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IEEE International Magnetics conference (INTERMAG)

作者： Pile, Santa Lesota, Oleg Peter, Silvan David Humer, Christina Gasser, Martin Johannes Kepler Univ Linz A-4040 Linz Austria Univ Appl Arts Vienna A-1010 Vienna Austria

ISBN: (纸本)9798350362213;9798350362220

analysis of complex data such as spin wave behavior requires the use of sophisticated visualization techniques, which might not always be enough. An approach to combining data sonification with interactive visualization of a spin-wave transient response in confined Ni80Fe20 microstrips of different shapes on uniform MW field excitation is discussed in this work. Developed prototype has been successfully presented in the science-communication framework at a digital art exhibition.

关键词： Spin Waves Sonification data analysis Magnonics

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Multi-target modeling of spine movements for signing Avatar

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UNIVERSAL ACCESS IN THE INFORMATION SOCIETY 2025年第1期24卷 5-17页

作者： Choudhury, Shatabdi DePaul Univ Sch Comp 243 S Wabash Ave Chicago IL 60604 USA

Virtual avatars are increasingly used in sign language interpretation (McDonald and Wolfe in Comput Speech Lang 54:1-20, 2019), and education (De Martino et al. in Univ Access Inf Soc 16(3):793-808, 2017) to facilitate communication between deaf and hard-of-hearing and hearing individuals. While technological advances have allowed the creation of avatars that can portray sign language with more realistic and believable motion, many of these avatars still lack naturalness and supporting movements. Often not included in linguistic annotations, these details are crucial for creating lifelike and communicative animations (Jancso et al. in International conference on computers helping people with special needs, Springer, Berlin, pp 438-445, 2016). This paper proposes using multi-target modeling of spine angle movements in signing avatars using motion capture data. We first describe the data collection and pre-processing steps of the motion capture data, including input features such as the spine angles and left and right wrist positions. We explore various modeling techniques, including deep learning, linear regression, and random forest. We examine the visualization of partial dependence plots (PDP) (Friedman in Ann Stat 29(5):1189-1232, 2001) and individual conditional expectation (ICE) plots to understand the relationships between the input and output variables. Our findings indicate that the deep learning model is the most effective and produces a smooth prediction. PDP and ICE plots provided valuable visualization insight into the behavior of the models and could be helpful in further analysis (Petch et al. in Can J Cardiol 38(2):204-213, 2021). The approach represents a promising step toward creating more realistic and expressive signing avatars, ultimately improving the engagement and user experience with the avatar.

关键词： Sign language Avatar Deep learning Multi-target regression Partial dependence plots Motion capture data

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Interactive Visual analysis of COVID-19 28

Interactive Visual Analysis of COVID-19

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28th International conference on Information Visualisation (IV)

作者： Varga, Margaret Ndoni, Adelica Traeber-Burdin, Susan Panganiban, April Rose Lavigne, Valerie Univ Oxford Dept Biol Oxford England NATO Commun & Informat Agcy NCIA The Hague Netherlands Fraunhofer FKIE Human Machine Syst Bonn Germany Air Force Res Lab Dayton OH USA Def Res & Dev Canada Valcartierr PQ Canada

ISBN: (纸本)9798350380170;9798350380163

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. It was first detected in China in December 2019. It spreads between people in close contact. On the 11(th) March 2020 the WHO declared the outbreak of the virus as a pandemic, which signaled a significant acceleration in the global response to the COVID-19 outbreak, and recognized the widespread transmission of the virus across multiple countries and continents. data regarding COVID-19 was gathered and made available for open access. These data sources offer invaluable information for tracking, raising awareness and understanding of COVID-19, recognizing its impact, as well as informing the general public, health authorities, policy makers, situation managers and decision makers. However, COVID-19 data in its raw form is complex and difficult to understand and analyze. The application of visualization together with human factor design principles in a complex systems framework provides an effective means for exploiting these big and complex datasets. These techniques can transform such inherently non-visual data into intuitive visual forms that enable users to gain insight into, and understanding of, information contained within the data. This paper discusses the application of visualization and development of interactive dashboards, set in a complex systems framework, to provide an effective means for the users to explore, analyze and gain awareness of the situation, thus enabling informed decision making.

关键词： COVID-19 visualization complex systems human factors visual analytics

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Summary of theWorkshop on Visual Methods and Analyzing Visual data in Human Computer Interaction 24

Summary of theWorkshop on Visual Methods and Analyzing Visua...

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Companion Proceedings of the conference on Interactive Surfaces and Spaces (ISS Companion)

作者： Wang, Zezhong Huron, Samuel Sturdee, Miriam Carpendale, Sheelagh Simon Fraser Univ Burnaby BC Canada Telecom Paris Inst Polytech Paris Paris France Univ St Andrews St Andrews Fife Scotland

ISBN: (纸本)9798400712784

Visual methods have become increasingly vital in Human Computer Interaction (HCI) research, particularly as we analyze and interpret the complex visual data that emerges from various interaction modalities. However, the methodologies for analyzing this visual data remain underdeveloped compared to textual data analysis. This workshop seeks to unite HCI researchers who work with visual data-such as hand sketches, photographs, physical artifacts, UI screenshots, videos, and information visualizations-to identify, name, and categorize methods for analyzing visual data in HCI.

关键词： Research Methods Qualitative Coding Analyzing Visuals

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data visualization analysis of Metacognition in BE Problem Solving: Re-categorization and Its Implications 8

Data Visualization Analysis of Metacognition in BE Problem S...

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8th International conference on Cloud Computing and Big data Analytics (ICCCBDA)

作者： Yin, Xueyan Guo, Guihang Guangdong Univ Foreign Studies South China Business Coll Sch English Language & Culture Guangzhou Peoples R China Guangdong Univ Foreign Studies Sch English Int Business Guangzhou Peoples R China

ISBN: (纸本)9781665455336

Widely acknowledged as knowledge and cognition about cognitive phenomena, metacognition has become a successful tool for researchers to investigate problem solving and other thinking processes in the instructional domain. However, much of the work on metacognition has studied these constructs piecemeal and mostly qualitatively with little evidence found about cognition in business English problem solving. In light of this, by statistically based re-categorization of metacognition in business English context, we investigated the interplay of metacognitive aspects in BE problem solving. 105 third-year college students participated in the study. Metacognitive aspects (metacognitive experiences, metacognitive knowledge and metacognitive regulation) were quantitatively measured with statistical tools of SPSS, AMOS and Wordclouds, in which questionnaires and semi-structured interviews were employed to further explore 2 questions: (1) What are the prominent factors constituting BE metacognition? (2) To what extent is metacognition positively related to BE problem solving and perceived performance? Three categories of BE metacognition are identified and the data visualization analysis indicate a complex interplay of metacognition in BE problem solving, in which metacognitive knowledge and metacognitive regulation play a statistically significant role.

关键词： data visualization analysis metacognition re-categorization BE problem solving metacognitive regulation metacognitive knowledge metacognitive experience

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Design failures in data visualization programming activities 24

Design failures in data visualization programming activities

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23rd Annual ACM Interaction Design and Children conference, IDC 2024

作者： Fernandez, Cassia Blikstein, Paulo Lopes, Roseli De Deus Lopes Electronics Systems Dept. Universidade de São Paulo São Paulo Brazil Teachers College Columbia University New York United States

ISBN: (纸本)9798400704420

In this pictorial, we critically analyze how students engaged in data representation activities using Playdata, a block-based programming environment tailored for data visualization purposes. Drawing upon data collected over two years with middle and high school students, we describe obstacles that impacted the interpretation of the data under analysis. These obstacles, here called "design failures", arose from either unexpected uses of the tool or shortcomings in the design of activities. We explore how each of these failures was used as an opportunity for refining both the tool's design and the associated activities. We conclude by offering recommendations for educators and researchers to support learners' engagement with visualization construction for effective reasoning with data. © 2024 ACM.

关键词： data visualization

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Understanding Comparative Genomics data visualization for Biodiversity Domain Through Persona-Based Interviews

Understanding Comparative Genomics Data Visualization for Bi...

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2024 IEEE International conference on Computing, ICOCO 2024

作者： Chan, Vei Siang Mohamed, Farhan Bin Salleh, Faezah Binti Mohd Iglesias, Andres Jamaludin, Najwa Ayuni Binti Mustafa Albakri, Ikmal Faiq Albakri Media and Game Innovation Center of Excellence Institute of Human Centered Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia Department of Biosciences Faculty of Science Universiti Teknologi Malaysia Johor Bahru Malaysia Department of Applied Mathematics and Computational Sciences Universidad de Cantabria Santander Spain Pervasive Computing & Educational Technology Department of Media Interactive Fakulti Teknologi Maklumat dan Komunikasi Universiti Teknikal Malaysia Melaka Melaka Malaysia

ISBN: (纸本)9798331530303

Understanding the needs of genomic data visualization techniques is important to help bioinformaticians to perform their comparative analytical tasks effectively. DNA sequencing datasets consist of a long sequential string of nucleotide base pairs combination and are often involved in multiple sequences alignment for comparative analysis. Therefore, existing challenges include designing suitable visualization layout and the need of user-centered approach to ensure optimal user experience. Existing works also featured heavily on the qualitative evaluation of comparative visualization tools, such as use cases and case studies, which are difficult to quantify and conduct follow up evaluation for tool improvement. Hence, this paper aims to understand the needs of visualization tools in comparative genomic analysis to identify visualization tasks and visual design requirements. The methodology includes the creation of semi-structured interview based on personas template as guiding questions and the synthesis of thematic analysis results. These results presented the requirements of the visualization tasks for the biodiversity domain based on comparative targets. For future work, this research will design, develop, and validate the comparative visualization tool based on the discovered requirements. ©2024 IEEE.

关键词： Genome

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High-level Grammars for visualization and Visual Analytics 36

High-level Grammars for Visualization and Visual Analytics

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36th SIBGRAPI conference on Graphics, Patterns and Images (SIBGRAPI)

作者： Moreira, Gustavo Laget, Marcos FerwiraI, Nivan Miranda, Fabio Univ Illinois Chicago IL 60680 USA Univ Fed Fluminense Niteroi RJ Brazil Univ Fed Pernambuco Recife PE Brazil

ISBN: (纸本)9798350338737;9798350338720

The increase in data availability and the popularization of data science brought a continuously growing need to use visualizations to explore complex data. Creating new visualizations, however, is a difficult task that often requires extensive programming expertise. High-level grammars for authoring visualizations provide a systematic and flexible way to specify visualizations in a declarative manner, lowering the entry barrier for data analysis. Such grammars effectively assist in the exploration of the visualization design space and of complex datasets. The goal of this tutorial paper is to then provide a summary of recently proposed grammars, so that a broad audience (e.g., students, researchers, practitioners) can better understand how they are designed and used in practice for visualization and visual analytics tasks.

关键词： Visual analytics

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Effective Use of Likert Scales in visualization Evaluations: A Systematic Review

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COMPUTER GRAPHICS FORUM 2022年第3期41卷 43-55页

作者： South, Laura Saffo, David Vitek, Olga Dunne, Cody Borkin, Michelle A. Northeastern Univ Boston MA 02115 USA

Likert scales are often used in visualization evaluations to produce quantitative estimates of subjective attributes, such as ease of use or aesthetic appeal. However, the methods used to collect, analyze, and visualize data collected with Likert scales are inconsistent among evaluations in visualization papers. In this paper, we examine the use of Likert scales as a tool for measuring subjective response in a systematic review of 134 visualization evaluations published between 2009 and 2019. We find that papers with both objective and subjective measures do not hold the same reporting and analysis standards for both aspects of their evaluation, producing less rigorous work for the subjective qualities measured by Likert scales. Additionally, we demonstrate that many papers are inconsistent in their interpretations of Likert data as discrete or continuous and may even sacrifice statistical power by applying nonparametric tests unnecessarily. Finally, we identify instances where key details about Likert item construction with the potential to bias participant responses are omitted from evaluation methodology reporting, inhibiting the feasibility and reliability of future replication studies. We summarize recommendations from other fields for best practices with Likert data in visualization evaluations, based on the results of our survey. A full copy of this paper and all supplementary material are available at https://***/exbz8/.

关键词： CCS Concepts • Human-centered computing → visualization design and evaluation methods Empirical studies in visualization

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visualization Techniques for Analyzing Learning Effects – Taking Python as an Example 5th

Visualization Techniques for Analyzing Learning Effects – T...

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5th EAI International conference on Multimedia Technology and Enhanced Learning, ICMTEL 2023

作者： Zhou, Keshuang Li, Yuyang Han, Xue Nanjing Normal University of Special Education Jiangsu Nanjing210000 China

ISBN: (纸本)9783031505799

With the advent of the information age, data visualization technology has gradually shown its unique features in various information fields, and its importance has gradually been attached importance by various governments and commercial departments. In teaching in our country, most schools simply use office software to create pie chart, histogram or table to realize visualization. This kind of teaching creates a single chart that doesn’t change at all. The content of the data visualization course of many school courses is outdated, and the way of visualization is not in line with the needs of The Times, that is, the content has been criticized as abstract, language mechanization, format and public culture [1]. In order to analyze the teaching quality and evaluate and improve it, this paper processes and analyzes the data exported from the teaching administration system based on python, mainly from three aspects: data acquisition, data processing and data analysis. Firstly, the python crawler technology is used to obtain students’ grades, secondly, the invalid data is processed, and finally, the matplotlib library is used to visualize the processed data, and the learning status of students in the class is analyzed and evaluated by combining the obtained images. Through the data processing of this paper, it realizes the hiding of the student’s name, protects the privacy of the student, and uses the graph to intuitively reflect the student’s grade distribution, which makes the grade analysis more convenient. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Python

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