Perspective Of Human Cognition Research Articles

DigCode—A generic mid-air gesture coding method on human-computer interaction

With high flexibility and rich semantic expressiveness, mid-air gesture interaction is an important part of natural human-computer interaction (HCI) and has broad application prospects. However, there is no unified representation frame for designing, recording, investigating and comparing HCI mid-air gestures. Therefore, this paper proposes an interpretable coding method, DigCode, for HCI mid-air gestures. DigCode converts the unstructured continuous actions into structured discrete string encoding. From the perspective of human cognition and expression, the research employed psychophysical methods to divide gesture actions into discrete intervals, defined the coding rules of representation in letters and numbers, and developed automated programs to enable encoding and decoding by using gesture sensors. The coding method can cover the existing representations of HCI mid-air gestures by considering human understanding and computer recognition and can be applied to HCI mid-air gesture design and gesture library construction.

Evaluating Effectiveness of Interactivity in Contour-Based Geospatial Visualizations.

Contour maps are an essential tool for exploring spatial features of the terrain, such as distance, directions, and surface gradient among the contour areas. User interactions in contour-based visualizations create approaches to visual analysis that are noticeably different from the perspective of human cognition. As such, various interactive approaches have been introduced to improve system usability and enhance human cognition for complex and large-scale spatial data exploration. However, what user interaction means for contour maps, its purpose, when to leverage, and design primitives have yet to be investigated in the context of analysis tasks. Therefore, further research is needed to better understand and quantify the potentials and benefits offered by user interactions in contour-based geospatial visualizations designed to support analytical tasks. In this paper, we present a contour-based interactive geospatial visualization designed for analytical tasks. We conducted a crowd-sourced user study (N=62) to examine the impact of interactive features on analysis using contour-based geospatial visualizations. Our results show that the interactive features aid in their data analysis and understanding in terms of spatial data extent, map layout, task complexity, and user expertise. Finally, we discuss our findings in-depth, which will serve as guidelines for future design and implementation of interactive features in support of case-specific analytical tasks on contour-based geospatial views.

Visions of light: New reconstruction techniques of photometric data and visual perception inside Etruscan painted tombs

This study utilises reconstruction technologies together with material and experimental photometric data to investigate how light intersects with perceptual processes inside subterranean painted tombs in Tarquinia, Italy. A fifth century BCE tomb, the Tomba dei Demoni Azzurri located in the Necropoli dei Monterozzi in Tarquinia, Italy is used to illustrate the usefulness of the methodology. Patterns involving the organisation of tomb imagery together with an analysis of specific lighting conditions in a scaled 3D space reframes tomb paintings in a manner that further recognises the performance of burial rites and other funerary activities from the perspective of human cognition. The methodology has applicability across archaeological settings and regions, particularly with respect to settings where little or no natural lighting is present.

A Three-Way Decision Methodology With Regret Theory via Triangular Fuzzy Numbers in Incomplete Multiscale Decision Information Systems

The three-way decision theory provides a three-way philosophical thinking to solve problems, and the regret theory quantifies the risk preferences of decision makers under different psychological behaviors. On the one hand, the combination of these two theories makes models more practical by considering the psychological behaviors of decision makers. On the other hand, we can effectively combine the advantages of the three-way decision theory with the regret theory to highlight the interpretability of decision making processes. In this paper, we propose a novel approximate estimation method for incomplete utility values via the regret theory and establish a wide sense of three-way decision model on incomplete multi-scale decision information systems. First, the degree of consistency for each scale is measured via using the dependency degree, then the optimal subsystem is selected by evaluating the scale selection cost. Further, the incomplete multi-scale evaluation information is transformed into triangular fuzzy numbers via linguistic term sets. Second, in light of fuzzy evaluation values and trade-off factors, an estimation method for incomplete fuzzy subsystems is constructed, which can be used to calculate the utility difference and regret-rejoicing values for pairwise comparisons. Finally, from the perspective of human cognition, the tri-partition and the corresponding decision rules are built by the tolerance degree, and the ranking of objects is calculated by the relative closeness degree. Additionally, multi-aspect comparative and experimental analyses are performed by extensive experiments, and the feasibility, validity and stability of the constructed model are shown by parametric analyses.

Understanding situation awareness in SOCs, a systematic literature review

Situation awareness is shown through human factors research to be a valuable construct to understand and improve how humans perform while operating complex systems in critical environments. Within cyber security one such environment is the Security Operations Center (SOC). With the increasing threat of hybrid warfare, knowledge about situation awareness within SOC environments, where human error or low performance may be detrimental, must be developed. This paper reports on the results of a Systematic Descriptive Literature Review of the current research on situation awareness within SOCs. The goal of the paper is to analyze how situation awareness is understood in the current research. To achieve this goal three aspects of understanding were addressed: Theoretical foundations; levels of conceptualization; and measurement of situation awareness. Theoretical foundations in the literature were assessed by how situation awareness was defined and the presence of references to theoretical models of SA. The results show a clear trend of basing the research on Endsley's three level situation awareness model; this model has been developed into a domain specific formulation called “Cyber Situation Awareness”. Some parts of the literature, particularly in research aimed at developing tools for improving situation awareness, lack a theoretical foundation; some refer to alternative theoretical foundations of situation awareness like Stanton et al.’s Distributed Situation Awareness. Further, a balance between conceptualizations on the individual, group and system level has been identified. Within research aimed at developing tools for improving situation awareness there are some examples of specialized and precise measurements of situation awareness, but in general the research seems too reliant on indirect measures of situation awareness. The paper concludes with the proposition of connecting the systems-based theoretical perspective of distributed situation awareness into the research, utilizing a systems level conceptualization of situation awareness. This might prove to be a useful bridge between the human cognitive perspective of situation awareness and the development of the complex technical environment of critical importance that SOCs represent.

Editorial: There Are Promises to Keep and Miles to Go Before I Leave…

Editorial: There Are Promises to Keep and Miles to Go Before I Leave…

Examining interaction techniques in data visualization authoring tools from the perspective of goals and human cognition: a survey

We review the state-of-the-art interaction techniques of visualization authoring tools. The visualization tools tend to help users in the creation, exploration, or presentation of visualizations. Also, they allow users to craft expressive designs or extract data from visualizations. The review presents the interaction techniques integrated into the tools for those mentioned above five high-level goals. We cover each goal’s tools and summarize how a sequence in the independent interaction techniques leads to the goal. We also discuss how well researchers had evaluated the usability and intuitiveness of interaction techniques. We aimed to reflect on the strengths and weaknesses of the evaluations. To that end, from the perspective of human cognition, we reviewed the goals, procedures, and findings of evaluations. Principally, human cognition is engaged when they perform tasks in a tool. The interaction techniques bridge the gap between human cognition and the goals they want to achieve from the tool. To sum up, in this review, we present a novel triad ‘goals-interaction techniques-cognition’ taxonomy. Besides, the review suggests the need for further work to enhance tools and understand users.

A Human-Cognitive Perspective of Users’ Password Choices in Recognition-Based Graphical Authentication

ABSTRACTGraphical password composition is an important part of graphical user authentication which affects the strength of the chosen password. Considering that graphical authentication is associated with visual search, perception, and information retrieval, in this paper we report on an eye-tracking study (N = 109) that aimed to investigate the effects of users’ cognitive styles toward the strength of the created passwords and shed light into whether and how the visual strategy of the users during graphical password composition is associated with the passwords’ strength. For doing so, we adopted Witkin’s Field Dependence-Independence theory, which underpins individual differences in visual information and cognitive processing, as graphical password composition tasks are associated with visual search. The analysis revealed that users with different cognitive processing characteristics followed different patterns of visual behavior during password composition which affected the strength of the created passwords. The findings underpin the need of considering human-cognitive characteristics as a design factor in graphical password schemes. The paper concludes by discussing implications for improving recognition-based graphical passwords through adaptation and personalization techniques based on individual cognitive characteristics.

워드 임베딩과 단어 네트워크 분석을 활용한 비지도학습 기반의 문서 다중 범주 가중치 산출 : 휴대폰 리뷰 사례를 중심으로

Due to the increased amounts of online documents, there is a growing demand for text categorization that categorizes documents into predefined categories. Many approaches to this problem are based on supervised machine learning which couldn’t be applied to unlabeled data. However, large number of documents, such as online cell phone reviews, have no category information and key categories are not predefined. To solve these problems, we propose unsupervised document multi-labeling method based on word embedding and word network analysis. After embedding words in a lower dimensional space using Word2Vec technique, we generate a weight matrix by calculating similarities between words. We create a word network using this matrix and extract the key categories from this network. With key category-weight matrix and co-occurrence matrix, we generate a document-category score matrix. To verify our proposed method, we collect 298,206 cell phone reviews from four review websites. Then, we compared the results of the proposed method with labeled documents from human cognitive perspective.

Multi-criteria game model based on the pairwise comparisons of strategies with Z-numbers

The Z-number is the most general representation of real-life information with reliability, and it also exhibits the highest descriptive power from the perspective of human cognition. This study focuses on the development of a computationally simple and effective Z-number model to address game problems by systematically comparing pairwise strategies derived from different players. The processing of Z-numbers requires computing fuzzy and probabilistic uncertainties; then, the cloud model is suggested to handle bimodal restriction in Z-numbers. In this manner, a novel concept of asymmetric normal Z-value (ANZ) is proposed. Subsequently, the concordance/discordance index and outranking relations of ANZs are suggested based on classic outranking rules. Next, an innovative game model is established by modeling the outranking relations of strategies of different players under multiple criteria. Finally, an illustrative example concerning enterprise market competition is provided to demonstrate the established model.

Presence and Absence of Individuals in Diagrammatic Logics: An Empirical Comparison

The development of diagrammatic logics is strongly motivated by the desire to make formal reasoning accessible to broad audiences. One major research problem, for which surprisingly little progress has been made, is to understand how to choose between semantically equivalent diagrams from the perspective of human cognition. The particular focus of this paper is on choosing between diagrams that represent either the presence or absence of individuals. To understand how to best make this choice, we conducted an empirical study. We found that representing the presence of individuals supported task performance either significantly better than, or no worse than, representing the absence of individuals. The particularly striking feature of our results was that representing the absence of individuals in a way that makes the diagram highly cluttered is detrimental to human cognition. As a result, diagrams with this feature should be avoided, but diagrams using presence (irrespective of diagram clutter) or low-cluttered absence can be used to support cognition in the context of the tasks performed in our study.

Situating Machine Intelligence Within the Cognitive Ecology of the Internet

The Internet is an important focus of attention for the philosophy of mind and cognitive science communities. This is partly because the Internet serves as an important part of the material environment in which a broad array of human cognitive and epistemic activities are situated. The Internet can thus be seen as an important part of the ‘cognitive ecology’ that helps to shape, support and (on occasion) realize aspects of human cognizing. Much of the previous philosophical work in this area has sought to analyze the cognitive significance of the Internet from the perspective of human cognition. There has, as such, been little effort to assess the cognitive significance of the Internet from the perspective of ‘machine cognition’. This is unfortunate, because the Internet is likely to exert a significant influence on the shape of machine intelligence. The present paper attempts to evaluate the extent to which the Internet serves as a form of cognitive ecology for synthetic (machine-based) forms of intelligence. In particular, the phenomenon of Internet-situated machine intelligence is analyzed from the perspective of a number of approaches that are typically subsumed under the heading of situated cognition. These include extended, embedded, scaffolded and embodied approaches to cognition. For each of these approaches, the Internet is shown to be of potential relevance to the development and operation of machine-based cognitive capabilities. Such insights help us to appreciate the role of the Internet in advancing the current state-of-the-art in machine intelligence.

Cognitive shape similarity assessment for 3D part search

Mass customization aims to satisfy diverse customer requirements with high product variety while maintaining reasonable manufacturing cost and lead time. Allowing customers to perceive product differentiation is a critical factor for most design methods developed for mass customization. This study examines 3D part search from the human cognitive perspective. We designed and conducted a quasi-factorial experiment to understand how structured variations of four factors—the shape, type, dimension, and location of the feature volume of a part model—affect human judgment of part similarity. The corresponding factorial similarity values were computed with different shape signatures in the form of the feature adjacency graph. The human responses were obtained by paired comparisons of test parts, and quantified as the cognitive similarity. Statistical analysis of the experimental results showed that the type and shape factors played an important role in the subjects’ judgments. Back-propagation neural networks were trained to model the correlations between the cognitive and the factorial similarity values. The performance of the networks validates our idea of incorporating human cognition into assessment of 3D part similarity. This study presents a systematic approach for personalized part search that reflects individual perception of shape similarity.

Coherent narrative summarization with a cognitive model

For summary readers, coherence is no less important than informativeness and is ultimately measured in human terms. Taking a human cognitive perspective, this paper is aimed to generate coherent summaries of narrative text by developing a cognitive model. To model coherence with a cognitive background, we simulate the long-term human memory by building a semantic network from a large corpus like Wiki and design algorithms to account for the information flow among different compartments of human memory. Proposition is the basic processing unit for the model. After processing a whole narrative in a cyclic way, our model supplies information to be used for extractive summarization on the proposition level. Experimental results on two kinds of narrative text, newswire articles and fairy tales, show the superiority of our proposed model to several representative and popular methods.

Comprometimento conjunto, normatividade e situatividade entre os muros da escola

Considerando a perspectiva situada e triádica da cognição humana e os conceitos de comprometimento conjunto, normatividade e situatividade, abordam-se os fatos e personagens presentes no filme Entre os muros da escola, em especial o comportamento da personagem-aluna Esmeralda. Observa-se a interação entre alunos e professores em termos do seu objetivo, o qual, diferentemente da idealização que supõe o aprendizado como a finalidade do ensino, mostra-se estar voltado para a aprovação; essa diferenciação acarreta o entendimento de que os reais papéis e ações das pessoas em sala de aula diferenciam-se muito dos que têm sido idealizados na sociedade. Tais postulações são comentadas em relação ao ensino do português como língua materna no Brasil.

RADICAL EXTRACTION USING AFFINE SPARSE MATRIX FACTORIZATION FOR PRINTED CHINESE CHARACTERS RECOGNITION

Each Chinese character is comprised of radicals, where a single character (compound character) contains one (or more than one) radicals. For human cognitive perspective, a Chinese character can be recognized by identifying its radicals and their spatial relationship. This human cognitive law may be followed in computer recognition. However, extracting Chinese character radicals automatically by computer is still an unsolved problem. In this paper, we propose using an improved sparse matrix factorization which integrates affine transformation, namely affine sparse matrix factorization (ASMF), for automatically extracting radicals from Chinese characters. Here the affine transformation is vitally important because it can address the poor-alignment problem of characters that may be caused by internal diversity of radicals and image segmentation. Consequently we develop a radical-based Chinese character recognition model. Because the number of radicals is much less than the number of Chinese characters, the radical-based recognition performs a far smaller category classification than the whole character-based recognition, resulting in a more robust recognition system. The experiments on standard Chinese character datasets show that the proposed method gets higher recognition rates than related Chinese character recognition methods.