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2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Supriya, K. Sangeetha Jeno Lovesum, S.P. Arora, Renuka Bhatia, Rishu Yadwad, Sunita Natrayan, L. Department of Computer Science & Engineering Christ University Bengaluru India Department of Computer Science & Engineering Jagannath University NCR Bahadurgarh India Department of Electronics and Communication Engineering Ganga Institute of Technology and Management Jhajjar India Department of Computer Science and Engineering Faculty of Engineering and Technology Parul institute of Engineering and Technology Parul University Vadodara India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai India

ISBN: (纸本)9798331504960

The proliferation of Internet of Things (IoT) devices has introduced significant security challenges due to the increased attack surface and the inherent vulnerabilities of interconnected systems. This paper proposes a novel security framework that integrates Artificial Intelligence (AI)-infused software and Virtual Replica Models, or Digital Twins, to enhance the robustness of IoT systems. The framework leverages AI-driven anomaly detection and predictive analysis to identify potential threats in real-time, while Digital Twins provide a virtual replica of the IoT ecosystem for continuous monitoring and simulation-based threat assessment. By fusing these technologies, the proposed solution enables proactive security measures, ensuring rapid response to cyberattacks and continuous system optimization. Extensive simulations and experimental results demonstrate the system’s ability to reduce attack detection times by 30%, while improving overall system resilience and minimizing false positive rates. This approach provides a scalable and adaptable solution for securing IoT infrastructures in various industries. © 2024 IEEE.

关键词： Risk assessment

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Arabic Handwritten Document OCR Solution with Binarization and Adaptive Scale Fusion Detection 6

Arabic Handwritten Document OCR Solution with Binarization a...

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6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Waly, Alhossien Tarek, Bassant Feteha, Ali Yehia, Rewan Amr, Gasser Fares, Ahmed Egypt-Japan University of Science and Technology E-JUST Faculty of Engineering Computer Science and Engineering Departement Alexandria21934 Egypt Benha University Faculty of Engineering Electrical Engineering Department Cairo11629 Egypt

ISBN: (纸本)9798350378511

The problem of converting images of text into plain text is a widely researched topic in both academia and industry. Arabic handwritten Text Recognation (AHTR) poses additional challenges due to diverse handwriting styles and limited labeled data. In this paper we present a complete OCR pipeline that starts with line segmentation using Differentiable Binarization and Adaptive Scale Fusion techniques to ensure accurate detection of text lines. Following segmentation, a CNN-BiLSTM-CTC architecture is applied to recognize characters. Our system, trained on the Arabic Multi-Fonts Dataset (AMFDS), achieves a Character Recognition Rate (CRR) of 99.20% and a Word Recognition Rate (WRR) of 93.75% on single-word samples containing 7 to 10 characters, along with a CRR of 83.76% for sentences. These results demonstrate the system's strong performance in handling Arabic scripts, establishing a new benchmark for AHTR systems. © 2024 IEEE.

关键词： Arabic Optical Character Recognition convolutional neural networks line segmentation recurrent neural networks Scene text detection

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Lithium mapping in a Mg-9Li-4Al-1Zn alloy using electron energy-loss spectroscopy

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Journal of Magnesium and Alloys 2023年第4期11卷 1170-1179页

作者： Yu Zhang Laure Bourgeois Yu Chen Zhuoran Zeng Nick Birbilis Philip N.H.Nakashima Department of Materials Science and Engineering Monash UniversityVIC 3800Australia Monash Centre for Electron Microscopy Monash UniversityVIC 3800Australia College of Engineering and Computer Science Australian National UniversityACT 2601Australia Faculty of Science Engineering and Built EnvironmentDeakin UniversityVIC 3125Australia

Magnesium-lithium alloys with high lithium content have been attracting significant attention because of their low density,high formability and corrosion *** properties are dependent on the distribution of lithium,which is difficult to map in the presence of *** this work,a ratio spectrum-imaging method with electron energy-loss spectroscopy(EELS)is demonstrated,which enables the mapping of *** application to LAZ941(Mg-9Li-4Al-1Zn in wt.%),this technique revealed that a key precipitate in the microstructure,previously thought by some to be Mg_(17)Al_(12),is in fact rich in *** result was corroborated with a structural investigation by high-angle annular dark-field scanning transmission electron microscopy(HAADF-STEM),showing this phase to be Al_(1-x)Zn_(x)Li,with x<<*** work indicates the potential offered by this technique for mapping lithium in materials.

关键词： Lithium mapping Magnesium alloys Electron energy-loss spectroscopy(EELS) High-angle annular dark-field scanning transmission electron microscopy(HAADF-STEM)

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Software design and FPGA implementation of optimized medical image fusion techniques

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Multimedia Tools and Applications 2025年 1-31页

作者： Elshazly, E.A. El-Shafai, Walid El-Hoseny, Heba El-Rabaie, El-Sayed M Zahran, O. Abdelwahab, Safey A. S. El-Halawany, M.M. Fikry, R.M. Elaraby, S.M. Faragallah, Osama S. Mohamed, Wael A. Mahmoud, Korany R. Abd El-Samie, Fathi E. Cairo Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Faculty of Computer Studies Arab Open University 11681 Riyadh Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif University 11099 Taif21944 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Benha University Benha Egypt Electronics and Communications Engineering Department Faculty of Engineering Helwan University Helwan Egypt Giza Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Nowadays, medical image fusion plays a crucial role in enhancing the diagnosis accuracy and the clinical decision-making process in various healthcare applications. This research work presents a comprehensive study of the design and implementation of optimized medical image fusion techniques using a combination of software and Field-Programmable Gate Array (FPGA) technologies. The proposed medical image fusion strategy is based on the utilization of Discrete Wavelet Transform (DWT) and Modified Central Force Optimization (MCFO). The implementation of the proposed technique as well as the traditional medical image fusion techniques is considered using an appropriate software design and FPGA. The presented techniques aim to overcome the limitations of traditional fusion techniques by integrating advanced image processing algorithms, optimization algorithms, and parallel computing capabilities offered by FPGA platforms. The first step in the proposed framework is to match the histogram of one of the images with that of the other, so that both images will have the same dynamic range. After that, the DWT is used to decompose the images that should be fused together. Based on some constraints, the MCFO optimization algorithm is used to evaluate the optimum level of decomposition and the optimum parameters for the best fusion quality. Finally, to improve the obtained visual quality and reinforce the information in the fusion result, an additional contrast enhancement step using adaptive histogram equalization is applied to the fusion result. Comparative study between the proposed optimized DWT-based fusion framework, the traditional Principal Component Analysis (PCA), Additive Wavelet Transform (AWT), and DWT-based fusion techniques is presented. Various metrics of fusion quality are considered, including average gradient, standard deviation, local contrast, entropy, edge strength, Peak Signal-to-Noise Ratio (PSNR), Qab/f, and processing time. The proposed optimized DWT-ba

关键词： MATLAB

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Enhancing Stock Price Prediction: A Hybrid Approach Leveraging Large Language Models and Deep Learning

Enhancing Stock Price Prediction: A Hybrid Approach Leveragi...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Ahmed, Mohamed Erfan Ebrahim, Gamal A. Abdelaal, Marwa A. Ain Shams University Faculty of Engineering Computer and Systems Engineering Department Cairo Egypt Sadat Academy for Management Sciences Faculty of Computers and Information Computer Science Department Cairo Egypt

ISBN: (纸本)9798350367560

Accurate stock price prediction is a challenging yet crucial goal in finance, with significant implications for investment decisions and risk management. This paper presents a comprehensive review of machine learning techniques for stock price prediction, examining traditional methods such as regression and ensemble models, as well as advanced approaches that integrate sentiment analysis and textual data sources. With the emergence of powerful Large Language Models (LLMs) such as ChatGPT, Llama and Gemini, we explore their potential for enhancing predictive accuracy using historical stock data. Key challenges are discussed, including data quality, model interpretability, and adapting to dynamic market conditions. Additionally, this paper proposes a trustworthy stock price prediction model based on LLMs enabling informed investment decision-making. Experimental results demonstrate that ChatGPT-4o model achieved a prediction accuracy of approximately 97%, which can be improved by tuning model parameters. Consequently, the paper highlights the potential of LLMs in improving stock price forecasting. © 2024 IEEE.

关键词： Prediction models

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Designing ChulaVerse: A Virtual World for Sustainable Community Engagement 21

Designing ChulaVerse: A Virtual World for Sustainable Commun...

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21st International Conference on Information Technology Based Higher Education and Training, ITHET 2024

作者： Kruachottikul, Pravee Tea-Makorn, Pinnaree Cooharojananone, Nagul Suchato, Atiwong Wuttisittikulkij, Lunchakorn Wanvarie, Dittaya Nupairoj, Natawut Kovitanggoon, Kittikul Cheetanom, Napat Phanomchoeng, Gridsada Chulalongkorn University Graduate Affairs Faculty of Medicine Bangkok Thailand Sasin School of Management Chulalongkorn University Bangkok Thailand Chulalongkorn University Faculty of Science Department of Mathematics and Computer Science Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Computer Engineering Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Electrical Engineering Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Mechanical Engineering Bangkok Thailand

ISBN: (纸本)9798331516635

The rapid adoption of digital technologies, accelerated by the COVID-19 pandemic, has driven the development of innovative virtual platforms. ChulaVerse, a metaverse platform developed by Chulalongkorn University, aims to foster sustainable community engagement through immersive solutions in education, healthcare, and commerce. This paper outlines the design and implementation of ChulaVerse, emphasizing its comprehensive digital ecosystem that allows users to participate in various activities within an interactive virtual environment. A user satisfaction survey was conducted with high school students to assess its effectiveness, revealing generally high levels of satisfaction, particularly in visual appeal and trial experiences. The survey also identified areas f or improvement, especially in meeting diverse user needs. While ChulaVerse successfully meets its primary objectives, further refinements a re necessary to enhance inclusion and functionality. These results will guide the ongoing development of the project, with a focus on refining its features to better align with user needs and preferences. ChulaVerse serves as a pioneering example in the emerging field of metaverse technologies, which have a potential in transforming educational and community engagement in universities. © 2024 IEEE.

关键词： Virtual environments

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Face Emotion Recognition System of Customer Service Using CNN Based on Embedded System 23

Face Emotion Recognition System of Customer Service Using CN...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Nawfal, Muhammad Zulkifli Prasetio, Barlian Henryranu Department of Computer Engineering Faculty of Computer Science Brawijaya University Indonesia Faculty of Computer Science Brawijaya University Indonesia

ISBN: (纸本)9798400708503

The aim of this research is to design a facial emotion recognition system based on Raspberry Pi and Convolutional Neural Network (CNN) for analyzing customers' facial expressions in academic customer service. The utilization of TensorFlow as the framework and the integration of the Pypaz library will support the facial emotion recognition approach by processing images and classifying emotional expressions. The implementation of this system is expected to provide objective data regarding customer satisfaction based on their facial expressions and help improve customer service performance. © 2023 ACM.

关键词： Emotion Recognition

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Current Trends and Challenges of Cloud Computing and Emerging Technological Utilization in Technical Education 5

Current Trends and Challenges of Cloud Computing and Emergin...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Kaswan, Suresh Goyal, Parul Khirasaria, Vivek Yugal, Lisha Amita Chandigarh University Department of Computer Science & Engineering Punjab Mohali India M. M. Engineering College Maharishi Markandeshwar Deemed to Be University Computer Science & Engineering Department Haryana Mullana India Sharda University Faculty of Engineering and Technology Uzbekistan Sharda University Department of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798350379945

This research study explores the impact of cloud computing on engineering education in India, focusing onhow it enhances educational outcomes. This study examines the potentialof strategic cloud implementation in higher education to accelerate development and competitiveness. The study analyzes the current state of technical education in India and identifies areas where cloud integration can drive positive changes. Key research questions are formulated to guide the exploration of creating intelligent cloud applications for effective technical education. © 2024 IEEE.

关键词： Cloud platforms

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Cloud Computing and Neutrosophic Logic: Navigating Uncertainty in Educational Administration

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Neutrosophic Sets and Systems 2025年 78卷 102-449页

作者： Yasser, Ibrahim Abd El-Khalek, Aya A. Khalid, Huda E. Salama, A.A. Essa, Ahmed K. Engineering Faculty University of Mansoura Mansoura35516 Egypt Communications and Electronics Engineering Department Nile Higher Institute for Engineering and Technology Mansoura35524 Egypt Telafer University The Administration Assistant for the President of the Telafer University Telafer Iraq Department of Mathematics and Computer Science Faculty of Sciences Port Said University Port Said42526 Egypt

Educational institutions face inherent uncertainties in student performance, stakeholder priorities, and data analysis. This paper explores how cloud computing, with its data storage, analytics, and collaboration tools, can address these uncertainties in educational administration. We propose a neutrosophic framework utilizing "truth," "falsity," and "indeterminacy" values to represent these complexities within educational data. Real-world case studies analyze how cloud computing can reduce uncertainties and improve decision-making. Our findings reveal that cloud computing offers significant potential for navigating the "fog" of educational administration, but its effectiveness is enhanced by considering the "indeterminacy" inherent in educational data through the neutrosophic framework. This research contributes a unique neutrosophic perspective to the use of cloud computing for improved and more informed decision-making in educational administration. © 2025, University of New Mexico. All rights reserved.

关键词： Case Studies Cloud Computing Decision-Making Educational Administration Educational Data Neutrosophic Logic Uncertainty

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Cyber Security Management through User Testing of E-Commerece Website - A Case Study 5

Cyber Security Management through User Testing of E-Commerec...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Kaswan, Suresh Yugal, Lisha Khirasaria, Vivek Amita Goyal, Parul Chandigarh University Department of Computer Science & Engineering Punjab Mohali India Sharda University Department of Computer Science & Engineering Greater Noida India Sharda University Faculty of Engineering and Technology Uzbekistan M. M. Engineering College Maharishi Markandeshwar Deemed to Be University Computer Science & Engineering Department Haryana Mullana India

ISBN: (纸本)9798350379945

Software testing is crucial for ensuring software quality, including security. This research presents a case study examining manual and open-source tool-based security testing of an e-commerce website. By applying various testing techniques, the study aims to identify potential vulnerabilities and assess security measures at different development stages. The findings will contribute to developing effective security testing strategies for web applications. © 2024 IEEE.

关键词： E-Commerce testing Security Testing Software Testing System testing

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