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The Gamification Advantage: Innovating Education through Engagement 9

The Gamification Advantage: Innovating Education through Eng...

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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Secure Video and Telemetry FPGA Architecture For UAVs 9

Secure Video and Telemetry FPGA Architecture For UAVs

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

作者： Psilias, Dimitrios Milidonis, Athanasios Lentaris, George Voyiatzis, Ioannis University of West Attica Department of Informatics and Computer Engineering Athens Greece

ISBN: (纸本)9798350342482

Unmanned Aerial Vehicles (UAVs) are used in a wide range of applications. However, since they are vulnerable to cyberattacks security protocols for their data are used. Common existing approaches for data encryption/decryption are based on commercial software platforms which execute their tasks with latency and consume a lot of energy. Moreover, they focus mostly on encrypting/decrypting telemetry data. This paper proposes a Field Programming Gate Array (FPGA)-based architecture for encrypting/decrypting all data exchanged between UAVs and their Ground Station (GS). This architecture uses the Advanced Encryption Standard (AES), known for its robustness, to enhance the confidentiality, integrity, and security. Experimental results show that the proposed architecture performs faster than implementations on well-known software platforms while it consumes less power. © 2024 IEEE.

关键词： electronic data interchange

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Enhancing Interaction with Data Lakes Using Digital Twins and Semantic Blueprints 19

Enhancing Interaction with Data Lakes Using Digital Twins an...

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19th International Conference on Evaluation of Novel Approaches to Software engineering, ENASE 2024

作者： Loizou, Spyros Pingos, Michalis Andreou, Andreas S. Department of Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9789897586965

Advanced analytical techniques and sophisticated decision-making strategies are imperative for handling extensive volumes of data. As the quantity, diversity, and speed of data increase, there is a growing lack of confidence in the analytics process and resulting decisions. Despite recent advancements, such as metadata mechanisms in Big Data Processing and Systems of Deep Insight, effectively managing the vast and varied data from diverse sources remains a complex and unresolved challenge. Aiming to enhance interaction with Data Lakes, this paper introduces a framework based on a specialized semantic enrichment mechanism centred around data blueprints. The proposed framework takes into account unique characteristics of the data, guiding the process of locating sources and retrieving data from Data Lakes. More importantly, it facilitates end-user interaction without the need for programming skills or database management techniques. This is performed using Digital Twin functionality which offers model-based simulations and data-driven decision support. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Lakes

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Investigating the Role of Digital Escape Rooms in Enhancing Educational Outcomes through Game-Based Learning 9

Investigating the Role of Digital Escape Rooms in Enhancing ...

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

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

ISBN: (纸本)9798350342482

This research investigates the integration of a Digital Educational Escape Room in teaching fifth-grade history. The study explores how the Digital Educational Escape Room can enhance student engagement, collaboration, and learning outcomes. The game is designed to improve students' understanding specifically of Justinian's reign. It aligns with the Bloom's taxonomy and involves six interactive puzzles that cater to various learning styles, including visual, auditory, and kinesthetic. The adapted evaluation framework assesses four critical dimensions: learning and training, system, user experience, and affective dimension. Forty-four fifth-grade students participated, engaging in the activities designed to improve their understanding of the history topic of Justinian's reign. Results indicated significant improvements in students' historical knowledge, critical thinking, and teamwork. Students reported high satisfaction levels and positive emotional engagement, despite encountering some technical issues. By integrating game-based learning with digital technology, digital escape rooms offer a promising alternative to traditional teaching methods, potentially transforming the educational experience for primary school students. © 2024 IEEE.

关键词： Bloom's Taxonomy Collaboration Critical Thinking Digital Educational Escape Room (DEER) Educational Technology Game-Based Learning History Education Interactive Learning Primary Education Student Engagement

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The Effect of Social Networking-Based Multimedia Repository on Promoting Open Educational Resources 4th

The Effect of Social Networking-Based Multimedia Repository ...

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

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

ISBN: (纸本)9783031733437

In recent years, the Open Education movement has emerged as an innovative approach in the field of education. Closely connected to it are the Open Educational Resources (ΟΕRs), which are hosted in Digital Repositories. Despite their unique advantages, global recognition, and increasing numbers, OERs have not yet become fully established. Teachers encounter various challenges in using OERs, including a lack of pedagogical knowledge about their value, usage, production, and integration into teaching. At the same time, many digital repositories are considered inadequate, facing issues such as difficulty in content search, incomplete content, and insufficient assistance for users. As such, this research aims to maximize OERs potential and utilization, introducing a social networking-based multimedia repository. This repository fosters interaction, communication, and collaboration, educating teachers about OERs. The main goal of the research is to determine whether incorporating social networking features into a repository could positively influence users’ experience, access frequency, and the utilization of OERs in teaching. A quantitative research method was employed, showing the positive impact of social networking features on teacher attitude and intention to use OERs in their instruction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Digital repository Multimedia content Open Education Open educational resources Social network

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Modeling Educational Strategies in Augmented Reality Learning Using Fuzzy Weights 9

Modeling Educational Strategies in Augmented Reality Learnin...

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

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

ISBN: (纸本)9798350342482

This paper shows the development and application of a fuzzy weight model methodology for the optimization of educational environments in augmented reality. A technology-based learning process in an augmented reality learning environment, notoriously able to improve spatial abilities and increase user engagement with the material learned as well as knowledge retention, has revolutionary potential in education. However, its effectiveness varies greatly. In this, we collaborated with 13 experts in augmented reality and education to deeply evaluate the following six key in-depth strategies: interactive feedback, gamified leaderboards, challenges, personalized learning path, AR-based simulations, and badges. Thus, strategies were rated upon the impact on the learners' outcome, and the ratings were agreed upon as a fuzzy set, because it is a subjective matter of evaluation. Normalization was done to get a balanced measurement that gave weights on which strategies are to be given higher priority. Such a model has been developed and implemented in a case study of AR-based spatial ability training application, focusing on AR-based simulations supplemented with interactive feedback. Pre- and post-tests among 30 respondents have shown significant improvements in the experimental group using the AR application over the control group using traditional means of spatial ability training. The results strongly support the potential of the model for later implementation in AR educational applications that focus on individual specifics and effective learning. © 2024 IEEE.

关键词： Contrastive Learning

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ViT-SENet-Tom: machine learning-based novel hybrid squeeze–excitation network and vision transformer framework for tomato fruits classification

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Neural Computing and Applications 2025年第9期37卷 6583-6600页

作者： Swapno, S M Masfequier Rahman Nobel, S. M. Nuruzzaman Islam, Md Babul Bhattacharya, Pronaya Mattar, Ebrahim A. Department of CSE Bangladesh University of Business and Technology Dhaka1216 Bangladesh Department of Computer Modeling Electronic and System Engineering UNICAL Rende Italy Department of Computer Science and Engineering Amity School of Engineering and Technology and Research and Innovation Cell Amity University West Bengal Kolkata India Robotics - Cybernetic College of Engineering University of Bahrain Manama Bahrain

Tomatoes are essential fruits in numerous nations for their vast demand. It is very important to maintain the freshness of tomatoes. One of the primary challenges in the recent culinary landscape is accurately identifying healthy tomatoes while effectively eliminating damaged or rejected ones. Existing approaches employ various strategies for categorizing tomato fruit, but they often suffer from inaccuracies, slow detection, and suboptimal performance. Thus, motivated by this gap, in this paper, we propose a novel machine learning (ML) framework, ViT-SENet-Tom, which is a hybrid vision transformer (ViT) model with squeeze and excitation (SENet) block network for fast, accurate, and efficient tomato fruit classification. The framework works on three tomato classes, respectively, the ripe, unripe, and reject. In developing the proposed model, we utilized advanced and newly designed layers and functions. This integration created a more complex and sophisticated neural network, significantly enhancing efficiency and contributing to the model’s novelty. Our chosen dataset was small initially, but we implemented augmentation techniques to increase its size. This approach made our system more reliable, efficient, and effective. The hybrid ViT-SENet framework employs encoders and self-attention networks with squeeze and excitation channel functions to allow precise, robust, fast, and efficient tomato classification. In simulation, the framework achieves a training accuracy of 99.87% and validation accuracy of 93.87%, indicating the precise classification of tomatoes. Besides, this work tests accuracy using fivefold cross-validation. The highest accuracy seen at fold-5 is 99.90%. These testing results demonstrate the efficacy of the proposed framework in real-deployment scenarios. The implementation has the potential to provide enhanced and more sustainable food security and safety in future. © The Author(s) 2025.

关键词： Fruits

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Fault Diagnosis Scheme for Railway Switch Machine Using Multi-Sensor Fusion Tensor Machine

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computers, Materials & Continua 2024年第6期79卷 4533-4549页

作者： Chen Chen Zhongwei Xu Meng Mei Kai Huang Siu Ming Lo School of Electronic and Information Engineering Tongji UniversityShanghai201804China Department of Architecture and Civil Engineering City University of Hong KongHong KongChina School of Computer Engineering Jimei UniversityXiamen361021China

Railway switch machine is essential for maintaining the safety and punctuality of train operations.A data-driven fault diagnosis scheme for railway switch machine using tensor machine and multi-representation monitoring data is developed *** existing methods,this approach takes into account the spatial information of the time series monitoring data,aligning with the domain expertise of on-site manual ***,a multi-sensor fusion tensor machine is designed to improve single signal data’s limitations in insufficient ***,one-dimensional signal data is preprocessed and transformed into two-dimensional ***,the fusion feature tensor is created by utilizing the images of the three-phase current and employing the CANDE-COMP/PARAFAC(CP)decomposition ***,the tensor learning-based model is built using the extracted fusion feature *** developed fault diagnosis scheme is valid with the field three-phase current *** experiment indicates an enhanced performance of the developed fault diagnosis scheme over the current approach,particularly in terms of recall,precision,and F1-score.

关键词： Railway switch machine tensor machine fault diagnosis

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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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A Facile Approach To Represent Neural Network With Less Storage Space

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IEEE Transactions on Emerging Topics in Computational Intelligence 2023年第4期7卷 1205-1216页

作者： Huang, Sheng-An Leu, Jenq-Shiou National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei Taiwan

Deep neural networks have been applied to different applications, such as image recognition, data analysis, natural language processing, and so on. Some companies regularly release their mobile applications to app stores. Usually, app stores have a restriction that overweight applications can not be downloaded until the smartphone connects to Wi-Fi. Unfortunately, the size of the application that consists of deep neural networks may be too large. In order to reduce the size of application, an efficient compression approach is highly desired. An efficient encoding for compressed neural networks is a critical point for reducing storage complexity. Most of previous studies focus on the sparse matrix encoding instead of the dense one. The dense matrix encoding methods have not been studied well. Meanwhile, sparse matrix encoding can not attain a high compression rate when encoding a dense matrix. Toward this end, we proposed an alternative compression algorithm that linearizes the weights on each layer and then stores linearized weights with critical information. For a dense matrix, our algorithm can achieve a higher compression rate than one existing sparse matrix encoding. Experiment results indicate that our proposed piecewise linearization scheme can make VGG-16, Resnet152, and Densenet169 achieve at least two times of the compression rates. In other words, neural networks parameters can be stored in 40-50% of the original space. © 2017 IEEE.

关键词： Linearization

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