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2nd International Conference on Foundation and Large Language Models, FLLM 2024

作者： Troussas, Christos Papakostas, Christos Krouska, Akrivi Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798350354799

Large Language Models (LLMs), such as ChatGPT, hold immense potential to irrevocably influence the dimension of educational technology by providing empowerment for personalized learning experiences. This paper covers the integration of ChatGPT into existing eLearning platforms toward supporting Java programming education. Using artificial intelligence-based capabilities of ChatGPT in natural language processing, our software enables instructors to generate individual module assessments tailored to a student's profile with unprecedented ease. Evaluation of the effectiveness and efficiency of the system was performed by a comprehensive review of the system, obtaining feedback from instructors and students, and analyzing test performance metrics. The evaluation showed that most teachers found the system very user friendly, with significant savings in time for test creation. Satisfaction related to personalized tests designed by ChatGPT was also adequate, and the average scores achieved on test cases set by ChatGPT were relatively high compared to those manually curated. Results underline the potential of ChatGPT-driven automated test generation for enhancing personalized programming education on eLearning platforms, making available tailored assessment, by consideration of individual needs of students, and increased learning outcomes and efficiency. © 2024 IEEE.

关键词： Java programming language

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FHRP Performance Measurement Using Etherchannel and Routing protocol OSPFv2, IGRP and BGPv4 on Three-Tier Enterprise Network Architecture Topology 12

FHRP Performance Measurement Using Etherchannel and Routing ...

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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Arini Fiade, Andrew Matin, Iik Muhamad Malik Rifandi, Ahmad Solahudin Informatics Engineering Uin Syarif Hidayatullah Jakarta Jakarta Indonesia Jakarta State Polytechnic Computer and Informatics Engineering Jakarta Indonesia Uin Syarif Hidayatullah Jakarta Informatics Engineering Jakarta Indonesia

ISBN: (纸本)9798331528799

Networks in enterprise scale require connectivity that runs continuously so that a backup network is needed that functions as a substitute for the main network in case of problems. Network problems can affect data traffic and Quality. This can be overcome by using a gateway redundancy protocol. To determine the performance of a computer network when switching from the main network to the backup network, performance measurements are needed. Performance measurements are carried out with several scenarios using TCP and UDP packet transmissions to determine the value of Quality of Service, namely Throughput, Jitter, Packet loss and Delay. The results of this study show a comparison of protocol redundancy (FHRP) using EIGRP and OSPF routing by producing the HSRP protocol has the best QoS performance using EIGRP and OSPF routing but has a delay value that is slightly not better than other combinations in several scenarios. © 2024 IEEE.

关键词： Redundancy

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A Personalized Fitness Application for Injury Rehabilitation Using Artificial Neural Networks 19

A Personalized Fitness Application for Injury Rehabilitation...

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19th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2024

作者： Kalofonos, Nikolaos Troussas, Christos Krouska, Akrivi Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798331504502

This paper presents a personalized fitness mobile application with the use of Artificial Intelligence (AI), namely Artificial Neural Networks (ANN), which contributes to injury rehabilitation. It automatically generates customized workout plans on a weekly basis, taking into consideration user-supplied data on issues such as injury type, fitness level, body mass index, and available equipment. The system continuously updates the workout plans with the help of feedback provided by the user to achieve the best recovery process. Built with React Native for the frontend and Django for the backend, this application guarantees access anytime, anywhere, with smooth data treatment. The paper further reflects on the general implications of using AI in e-fitness, stresses intuitive user interfaces, and furthers possibilities such technologies could undergo. © 2024 IEEE.

关键词： Electronic health record

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The Gamification Advantage: Innovating Education through Engagement 9

The Gamification Advantage: Innovating Education through Eng...

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9th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2024

作者： Strousopoulos, Panagiotis Troussas, Christos Krouska, Akrivi Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798350342482

The study identifies how the game elements of points, badges, and leaderboards could be used to engage students to enhance learning outcomes in educational settings. As the innovative teaching paradigm is gaining importance every day, gamification is unrolling as a provoking approach to engaging and motivating students by making the learning process more captivating and interactive. Thus, the main goal is to consider how these factors impact students' intrinsic and extrinsic motivation and how they can result in better academic performance and higher knowledge retention. Besides, the work will help to evaluate how consistent gamification is with the existing educational theories, which are behaviorism, constructivism, and cognitivism, and how these theories help to implement those elements of gamification effectively. The paper discusses how its practicality and success in diverse educational environments have been highlighted using a good number of case studies. Eventually, it tries to give an overall view of gamification's role in modern education and emphasizes the potentiality of redefining traditional learning paradigms. © 2024 IEEE.

关键词： Federated learning

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Personalized Hint Delivery in Multimedia Learning Environments Using Learning Styles: An Integrated Approach with Artificial Neural Networks and Weighted Sum Model 19

Personalized Hint Delivery in Multimedia Learning Environmen...

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19th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2024

作者： Troussas, Christos Krouska, Akrivi Papakostas, Christos Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798331504502

This paper introduces a novel multimedia learning environment designed to support holistic learning of web development. ANNs and the WSM model have been adopted to implement the framework of the VARK learning style model in order to dynamically provide personalized educational hints that assist learners to overcome difficulties and deepen their understanding, thus acquiring a higher level of knowledge in a more general and effective way. In our approach, hints are not an adjunct but a core feature of the learning process, dynamically tailored to each learner in their time of need. An ANN combined with a WSM collaborates to achieve optimal delivery of these hints, ensuring they are timely and context-aware according to the learning styles of individual students defined by the VARK model. Students receive the best possible guidance to make learning much more effective. A structured questionnaire-based evaluation followed by statistical hypothesis testing showed promising results for the efficacy of this multimedia learning environment. © 2024 IEEE.

关键词： Contrastive Learning

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EPM: Evolutionary Perception Method for Anomaly Detection in Noisy Dynamic Graphs

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IEEE Transactions on Knowledge and Data engineering 2025年第7期37卷 4035-4048页

作者： Wang, Huan Chen, Junyang Wu, Yirui Leung, Victor C. M. Wang, Di King Abdullah University of Science and Technology Division of Computer Electrical and Mathematical Sciences and Engineering Saudi Arabia Huazhong Agricultural University College of Informatics China Shenzhen University College of Computer Science and Software Engineering China Hohai University College of Computer and Information China

With the rapid expansion of interactions across various domains such as knowledge graphs and social networks, anomaly detection in dynamic graphs has become increasingly critical for mitigating potential risks. However, existing anomaly detection methods often assume noise-free dynamic graphs, overlooking the prevalence of noisy dynamic graphs in real-world applications. Specifically, noisy dynamic graphs affected by structural noises-such as spurious and missing nodes and edges-struggle to consistently provide reliable structural evidence for anomaly detection. To tackle this challenge, we propose an Evolutionary Perception Method (EPM) for identifying anomalous nodes in noisy dynamic graphs by resisting the interference of structural noises. EPM primarily consists of two components: a dynamic fitter and a filtering reviser. The dynamic fitter characterizes the interaction dynamics of nodes that removes and generates links at each period as a multiple superposition state, utilizing various link prediction algorithms to fit evolutionary mechanisms. Additionally, the filtering reviser designs evolutional entropies to quantify the evolutional uncertainty in multiple superposition states, further designing the Kalman filter to optimize these entropies. Extensive experiments show that the proposed EPM method surpasses state-of-the-art approaches in detecting anomalous nodes in noisy dynamic graphs. © 1989-2012 IEEE.

关键词： Kalman filters

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Book Recommender System Using Content-Based Filtering for PNJ Press Website 10

Book Recommender System Using Content-Based Filtering for PN...

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10th International Conference on Education and Technology, ICET 2024

作者： Liliana, Dewi Yanti Nalawati, Rizki Elisa Iswara, Ratna Widya Aisyah, Alifiah Putri Malo, Hana Octavia Trinida Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia

ISBN: (纸本)9798331522483

The vast collections in book publishers and bookstores make it challenging for users to find books on specific topics without knowing the exact titles. An information system with a book recommendation feature can significantly enhance the efficiency of a book search. Recommender systems, which predict or suggest items of interest based on user interactions and queries, are widely used across various platforms to personalize user experiences. This study focuses on developing a Content-Based Filtering recommender system for PNJ Press, a book publisher of the academic community of Jakarta State Polytechnic. The system compares user search queries with the content of book titles and abstracts to provide relevant recommendations. Previous research has demonstrated the effectiveness of Content-Based Filtering in various domains, highlighting its potential for improving book search efficiency on the PNJ Press website. The system achieved a precision of 91.84% and a recall of 97.83%, resulting in an overall accuracy rate of 90%. Additionally, the study found that the combined attributes of book titles and abstracts significantly influence recommendation results. © 2024 IEEE.

关键词： content-based filtering cosine similarity PNJ press website recommender system text mining

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FASTER-AI: A Comprehensive Framework for Enhancing the Trustworthiness of Artificial Intelligence in Web Information Systems 20

FASTER-AI: A Comprehensive Framework for Enhancing the Trust...

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20th International Conference on Web Information Systems and Technologies, WEBIST 2024

作者： Troussas, Christos Papakostas, Christos Krouska, Akrivi Mylonas, Phivos Sgouropoulou, Cleo Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (纸本)9789897587184

With increasing embedding of artificial intelligence (AI) in web information systems (WIS), the maximum assurance on the reliability of such AI systems is solicited. Although this aspect is gaining importance, no comprehensive framework has yet been developed to ensure AI reliability. This paper aims to bridge that gap by proposing the AI FASTER framework to enhance the reliability of AI in WIS. The key dimensions of concern within the framework are FASTER-AI: Fairness/bias mitigation, explainability/transparency, security/privacy, robustness, and ethical considerations/accountability. Each one guides in precisely the area where trust shall be accomplished: a decrease in bias, model interpretability, protection of data, resilience of models, and ethics in governance. The implementation methodology for these dimensions involves preliminary assessment, planning, integration, testing, and continuous improvement. Validation of proof for FASTER-AI was created based on in-depth case studies across different verticals: e-commerce, finance, health, and fraud detection. This work has demonstrated how FASTER-AI is applied through illustrative case studies showing promising performance. From the initial results of high improvement in terms of fairness, transparency, security, and robustness, it may be effectively inferred that FASTER-AI can be successfully applied. Copyright © 2024 by SCITEPRESS.

关键词： Differential privacy

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Personalized Path Planning Estimation of Georeferenced Urban Scene Considering Criminality Map: The Case of Attica 4th

Personalized Path Planning Estimation of Georeferenced Urban...

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4th International Conference on Novel and Intelligent Digital Systems, NiDS 2024

作者： Yiakoumettis, Christos Karanikolas, Nikitas Department of Informatics and Computer Engineering University of West Attica Aigaleo Greece

ISBN: (纸本)9783031733437

This paper introduces an advanced georeferenced path planning methodology that enhances urban navigation by incorporating crime statistics to ensure safety and adherence to user preferences. Leveraging a combination of Geographic Information Systems (GIS) and 3D urban modeling, our approach proposes a unique platform that personalizes route planning within the urban landscape of Attica, Greece. Our approach is taking into consideration user’s preferences considering qualitative and quantitative features and a Criminality Map. Initially the user profile is estimated based on a pairwise comparison approach of inductive-based learning methodology using Analytical Hierarchy Process (AHP). The proposed platform provides a personalized path planning estimation for urban areas by aligning geographic data with both user-specific preferences and safety considerations. The efficacy of our approach is demonstrated through a detailed case study of Attica (Greece), where over 700 georeferenced models are analyzed for path planning alongside with criminal reports of Police for the year 2022. This research highlights the potential of combining safety metrics with personalization in path planning, offering significant implications for the development of smart navigation systems in urban environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Crime

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Affective Computing in Intelligent Tutoring Systems: Exploring Insights and Innovations 9

Affective Computing in Intelligent Tutoring Systems: Explori...

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9th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2024

作者： Tasoulas, Theofanis Troussas, Christos Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798350342482

Integrating intelligent tutoring systems (ITS) into education has significantly enriched personalized learning experiences for students and educators alike. However, these systems often neglect the critical role of emotions in the learning process. By integrating affective computing, which empowers computers to recognize and respond to emotions, ITS can foster more engaging and impactful learning environments. This paper explores the utilization of affective computing techniques, such as facial expression analysis and voice modulation, to enhance ITS functionality. Case studies and existing systems have been scrutinized to comprehend design decisions, outcomes, and guidelines for effective integration, thereby enhancing learning outcomes and user engagement. Furthermore, this study underscores the necessity of considering emotional aspects in the development and deployment of educational technology to optimize its influence on student learning and well-being. A major conclusion of this research is that integration of affective computing into ITS empowers educators to customize learning experiences to students' emotional states, thereby enhancing educational effectiveness. To achieve this, it is crucial for such systems to make informed design decisions and adhere to established guidelines. These design decisions may involve selecting appropriate emotion recognition algorithms and integrating them seamlessly into the ITS interface, while guidelines can offer practical insights into effectively implementing affective computing techniques in ITS, such as ensuring data privacy and security measures are in place and providing adequate training for educators on interpreting emotional data. © 2024 IEEE.

关键词： Contrastive Learning

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