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作者： Wang, Yufeng Zhang, Xu Ma, Jianhua Jin, Qun School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China Faculty of Computer & Information Sciences Hosei University Tokyo Japan Department of Human Informatics and Cognitive Sciences Waseda University Tokyo Japan

As a distributed learning framework, Federated Learning (FL) allows different local learners/participants to collaboratively train a joint model without exposing their own local data, and offers a feasible solution to legally resolve data islands. However, among them, the data privacy and model security are two challenges. The former means that, if original data are used for trained FL models, various methods can be used to deduce the original data samples, thereby causing the leakage of data. The latter implies that unreliable/malicious participants may affect or destroy the joint FL model, through uploading wrong local model parameters. Therefore, this paper proposes a novel distributed FL training framework, namely LDP-Fed+, which takes into account differential privacy protection and model security defense. Specifically, firstly, a local perturbation module is added at the local learner side, which perturbs the original data of local learners through feature extraction, binary encoding and decoding, and random response. Then, through using the perturbed data, local neural network model is trained to obtain the network parameters that meet local differential protection, to effectively deal with model inversion attacks. Secondly, a security defense module is added on the server side, which uses the auxiliary model and differential index mechanism to select an appropriate number of local disturbance parameters for aggregation to enhance model security defense and deal with membership inference attacks. The experimental results show that, compared with other federated learning models based on differential privacy, LDP-Fed+ has stronger robustness for model security and higher accuracy for model training while ensuring strict privacy protection. © 2022 John Wiley & Sons, Ltd.

关键词： Learning systems

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Improved RC6 Block Cipher Based on Data Dependent Rotations

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computers, Materials & Continua 2022年第1期70卷 1921-1934页

作者： Osama S.Faragallah Ibrahim F.Elashry Ahmed AlGhamdi Walid El-Shafai S.El-Rabaie Fathi E.Abd El-Samie Hala S.El-sayed Mohamed A.Elaskily Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electrical Communications Faculty of EngineeringKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Informatics Electronic Research Institute(ERI)CairoEgypt

This paper introduces an Improved RC6(IRC6)cipher for data encryption based on data-dependent *** proposed scheme is designed with the potential of meeting the needs of the Advanced Encryption Standard(AES).Four parameters are used to characterize the proposed *** parameters are the size of the word(w)in bits,the number of rounds(r),the length of the secret key(b)in bytes,and the size of the block(L)in *** main feature of IRC6 is the variable number of working registers instead of just four registers as in RC6,resulting in a variable block size for plaintext and *** IRC6 cipher is designed to improve the robustness against attacks by increasing the diffusion for each round and providing greater security with fewer *** effectiveness of the proposed IRC6 scheme is verified against theoretical *** proposed IRC6 scheme depends on full diffusion and confusion mechanisms regardless of the utilized block *** proposed IRC6 scheme saves 70%of the encryption time and 64%of the decryption time of *** simulation results prove that the IRC6 achieves a better encryption/decryption time compared to the ***,the proposed IRC6 is anticipated to fulfill the market needs and system security requirements.

关键词： Cryptography block cipher RC6,IRC6,AES

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Indoor 3D Visible Light Positioning Analysis with Channel Estimation Errors 30

Indoor 3D Visible Light Positioning Analysis with Channel Es...

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30th International Conference on Systems, Signals and Image Processing, IWSSIP 2023

作者： Bozanis, Dimitrios Evgenidis, Nikos G. Papanikolaou, Vasilis K. Bouzinis, Pavlos S. Tegos, Sotiris A. Dowhuszko, Alexis A. Diamantoulakis, Panagiotis D. Karagiannidis, George K. Department of Electrical and Computer Engineering Thessaloniki54124 Greece Germany University of Macedonia Department of Applied Informatics Thessaloniki54636 Greece Aalto University Department of Communications and Networking Espoo02150 Finland Cyber Security Systems and Applied Ai Research Center Lebanon

ISBN: (纸本)9798350337297

Since radio-frequency signals are affected signifi-cantly by multipath fading, the localization accuracy they offer cannot meet the sixth generations (6G) demanding specifications. On the other hand, visible light positioning (VLP) has emerged as a low cost alternative that takes into account the highly deterministic channel characteristics of visible light communications to provide cm-level accuracy provided that the investigated spaces are adequately covered by LEDs. However, imperfect channel state information and modeling can lead to positioning errors. In this paper, localization accuracy is quantified in terms of channel estimation errors via low complexity lateration algorithm. The channel estimation errors can be caused by a variety of issues and the provided analysis is general so that it can be easily applied to a plethora of applications. Finally, Monte Carlo simulations validate the proposed method and offer valuable insights for the design and performance bounds of VLP systems. © 2023 IEEE.

关键词： Monte Carlo methods

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An Implementation of A Bus Following Model in an 802.11p Based Simulator in MATLAB

An Implementation of A Bus Following Model in an 802.11p Bas...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Felipe Inigo Xavier Reyes Gan Gian Paolo T. Mayuga Luke Bennett King Lao Elmer R. Magsino Department of Electronics Computer and Communications Engineering Ateneo de Manila University Quezon City Philippines Department of Electronics and Computer Engineering De La Salle University Manila Philippines

Tailored to address the lack of communications systems between bus and bus stops, this paper explores the use of IEEE 802.11p, a form of Dedicated Short Range Communication (DSRC), for communication in a Bus Rapid Transit (BRT) system using MATLAB through modification of an existing application Vehicle Ad-Hoc Network (VANET) Toolbox. Adding a bus mobility model and a bus entity, a Bus-Following model (BFM) is employed within a single lane setup following the BRT system. Multiple test simulations were conducted, varying in number of buses, bus stops, and information messages. Graphical representations of the communications as well as the generated information messages show that the system works according to the intended design. The simulator was also tested to the scale of a major Philippine road using the latest available passenger inflow and outflow data. The results show that communications between bus and bus stops were within acceptable parameters for latency and Packet Delivery Ratio while also showing that a bus to bus stop ratio of 2:1 was not sufficient to handle the passenger flow of EDSA during the 7AM rush hour. Overall, a verified simulator within the open-source VANET Toolbox is presented.

关键词： Technological innovation Smart cities Mobility models Communication systems Roads Layout Vehicular ad hoc networks

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Breast Cancer Classification Model Using Principal Component Analysis and Deep Neural Network 1

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World Conference on Information Systems for Business Management, ISBM 2022

作者： Sindhuja, M. Poonkuzhali, S. Vigneshwaran, P. Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Tamil Nadu Thandalam Chennai602105 India Department of Computer Science and Engineering Rajalakshmi Engineering College Tamil Nadu Thandalam Chennai602105 India Department of Networking and Communications SRM Institute of Science and Technology Tamil Nadu Kattankulathur Chengalpattu603203 India

ISBN: (数字)9789811974472

ISBN: (纸本)9789811974465

Life-threatening cancer is prevalent over the globe. According to statistics, most people are diagnosed with cancer in the later stages, even though cancer can be prevented and cured in early stages. The goal of this research is to diagnose a breast cancer is either benign or malignant, as well as to forecast the likelihood of a cancer recurrence even after a course of therapy has been completed. Despite the fact that many machine learning algorithms have resulted in strong predictions, the accuracy in the early stages of categorization is not up to the expected level. Deep learning (DL), a higher degree of machine learning, can forecast breast cancer types and recurrences. Classifiers were built using a deep neural network (DNN) that used Principal Component Analysis (PCA) to choose features. Different machine learning techniques are compared with the proposed system’s accuracy. Early-stage breast cancer prediction is more accurate with the DNN-based method. The clinical management system will benefit from the proposed system since it will aid in identification of cancer at an early stage and the subsequent provision of appropriate therapy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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A Novel Downlink IM-NOMA Scheme

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the communications Society 2021年 2卷 235-244页

作者： Almohamad, Abdullateef Hasna, Mazen O. Althunibat, Saud Qaraqe, Khalid Department of Electrical Engineering Qatar University Doha Qatar Department of Communications Engineering Al-Hussein Bin Talal University Ma'an Jordan Department of Electrical and Computer Engineering Texas Am University at Qatar Doha Qatar

In the next generations of communication systems, resources' scarcity devolves to a more critical point as a consequence of the expected massive number of users to be served. Furthermore, the users' contradicting requirements on quality of service forces the network to behave in a dynamic way in terms of the multiple access orchestration and resource assignment between users. Hence, the linear relation between the number of served users and the required (orthogonal or semi-orthogonal) resources in the orthogonal multiple access (OMA) schemes is no longer sufficient. As promising candidates, Non-orthogonal multiple access (NOMA) schemes and index modulation (IM) techniques are emerging to satisfy the ever-increasing connectivity demands and spectral efficiency. In this article, a novel IM-based NOMA downlink scheme, termed as IM-NOMA, is proposed, where the base station (BS) selects a channel or more to serve each user based on the IM concept and the corresponding power level is allocated based on the NOMA concept. At the users' ends, maximum likelihood and successive interference cancellation (SIC) detection methods are considered and their error rate, outage probability and computational complexity are studied. Simulation results confirm the advantage of the proposed IM-NOMA scheme and that it can outperform the conventional NOMA system. © 2020 IEEE.

关键词： Quality of service

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AQROM:A quality of service aware routing optimization mechanism based on asynchronous advantage actor-critic in software-defined networks

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Digital communications and Networks 2024年第5期10卷 1405-1414页

作者： Wei Zhou Xing Jiang Qingsong Luo Bingli Guo Xiang Sun Fengyuan Sun Lingyu Meng School of Information and Communication Guilin University of Electronic TechnologyGuilin541004China The 34th Research Institute of China Electronics Technology Group Corporation Guilin541004China Guangxi Key Laboratory of Optical Network and Optical Information Security Guilin541004China State Key Laboratory of Information Photonics and Optical Communications BeijingUniversity of Posts and TelecommunicationsBeijing100876China Department of Electrical and Computer Engineering University of New MexicoAlbuquerqueNM87131USA

In Software-Defined Networks(SDNs),determining how to efficiently achieve Quality of Service(QoS)-aware routing is challenging but critical for significantly improving the performance of a network,where the metrics of QoS can be defined as,for example,average latency,packet loss ratio,and *** SDN controller can use network statistics and a Deep Reinforcement Learning(DRL)method to resolve this *** this paper,we formulate dynamic routing in an SDN as a Markov decision process and propose a DRL algorithm called the Asynchronous Advantage Actor-Critic QoS-aware Routing Optimization Mechanism(AQROM)to determine routing strategies that balance the traffic loads in the *** can improve the QoS of the network and reduce the training time via dynamic routing strategy updates;that is,the reward function can be dynamically and promptly altered based on the optimization objective regardless of the network topology and traffic *** can be considered as one-step optimization and a black-box routing mechanism in high-dimensional input and output sets for both discrete and continuous states,and actions with respect to the operations in the *** simulations were conducted using OMNeT++and the results demonstrated that AQROM 1)achieved much faster and stable convergence than the Deep Deterministic Policy Gradient(DDPG)and Advantage Actor-Critic(A2C),2)incurred a lower packet loss ratio and latency than Open Shortest Path First(OSPF),DDPG,and A2C,and 3)resulted in higher and more stable throughput than OSPF,DDPG,and A2C.

关键词： Software-defined networks Asynchronous advantage actor-critic QoS-aware routing optimization mechanism

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A New Method for Scene Classification from the Remote Sensing Images

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computers, Materials & Continua 2022年第7期72卷 1339-1355页

作者： Purnachand Kollapudi Saleh Alghamdi Neenavath Veeraiah Youseef Alotaibi Sushma Thotakura Abdulmajeed Alsufyani Department of CSE B V Raju Institute of TechnologyNarsapurMedakTelanganaIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaVijayawadaA.P.India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of ECE P.V.P Siddhartha Institute of TechnologyVijayawadaIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The mission of classifying remote sensing pictures based on their contents has a range of applications in a variety of *** recent years,a lot of interest has been generated in researching remote sensing image scene *** sensing image scene retrieval,and scene-driven remote sensing image object identification are included in the Remote sensing image scene understanding(RSISU)*** the last several years,the number of deep learning(DL)methods that have emerged has caused the creation of new approaches to remote sensing image classification to gain major breakthroughs,providing new research and development possibilities for RS image classification.A new network called Pass Over(POEP)is proposed that utilizes both feature learning and end-to-end learning to solve the problem of picture scene comprehension using remote sensing imagery(RSISU).This article presents a method that combines feature fusion and extraction methods with classification algorithms for remote sensing for scene *** benefits(POEP)include two *** multi-resolution feature mapping is done first,using the POEP connections,and combines the several resolution-specific feature maps generated by the CNN,resulting in critical advantages for addressing the variation in RSISU data ***,we are able to use Enhanced pooling tomake the most use of themulti-resolution feature maps that include second-order *** enablesCNNs to better cope with(RSISU)issues by providing more representative feature *** data for this paper is stored in a UCI dataset with 21 types of *** the beginning,the picture was pre-processed,then the features were retrieved using RESNET-50,Alexnet,and VGG-16 integration of *** characteristics have been amalgamated and sent to the attention layer,after this characteristic has been fused,the process of classifying the data will take *** utilize an ensemble classifier in our classification a

关键词： Remote sensing RSISU DL RESNET-50 VGG-16

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Control of Master-Slave DC Microgrid with Optical Fiber Communication Link 15

Control of Master-Slave DC Microgrid with Optical Fiber Comm...

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15th International Renewable Energy Congress, IREC 2025

作者： Alfergani, Asma Shaltami, Farhat M. Alfaitor, Khalid Ateea Khalil, Ashraf Mohamed, Faisal University of Benghazi Electrical and Electronics Engineering Department Benghazi Libya College of Electrical and Electronics Technology - Benghazi Benghazi Libya University of Benghazi Faculty of Information Technology Department of Computer Networks and Communications Benghazi Libya Dtu Engineering Technology Technical University of Denmark Kongens LyngbyDK-2750 Denmark Authority of Natural Science Research and Technology Tripoli Libya

ISBN: (纸本)9798331516772

In this paper, a model for the master-slave DC Microgrid over a fiber optic link is proposed. The delay margin is calculated according to Lyapunov-Krasovskii functional using the LMI toolbox in Matlab with the binary iteration algorithm. The optical fiber link is implemented using optisystem simulator. The optical fiber link is set to transmit the digitalized reference current from master controller to the slave controller. The link tested at 100Mbps, 1Gbps and 2.5Gbps data rate values and several optical fiber lengths and wavelength of 1550nm and 1400nm. The results show that the performance of the link is sufficient at received power more than -30dBm for all data rate values at 1550nm. While at 1400nm, the attenuation rate is very high. Therefore, the link must be 10km to achieve acceptable performance. This wavelength is used in this simulation to avoid the C band and O band, which used for telecommunication purposes. © 2025 IEEE.

关键词： MATLAB

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Evolution of Metallic Connection Technologies of Busbar in Silicon Solar Cells: Brief Review 15

Evolution of Metallic Connection Technologies of Busbar in S...

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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： Silveira, A.M.C. Neves, M.R.M. Garcia, R. Alvarez, H. Villalva, M.G. Marques, F.C. Kretly, L.C. School of Electrical and Computer Engineering Communications Department - DECOM Campinas Brazil School of Electrical and Computer Engineering Dept. of Systems and Energy - DSE Campinas Brazil Institute of Physics Gleb Wataghin Dept. of Applied Physics - DFA Campinas Brazil Build Your Dreams Company - BYD Dept. Research and Development - R&D Campinas Brazil

ISBN: (纸本)9798350314182

This work consists of presenting a brief review of the evolution of metallic connection technologies in busbars applied to the front and rear of solar cells, thus demonstrating their fundamentals, materials and essential manufacturing processes that impact on improving the energy efficiency of solar modules. In this brief review, one can follow the technical limitations that led to the evolution of metallic connection technologies in busbars over time and their impacts on the photovoltaic market. Contributing to a broad understanding of the resistive components of solar cells that consists of the series resistance parameter. © 2023 IEEE.

关键词： Busbarless Effective Shadow Ribbon Busbar Serie Resistance Solar cell TLM Wire Busbar

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