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EEG-based Incongruency Decoding in AR with sLDA, SVM, and EEGNet

Current Directions in Biomedical Engineering 2024年第3期10卷 21-24页

作者： Wimmer, Michael Veas, Eduardo E. Müller-Putz, Gernot R. Know-Center Graz Austria Institute of Neural Engineering Graz Austria Institute of Interactive Systems and Data Science Graz Austria

Augmented reality (AR) technologies enhance a user’s physical environment by providing contextual information about their surroundings. This information might appear incongruent to users, either due to their current mental context or factual errors in the data. This paper explores the feasibility of incongruency decoding using electroencephalographic (EEG) signals from 19 participants acquired during an interactive AR task. Previous studies on single-trial N400 decoding for brain-computer interfaces using EEG data are limited. Therefore, we implemented commonly used classification approaches and assessed their decoding performance compared to the convolutional neural network EEGNet. We found that the investigated approaches offer comparable accuracies ranging from 63.3% to 64.8%. Successful decoding of incongruency effects can foster more contextually appropriate interactions within AR environments. © 2024 The Author(s), published by De Gruyter.

关键词： Convolutional neural networks

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The Framing Loop: Do Users Repeatedly Read Similar Framed News Online?

The Framing Loop: Do Users Repeatedly Read Similar Framed Ne...

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2024 ACM International Conference on Intelligent User Interfaces Workshops, IUI-WS 2024

作者： Reiter-Haas, Markus Lex, Elisabeth Graz University of Technology Institute of Interactive Systems and Data Science Sandgasse 36/III Graz8010 Austria

It is well established in psychology that framing of content affects the behavior of people. This effect is, however, only sparsely explored in information-seeking and retrieval behavior. In the present work, we consider the diversity of consumed content and repetition patterns regarding their framing. We conduct a framing analysis in the MIcrosoft News dataset (MIND) comprising textual content and user interaction behaviors. By extracting the frames of the item sequences, we uncover a tendency of users to consume similar framed news repeatedly when sticking to the same type of content. Consequently, framing biases are important to consider in information systems. We hope that our work inspires future research on corresponding debiasing methods. © 2024 Copyright for this paper by its authors.

关键词： Behavioral research

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Immersive virtual reality for extending the potential of building information modeling in architecture,engineering,and construction sector:systematic review

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International Journal of Digital Earth 2022年第1期15卷 503-526页

作者： Saeed Safikhani Stephan Keller Gerald Schweiger Johanna Pirker Institute of Interactive Systems and Data Science Graz University of TechnologyGrazAustria Institute of Software Technology Graz University of TechnologyGrazAustria

The field of architecture,engineering,and construction(AEC)is continually striving to use resources efficiently and manage complex *** more than ever,there is a strong need for digital transformation in *** improvement in the accessibility of consumer-based head-mounted displays(HMD)is attracting different entertainment and research fields to immersive virtual reality(VR)*** Information Modeling(BIM)is known as a promising technology in *** full potential of BIM is not yet employed to empower this field,however,and this could be a result of some barriers still to be surmounted by BIM in both technological and management *** of these barriers is the communication and collaboration between design,construction,operation,and maintenance *** can fill this gap by providing additional capabilities for BIM which either were not available before or were not possible to employ in practical *** this paper,we systematically review recent research around the application of VR in BIM and discuss the results using the PRISMA *** discuss the most commonly used technologies,software,and evaluation methods and the various applications of VR in the reviewed ***,we extend the discussion by summarizing the potential future work in this area.

关键词： Building information modeling architecture engineering construction virtual reality BIM VR

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Knowledge Leaks in data-Driven Business Models? Exploring Different Types of Knowledge Risks and Protection Measures

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Schmalenbach Journal of Business Research 2024年第3期76卷 357-396页

作者： Fruhwirth, Michael Pammer-Schindler, Viktoria Thalmann, Stefan Know-Center GmbH Institute for Interactive Systems and Data Science Faculty of Computer Science and Biomedical Engineering Graz University of Technology Silicon Austria Labs GmbH Business Analytics and Data Science-Center (BANDAS-Center) School of Business Economics and Social Sciences University of Graz

data-driven business models imply the inter-organisational exchange of data or similar value objects. data science methods enable organisations to discover patterns and eventually knowledge from data. Further, by training machine learning models, knowledge is materialised in those models. Thus, organisations might risk the exposure of competitive knowledge by sharing data-related value objects, such as data, models or predictions. Although knowledge risks have been studied in traditional business models, little research has been conducted in the direction of data-driven business models. In this explorative qualitative study, we conducted 28 expert interviews in three rounds (two exploratory and one evaluatory) and identified five types of risks along the three basic types of value objects: data, models and predictions. These risks depend on the context, i.e., when competitive knowledge could be discovered from shared value objects. We found that those risks can be mitigated by technology, contractual regulations, trusted relationships, and adjusting the business model design. In this study, we show that the risk of knowledge leakage is a relevant risk factor in data-driven business models. Overall, knowledge risks should be considered already during business model design, and their management requires an interdisciplinary approach via a balanced assessment. The level of knowledge protection from a technology perspective highly depends on computer science innovations and thus is a moving target. As an outlook, we suggest that knowledge risk will become even more relevant with the extensive usage of machine learning and artificial intelligence in data-driven business models. © The Author(s) 2024.

关键词： Business model innovation data analytics data-driven business models Knowledge risks Risk management Value objects

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An interactive Chess-Puzzle-Simulation for Computer science Education 8

An Interactive Chess-Puzzle-Simulation for Computer Science ...

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8th International Conference of the Immersive Learning Research Network, iLRN 2022

作者： Holly, Michael Tscherko, Jan-Heliodor Pirker, Johanna Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria

ISBN: (纸本)9781734899528

The hype around the series 'The Queen's Gambit' led to a boom in playing chess. The game enhances strategic thinking, stimulates intellectual creativity, and improves problem-solving. These skills are increasingly in demand and also essential in the field of computer science (CS). Traditional teaching approaches are often insufficient to teach CS concepts. interactive and digital experiences can be used to create an exciting, engaging, and realistic learning environment. In this paper, we explore the potential of a chess-based learning approach to increase motivation in CS. The application includes an interactive chess-puzzle simulation to teach the concept of state machines using a chessboard as an input field. We present a study with 35 students for evaluating the students' motivation, emotions, and workload with a focus on the learning experience. The results indicate a positive impact on the learning process and engage students in learning computer science. © 2022 Immersive Learning Research Network.

关键词： Students

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Microservice Architecture of Modern eLearning Application 5

Microservice Architecture of Modern eLearning Application

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5th IEEE International Conference on Communications, Information, Electronic and Energy systems, CIEES 2024

作者： Schukin, Alexander Scerbakov, Nikolai Rezedinova, Eugenia Peter the Great St. Petersburg Polytechnic University Institute of Computer Science and Cybersecurity St. Petersburg Russia Graz University of Technology Institute of Interactive Systems and Data Science Graz Austria

ISBN: (纸本)9798350352863

Learning Management systems (LMS) have been integral to educational institutions for over 20 years. Technically, an LMS consists of functional components designed to deliver, discuss, explain educational materials, and assess user knowledge through various paradigms such as uploading assignments and online questionnaires. The prolonged and intensive use of such systems emphasizes the importance of their maintainability, allowing the accommodation of new components and the replacement of outdated ones. Over the years, the technological foundation of LMS components has transitioned from early versions of PHP to advanced Java, Python, and JavaScript packages. data repositories have evolved from local relational databases to shared NoSQL databases. Communication technologies have shifted from NNTP news servers to multiple social applications like WhatsApp and *** this paper, we present architectural solutions implemented in a modern LMS called WBT-Master. This architecture specifically addresses the maintainability of modern LMS, ensuring they evolve alongside emerging Internet technologies. The practical significance of our work lies in its ability to support very heterogeneous components within a logically unified LMS framework. By discussing the architecture of WBT-Master, we offer a method for incorporating both old and new technological platforms into a single system. Additionally, we use this architecture to interface with cloud services, foster social interactions, and optimize user experience. This contributes to the evolution of E-Learning platforms, offering enhanced and more interactive educational experiences for both learners and educators. © 2024 IEEE.

关键词： Cloud computing architecture

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A Qualitative Investigation to Design Empathetic Agents as Conversation Partners for People with Autism Spectrum Disorder

arXiv

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arXiv 2024年

作者： Poglitsch, Christian Pirker, Johanna ISDS - Institute of Interactive Systems and Data Science University of Technology Graz Graz Austria Media Informatics Group Ludwig-Maximilians University Munich Munich Germany

Autism Spectrum Disorder (ASD) can profoundly affect reciprocal social communication, resulting in substantial and challenging impairments. One aspect is that for people with ASD conversations in everyday life are challenging due to difficulties in understanding social cues, interpreting emotions, and maintaining social verbal exchanges. To address these challenges and enhance social skills, we propose the development of a learning game centered around social interaction and conversation, featuring Artificial Intelligence agents. Our initial step involves seven expert interviews to gain insight into the requirements for empathetic and conversational agents in the field of improving social skills for people with ASD in a gamified environment. We have identified two distinct use cases: (1) Conversation partners to discuss real-life issues and (2) Training partners to experience various scenarios to improve social skills. In the latter case, users will receive quests for interacting with the agent. Additionally, the agent can assign quests to the user, prompting specific conversations in real life and providing rewards for successful completion of quests. © 2024, CC BY.

关键词： Chatbots

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The Synergy of Educational Technologies and Self-regulated Learning: A Systematic Scoping Literature Review 27th

The Synergy of Educational Technologies and Self-regulated...

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27th International Conference on interactive Collaborative Learning, ICL 2024

作者： Brünner, Benedikt Burgsteiner, Harald Schön, Sandra Ebner, Martin Institute of Interactive Systems and Data Science Graz University of Technology Graz Austria Educational Technology Graz University of Technology Graz Austria Institute for Digital Media Education University of Teacher Education Graz Austria

ISBN: (纸本)9783031856488

The rapid advancement of artificial intelligence (AI) technology necessitates addressing the topic of self-regulated learning (SRL) given its potential for personalized learning experiences. Educational Technologies (EdTech) have the capacity to facilitate SRL within educational contexts, particularly in remote learning scenarios. This study explores the interplay between EdTech and SRL, highlighting their synergistic relationship. Through a systematic scoping literature review following the methodology of Peters et al., evidence from 328 records in the Scopus database was synthesized, with an analysis of 112 reports meeting the inclusion criteria published between January 2015 and February 2024. Zimmerman’s cyclical phases model emerged as the predominant SRL framework in connection with EdTech. Additionally, the identified EdTechs were categorized into eleven clusters based on shared characteristics and mapped onto Zimmerman’s SRL model to create an EdTech-SRL-Synergy-Map. Recommendations are made for future research, particularly in the secondary education sector, and the significance of SRL practices in an educational landscape permeated by AI is emphasized. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Self-supervised learning

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A Qualitative Investigation to Design Empathetic Agents as Conversation Partners for People with Autism Spectrum Disorder

A Qualitative Investigation to Design Empathetic Agents as C...

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IEEE Symposium on Computational Intelligence and Games, CIG

作者： Christian Poglitsch Johanna Pirker ISDS - Institute of Interactive Systems and Data Science University of Technology Graz Graz Austria Media Informatics Group Ludwig-Maximilians University Munich Munich Germany

ISBN: (数字)9798350350678

ISBN: (纸本)9798350350685

关键词： Training Autism Emotion recognition Oral communication Games Learning (artificial intelligence) Interviews

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Transparency, Privacy, and Fairness in Recommender systems

arXiv

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arXiv 2024年

作者： Kowald, Dominik Institute of Interactive Systems and Data Science Graz University of Technology Austria

Recommender systems have become a pervasive part of our daily online experience by analyzing past usage behavior to suggest potential relevant content, e.g., music, movies, or books. Today, recommender systems are one of the most widely used applications of artificial intelligence and machine learning. Therefore, regulations and requirements for trustworthy artificial intelligence, for example, the European AI Act, which includes notions such as transparency, privacy, and fairness are also highly relevant for the design, development, evaluation, and deployment of recommender systems in practice. This habilitation elaborates on aspects related to these three notions in the light of recommender systems, namely: (i) transparency and cognitive models, (ii) privacy and limited preference information, and (iii) fairness and popularity bias in recommender systems. Specifically, with respect to aspect (i), we highlight the usefulness of incorporating psychological theories for a transparent design process of recommender systems. We term this type of systems psychology-informed recommender systems. We also use models of human memory theory to develop cognitive-inspired algorithms for tag and music recommendations, and find that these algorithms are capable of outperforming related methods in terms of recommendation accuracy. Additionally, we show that cognitive models can further contribute to transparency aspects of recommender systems by illustrating how the models’ components have contributed to generate the recommendation lists. In aspect (ii), we study and address the trade-off between accuracy and privacy in differentially-private recommendations. We design a novel recommendation approach for collaborative filtering based on an efficient neighborhood reuse concept, which reduces the number of users that need to be protected with differential privacy. Furthermore, we address the related issue of limited availability of user preference information, e.g., click data, in t

关键词： Differential privacy

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