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HCI International 2024 Posters : 26th International Conference on Human-Computer Interaction, HCII 2024, Washington, DC, USA, June 29 – July 4, 2024, Proceedings, Part VII / / edited by Constantine Stephanidis, Margherita Antona, Stavroula Ntoa, Gavriel Salvendy



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Autore: Stephanidis Constantine Visualizza persona
Titolo: HCI International 2024 Posters : 26th International Conference on Human-Computer Interaction, HCII 2024, Washington, DC, USA, June 29 – July 4, 2024, Proceedings, Part VII / / edited by Constantine Stephanidis, Margherita Antona, Stavroula Ntoa, Gavriel Salvendy Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Edizione: 1st ed. 2024.
Descrizione fisica: 1 online resource (475 pages)
Disciplina: 005.437
004.019
Soggetto topico: User interfaces (Computer systems)
Human-computer interaction
Application software
Artificial intelligence
Computer networks
User Interfaces and Human Computer Interaction
Computer and Information Systems Applications
Artificial Intelligence
Computer Communication Networks
Altri autori: AntonaMargherita  
NtoaStavroula  
SalvendyGavriel  
Nota di contenuto: Intro -- Foreword -- HCI International 2024 Thematic Areas and Affiliated Conferences -- List of Conference Proceedings Volumes Appearing Before the Conference -- Preface -- 26th International Conference on Human-Computer Interaction (HCII 2024) -- HCI International 2025 Conference -- Contents - Part VII -- AI Algorithms and Tools in HCI -- AI-Generated User Stories Supporting Human-Centred Development: An Investigation on Quality -- 1 Introduction -- 2 Related Work -- 2.1 User Stories Advantages: Simple, Structured, Estimatable -- 2.2 Quality of User Stories -- 2.3 Quality Assessment Frameworks for User Stories -- 2.4 Tools Utilizing AI, Supporting the Generation of User Stories -- 3 Investigation on the Quality of AI-Generated User Stories -- 3.1 AI Tools Selection and Prompt Preparation -- 3.2 Quality Assessment of Generated User Stories -- 4 Procedure -- 4.1 AI Tool Selection -- 4.2 Evaluation of the User Stories -- 5 Results -- 6 Discussion and Conclusion -- 7 Future Work -- References -- Enhance Deepfake Video Detection Through Optical Flow Algorithms-Based CNN -- 1 Introduction -- 2 Literature Review -- 3 Study Methodology -- 3.1 Data Collection and Pre-processing -- 3.2 Model Architecture Design -- 3.3 Training and Evaluation -- 4 Results and Discussion -- 5 Conclusion -- References -- Decoding the Alignment Problem: Revisiting the 1958 NYT Report on Rosenblatt's Perceptron Through the Lens of Information Theory -- 1 Introduction -- 2 Theoretical Background -- 2.1 The Alignment of the "AI Alignment" Problem -- 2.2 Shannon's Communication Channel for Universal Communications -- 2.3 The Information-Theoretic Analysis for General Communications -- 3 The Alignment Problem in One-Way Communications -- 3.1 Deconstructing the Alignment Problem in One-Way Communications -- 3.2 The Thought Experiment of Building a User Interface Perceptron (UIP).
3.3 The Multi-Dimensional Nature of UI-Perceptron -- 4 The Alignment Problem for Interactive Communications -- 4.1 The Differences Between One-Way and Two-Way Communications -- 4.2 The Functional Purposes in Interactive Two-Way Communications -- 4.3 The Alignments in Weaver's Three Levels of Communications Problems -- 5 Conclusion -- References -- Evaluation of Adversarial Examples Based on Original Definition -- 1 Introduction -- 2 Related Work -- 3 Evaluation Method -- 3.1 Dataset -- 3.2 Methods for Creating AEs -- 3.3 Methods for Conducting Survey -- 4 Evaluation Results -- 4.1 Creating AEs with Minimum Noise -- 4.2 Impact of Noise Discernibility -- 4.3 Impact of Subject Identifiability -- 5 Conclusion -- References -- SD-WEAT: Towards Robustly Measuring Bias in Input Embeddings -- 1 Introduction -- 1.1 WEAT: The Word Embedding Association Test -- 1.2 Applications of WEAT -- 1.3 Objective -- 2 Methodology -- 3 Results -- 3.1 SD-WEAT is Correlated with WEAT in Bias Evaluation -- 3.2 SD-WEAT's Attribute Set Size Did Not Affect Bias Evaluation -- 3.3 Using SD-WEAT to Evaluate Various Embedding Methods -- 4 Discussion -- 5 Conclusion -- References -- Generating Architectural Floor Plans Through Conditional Large Diffusion Model -- 1 Introduction -- 2 Methods -- 2.1 Identify the Conditions -- 2.2 Data Collection and Annotation -- 2.3 Textural Caption -- 2.4 Training the Generation Model -- 3 Evaluation -- 4 Limitations and Future Works -- 5 Conclusion -- References -- Enhancing Scientific Research and Paper Writing Processes by Integrating Artificial Intelligence Tools -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Participants -- 3.2 Materials -- 3.3 Procedure -- 4 Results and Discussion -- 5 Conclusions -- References -- Evaluating the Performance of LLMs on Technical Language Processing Tasks -- 1 Introduction -- 2 A Hard Problem.
3 The Tools -- 4 The Questions and Answer Evaluation -- 4.1 Data Collection and Survey Design -- 4.2 Evaluation -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Exploring the Combination of Artificial Intelligence and Traditional Color Design: A Comparative Analysis and Outlook of Aesthetics, Theme Conformity, and Traditional Color Embodiment -- 1 Introduction -- 1.1 Chinese Traditional Colors -- 1.2 Algorithms for Color Extraction and Filling -- 2 Methodology -- 3 Practical Application of Color Extraction and Filling in Design -- 3.1 Theme Selection and Line Drawing -- 3.2 Color Material Chart Collection and Processing -- 3.3 Color Extraction and Filling -- 3.4 Artificial Coloring -- 4 Results -- 5 Conclusion -- References -- Artificial Intelligence and the Unveiling of Boundaries: Reflection on the Intersection of Creativity, Technology, and Humanity -- 1 Art and Science-New Issues in Contemporary Art -- 2 The Wonder of Imagination - The Complementarity of Rational Perception and Life Experience -- 3 Conclusion -- References -- When to Observe or Act? Interpretable and Causal Recommendations in Time-Sensitive Dilemmas -- 1 Introduction -- 2 Background -- 3 Method -- 3.1 Causal Decision Networks (CDNs) -- 3.2 Time-Constrained Causal Decision-Making Problems (TCCDPs) -- 3.3 Solution Strategies -- 3.4 Simulation Support -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Improving Real-Time Object Tracking Through Adaptive Feature Fusion and Resampling in Particle Filters -- 1 Introduction -- 2 Related Research -- 3 Review of PF Algorithm -- 4 Proposed Method -- 4.1 Feature Extraction -- 4.2 Color Feature -- 4.3 Edge Feature -- 4.4 Masking System -- 4.5 Adaptive Resampling -- 5 Experiment and Result Analysis -- 5.1 Evaluation Method -- 5.2 Performance Evaluation -- 5.3 Comparison with Traditional Model.
6 Discussion and Conclusion -- References -- Differentiable Forests: The Random Journey Continues -- 1 Tree-Based Ensemble Models -- 1.1 Traditional Random Forests -- 1.2 Adaboost -- 1.3 XGBoost -- 1.4 Random Hinge Forests and Ferns -- 2 Experiment -- 2.1 Libraries and Resources -- 2.2 TRF -- 2.3 ADA -- 2.4 XGB -- 2.5 RHFo and RHFe -- 3 Conclusion -- 3.1 Limitations and Future Work -- References -- Maximizing Efficiency in Real-Time Invariant Object Detection: A Multi-algorithm Approach -- 1 Introduction -- 2 Defining Invariant Objects -- 3 Algorithm -- 3.1 Edition 1 - Only Template Matching -- 3.2 Edition 2 - Template Matching with CSRT -- 3.3 Edition 3 - Template Matching with CSRT and Optimizations -- 4 Guide to Choosing Optimal Edition -- 5 Mouse Tracker for Videos - Python Application -- 6 Conclusion -- References -- Computational Approaches to Analysing Literary Images: A Case Study of Legends of the Condor Heroes -- 1 Introduction -- 2 Methodology -- 2.1 Data -- 2.2 Methods -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Interacting with Large Language Models and Generative AI -- Human-Centric Interaction Design of RecoBot: A Study for Improved User Experience -- 1 Introduction -- 2 Background -- 3 Methods -- 3.1 Metrics -- 3.2 Variations in Interaction Mechanisms and Conversation Types -- 3.3 Design and Participants -- 3.4 Procedure and Tasks -- 3.5 Chatbot and Alignment of Tasks Amongst Groups -- 4 Data Collection and Analysis -- 5 Discussion and Implications -- 6 Conclusion and Future Directions -- References -- Actions, Not Apps: Toward Using LLMs to Reshape Context Aware Interactions in Mixed Reality Systems -- 1 Introduction -- 2 Related Works -- 2.1 Ontology Based User Modeling for in AR Museum System -- 2.2 Pervasive Augmented Reality -- 2.3 Glanceable AR for Everyday Information Access Tasks.
3 Action Centric Interaction for Mixed Reality -- 4 Action Sandbox Workspace -- 4.1 Ontology of Context, Intention, Content, and Action -- 4.2 Action Marketplace -- 5 Preliminary Testing of the Reasoning of LLMs -- 6 On-Going Works and Next Steps -- References -- User Experience with ChatGPT: Insights from a Comprehensive Evaluation -- 1 Introduction -- 2 Evaluating the User Experience with ChatGPT -- 2.1 Questionnaire Structure -- 2.2 Analysis of the Sample of Participants -- 2.3 Test Results -- 2.4 Analysis and Discussion -- 3 Conclusions and Future Works -- References -- Decoding the AI's Gaze: Unraveling ChatGPT's Evaluation of Poetic Creativity -- 1 Introduction -- 1.1 ChatGPT as an Evaluator -- 1.2 Characteristics of Decision Making in Humans vs. in AI -- 2 Materials and Procedure -- 2.1 Method -- 2.2 Data Analysis -- 3 Results -- 3.1 Classification Rates and Confidence of ChatGPT -- 3.2 Do Markers Differ Between Poems Classified as Human-Written and AI-Generated ? -- 4 Discussion -- References -- Co-writing with AI: How Do People Interact with ChatGPT in a Writing Scenario? -- 1 Introduction -- 2 Materials and Methods -- 2.1 Participants -- 2.2 Materials and Procedure -- 2.3 Statistical Analyses -- 3 Results -- 3.1 Analysis of Participants' Use of ChatGPT -- 3.2 Characteristics of Participants' Interaction with ChatGPT -- 3.3 Qualitative Analysis of Participants' Approach to the Task and Prompting Behavior -- 3.4 Analysis of Prompts in Relation to Participant Characteristics -- 3.5 Analysis of Approach to the Task and Participant Characteristics -- 4 Discussion -- References -- Plain Language to Address Dimensionality in Feature-Contribution Explanations for End-Users -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Datasets and Model -- 3.2 Participants -- 3.3 Questionnaire Procedure -- 4 Results -- 4.1 Participant Demographics.
4.2 Self-reported Responses.
Sommario/riassunto: The seven-volume set CCIS 2114-2120 contains the extended abstracts of the posters presented during the 26th International Conference on Human-Computer Interaction, HCII 2024, held in Washington, DC, USA, during June 29–July 4, 2024. The total of 1271 papers and 309 posters included in the HCII 2024 proceedings were carefully reviewed and selected from 5108 submissions. The posters presented in these seven volumes are organized in the following topical sections: Part I: HCI Design Theories, Methods, Tools and Case Studies; User Experience Evaluation Methods and Case Studies; Emotions in HCI; Human Robot Interaction. Part II: Inclusive Designs and Applications; Aging and Technology. Part III: eXtended Reality and the Metaverse; Interacting with Cultural Heritage, Art and Creativity. Part IV: HCI in Learning and Education; HCI in Games. Part V: HCI in Business and Marketing; HCI in Mobility and Automated Driving; HCI in Psychotherapy and Mental Health. Part VI: Interacting with the Web, Social Media and Digital Services; Interaction in the Museum; HCI in Healthcare. Part VII: AI Algorithms and Tools in HCI; Interacting with Large Language Models and Generative AI; Interacting in Intelligent Environments; HCI in Complex Industrial Environments. .
Titolo autorizzato: HCI International 2024 Posters  Visualizza cluster
ISBN: 9783031621109
9783031621093
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910865266503321
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Serie: Communications in Computer and Information Science, . 1865-0937 ; ; 2120