generalized crime and criminal motives is provided. A framework is proposed suggesting that criminological theories have evolved along two categorical dimensions: determinism‐indeterminism, and individualism‐collectivism. The paper then reasons that future computer crime research will benefit by considering indeterminist‐collectivist (constructivist) theories. Two such theories, social construction of technology, and actor‐network theory, are proposed in the discussion section, along with some cybercrime examples. The paper invites a deeper consideration of the origins and motivations of computer‐based criminality as a means of building stronger theory and ultimately advancing more proactive and effective solutions.

Perception of the temporal order of digits during rapid serial visual presentation is influenced by their ordinality.

Psychological research has extensively shown that individuals are limited in their ability to process environmental information temporally. In a rapid serial visual presentation, the ability to identify the second of two targets presented in close succession among distractors is usually impaired, a phenomenon known as attentional blink (AB). Paradoxically, when the second target immediately succeeds the first one (lag 1), such an ability is relatively spared, but individuals are more prone to misreport their correct temporal succession. Competitive mechanisms based on prior entry and perceptual integration processes have been suggested to account for the apparent loss of temporal information. We report findings from four experiments, showing that, once identified, categorical dimensions of the stimuli used as targets (here, the ordinality of numbers) may guide the perception and the resulting report of their temporal order. Specifically, at lag 1 individuals more frequently encode the two digits in ascending order. Such a biased regularization may represent another possible outcome of the failure in temporal segregation observed at lag 1, indicating that a mechanism based on prior entry is not generalizable in explaining order reversals. The kind of stimuli chosen as targets in AB paradigms can activate high-level categorical dimensions capable of influencing the performance on this task.

Language as a cue for social categorization in bilingual communities.

This registered report article investigates the role of language as a dimension of social categorization. Our critical aim was to investigate whether categorization based on language occurs even when the languages coexist within the same sociolinguistic context, as is the case in bilingual communities. Bilingual individuals of two bilingual communities, the Basque Country (Spain) and Veneto (Italy), were tested using the memory confusion paradigm in a 'Who said what?' task. In the encoding part of the task, participants were presented with different faces together with auditory sentences. Two different languages of the sentences were presented in each study, with half of the faces always associated with one language and the other half with the other language. Spanish and Basque languages were used in Study 1, and Italian and Venetian dialect in Study 2. In the test phase, the auditory sentences were presented again and participants were required to decide which face uttered each sentence. As expected, participants error rates were high. Critically, participants were more likely to confuse faces from the same language category than from the other (different) language category. The results indicate that bilinguals categorize individuals belonging to the same sociolinguistic community based on the language these individuals speak, suggesting that social categorization based on language is an automatic process.

Face mask use as a categorical dimension in social perception

Prevention measures aimed at combating COVID-19 pandemic strongly impact several aspects of social life. In particular, interpersonal perception is affected as a function of whether the persons perceived wear or not face masks. In two experimental studies, we here explored whether people rely on the presence vs. absence of face masks when encoding information in memory about other individuals. In a memory confusion paradigm, participants were initially presented with individuals either wearing a face mask or not, each conveying a series of sentences. Next, participants were probed about the identity of the speaker of each sentence. Results showed that it was more likely to erroneously attribute a sentence to a speaker who also was wearing a face mask (or not) as the original speaker, demonstrating that the cue about wearing or not a face mask was spontaneously used to encode information. Study 2 ruled out an alternative explanation based on perceptual processes, suggesting that face masks represent meaningful social objects. Overall, it emerged that participants spontaneously categorize others as a function of whether they wear a mask or not. Findings also confirmed previous research evidence about the more positive evaluation of mask wearers as compared to non-wearers, and the overall detrimental impact that face masks may have on the correct identification of social targets.

C-3DP: A cross-cluster analysis model to identify latent categorical customer attributes

Using two-dimensional clustering methods to segment a customer database is a popular practice. The advantage of two-dimensional clustering is the ability to map customers according to a well-defined business logic. For example, how many segments can be identified based on the customers' age group and RFM score? Such an approach also has the advantage of reducing the dimensionality of datasets and a model's training time. Conversely, the trade-off of clustering on two dimensions is to ignore all the other dimensions potentially available in a CRM or web analytics platform. As such, the qualitative traits analysis of each segment from available customer dimensions can be challenging, especially for categorical dimensions with higher cardinality. In order to maximise the customer insights derived from cluster analysis, the paper proposes a qualitative trait prevalence scoring system: the C-3DP index (categorical density, dominance and diversity prevalence index). This technique maps a subset of dominant qualitative segment traits using a simple algorithm, as opposed to relying solely on traditional descriptive analytics approaches.

Efficacy of a light convex appliance and mouldable ring in an early postoperative stoma with effluent leakage

Aim: This study aimed to analyse the impact of using both a light convex appliance and mouldable ring in the early postoperative period on leakage frequency, peristomal skin health and quality of life after discharge. Methods: This prospective non-randomised study was performed in patients with a digestive stoma experiencing effluent leakage during the early postoperative period. Evaluation was performed at baseline (V1) during admission and at 2–3 weeks after discharge (V2). The outcomes measurements were: number of leaks per day; satisfaction (0 to 10 VAS scale); DET score evaluating discolouration (D); erosion/ulceration (E) and tissue overgrowth (T); stoma morphology and NANDA International nursing diagnosis, which measures anxiety, fear and image deterioration as well as insomnia. NANDA International diagnosis were evaluated as a percentage of cases with the diagnosis and categorically according to several dimension scores. Signed rank, McNemar, chi-squared and Bowker's tests were used for comparison. Results: Of 257 patients screened, 244 completed the study. The mean number of leak episodes using the light convex appliance and mouldable ring in the early postoperative period decreased from 3.4±5.2 (V1) to 1.3±2.3 (V2) (p<0.0001). Mean discolouration, erosion and tissue overgrowth (DET) score decreased from 3.3±3.3 (V1) to 1.6±2.3 (V2) (p<0.0001). Mean self-reported satisfaction with the appliance increased from 5.1±2 (V1) to 7.2±1.7 (V2) (p<0.0001). The proportion of patients with a retracted peristomal area changed from 27.9% to 21.7%, while that of patients with protruded stoma increased from 32.9% to 40% (p=0.025). Regarding NANDA International diagnosis, anxiety reduced from 36.5% to 9.5% (p<0.0001), fear from 40.6% to 4.9% (p<0.0001), image deterioration from 19.2% to 10.9% (p=0.002) and insomnia from 39.3% to 2.5% (p<0.0001). All the categorical dimensions evaluated for each NANDA International diagnosis improved (p<0.0001). Conclusion: Patients with an ostomy and effluent leakage in the early postoperative period clearly benefited from the use of both a light convex appliance and mouldable ring. This approach had a positive impact on number of leakages per day, peristomal skin status and patient satisfaction, as well as meeting several NANDA International nursing diagnosis criteria.

Hot-spots detection in count data by Poisson assisted smooth sparse tensor decomposition

Count data occur widely in many bio-surveillance and healthcare applications, e.g. the numbers of new patients of different types of infectious diseases from different cities/counties/states repeatedly over time, say, daily/weekly/monthly. For this type of count data, one important task is the quick detection and localization of hot-spots in terms of unusual infectious rates so that we can respond appropriately. In this paper, we develop a method called Poisson assisted Smooth Sparse Tensor Decomposition (PoSSTenD), which not only detect when hot-spots occur but also localize where hot-spots occur. The main idea of our proposed PoSSTenD method is articulated as follows. First, we represent the observed count data as a three-dimensional tensor including (1) a spatial dimension for location patterns, e.g. different cities/countries/states; (2) a temporal domain for time patterns, e.g. daily/weekly/monthly; (3) a categorical dimension for different types of data sources, e.g. different types of diseases. Second, we fit this tensor into a Poisson regression model, and then we further decompose the infectious rate into two components: smooth global trend and local hot-spots. Third, we detect when hot-spots occur by building a cumulative sum (CUSUM) control chart and localize where hot-spots occur by their LASSO-type sparse estimation. The usefulness of our proposed methodology is validated through numerical simulation studies and a real-world dataset, which records the annual number of 10 different infectious diseases from 1993 to 2018 for 49 mainland states in the United States.

Interdisciplinary applications of human time use with generalized lexicons.

Time use studies quantify what people do, over particular time intervals. The results of these studies have illuminated diverse and important aspects of societies and economies, from populations around the world. Yet, these efforts have advanced in a fragmented manner, using non-standardized descriptions (lexicons) of time use that often require researchers to make arbitrary designations among non-exclusive categories, and are not easily translated between disciplines. Here we propose a new approach, assembling multiple dimensions of time use to construct what we call the human chronome, as a means to provide novel interdisciplinary perspectives on fundamental aspects of human behaviour and experience. The approach is enabled by parallel lexicons, each of which aims for low ambiguity by focusing on a single coherent categorical dimension, and which can then be combined to provide a multi-dimensional characterization. Each lexicon should follow a single, consistent theoretical orientation, ensure exhaustiveness and exclusivity, and minimize ambiguity arising from temporal and social aggregation. As a pragmatic first step towards this goal, we describe the development of the Motivating- Outcome- Oriented General Activity Lexicon (MOOGAL). The MOOGAL is theoretically oriented towards the outcomes of activities, is applicable to any human from hunter-gatherers to modern urbanites, and deliberately focuses on the physical outcomes which motivate the undertaking of activities to reduce ambiguity from social aggregation. We illustrate the utility of the MOOGAL by comparing it with existing economic, sociological and anthropological lexicons, showing that it exhaustively covers the previously-defined activities with low ambiguity, and apply it to time use and economic data from two countries. Our results support the feasibility of using generalized lexicons to incorporate diverse observational constraints on time use, thereby providing a rich interdisciplinary perspective on the human system that is particularly relevant to the current period of rapid social, technological and environmental change.

Representations of General Linear Groups in the Verlinde Category

In this article, we construct affine group schemes GL(X) where X is any object in the Verlinde category in characteristic p and classify their irreducible representations. We begin by showing that for a simple object X of categorical dimension i, this representation category is semisimple and is equivalent to the connected component of the Verlinde category for SLi. Subsequently, we use this along with a Verma module construction to classify irreducible representations of GL(nL) for any simple object L and any natural number n. Finally, parabolic induction allows us to classify irreducible representations of GL(X) where X is any object in Verp.