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Multi-modal data exploration in a Mixed Reality Environment Using Coordinated Multiple Views

Multi-modal Data Exploration in a Mixed Reality Environment ...

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Human Interface and the Management of Information (HIMI) part of International conference on Human-Computer Interaction (HCII)

作者： Sardana, Disha Kahu, Sampanna Yashwant Gracanin, Denis Matkovic, Kresimir Virginia Tech Blacksburg VA 24061 USA VRVis Res Ctr Vienna Austria

ISBN: (纸本)9783030783204;9783030783211

Immersive analytics is an emerging field of data exploration and analysis in immersive environments. The main idea is to use visual analytics in a fully immersive 3D space. The availability of immersive Extended Reality systems has increased tremendously recently, but it is still not as widely used as conventional 2D displays. We describe an immersive analysis system for spatio-temporal data and compare how it performs in an immersive environment and on a conventional 2D display. We provide a novel view called map-plot that enables analysis and exploration of spatial time series data. We also design an embodied interaction for the map-plot view. The approach is realized based on the coordinated multiple views paradigm. In addition to the map-plot view, several standard views are available. Voice commands and spatial audio are used to support interaction and increase users' embodiment. The findings from a user study show that developed system is much more efficient in a real immersive environment than using conventional 2D displays.

关键词： Immersive analytics Mixed reality Embodied interaction Coordinated multiple views

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Effect of Gaze visualization on Task Efficiency and User Behavior for Guidance Scenarios in Co-Located AR Collaboration

Effect of Gaze Visualization on Task Efficiency and User Beh...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE conference on

作者： Froso Sarri Katerina Mania School of Electrical & Computer Engineering Technical University of Crete Greece

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Augmented Reality (AR)-enabled collaboration enhances contextual guidance in shared environments, where unambiguous cues are essential, for swift and accurate task completion. Gaze-based cues offer clear, non-verbal indication of intent, reducing interaction ambiguity. While prior research has studied the effectiveness of gaze-based visualization in scenarios where collaborators share the same level of knowledge, less attention has been shown to guidance scenarios, where one user provides task-related information to another. Existing studies often focus on task outcomes (e.g., completion time, error rate) without analyzing gaze data to gain further insight into user behavior and attention. This study leverages gaze-based cues as an active means of communication in guidance scenarios, assessing their impact on both task performance and user behavior through gaze data analysis. The developed system incorporates gaze-based visualizations, including dynamic representations of gaze behavior, to deliver task-critical guidance. These are compared to verbal instructions using quantitative metrics for task effectiveness and gaze analysis, alongside subjective feedback, to determine whether they reduce ambiguity and enhance collaboration. Our study showed that gaze-based visualizations significantly reduced task related errors, with contextual triggered cues offering the best balance between speed and correctness. Gaze analysis revealed that gaze-based visualizations effectively directed participants’ attention to task-relevant areas, reducing unnecessary visual exploration. Participants reported lower perceived workload in gaze-based conditions, further supporting their effectiveness in enhancing collaboration and reducing ambiguity.

关键词： Human computer interaction Measurement Hands visualization Three-dimensional displays Error analysis Collaboration data visualization Information sharing Augmented reality

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Unmasking Public Perception: A Mixed-Methods exploration of Social Media Discourse on U.S. Illegal Immigration

Unmasking Public Perception: A Mixed-Methods Exploration of ...

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IEEE International conference on Big data

作者： Salim Sazzed Sharif Ullah Department of Computer Science Georgia Southern University GA USA Department of Computer Science and Engineering University of Central Arkansas Conway AR USA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

With illegal immigration remaining a contentious issue in the United States, understanding public perception—particularly as expressed on social media—is vital for informed policymaking and advocacy. This study investigates the discourse surrounding illegal immigration in the U.S. through both quantitative and qualitative analyses of data from Reddit. We identify key themes and perspectives on four critical aspects: (i) U.S. policy toward illegal immigration, (ii) strategies for mitigating illegal immigration, (iii) issues arising from illegal immigration, and (iv) hostile rhetoric targeting undocumented immigrants. Additionally, we conduct emotion analysis to ascertain prevalent emotional responses within the discourse. Our findings reveal both challenges and perceived benefits associated with lenient border policies, including difficulties in monitoring extensive border areas and the exploitation of low-wage labor. We observe a wide range of suggested measures to reduce illegal migration, including stringent actions against employers of undocumented workers, proposals to abolish birthright citizenship, and calls for increased legal migration. Emotion analysis indicates significant levels of anger and disgust expressed in the comments. Furthermore, we document instances of anti-immigrant rhetoric, some of which are inhumane and include calls for violence against undocumented individuals. This research provides valuable insights into societal attitudes toward illegal immigration, informing policymakers and advocacy groups in their decision-making.

关键词： Social networking (online) Law Decision making Big data Rhetoric Emotional responses Proposals Monitoring

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Textual vs. visual Fake News: A Deception Showdown 10

Textual vs. Visual Fake News: A Deception Showdown

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10th IEEE International conference on Cloud Computing in Emerging Markets, CCEM 2021

作者： Caramancion, Kevin Matthe College of Emergency Preparedness and Cybersecurity University at Albany State University of New York Albany New York United States

ISBN: (纸本)9781665408813

This paper explores how the textuality or style of contents (iv) affect the mis/disinformation risk of information consumers. Using a 20-item test that consists of 10 purely textual contents and 10 visual contents, the author tested which could likely to be more deceptive (DV1) to the subjects (N=33). The second part of the analysis measured which among the two ignited more Doubt (DV2) among the participants. The main data analysis technique employed for this study is a paired sample t-Test. Important findings of the study include the revelation that purely textual contents can be slightly more deceptive, and visual contents can ignite more Doubt. The intended target audience of this paper are information scientists, digital forensic professionals, communication experts, policymakers possibly seeking references on this aspect. © 2021 IEEE.

关键词： Cybersecurity

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visual analysis of Spatio-temporal Phenomena with 1D Projections

Visual Analysis of Spatio-temporal Phenomena with 1D Project...

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Eurographics / IEEE VGTC conference on visualizaation

作者： Franke, M. Martin, H. Koch, S. Kurzhals, K. Univ Stuttgart Stuttgart Germany Swiss Fed Inst Technol Zurich Switzerland Inst Adv Res Artificial Intelligence Vienna Austria

It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio-temporal data, based on a set of neighborhood-preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real-world application scenarios and discuss the feedback we received from domain and visualization experts.

关键词： Computer graphics

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THE BRIDGE OVER THE ADDA RivER IN BRivIO: HISTORY, FULL-SCALE TESTING AND FE MODELLING

THE BRIDGE OVER THE ADDA RIVER IN BRIVIO: HISTORY, FULL-SCAL...

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12th International conference on Structural analysis of Historical Constructions (SAHC 2021)

作者： Zonno, Giacomo Gentile, Carmelo Politecn Milan Dept Architecture Built Environm & Construct Engn Piazza Leonardo Da Vinci 32 I-20133 Milan Italy

ISBN: (纸本)9788412322200

Selected results from the investigation program of a historic R. C. bridge are presented in the paper. The bridge, crossing the Adda river between the Municipalities of Brivio and Cisano Bergamasco, consists of three tied arch spans, about 44.0 m length each, and represents a crucial node for the vehicular traffic of the region. After a maintenance intervention performed on one pier, the local Authorities committed to Politecnico di Milano an extensive investigation including: (1) documentary research and review of the bridge history;(ii) visual inspection and geometric survey of each span;(iii) full-scale load tests and ambient vibration tests;(iv) FE modelling of each span and validation of the numerical models (through comparison with the available experimental results) and (v) structural assessment of the bridge in its present condition. After a concise review of the bridge history, the paper summarizes the complete results of the experimental tests performed on one span (visual inspection, geometric survey, full-scale load tests and dynamic tests) as well as the development of numerical models.

关键词： Reinforced Concrete Arch Bridge Operational Modal analysis Finite Element Modeling and Updating Non-Destructive techniques

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VEHICLE: Validation and exploration of the Hierarchical Integration of Conflict Event data

VEHICLE: Validation and Exploration of the Hierarchical Inte...

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Eurographics / IEEE VGTC conference on visualizaation

作者： Mayer, B. Lawonn, K. Donnay, K. Preim, B. Meuschke, M. Univ Magdeburg Dept Simulat & Graph Magdeburg Germany Univ Jena Dept Comp Sci Jena Germany Univ Zurich Dept Polit Sci Zurich Switzerland

The exploration of large-scale conflicts, as well as their causes and effects, is an important aspect of socio-political analysis. Since event data related to major conflicts are usually obtained from different sources, researchers developed a semi-automatic matching algorithm to integrate event data of different origins into one comprehensive dataset using hierarchical taxonomies. The validity of the corresponding integration results is not easy to assess since the results depend on user-defined input parameters and the relationships between the original data sources. However, only rudimentary visualization techniques have been used so far to analyze the results, allowing no trustworthy validation or exploration of how the final dataset is composed. To overcome this problem, we developed VEHICLE, a web-based tool to validate and explore the results of the hierarchical integration. For the design, we collaborated with a domain expert to identify the underlying domain problems and derive a task and workflow description. The tool combines both traditional and novel visual analysis techniques, employing statistical and map-based depictions as well as advanced interaction techniques. We showed the usefulness of VEHICLE in two case studies and by conducting an evaluation together with conflict researchers, confirming domain hypotheses and generating new insights.

关键词： Integration

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Overview of the ImageCLEF 2022: Multimedia Retrieval in Medical, Social Media and Nature Applications 13th

Overview of the ImageCLEF 2022: Multimedia Retrieval in Medi...

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13th International conference of the CLEF-Association (CLEF) - Experimental IR meets Multilinguality, Multimodality, and Interaction

作者： Ionescu, Bogdan Muller, Henning Peteri, Renaud Ruckert, Johannes Ben Abacha, Asma de Herrera, Alba G. Seco Friedrich, Christoph M. Bloch, Louise Brungel, Raphael Idrissi-Yaghir, Ahmad Schafer, Henning Kozlovski, Serge Cid, Yashin Dicente Kovalev, Vassili Stefan, Liviu-Daniel Constantin, Mihai Gabriel Dogariu, Mihai Popescu, Adrian Deshayes-Chossart, Jerome Schindler, Hugo Chamberlain, Jon Campello, Antonio Clark, Adrian Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Sierre Switzerland Univ La Rochelle La Rochelle France Univ Appl Sci & Arts Dortmund Dortmund Germany Microsoft Redmond WA USA Univ Essex Colchester Essex England Inst Informat Minsk BELARUS Univ Warwick Coventry W Midlands England Univ Paris Saclay LIST CEA F-91120 Palaiseau France Wellcome Trust Res Labs London England

ISBN: (纸本)9783031136436;9783031136429

This paper presents an overview of the ImageCLEF 2022 lab that was organized as part of the conference and Labs of the Evaluation Forum - CLEF Labs 2022. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2022, the 20th edition of ImageCLEF runs four main tasks: (i) a medical task that groups two previous tasks, i.e., caption analysis and tuberculosis prediction, (ii) a social media aware task on estimating potential real-life effects of online image sharing, (iii) a nature coral task about segmenting and labeling collections of coral reef images, and (iv) a new fusion task addressing the design of late fusion schemes for boosting the performance, with two real-world applications: image search diversification (retrieval) and prediction of visual interestingness (regression). The benchmark campaign received the participation of over 25 groups submitting more than 258 runs.

关键词： Medical image classification medical image caption analysis tuberculosis prediction coral image segmentation and classification prediction of effects of online image sharing late fusion for search diversification and interestingness prediction ImageCLEF lab

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Adaptive visualizations for enhanced data understanding and interpretation 21

Adaptive visualizations for enhanced data understanding and ...

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29th ACM conference on User Modeling, Adaptation and Personalization, UMAP 2021

作者： Amyrotos, Christos UCLan Cyprus Pyla Cyprus

ISBN: (纸本)9781450383660

In a data driven economy where data volume and dimensions are explosively increasing, businesses rely on business intelligence and analytics (BI&A) platforms for analysing their data and coming to beneficial decisions. With the ever-growing generation of data, the process of data analysis is becoming more complicated for the business users, as the exploration of more demanding use cases increases. While the existing BI&A platforms provide myriads of data visualizations that support data exploration, none of those account for the user's individual differences, needs or requirements, and thus may hinder the user's understanding of visual data and consequently their decision-making processes. This work embarks on an interdisciplinary endeavour to introduce a human-centred adaptive data visualizations framework in the context of business, as the core of an adaptive data analytics platform, that aims to enhance the business user's decision making by increasing her understanding of data. The framework is built using a multi-dimensional human-centred user model that goes beyond traditional user characteristics and accounts for cognitive factors, domain expertise and experience and factors related to the business context i.e., data, visualizations and tasks;a data visualization engine that will recommend to the unique-user the best-fit data visualizations based on the abovementioned user model;and an intelligent data analytics component that enhances the efficiency and effectiveness of the data exploration process by leveraging user interactions during the explorations to further inform the user model on the user's expertise and experience. © 2021 Owner/Author.

关键词： data visualization

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Mondrian Abstraction and Language Model Embeddings for Differential Pathway analysis

Mondrian Abstraction and Language Model Embeddings for Diffe...

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IEEE International conference on Bioinformatics and Biomedicine (BIBM)

作者： Fuad Al Abir Jake Y. Chen Department of Computer Science University of Alabama at Birmingham Birmingham AL USA Systems Pharmacology AI Research Center (SPARC) School of Medicine University of Alabama at Birmingham Birmingham AL USA

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

In this study, we introduce the Mondrian Map, an innovative visualization tool inspired by Piet Mondrian’s abstract art, to address the complexities inherent in visualizing biological networks. The Mondrian Map enables clear and meaningful representations of biological pathways by converting intricate biological data into a structured and intuitive format, facilitating a deeper understanding of molecular dynamics. Each pathway is represented by a square whose size corresponds to fold change, with color indicating the direction of regulation (up or down) and statistical significance. The spatial arrangement of pathways is derived from language model embeddings, preserving neighborhood relationships and enabling the identification of clusters of related pathways. Additionally, colored lines highlight potential crosstalk between pathways, with distinctions between short- and long-range functional interactions. In a glioblastoma multiforme (GBM) case study, the Mondrian Map effectively revealed distinct pathway patterns across patient profiles at different stages of disease progression. By surpassing traditional enriched pathway tables and presenting pathways in a relative context without causing visual information overload, this work highlights the tool’s potential to enhance downstream bioinformatics analyses by providing a more comprehensive and visually accessible overview of pathway interactions, offering new avenues for therapeutic exploration and personalized medicine.

关键词： Analytical models visualization Image color analysis Biological system modeling Precision medicine data visualization data models Regulation Bioinformatics Diseases

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