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IEEE International Conference on electronic Information and Communication technology (ICEICT)

作者： Xingxing Yang Botao Feng Xiao Ding Wenzhe Gu Sanshan Sun Kwok L. Chung College of Electronics and Information Engineering Shenzhen University Shenzhen China Faculty of Humanities and Arts Macau University of Science and Technology Macau China School of Computer Science and Engineering Huizhou University Huizhou China College of Physics and Electronic Engineering Sichuan Normal University Sichuan China School of Computer Science and Engineering Huizhou University Huizhou P. R. China

In this paper, a reflection element sensitive to polarization direction is proposed, which can independently control the phase of incident wave in dual polarized directions. Then, a reflectarray including the proposed 7×7 elements is designed to offer dual-polarized deflection. The results show that the reflectarray achieves a -15° beam deflection with an X-axis polarized incident wave. In contrast, it realizes a +15° beam deflection with a Y-–axis polarized wave. In addition, the cross polarization (X-pol) level is less than -20 dB, and the gain of the array is higher than that of the waveguide feed by 8 dBi. Therefore, significant gain enhancement can be successfully obtained.

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Game-Theory-Guided Reinforcement Learning for Autonomous Vehicles in Highway Scenarios

Game-Theory-Guided Reinforcement Learning for Autonomous Veh...

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IEEE Information technology and Mechatronics engineering Conference (ITOEC)

作者： Jiayang Wang Wanlu Sun Pengbo Xiao Qian Li Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia XC-AS/EDR3-CN Bosch Automotive Products (Suzhou) Co. Ltd. Suzhou China College of Mechanical Engineering Hangzhou University of Electronic Science and Technology Hangzhou China State Key Laboratory of Engines Tianjin University Tianjin China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

Autonomous vehicles have become a popular topic with the development of technology. In the early stages of an automated driving system, the key to correctly guiding the vehicle’s behavior lies in the effective collection and application of expert driving experience. This study introduces a game-theoretic guided reinforcement learning (GTG-RL) framework that merges game-theoretic expert models with reinforcement learning to enhance decision-making efficiency for autonomous vehicles in complex motorway scenarios. Validation confirms the framework’s effectiveness in improving performance and adaptability under dynamic traffic conditions. The results underscore the potential of integrating game-theoretic expertise with reinforcement learning to tackle autonomous driving challenges.

关键词： Road transportation Adaptation models Mechatronics Computational modeling Decision making Reinforcement learning Computational efficiency Vehicle dynamics Information technology Autonomous vehicles

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Fused Fuzzy Deep Learning and Information Steganography for Privacy Preservation in Medical Consumer electronics

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IEEE Transactions on Consumer electronics 2025年

作者： Chen, Jingxue Zhao, Pengbiao Deng, Erqiang Khan, Fazlullah Alturki, Ryan Alshawi, Bandar Xiong, Hu School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China the School of Computer Science Faculty of Science and Engineering University of Nottingham Ningbo China Zhejiang Ningbo315104 China the KKR and KSR institute of technology and sciences Andhra Pradesh Guntur India the Division of Research and Development Lovely Professional University Phagwara India the University Centre of Research and Development Chandigarh University Mohali India the Department of Computer and Network Engineering College of Computing Umm Al-Qura University Makkah Saudi Arabia the Department of Software Engineering College of Computing Umm Al-Qura University Makkah Saudi Arabia

—Medical Consumer electronics (MCE) have greatly facilitated people’s lives, allowing patients to obtain personal medical information including medical images. These medical images obtained from MCE need to be processed using segmentation, diagnosis, recognition to obtain useful information. Deep learning plays an important role in medical image segmentation and recognition. However, other personal information about the patient, such as previous cases, is often required to determine the final diagnosis. However, sending personal information and medical images generated through MCE to the clinic directly exposes patient privacy. Therefore, in this paper, we propose a digital medical image privacy protection framework based on information steganography with fuzzy deep learning. The proposed framework transforms patient privacy information into invisible noise and hides it in the deep covert space of the image. This method plays a crucial role in ensuring patient privacy and data security. Furthermore, this method can ensure a high level of image segmentation accuracy that supports the development of personalized medical services. The experimental results show that the proposed framework can embed patient information in medical images without affecting the segmentation task, and effectively protect privacy. Finally, the proposed framework provides new possibilities and impetus for the popularization of MCE. © 2025 IEEE.

关键词： Medical imaging

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Sustainability of 5G Green Network toward D2D Communication with RF- Energy Techniques

Sustainability of 5G Green Network toward D2D Communication ...

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2021 International Conference on Intelligent Technologies, CONIT 2021

作者： Pradhan, Devasis Sahu, Prasanna Kumar Dash, A. Tun, Hla Myo Acharya Institute of Technology Department of Electronics and Communication Engineering Dr. Sarvepalli Radha Krishnan Road Bengaluru India NIT Rourkela Department of Electrical Engineering Odisha India Department of Electronics and Telecommunication Engineering India Yangon Technological University Faculty of Electrical and Computer Engineering Department of Electronic Engineering Myanmar

ISBN: (纸本)9781728185835

As the world pushes toward the utilization of greener innovation and limits energy squander, energy productivity in the remote organization has gotten more basic than any other time in recent memory. The cutting edge network, for example, 5G, are being intended to improve energy productivity and accordingly establish a basic part of the exploration and network planning. The 5G Green era required to convey a wide scope of administrations that incorporates upgraded versatile broadband, gigantic machine-type correspondence and ultra-dependability, and low inertness. Presently various difficulties and open doors for the plan of modern client affiliation instruments. Thus, considerable examination endeavors are committed to the issues of client relationship in HetNets, massive MIMO, mmWave, and energy harvesting. The paper further discussed the new security highlights including various innovations applied to 5G Green Communication, such as heterogeneous networks, gadget to-gadget interchanges or D2D Communication, enormous different info numerous yield, programming characterized networks, and the Internet of Things(IoT). © 2021 IEEE.

关键词： Heterogeneous networks

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Quantum-Inspired Resource Optimization for 6G Networks: A Survey

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IEEE Communications Surveys and Tutorials 2024年

作者： Butt, Muhammad Omair Waheed, Nazar Duong, Trung Q. Ejaz, Waleed Lakehead University Department of Electrical Engineering ON Canada Faculty of Computing Information Systems Higher Colleges of Technology United Arab Emirates 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 BelfastBT7 1NN United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of

The Internet of things (IoT) drives an exponential surge in computing and communication devices. Consequently, it triggers capacity, coverage, interference, latency, and security issues in the existing communication networks. The forthcoming sixth-generation (6G) networks will address these issues by providing comprehensive solutions. In particular, quantum communication technology can potentially address the challenges of 6G networks. However, its implementation requires substantial infrastructure upgrades. Therefore, the quantum-inspired (QI) techniques offer an intermediate resort due to their ability to utilize the classical communication infrastructure for design and implementation. Hence, we review QI techniques in this survey that address radio resource optimization challenges across various communication aspects, including channel assignment, reconfigurable intelligent surfaces, spectrum sensing, unmanned aerial vehicle-assisted networks, and related areas. The analysis explores diverse aspects, including objectives, constraints, problem characterization, proposed solutions, and lessons learnt. Research indicates that QI techniques offer advantages such as faster convergence and reduced complexity, providing promising solutions to complex optimization problems in communication networks. Furthermore, we identify the future directions, research gaps, and ongoing challenges from the QI radio resource optimization dataset. © 1998-2012 IEEE.

关键词： Quantum communication

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Fluid Antenna Systems Enabling 6G:Principles, Applications, and Research Directions

arXiv

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arXiv 2024年

作者： Wu, Tuo Zhi, Kangda Yao, Junteng Lai, Xiazhi Zheng, Jianchao Niu, Hong Elkashlan, Maged Wong, Kai-Kit Chae, Chan-Byoung Ding, Zhiguo Karagiannidis, George K. Debbah, Mérouane Yuen, Chau The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The School of Electrical Engineering and Computer Science Technical University of Berlin Berlin10623 Germany The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The School of Computer Science Guangdong University of Education Guangdong Guangzhou China The School of Computer Science and Engineering Huizhou University Huizhou516000 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom The Yonsei Frontier Laboratory Yonsei University Seoul03722 Korea Republic of The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of The Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates The Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece Lebanon Lebanon The Center for 6G Technology Khalifa University of Science and Technology P. O. Box 127788 Abu Dhabi United Arab Emirates

Fluid antenna system (FAS), a novel advancement in reconfigurable antenna technologies, offers unprecedented shape and position flexibility. This innovative approach is emerging as an exciting and potentially transformative technology for wireless communication systems. FAS encompasses any software-controlled fluidic, conductive, or dielectric structure capable of dynamically altering an antenna’s shape and position to modify critical parameters such as gain, radiation pattern, operating frequency, and other key characteristics. Given its unique capabilities, FAS is highly anticipated to play a significant role in shaping the upcoming sixth-generation (6G) wireless networks. This article explores this potential by addressing four major questions: 1) Is FAS crucial to 6G? 2) How can FAS be characterized? 3) What are the applications of FAS? 4) What challenges and future research directions are associated with FAS? In particular, five promising research directions that highlight FAS’s potential are examined. Finally, we conclude by demonstrating the impressive performance of FAS, reinforcing its relevance and promise in future networks. © 2024, CC BY.

关键词： Liquefied gases

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Weak Augmentation Guided Relational Self-Supervised Learning

arXiv

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arXiv 2022年

作者： Zheng, Mingkai You, Shan Wang, Fei Qian, Chen Zhang, Changshui Wang, Xiaogang Xu, Chang The School of Computer Science Faculty of Engineering The University of Sydney Australia The SenseTime Research The University of Science and Technology China China Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong

Self-supervised Learning (SSL) including the mainstream contrastive learning has achieved great success in learning visual representations without data annotations. However, most methods mainly focus on the instance level information (i.e., the different augmented images of the same instance should have the same feature or cluster into the same class), but there is a lack of attention on the relationships between different instances. In this paper, we introduce a novel SSL paradigm, which we term as relational self-supervised learning (ReSSL) framework that learns representations by modeling the relationship between different instances. Specifically, our proposed method employs sharpened distribution of pairwise similarities among different instances as relation metric, which is thus utilized to match the feature embeddings of different augmentations. To boost the performance, we argue that weak augmentations matter to represent a more reliable relation, and leverage momentum strategy for practical efficiency. The designed asymmetric predictor head and an InfoNCE warm-up strategy enhance the robustness to hyper-parameters and benefit the resulting performance. Experimental results show that our proposed ReSSL substantially outperforms the state-of-the-art methods across different network architectures, including various lightweight networks (e.g., EfficientNet and MobileNet). Copyright © 2022, The Authors. All rights reserved.

关键词： Supervised learning

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Ensemble Modeling for the Classification of Birth Data

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Intelligent Automation & Soft Computing 2024年第4期39卷 765-781页

作者： Fiaz Majeed Abdul Razzaq Ahmad Shakir Maqbool Ahmad Shahzada Khurram Muhammad Qaiser Saleem Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Osama E.Sheta Department of Information Technology University of GujratGujrat50700Pakistan School of Digital Convergence Business University of Central PunjabRawalpindi46000Pakistan Faculty of Computing The Islamia University of BahawalpurBahawalpur63100Pakistan College of Computer Science and Information Technology Al Baha UniversityAl Baha1988Saudi Arabia School of Computer Science and Engineering Yeungnam UniversityGyeongsan38541Republic of Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaLibreville1989Gabon Department of Electrical and Electronic Engineering Science School of Electrical EngineeringUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia College of Computer Science and Engineering University of Ha’ilHa’il55476Saudi Arabia College of Science Zagazig UniversityZagazig44511Egypt

Machine learning(ML)and data mining are used in various fields such as data analysis,prediction,image processing and especially in *** in the past decade have focused on applying ML and data mining to generate conclusions from historical data in order to improve healthcare systems by making predictions about the *** ML algorithms,researchers have developed applications for decision support,analyzed clinical aspects,extracted informative information from historical data,predicted the outcomes and categorized diseases which help physicians make better *** is observed that there is a huge difference between women depending on the region and their social *** to these differences,scholars have been encouraged to conduct studies at a local level in order to better understand those factors that affect maternal health and the expected *** this study,the ensemble modeling technique is applied to classify birth outcomes based on either cesarean section(C-Section)or normal delivery.A voting ensemble model for the classification of a birth dataset was made by using a Random Forest(RF),Gradient Boosting Classifier,Extra Trees Classifier and Bagging Classifier as base *** is observed that the voting ensemble modal of proposed classifiers provides the best accuracy,i.e.,94.78%,as compared to the individual *** algorithms are more accurate due to ensemble models,which reduce variance and classification *** is reported that when a suitable classification model has been developed for birth classification,decision support systems can be created to enable clinicians to gain in-depth insights into the patterns in the *** such a system will not only allow health organizations to improve maternal health assessment processes,but also open doors for interdisciplinary research in two different fields in the region.

关键词： Birth data classification ensemble model machine learning

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人类泛基因组参考图谱发布开启基因组学领域的新篇章

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Science Bulletin 2023年第14期68卷 1484-1487页

作者：王博党宁馨杨晓飞徐书华叶凯 School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of Genetic Engineering Human Phenome InstituteZhangjiang Fudan International Innovation CenterCenter for Evolutionary BiologySchool of Life SciencesFudan UniversityShanghai 200032China Ministry of Education Key Laboratory of Contemporary Anthropology Collaborative Innovation Center for Genetics and DevelopmentFudan UniversityShanghai 200032China Department of Liver Surgery and Transplantation Liver Cancer InstituteZhongshan HospitalFudan UniversityShanghai 200032China School of Life Science and Technology Shanghai Tech UniversityShanghai 201210China

The significance of DNA sequencing in advancing medicalresearch,improving healthcare practices,and enhancing ourunderstanding of human evolution cannot be *** yearmarks the 20th anniversary of the completion of the Human Genome Project(HGP)in 2003,with the draft human genome reference published in 2001[1,2].However,even with the latesthuman reference genome,GRCh38,there remain gaps totalingapprox.150 Mb,involving complex sequence in the pericentromeric and subtelomeric regions,as well as recent segmentalduplications and both ampliconic gene and ribosomal DNA(rDNA)arrays[3].A groundbreaking achievement was recently accomplished by the Telomere-to-Telomere(T2T)consortium whosuccessfully closed the remaining gaps and completed the firstend-to-end assembly of a human haploid genome,known as T2TCHM13[3].

关键词：基因组学 breaking accomplished

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Governance of Water and Electricity Sectors in Developing Countries: A Review 4th

Governance of Water and Electricity Sectors in Developing Co...

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4th International Conference on Communication, Devices and Computing (ICCDC 2023)

作者： Kamabu, Tsongo P. Musibono, Eyul’Anki D. Banza, Banza B. Mayobo, Mowene G. Siti, Mukwanga W. Sumaili, J. Bansal, Ramesh C. Abo-Khalil, Ahmed G. Mbukani, Mwana W. K. Tungadio, Diambomba H. Tshikala, Kiseya F. Madiba, T. Mbungu, Nsilulu T. Department of Electrical Engineering University of Kinshasa Kinshasa Democratic Republic Congo Department of Environmental Sciences University of Kinshasa Kinshasa Democratic Republic Congo Department of Electrical Engineering School of Engineering University of Lubumbashi Lubumbashi Democratic Republic Congo Department of Electrical Engineering University of Nouveaux Horizons Lubumbashi Democratic Republic Congo Department of Mechanical Engineering University of Kinshasa Kinshasa Democratic Republic Congo Department of Electrical Engineering Tshwane University of Technology Pretoria South Africa INESC TEC Porto Portugal Department of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa Department of Electrical Engineering College of Engineering Assuit University Assuit71515 Egypt Department of Electro-Mechanic Polytechnic Faculty University of Lubumbashi Lubumbashi Democratic Republic Congo

ISBN: (纸本)9789819927098

Against a backdrop of massive population growth, the supply of essential urban services, such as water and power, in developing countries is not growing at nearly the same pace. The critical aspects of this urban development are poorly understood. The main objective of this study was to identify and analyze the different forms of governance in the water and electricity sectors in developing countries based on the existing literature. The synthesis of several studies shows that there is not one mode of governance that fits every time and place. In most cases, municipal authority involves the private sector in water and electricity management. In many countries that have liberalized electricity generation, regulation of municipal utilities is being reformed through the introduction of incentive regulation models. Engaging the population through anti-corruption campaigns is an effective way to improve governance. Given the cost of expanding the conventional power grid, solar PV has proven to be a safe and sustainable way to power urban and peri-urban districts. However, success in promoting this energy source lies in the involvement of the national and/or provincial government through incentive measures. We conclude that the governance of water and electricity in developing countries is successful when the following criteria are applied: decentralization, liberalization, public–private partnerships and community involvement. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Developing countries

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