Augmented Cognition : 18th International Conference, AC 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29–July 4, 2024, Proceedings, Part II / / edited by Dylan D. Schmorrow, Cali M. Fidopiastis

• Autore: Schmorrow Dylan D
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (282 pages)
• Disciplina: 5,437; 4,019
• Soggetto topico: User interfaces (Computer systems); Human-computer interaction; Artificial intelligence; Computer networks; Computers; Social sciences - Data processing; Image processing - Digital techniques; Computer vision; User Interfaces and Human Computer Interaction; Artificial Intelligence; Computer Communication Networks; Computing Milieux; Computer Application in Social and Behavioral Sciences; Computer Imaging, Vision, Pattern Recognition and Graphics
• Altri autori: FidopiastisCali M
• Nota di contenuto: Intro -- Foreword -- HCI International 2024 Thematic Areas and Affiliated Conferences -- List of Conference Proceedings Volumes Appearing Before the Conference -- Preface -- 18th International Conference on Augmented Cognition (AC 2024) -- HCI International 2025 Conference -- Contents - Part II -- Contents - Part I -- Advances in Augmented Cognition Technologies -- Advancing EEG-Based Gaze Prediction Using Depthwise Separable Convolution and Enhanced Pre-processing -- 1 Introduction -- 1.1 Research Questions -- 2 Related Work -- 3 Methods -- 4 Dataset -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- A Novel Loss Function Utilizing Wasserstein Distance to Reduce Subject-Dependent Noise for Generalizable Models in Affective Computing -- 1 Introduction -- 2 Background -- 3 Methods -- 3.1 Optimal Transport Theory -- 3.2 Models -- 3.3 Autoencoder Error Decomposition -- 3.4 Datasets -- 4 Results -- 5 Conclusion and Future Works -- References -- Enhancing Eye-Tracking Performance Through Multi-task Learning Transformer -- 1 Introduction -- 1.1 Research Questions -- 2 Related Work -- 2.1 Deep Learning for EEG Tasks -- 2.2 MTL for EEG Tasks -- 2.3 Vision Transformers (ViTs) -- 3 Methods -- 3.1 Model Architecture -- 3.2 Representation Module -- 3.3 Prediction Module -- 3.4 Reconstruction Module -- 3.5 Multi-task Learning Framework -- 4 Experiments -- 4.1 Dataset -- 4.2 Baseline Models -- 4.3 Implementation Details -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Fusing Pretrained ViTs with TCNet for Enhanced EEG Regression -- 1 Introduction -- 2 Related Work -- 2.1 Deep Learning in EEG -- 2.2 ViTs in Non-Image Data Analysis -- 2.3 Temporal Convolutional Networks (TCNet) -- 3 Methods -- 3.1 EEGEyeNet Dataset -- 3.2 EEGViT-TCNet Model Architecture -- 3.3 Training and Evaluation Procedure -- 4 Results -- 4.1 Performance Benchmarking. ; 4.2 Computational Efficiency and Speed Enhancement -- 4.3 Ablation Studies -- 5 Discussion -- 6 Conclusion -- References -- Effect of Kernel Size on CNN-Vision-Transformer-Based Gaze Prediction Using Electroencephalography Data -- 1 Introduction -- 1.1 Research Question -- 2 Related Work -- 2.1 Dataset -- 2.2 State-of-the-Art -- 3 Experiment -- 3.1 Model -- 3.2 Training Parameters and Software Implementation -- 3.3 Environment Setup -- 3.4 Evaluation -- 4 Discussion -- 4.1 Limitations -- 5 Conclusion -- References -- Better Results Through Ambiguity Resolution: Large Language Models that Ask Clarifying Questions -- 1 Introduction -- 2 Background -- 2.1 Context, Ambiguity, and User Needs -- 2.2 Prior Work -- 2.3 Existing Benchmarks and Evaluation Methods -- 3 System Architecture -- 4 Methodology -- 4.1 Experiment Design -- 5 Results -- 5.1 Participant Responses -- 6 Discussion -- 7 Future Work -- Appendix: Example Prompt and Response Log -- References -- Enhancing Representation Learning of EEG Data with Masked Autoencoders -- 1 Introduction -- 2 Related Work -- 2.1 Masked Modeling in Language and Vision -- 2.2 Masked Autoencoder for EEG Data -- 2.3 EEG-Based Gaze Estimation -- 3 Methods -- 3.1 Masking Mechanism -- 3.2 Encoder Design -- 3.3 Decoder Design -- 3.4 Reconstruction Task -- 4 Experiment Setting -- 4.1 EEG Data -- 4.2 Training -- 5 Results -- 5.1 Encoder's Performance -- 5.2 Encoder's Efficiency -- 6 Discussion and Conclusion -- References -- Applications of Augmented Cognition in Various Contexts -- Small Languages and Big Models: Using ML to Generate Norwegian Language Social Media Content for Training Purposes -- 1 Introduction -- 2 Theory -- 2.1 Influence Operations -- 2.2 AI and Influence Operations -- 2.3 Fake News in Social Media -- 2.4 Intersection of Fake News and Language Models -- 2.5 Different Strategies -- 3 Methodology. ; 3.1 Language Model Preparation -- 3.2 Cyber-Social Media Simulator: Somulator -- 3.3 Supplementary Tests -- 4 Results -- 4.1 22 Factorial Within-Subject Design -- 4.2 Embedded Research Design -- 4.3 Group Interview -- 5 Discussion -- 5.1 Findings and Analysis -- 5.2 Further Considerations -- 6 Conclusion -- 6.1 Funding -- References -- Early Use of Augmented Cognition for Online Learning Games in Hawai'i -- 1 Introduction -- 1.1 Games, Gamification, and Serious Games -- 1.2 Internet and Game Research -- 1.3 Game Research -- 2 Hawai'i Background -- 2.1 Past Online Instruction in Hawai'i with Simulations -- 2.2 The U.S. and Hawai'i in the Present Context -- 2.3 K-12 Online Instruction in Hawai'i's K-12 Schools -- 2.4 Moving to Online Instruction During Covid-19 -- 3 Discussion -- References -- Collaborative Game: Using Explicit Biofeedback to Enhance Empathy Loop -- 1 Introduction -- 2 Materials and Methods -- 3 Goal Setting and Experiment Development -- 4 Experiment Description -- 5 Analysis of Experimental Results -- 6 Conclusion -- References -- Reflection of Individual Differences on Emotion Map for Kansei Evaluation of Packaging Design with Physiological Indexes -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 HRV Index -- 3.2 EEG Index -- 3.3 Visualization Steps for Emotion Map -- 3.4 Normalization Methods -- 4 Experiment -- 4.1 Experiment Overview -- 4.2 Experimental Procedure -- 5 Results -- 5.1 Comparison Evaluation Results of Physiological Indexes -- 5.2 Comparison Results of Normalization Methods for Evaluation Using Emotion Map -- 5.3 Comparison Results of SAM -- 5.4 Discussion -- 6 Conclusion -- References -- Tabletop Exercise for Ransomware Negotiations -- 1 Introduction -- 2 Preparation -- 3 Ransomware Negotiations -- 3.1 Conditions -- 3.2 Strategies -- 4 Tabletop Exercise for Ransomware Negotiations -- 4.1 Tabletop Exercise. ; 4.2 Concept -- 5 Conclusion -- References -- The Role of Cognition in Developing Successful Cybersecurity Training Programs - Passive vs. Active Engagement -- 1 Introduction -- 2 Cybersecurity Training -- 2.1 Limitations of Current Training Approaches -- 3 Habits -- 3.1 Habit Creation -- 4 Passive vs Active Engagement -- 4.1 Habits in Cybersecurity -- 4.2 Passive Engagement -- 4.3 Active Engagement -- 5 Practical Applicability -- 5.1 Ability -- 5.2 Motivation -- 5.3 Triggers/Cues -- 5.4 Interface Design -- 6 Conclusion -- References -- Health Informatics Associations Between Mindfulness Traits and Health Outcomes in Veterans with Chronic Multi-symptom Illness -- 1 Introduction -- 1.1 Study Summary -- 2 Materials and Methods -- 2.1 Self-report and Cognitive Measures -- 2.2 Electroencephalography (EEG) -- 2.3 Analysis -- 3 Results -- 3.1 Association Between Mindfulness and Self-reported Symptoms -- 3.2 Association Between Mindfulness and Cognitive Assessment -- 3.3 Association Between Mindfulness and EEG -- 4 Discussion -- 4.1 Dual Modes of Cognitive Control, Personality Meta-traits, and Dual Mode Mindfulness -- 4.2 Mindfulness for Veterans, Service Members and Civilians -- 4.3 Limitations -- 5 Conclusion -- References -- The AugCog of Work -- 1 Introduction -- 2 Future of Work -- 3 Education -- 4 Industry -- 5 Insight and Wisdom -- 6 Productivity -- 6.1 Automation -- 7 Current Directions -- 8 Conclusion -- References -- Distance-Based Lifestyle Medicine for Veterans with Chronic Multi-symptom Illness (CMI): Health Coaching as Behavioral Health Intervention for Clinical Adherence -- 1 Introduction -- 1.1 Whole Health for Veterans: Health Coaching for Complex Illness Care -- 1.2 Chronic Multisymptom Illness (CMI) -- 1.3 Barriers to Care -- 2 Method -- 2.1 Participants -- 2.2 Telehealth -- 2.3 WRIISC Health Coaching Intervention. ; 2.4 Statistical Analysis -- 3 Results -- 3.1 Demographics -- 3.2 Mid-Intervention Evaluation -- 3.3 Immediate Post-intervention Evaluation -- 4 Discussion -- 4.1 Study Limitations and Future Directions -- 4.2 Conclusions -- References -- What Works Well? A Safety-II Approach to Cybersecurity -- 1 The Way of Working in the Cybersecurity Domain -- 2 From 'What Goes Wrong' to 'What Goes Right': Lessons from Safety Science -- 3 Putting Incidents Centre Stage: A Model for Cybersecurity in Organisations -- 4 Using the PPDRG Model to Get an Understanding of What Goes Right -- 5 Prevention from a Safety-II Perspective -- 5.1 Phishing -- 5.2 Screen Locking and Clean Desk Policy -- 6 Detection from a Safety-II Perspective -- 7 Preparedness and Response from a Safety-II Perspective -- 8 A Research Agenda for What Goes Right in Cybersecurity -- 8.1 End-Users -- 8.2 Teams -- 8.3 Organisations -- 9 Conclusion -- References -- Author Index.
• Sommario/riassunto: This book constitutes the refereed proceedings of the 18th International Conference on Augmented Cognition, AC 2024, held as part of the 26th HCI International Conference, HCII 2024, which took place in Washington, DC, USA, during June 29–July 4, 2024. The total of 1271 papers and 309 posters included in the HCII 2024 proceedings was carefully reviewed and selected from 5108 submissions. The AC 2024 proceedings were organized in the following topical sections: Part I: Understanding cognitive processes and human performance; advancing cognitive abilities and performance with augmented tools; Part II: Advances in augmented cognition technologies; applications of augmented cognition in various contexts.
• Titolo autorizzato: Augmented Cognition
• ISBN: 9783031615726; 9783031615719
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910865254303321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 14695