检索结果-内蒙古大学图书馆

2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Reddy, M. Jithender Kotiyal, Arnav Lakhanpal, Sorabh Badhoutiya, Arti Mounika, T. Jayanthi, Muthuswamy Vasavi College of Engineering Dept. of Computer Science and Engineering Telangana Hyderabad India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Lovely Professional University Punjab Phagwara India GLA University Department of Electrical Engineering Mathura India MLR Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India New Horizon College of Engineering Department of Electronics and Communication Engineering Bangalore India

ISBN: (纸本)9798331512965

Technology such as machine learning in healthcare has pushed privacy concerns to the point that the handling of sensitive patient data has become paramount. In the context of FL, predictive analytics without data sharing between institutions can be performed through the process. Next, we explore the application of FL in healthcare in order to maintain data privacy while obtaining robust predictive models. FL utilizes aggregated decentralized data from multiple healthcare providers to reduce the chance of data breaches and continue to be compliant with rigorous regulatory frameworks, like HIPAA and GDPR, while doing so. In this work, we evaluate the model performance of FL models in predicting different types of health outcomes in comparison with traditional centralized models. We show that FL can achieve similar predictive accuracy while maintaining data privacy, which makes the choice of FL as a viable alternative to privacy sensitive healthcare environments. Second, applying FL is very challenging: there are communication overhead, data heterogeneity, and security risks. This study also considers ways to minimize these challenges. The results demonstrate the promise of Federated Learning as an innovative paradigm for applying predictive analytics in healthcare, indicative of a robust shift toward more secure, efficient and privacy preserving healthcare systems. © 2025 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Development of Hybrid Charging Station for Electric Vehicles 1

Development of Hybrid Charging Station for Electric Vehicles

引用

1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Mosetse, Tsaone Karabo Samikannu, Ravi Yahya, Abid Kalpana, C. Ramkumar, M Siva Vidyalakshmi, R. Botswana International University of Science and Technology Department of Electrical Computer and Telecommunications Engineering Palapye Botswana Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India Karpagam Institute of Technology Department of Computer Science Engineering Tamil Nadu Coimbatore India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Karpagam College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350359756

Electric Vehicles (EVs) are growing more popular due to their low-carbon and ecologically ideal qualities. Many studies show the declining supply of fuels and the importance of using renewable energy systems to reduce the air pollution. The EVs capable to exceed the performance of Internal Combustion Engines (ICE). The main problem is infrastructure to facilitate EV charging. The project focuses on research, designing and implementation of the Solar Photo Voltaic (SPV) charging station for EV which will improve reliability and convenience for charging EV's. The design model won't be reliant on the grid power as the main power supply but solar energy. The design model consists of the Solar PV panel, the charge controller circuit, battery, transformer, voltage regulator, the automatic transfer changeover and the load which is connected to the automatic transfer changeover. The project report also shows the activity log of all the tasks carried out throughout the period of the design simulation and hardware development of the model. © 2023 IEEE.

关键词： Internal combustion engines

来源：评论

学校读者我要写书评

暂无评论

An Efficient Shortest Path Optimized Algorithm for Vehicle Adhoc Networks System 7

An Efficient Shortest Path Optimized Algorithm for Vehicle A...

引用

7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Shalini, K. Reddy, K. Harinath Punati, Kondalarao Kavin, K.S. Veena, P. Pushpalatha, K. Vardhaman College of Engineering Department of Artificial Intelligence and Data Science Shamshabad India Annamacharya Institute of Technology and Sciences Department of Electrical and Electronics Engineering Rajampet India Hyderabad Institute of Technology and Management Faculty of Electronics and Communication Engineering Hyderabad500090 India Government College of Engineering Department of Electrical and Electronics Engineering Tamilnadu Tirunelveli India N. S. S. Polytechnic College Department of Computer Engineering Pandalam Pathanamthitta India Coimbatore Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore641109 India

ISBN: (纸本)9798350372816

VANET (Vehicular ad-hoc network) is a network of advanced automobiles designed to solve the problem of mobility and, as a result, reduce the number of accidents. Because VANET is a type of MANET (mobile ad hoc network) surrounded by human-driven nodes, the social concept can be used to explain VANET routing decisions. This motivates academics to look into the possibilities of using Social Network Analysis (SNA) to create routing strategies. The most critical problem in any system is parcel drop. Social characteristics-based architectures encounter comparable challenges, resulting in inefficient message delivery. In this research, the dragonfly method is used to the shortest path methodology for fixed line VANET with the purpose of reducing package drop and increasing network reliability. This is made achievable by sculpted system of values centralization analysis, which improves the decision via dragonfly optimization methodology. The behavior of the using nodes capability then be determined by the importance computation. In this study, the sustainability of the optimized shortest path system is measured in terms of End to End delay, Energy Consumption, Packet Loss, and Throughput. The dragonfly algorithm's throughput evaluation is 650 kbps as compared to the traditional way. © 2024 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Terahertz deep learning fusion computed tomography

引用

Optics Express 2024年第10期32卷 17763-17774页

作者： Hung, Yi-Chun Su, Weng-Tai Chao, Ta-Hsuan Lin, Chia-Wen Yang, Shang-Hua Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Department of Computer Science McCormick School of Engineering and Applied Science Northwestern University EvanstonIL60208 United States Institute of Electronics Engineering National Tsing Hua University Hsinchu30013 Taiwan Terahertz Optics and Photonics Center National Tsing Hua University Hsinchu30013 Taiwan

Terahertz (THz) tomographic imaging based on time-resolved THz signals has raised significant attention due to its non-invasive, non-destructive, non-ionizing, material-classification, and ultrafast-frame-rate nature for object exploration and inspection. However, the material and geometric information of the tested objects is inherently embedded in the highly distorted THz time-domain signals, leading to substantial computational complexity and the necessity for intricate multi-physics models to extract the desired information. To address this challenge, we present a THz multi-dimensional tomographic framework and multi-scale spatio-spectral fusion Unet (MS3-Unet), capable of fusing and collaborating the THz signals across diverse signal domains. MS3-Unet employs multi-scale branches to extract spatio-spectral features, which are subsequently processed through element-wise adaptive filters and fused to achieve high-quality THz image restoration. Evaluated by geometry-variant objects, MS3-Unet outperforms other peer methods in PSNR and SSIM. In addition to the superior performance, the proposed framework additionally provides high scalable, adjustable, and accessible interface to collaborate with different user-defined models or methods. © 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Adaptive filters

来源：评论

学校读者我要写书评

暂无评论

Human Detection and Tracking using Machine Learning Algorithm

Human Detection and Tracking using Machine Learning Algorith...

引用

2024 International Conference on Advances in Computing Research on science engineering and Technology, ACROSET 2024

作者： Nallasivan, G. Thatikonda, Ramya Geetha, M. Bhuvanesh, A. Ramraj, S. Sreethu, S. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India University of the Cumberlands Department of Information Technology Williamsburg United States Sri Eshwar College of Engineering Department of Electrical and Electronics Engineering Coimbatore India Psn College of Engineering and Technology Department of Electrical and Electronics Engineering Tirunelveli India

ISBN: (纸本)9798350388800

The use of OpenCV and its capabilities for person tracking and detection is suggested by this project. The technique works well for following people in a variety of situations, such as busy places, people who are obscured, and people who are moving. The robustness and precision of the estimated model are illustrated through the use of visuals to visualize tracking data. The suggested approach surpasses existing sophisticated algorithms in terms of Intersection over Union (IoU) and mean Average Precision (mAP), achieving excellent accuracy. Potential applications for the proposed method include robots, human-computer interaction, and surveillance. The limits of the suggested approach are also covered, along with suggestions for further research and development. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A comprehensive survey on 6G-security: physical connection and service layers

引用

Discover Internet of Things 2025年第1期5卷 1-30页

作者： Saeed, Mamoon M. Saeed, Rashid A. Hasan, Mohammad Kamrul Ali, Elmustafa Sayed Mazha, Tehseen Shahzad, Tariq Khan, Sunawar Hamam, Habib Sana00967 Yemen Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electronics Engineering College of Electronics Engineering Sudan University of Science and Technology Omdurman Sudan Bangi43600 Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Red Sea University Port Sudan33312 Sudan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Computer Science and Software Engineering International Islamic University Islamabad44000 Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa BP 1989 Av. Grandes Ecoles Libreville Gabon Bridges for Academic Excellence-Spectrum Tunis Tunisia Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

After adopting 5G technology, businesses and academia have started working on sixth-generation wireless networking (6G) technologies. Mobile communications options are expected to expand in areas where previous generations could not do so. 6G networks are anticipated to be constructed using various diverse technologies. These encompass diverse cutting-edge advancements, such as distributed ledger systems like blockchain, visible light communications (VLC), post-quantum cryptography, edge computing, molecular communication, THz, and other advances. These advances necessitate a reassessment of previous security strategies from a security perspective. In the future, networks must adhere to stricter criteria for authentication, encryption, access control, connectivity, and detection of harmful activities. Ensuring privacy and dependability necessitates the implementation of supplementary security protocols. The essay explores the primary concerns and challenges related to the security of the 6G network. This paper describes the improvements in security in communications from 1G through 6G. This paper divides security in the sixth generation into three layers: physical, connection, and service. Each layer-by-layer discusses the standard technologies and security issues for each technology proposed in each sixth-generation security layer. All proposed solutions for each of the three layers are discussed in Sixth Generation Security. It also reviews all proposed solutions for each layer, indicating the proposed solution and its limitations. © The Author(s) 2025.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Geo2ComMap: Deep Learning-Based MIMO Throughput Prediction Using Geographic Data

引用

IEEE Wireless Communications Letters 2025年第6期14卷 1831-1835页

作者： Lin, Fan-Hao Huang, Tzu-Hao Wen, Chao-Kai Duong, Trung Q. National Sun Yat-sen University Institute of Communications Engineering Kaohsiung80424 Taiwan National Yang Ming Chiao Tung University Institute of Electrical Control Engineering Hsinchu300 Taiwan Memorial University Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada Queen's University Belfast School of Electronics Electrical Engineering and Computer Science Belfast United Kingdom

Accurate communication performance prediction is crucial for wireless applications such as network deployment and resource management. Unlike conventional systems with a single transceiver antenna, throughput (Tput) estimation in antenna array-based multiple-output multiple-input (MIMO) systems is computationally intensive, i.e., requiring analysis of channel matrices, rank conditions, and spatial channel quality. These calculations impose significant computational and time burdens. This paper introduces Geo2ComMap, a deep learning-based framework that leverages geographic databases to efficiently estimate multiple communication metrics across an entire area in MIMO systems using only sparse measurements. To mitigate extreme prediction errors, we propose a sparse sampling strategy. Extensive evaluations demonstrate that Geo2ComMap accurately predicts full-area communication metrics, achieving a median absolute error of 27.35 Mbps for Tput values ranging from 0 to 1900 Mbps. © 2012 IEEE.

关键词： Antenna arrays

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Detection Using Variational Mode Decomposition (VMD) and Weighted Bidirectional Extreme Learning Machine

Breast Cancer Detection Using Variational Mode Decomposition...

引用

2023 International Conference in Advances in Power, Signal, and Information Technology, APSIT 2023

作者： Joshi, Sukumar Samanta, Indu Sekhar Panda, Subhasis Rout, Pravat Kumar Swain, Kunjabihari Siksha 'o' Anusandhan University Dept. of Electrical Engineering Bhubaneswar India Siksha 'o' Anusandhan University Dept. of Computer Science and Engineering Bhubaneswar India Siksha 'o' Anusandhan University Department of Electrical and Electronics Engineering India Nist Institute of Science and Technology Dept. of Electrical and Electronics Engineering Berhampur India

ISBN: (纸本)9798350339369

Breast cancer is a principal cause of mortality among women globally, and early identification and diagnosis can significantly increase patients' survival rates. This paper introduces a novel approach for detecting breast cancer using Variational Mode Decomposition (VMD) and a Weighted Bidirectional Extreme Learning Machine (WBELM). The proposed technique utilizes VMD to break mammographic images into multiple modes, each signifying distinct frequency constituents. Following this decomposition, the WBELM is deployed to classify these modes into benign or malignant categories. The method's efficacy is assessed using the Digital Database for Screening Mammography (DDSM), and the simulations demonstrate a commendable accuracy rate of 97.61 %, a sensitivity rate of 97.54 %, and a specificity rate of 97.68%. © 2023 IEEE.

关键词： Variational mode decomposition

来源：评论

学校读者我要写书评

暂无评论

IoT based ECG Signal Feature Extraction and Analysis for Heart Disease Risk Assessment

IoT based ECG Signal Feature Extraction and Analysis for Hea...

引用

2023 International Conference on Sustainable Computing and Smart Systems, ICSCSS 2023

作者： Satheeskumaran, S. Sasikala, K. Neeraj, Kumar Senthilkumar, A. Sharath Babu, N. Anurag Univerity Department of Electronics and Communication Engineering Hyderabad India Vels Univerity Department of Electrical and Electronics Engineering Chennai India Sri Vishnu Engineering College for Women Department of Computer Science and Engineering India

ISBN: (纸本)9798350333602

Digital healthcare solutions are being created to meet the demands of the healthcare industry. Advances in IoT and cloud computing have led to the development of numerous smart healthcare solutions for elderly people and people with chronic diseases. Healthcare centres and physicians get the opportunity to assess the health of patients from anywhere through the developed smart systems. In this work, an IoT and cloud-based healthcare system is developed for ECG signal parameter extraction and machine learning-based analysis that will be helpful in heart disease risk assessment. The minimal local signal processing required by IoT-based healthcare equipment is made possible by cloud computing. However, there are certain concerns related to service quality issues while employing a cloud framework for real-time monitoring and signal processing. This work proposes ECG beat rate detection and machine learning-based analysis in an IoT-based framework. Finding the precise location of the QRS complex during ECG data processing facilitates the detection of heart rate variability (HRV) parameters, which will play a crucial role in the risk assessment of heart diseases. © 2023 IEEE.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

引用

computers, Materials & Continua 2023年第5期75卷 3189-3201页

作者： Shakti Raj Chopra Parulpreet Singh Ahmed Alhussen Nitin Mittal MohdAnul Haq School of Electronics and Electrical Engineering Lovely Professional UniversityPhagwaraPunjab144411India Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia University Centre for Research and Development Chandigarh UniversityMohaliPunjab140413India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Many extensive UAV communication networks have used UAV cooperative *** networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base *** only is coverage maximization,but also better connectivity,a fundamental design challenge that must be *** number of applications for unmanned aerial vehicles(UAVs)operating in unlicensed bands is fast expanding as the Internet of Things(IoT)*** bands,however,have become overcrowded as the number of systems that use them *** Radio(CR)and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,and hence as technological solutions for future generations,from this *** a result,combining CR with UAVs has the potential to give significant benefits for large-scale UAV *** paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient *** maximization,power control,and enhanced connection quality are the three steps of the proposed *** satisfy the desired signal-to-noise ratio,the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural,suburban,and urban macro deployment scenarios of the ITU-R M.2135 standard(SNR).

关键词： UAV networks multi-UAV coverage energy-efficient FER SNR

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：