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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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Self-Adaptive Facial Expression Recognition Based on Local Feature Augmentation and Global information Correlation

Self-Adaptive Facial Expression Recognition Based on Local F...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Yan, Lingyu Xia, Jinyao Wang, Chunzhi Hubei University of Technology Faculty of Computer Science WuHan430086 China Hubei University of Technology Department of Computer Science WuHan430086 China

ISBN: (纸本)9798350337020

Facial expression recognition(FER) is one of the important research in computer vision, which has been widely applied in human-computer interaction, education, healthcare, transportation, etc. However, the wide application of facial expression recognition technology also brings new challenges, where occlusion and pose variation are two of the worst factors that disturb facial expression recognition in the wild. We propose a facial expression recognition method based on local feature augmentation and multi-scale global correlation which can adaptively extract robust local features and global features from the feature level to suppress the disturbances of occlusion and pose variation on facial expression recognition. The experimental results show that our method performs well on the RAF-DB dataset and has stronger robustness compared with other algorithms. © 2023 IEEE.

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Studying of Machine Learning Models for Forecasting Macroeconomic Indicators 27

Studying of Machine Learning Models for Forecasting Macroeco...

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27th International Conference on Advanced Communications technology, ICACT 2025

作者： Ngoc, Lan Dong Thi Ngo-Thi-Thu-Trang Kim, Kyoung-Mok Pham, Vung Nguyen, Ha-Nam Department of Economic Information System Academy of Finance Hanoi Viet Nam Faculty of Information Technology University of Engineering and Technology Vietnam National University Hanoi Viet Nam Posts and Telecommunications Institute of Technology Hanoi122300 Viet Nam Computer Science Department Sam Houston State University HuntsvilleTX77340 United States Department of Medical Information Sahmyook Health University Seoul Korea Republic of Faculty of Information Technology Electric Power University Hanoi Viet Nam

ISBN: (纸本)9791188428137

This study explores the application of machine learning models in forecasting macro-economic indicators, including GDP, inflation rate, unemployment rate, and exchange rate across 11 Southeast Asian countries. The models used include Linear Regression, ARIMA, Random Forest, XGBoost, LSTM, and SVM. We conducted a performance comparison of each model based on MAE, RMSE, and R2 metrics to evaluate the accuracy of the forecasts. The experimental results indicate that Random Forest and XGBoost models excel in predicting nonlinear and complex indicators such as GDP and unemployment rate, while ARIMA and Linear Regression models perform better in time series with clear regular patterns, like inflation rate. The LSTM model shows inconsistent effective-ness, requiring large data volumes and complex optimization processes. SVM demonstrates potential in handling nonlinear data but requires careful tuning. This study concludes that using machine learning models presents significant potential for improving the accuracy of macroeconomic forecasting. However, model tuning and optimization are essential to match the characteristics of each type of economic indicator. Future research directions include developing hybrid models and integrating additional factors such as market sentiment, social and environmental indicators (ESG) to enhance forecasting outcomes. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.

关键词： Inflation

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Developing Accurate Sri Lankan Sign Language to Tamil Vocal And American Sign Language Translation 10

Developing Accurate Sri Lankan Sign Language to Tamil Vocal ...

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10th International Conference on Engineering and Emerging Technologies, ICEET 2024

作者： Ratnasingam, Sabaskaran Sakajarasa, Dilaxshan Chamara, Didula Gamage, Aruna Ishara Sri Lanka Institue of Information Technology Department of Computer Science & Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798331532895

This research presents a web-based real-time Sri Lankan Sign Language (SLSL) translation system aimed at bridging communication gaps for individuals with speech and hearing disabilities. Leveraging advanced machine learning, the system translates SLSL gestures into Tamil vocal language and American Sign Language (ASL), supported by video-to-text conversion with Yolo-NAS, voice model and clips of animated 3D characters. Key objectives included accurate vocabulary mapping for selected vocabularies, real-time translation with minimal latency, an audio player to display Tamil voice and animated 3D characters to convey nuanced ASL gestures. The system is integrated as one website, but each translation part has separate pages where users can navigate and fulfill their needs. User feedback highlighted the simple and direct user interface design and fluidity of interactions, particularly the animated 3D characters in SLSL to ASL translation. Challenges included optimizing gesture rendering and expanding vocabulary coverage, which will be addressed in future work. This research underscores the potential of AI-driven solutions for enhancing accessibility and inclusivity in communication with cross-lingual and cross-model communication features. © 2024 IEEE.

关键词： User interfaces

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Intense Triad Defender for End-User Security in Cyber Physical system 2

Intense Triad Defender for End-User Security in Cyber Physic...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Sheryl Sharon, G. Maranco, M. Nidhya, R. Sivakumar, M. Coimbatore Institute of Technology Department of Computer Science and Engineering Coimbatore641014 India SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Networking and Communications Kattankulathur603203 India Madanapalle Institute of Technology and Science Department of Computer Science and Engineering Andhra Pradesh Madanapalle India

ISBN: (数字)9798350365269

ISBN: (纸本)9798350365269

The rapid advancement of technology has undoubtedly brought comfort to humanity, but it also necessitates robust authentication measures to ensure security in the ever-expanding e-world. This research aims to address the critical aspects of security, focusing on end-user authentication. The proposed solution incorporates multiple factors, including location-based authentication, text-based authentication with enhanced encryption standards, and facial recognition authentication. Location-based authentication serves to restrict access geographically, mitigating the risk of impersonation by enforcing strict geographic limits on facility access. Strong text passwords, utilizing a unique algorithm with a classic salt method, add an extra layer of complexity for potential attackers, making it challenging to compromise user credentials. The incorporation of facial recognition technology acts as a deterrent against non-human entities attempting unauthorized access. Leveraging deep learning and API servers ensures precision and scalability in the model, enhancing its effectiveness in real-world scenarios. These multi-factor authentication techniques collectively contribute to a secure, reliable, and forward-looking solution to address the evolving landscape of digital security threats. In adhering to the age-old adage "prevention is better than cure,"the research emphasizes the importance of proactive measures to safeguard against potential security breaches. © 2024 IEEE.

关键词： Network security

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Bridging Language Barriers: An Open Source Typing Tool with a Vision for Indian Language Integration

Bridging Language Barriers: An Open Source Typing Tool with ...

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2024 IEEE International Conference on Intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Swain, Satyaprakash Kumar Jayasingh, Suvendra Mishra, Raj Kumar Kabat, Manas Ranjan Swain, Chinmaya Kumar Institute of Management of Information Technology Cuttack Bput Department of Computer Science and Engineering Odisha Cuttack India

ISBN: (纸本)9798331508432

In an increasingly interconnected world, language diversity should be celebrated rather than hindered. This paper delves into the significance of open-source technology as a means of breaking down language barriers and promoting linguistic inclusivity. Focusing on the development of an open-source language typing tool, this research addresses a critical need in digital communication. While several commercial software solutions exist for language input, their proprietary nature limits accessibility and customization. In contrast, the proposed tool, crafted in Python, embraces the open-source ethos, fostering collaboration and allowing for tailored solutions to accommodate the unique linguistic nuances of Indian Languages. The core aim of this study is twofold. First, it seeks to establish a robust and user-friendly open-source input tool for Odia and Hindi with both Rule Based and free typing. Second, it lays the foundation for broader Indian language integration, recognizing the rich tapestry of languages spoken throughout the country. © 2024 IEEE.

关键词： Python

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Bi-Static Inverse Synthetic Aperture Radar Imaging Based on 5G NR Signal 23

Bi-Static Inverse Synthetic Aperture Radar Imaging Based on ...

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23rd International Symposium on Electrical Apparatus and Technologies, SIELA 2024

作者： Lazarov, Andon Kostadinov, Todor Nikola Vaptzarov Naval Academy Information Technology Department Varna Bulgaria Burgas Free University Computer Science and Engineering Faculty Burgas Bulgaria

ISBN: (纸本)9798350382365

This study addresses Bi-static Inverse Synthetic Aperture Radar (BISAR) concept with a 5G NR waveform. BISAR scenario with uncooperative transmitter and specially designed receiver, and flying target as helicopter is discussed. The positions of the transmitter, receiver and flying target are defined by vector kinematic equations. Mathematical models of 5G NR waveform and BISAR signal reflected from a target with complex geometry are described. Two dimensional (2-D) image reconstruction is realized by applying correlation with an emitted waveform or Fourier transform on a range direction, and Fourier transform on an azimuth direction. Simulation experimental results are provided to illustrate the correctness of mathematical models and imaging algorithms. © 2024 IEEE.

关键词： Inverse synthetic aperture radar

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Enhancing single-lead electrocardiogram arrhythmia detection with empirical mode decomposition

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Neural Computing and Applications 2025年第17期37卷 11583-11605页

作者： Issa, Mohamed F. Yousry, Ahmed Tuboly, Gergely Wang, Zeyu Zoltan, Juhasz Selim, Mazen M. AbuEl-Atta, Ahmed H. Department of Scientific Computing Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Computer Science Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Electrical Engineering and Information Systems University of Pannonia Veszprem8200 Hungary Department of Mechatronics Delta University for Science and Technology Gamasa35712 Egypt

Cardiac arrhythmias pose a significant challenge to health care, requiring accurate and reliable detection methods to enable early diagnosis and treatment. However, traditional ECG beat classification methods often lack robustness and fail to generalize effectively to diverse clinical scenarios, particularly when using single-lead-I recordings, which are less studied compared to lead II. To address this gap, this paper proposes a novel method that combines deep learning and empirical mode decomposition (EMD) for arrhythmia detection using single-lead-I ECG recordings obtained with electrodes on each hand. The hybrid model comprises 149 layers of one-dimensional convolution, max pooling, and residual blocks. By leveraging EMD, it classifies ECG beats into normal beats, premature ventricular contractions, and atrial premature beats with high sensitivity (99.86%, 99.72%, and 99.84%, respectively) using the first four intrinsic mode functions (IMFs). The proposed method is applicable in clinical and out-of-hospital monitoring scenarios, and an accompanying web application provides real-time analysis and diagnostic results. This approach addresses a critical gap in lead-I ECG analysis, enhancing diagnostic precision and expanding the scope of ECG applications in health care. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Empirical mode decomposition

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Large-Scale Expensive Optimization with a Switching Strategy

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Complex system Modeling and Simulation 2022年第3期2卷 253-263页

作者： Mai Sun Chaoli Sun Xiaobo Li Guochen Zhang Farooq Akhtar School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China Department of Computer Sciences and Information Technology University of Kotli Azad Jammu and KashmirKotli 11100Pakistan

Some optimization problems in scientific research,such as the robustness optimization for the Internet of Things and the neural architecture search,are large-scale in decision space and expensive for objective *** order to get a good solution in a limited budget for the large-scale expensive optimization,a random grouping strategy is adopted to divide the problem into some low-dimensional sub-problems.A surrogate model is then trained for each sub-problem using different strategies to select training data *** that,a dynamic infill criterion is proposed corresponding to the models currently used in the surrogate-assisted sub-problem ***,an escape mechanism is proposed to keep the diversity of the *** performance of the method is evaluated on CEC’2013 benchmark *** results show that the algorithm has better performance in solving expensive large-scale optimization problems.

关键词： large-scale optimization problems computationally expensive problems random grouping surrogate models

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Cryptocurrency volatility prediction based on price, return and volatility cross-correlation using LSTM 11

Cryptocurrency volatility prediction based on price, return ...

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11th International Symposium on Telecommunication, IST 2024

作者： Abarghouie, Masoud Omidvari Alizadeh, Sasan H. Khademzadeh, Ahmad Islamic Azad University Science and Research Branch Department of Computer Engineering Tehran Iran Faculty of Information Technology Tehran Iran Tehran Iran

ISBN: (纸本)9798350356250

The rise of cryptocurrencies as a major economic factor has drawn interest from both individual investors and regulators. This has led researchers to explore new ways to predict cryptocurrency volatility. This research proposes a new approach for more accurately predicting the conditional variance of cryptocurrencies while previous research did not investigate cross-correlation among cryptocurrency mean and volatility landscapes. This research precisely uses a method to select the most relevant features based on the cross-correlation between price, returns, and volatility. Experiments on eight cryptocurrencies that have the largest market capacity from 2018 to 2024 show that this approach is effective. By considering stronger cross-correlation when choosing the data used for volatility prediction using LSTM, the research substantially reduces the error of prediction. The findings of this research can be used to predict the volatility of other cryptocurrencies and the stock markets. © 2024 IEEE.

关键词： Prediction models

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