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Affective Computing in Intelligent Tutoring Systems: Exploring Insights and Innovations

Affective Computing in Intelligent Tutoring Systems: Explori...

South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

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

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

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.

关键词： computers Training Affective computing Sentiment analysis Emotion recognition Technological innovation Text analysis Feature extraction Classification algorithms Guidelines

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Performance Analysis of an Artificial Intelligence Nanosystem with Biological Internet of Nano Things

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computer Modeling in engineering & Sciences 2022年第10期133卷 111-131页

作者： Saied M.Abd El-atty Nancy A.Arafa Atef Abouelazm Osama Alfarraj Konstantinos A.Lizos Farid Shawki Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufEgypt Computer Science Department Community CollegeKing Saud UniversityRiyadhSaudi Arabia Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)OsloNorway

Artificial intelligence(AI)has recently been used in nanomedical applications,in which implanted intelligent nanosystems inside the human body were used to diagnose and treat a variety of ailments with the help of the Internet of biological Nano Things(IoBNT).Biological circuit engineering or nanomaterial-based architectures can be used to approach the *** nanomedical applications,the blood vascular medium serves as a communication channel,demonstrating a molecular communication system based on flow and *** paper presents a performance study of the channel capacity for flow-based-diffusive molecular communication nanosystems that takes into account the ligand-receptor binding *** earlier studies,we take into account the effects of biological physical characteristics such as blood pressure,blood viscosity,and vascular diameter on channel ***,in terms of drug transmission error probability,the inter-symbol interference(ISI)phenomenon is applied to the proposed *** numerical results show that the proposed AI nanosystems-based IoBNT technology can be successfully implemented in future nanomedicine.

关键词： Nanosystem AI Internet of biological Nano Things(IoBNT) channel capacity

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Compact and Efficient Neural Networks for Image Recognition Based on Learned 2D Separable Transform

Compact and Efficient Neural Networks for Image Recognition ...

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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Maxim Vashkevich Egor Krivalcevich Department of Computer Engineering Belarusian State University of Informatics and Radioelectronics Minsk Belarus

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The paper presents a learned two-dimensional separable transform (LST) that can be considered as a new type of computational layer for constructing neural network (NN) architecture for image recognition tasks. The LST based on the idea of sharing the weights of one fullyconnected (FC) layer to process all rows of an image. After that, a second shared FC layer is used to process all columns of image representation obtained from the first layer. The use of LST layers in a NN architecture significantly reduces the number of model parameters compared to models that use stacked FC layers. We show that a NN-classifier based on a single LST layer followed by an FC layer achieves 98.02% accuracy on the MNIST dataset, while having only 9.5k parameters. We also implemented a LST-based classifier for handwritten digit recognition on the FPGA platform to demonstrate the efficiency of the suggested approach for designing a compact and high-performance implementation of NN models.

关键词： Accuracy Image recognition Quantization (signal) Two-dimensional displays Transforms Artificial neural networks computer architecture Image representation Field programmable gate arrays Image classification

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Lightweight Privacy Architecture for Homomorphic Operations in e-Health Systems

Lightweight Privacy Architecture for Homomorphic Operations ...

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IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)

作者： K. Tsantikidou N. Sklavos Computer Engineering and Informatics Department SCYTALE Group University of Patras Hellas

ISBN: (数字)9798331521219

ISBN: (纸本)9798331521226

In recent years, traditional hospital facilities are adopting new technologies that provide novel services. Nevertheless, these services may be performed by third parties, that pose a threat to data privacy. As health data is sensitive, it must be constantly encrypted from the moment it is collected. Thus, an appropriate privacy scheme that is suitable for the resource constrained e-Health environment is required. In this paper, a lightweight privacy architecture, applied for homomorphic operations in IoT systems for e-Health is proposed. The focus is its easy implementation in devices with resource limitations, while also enhancing privacy. Two security versions of the same architecture are presented, with different parameters. Each proposed version achieves a minimum of 70.27% and 49.2% resource reduction compared to published related works. The proposed compact version achieves a minimum of 19.7% area-delay reduction compared to published designs. The main reasons for these results are the employment of synthesizable operations, the fusion of functions and the pipeline architecture of operations.

关键词： Privacy Data privacy Hospitals Pipelines Employment Internet of Things Cryptography Homomorphic encryption

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

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

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International Conference on Education and Technology (ICET)

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

ISBN: (数字)9798331522483

ISBN: (纸本)9798331522490

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.

关键词： Presses Accuracy Filtering Collaborative filtering Education Market research Information filters User experience Recommender systems Information systems

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Modeling Educational Strategies in Augmented Reality Learning Using Fuzzy Weights

Modeling Educational Strategies in Augmented Reality Learnin...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

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

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

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.

关键词： Training Weight measurement Fuzzy sets Three-dimensional displays Social networking (online) Focusing Machine learning Market research Augmented reality Optimization

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Private Computation of Boolean Functions Using Single Qubits 15th

Private Computation of Boolean Functions Using Single Qubit...

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15th International Conference on Parallel Processing and Applied Mathematics, PPAM 2024

作者： Rahmani, Zeinab Pinto, Armando N. Barbosa, Luis S. Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal Instituto de Telecomunicações Aveiro Portugal International Iberian Nanotechnology Laboratory Braga Portugal Department of Computer Science University of Minho Braga Portugal Institute of Systems and Computer Engineering Technology and Science Braga Portugal

ISBN: (纸本)9783031856990

Secure Multiparty Computation (SMC) facilitates secure collaboration among multiple parties while safeguarding the privacy of their confidential data. This paper introduces a two-party quantum SMC protocol designed for evaluating binary Boolean functions using single qubits. Complexity analyses demonstrate a reduction of 66.7% in required quantum resources, achieved by utilizing single qubits instead of multi-particle entangled states. However, the quantum communication cost has increased by 40% due to the amplified exchange of qubits among participants. Furthermore, we bolster security by performing additional quantum operations along the y-axis of the Bloch sphere, effectively hiding the output from potential adversaries. We design the corresponding quantum circuit and implement the proposed protocol on the IBM Qiskit platform, yielding reliable outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Qubits

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An Attention-Based Deep Network for Plant Disease Classification

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Machine Graphics and Vision 2024年第1期33卷 47-67页

作者： Bera, Asish Bhattacharjee, Debotosh Krejcar, Ondrej Department of Computer Science and Information Systems Birla Institute of Technology and Science Rajasthan Pilani India Department of Computer Science and Engineering Jadavpur University West Bengal Kolkata India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Králové Czech Republic Škoda Auto University Mladá Boleslav Czech Republic Universiti Teknologi Malaysia Kuala Lumpur Malaysia

Plant disease classification using machine learning in a real agricultural field environment is a difficult task. Often, an automated plant disease diagnosis method might fail to capture and interpret discriminatory information due to small variations among leaf sub-categories. Yet, modern Convolutional Neural Networks (CNNs) have achieved decent success in discriminating various plant diseases using leave images. A few existing methods have applied additional pre-processing modules or sub-networks to tackle this challenge. Sometimes, the feature maps ignore partial information for holistic description by part-mining. A deep CNN that emphasizes integration of partial descriptiveness of leaf regions is proposed in this work. The efficacious attention mechanism is integrated with high-level feature map of a base CNN for enhancing feature representation. The proposed method focuses on important diseased areas in leaves, and employs an attention weighting scheme for utilizing useful neighborhood information. The proposed Attention-based network for Plant Disease Classification (APDC) method has achieved state-of-the-art performances on four public plant datasets containing visual/thermal images. The best top-1 accuracies attained by the proposed APDC are: PlantPathology 97.74%, PaddyCrop 99.62%, PaddyDoctor 99.65%, and PlantVillage 99.97%. These results justify the suitability of proposed method. © 2024 Institute of Information Technology, Warsaw University of Life Sciences - SGGW. All rights reserved.

关键词： Convolutional neural networks

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Assessing the Impact of Integrating ChatGPT as an Advice Generator in Educational Software

Assessing the Impact of Integrating ChatGPT as an Advice Gen...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

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

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

This paper reports on the study of the integration of ChatGPT as an advice generator in custom educational software developed for Java programming. The software, in cooperation with ChatGPT API, pursues providing real-time, context-specific advice to students for better learning. This work adopted a two-fold evaluation approach to evaluating this integration. First, this study examines the effectiveness of this integration with the help of the Interrupted Time Series Analysis methodology to measure possible improvement in the performance metrics of the students in terms of error rates and task completion times. Second, this work presents a custom-designed questionnaire used to get student perceptions regarding the clarity, usefulness, and impact of ChatGPT’s advice, and the level of student satisfaction with the user interface. The key takeaways from this research study are the substantial improvements in performance metrics that were noted quantitatively, with students achieving lower error rates and faster completion times after the intervention of ChatGPT. Qualitatively, learners express their satisfaction with the clarity of advice, which gives them an understanding that works on their learning and confidence in Java programming. These findings point toward the promise of integrating such advanced AI solutions in educational software toward a significant improvement in learning outcomes and the necessity of human-aided continuous user feedback for system refinement.

关键词： Java Error analysis Time series analysis User interfaces Chatbots Software Generators Time measurement Artificial intelligence Programming profession

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The Gamification Advantage: Innovating Education through Engagement

The Gamification Advantage: Innovating Education through Eng...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

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

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

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.

关键词： Design automation Social networking (online) Scalability Education Europe Games computer networks Research and development

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