检索结果-内蒙古大学图书馆

IEEE Transactions on Artificial Intelligence 2025年第4期6卷 989-1002页

作者： Li, Dandan Xia, Jiaxing Li, Jiangfeng Xiao, Changjiang Stankovic, Vladimir Stankovic, Lina Shi, Qingjiang Tongji University School of Computer Science and Technology Shanghai201804 China China University of Mining and Technology Artificial Intelligence Research Institute Jiangsu Xuzhou221008 China Tongji University College of Surveying and Geo-Information Shanghai200092 China University of Strathclyde Department of Electronic and Electrical Engineering GlasgowG1 1XJ United Kingdom

Predicting the electricity consumption of individual appliances, known as appliance-level energy consumption (ALEC) prediction, is essential for effective energy management and conservation. Despite its importance, research in this area is limited and faces several challenges: 1) the correlation between the usage of different appliances has rarely been considered for ALEC prediction;2) a learnable strategy for obtaining the optimal correlation between different appliance behaviors is lacking;and 3) it is difficult to accurately quantify the usage relationship among different appliances. To address these issues, we propose a graph-based temporal-spatial network that employs a learnable adjacency matrix for appliance-level load prediction in this work. The network comprises a temporal graph convolutional network (TGCN) and a learnable adjacency matrix that enables us to utilize correlations between appliances and quantify their relationships. To validate our approach, we compared our model with six others: a TGCN model with a fixed adjacency matrix where all elements are set to 0;a TGCN model with a fixed adjacency matrix where all elements are set to 0.5, except for the diagonal;a TGCN model with a randomly generated adjacency matrix, except for the diagonal;an Aug-LSTM model;a model with ResNetPlus architecture;and a feed-forward deep neural network. Five houses in four datasets: AMPDs, REFIT, UK-DALE, and SC-EDNRR are utilized. The metrics used in this study include root mean square error, explained variance score, mean absolute error, F-norm and coefficient of determination. Our experiments have validated the accuracy and practicality of our proposed approach across different datasets. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

ADA-FInfer: Inferring Face Representations From Adaptive Select Frames for High-Visual-Quality Deepfake Detection

引用

IEEE Transactions on Dependable and Secure Computing 2025年第3期22卷 3011-3027页

作者： Hu, Juan Liang, Jinwen Qin, Zheng Liao, Xin Zhou, Wenbo Lin, Xiaodong Hunan University College of Computer Science and Electronic Engineering Changsha410012 China The Hong Kong Polytechnic University Department of Computing Hong Kong University of Science and Technology of China CAS Key Laboratory of Electromagnetic Space Information Anhui 230026 China University of Guelph School of Computer Science GuelphONN1G 2W1 Canada

Interpretable deepfake detection is gaining attentionfor providing explainable, trustworthy results, avoiding the limitations of ‘black-box’ models. Current interpretable methods focus on visible artifacts in low-visual-quality deepfakes, but theseartifacts become less apparent in high-visual-quality deepfakesgenerated by advanced models. With advancements in deep generative models, producing high-visual-quality deepfakes has become a strategy to evade detection. To address this, we proposeADA − FInfer, an adaptive frame selection and interpretable facerepresentation inference method for detecting high-visual-qualitydeepfakes. ADA − FInfer adaptively selects frames by analyzingoptical flow to reveal manipulations. We also introduce an adaptiveattack method that manipulates specific frames, and our adaptiveselection strategy shows resistance to such attacks. ADA − FInferuses an encoder to learn face representations from source and targetfaces, applying a representation-prediction loss to maximize the distinction between real and fake videos. To provide further insights,we employ the joint entropy, mutual information, and conditionalentropy analyses to explain the method’s effectiveness. Extensiveexperiments and ablation studies demonstrate that ADA − FInferachieves promising performance in detecting high-visual-qualitydeepfakes. © 2004-2012 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Distributed Estimation and Motion Control in Multi-Agent Systems Under Multiple Attacks

引用

IEEE Transactions on Automation Science and engineering 2025年 22卷 12548-12559页

作者： Jenabzadeh, Ahmadreza Shu, Zhan Huang, Tingwen Zhu, Quanmin Shang, Yilun Cui, Yukang Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Peng Cheng Laboratory Shenzhen518000 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China University of the West of England School of Engineering BristolBS16 1QY United Kingdom Northumbria University Faculty of Engineering and Environment Department of Computer and Information Sciences Newcastle upon TyneNE1 8ST United Kingdom

This paper addresses the problem of distributed estimation and motion control (DEMC) in multi-agent systems (MASs) with both linear and Lipschitz nonlinear dynamics. Unlike conventional DEMC methods designed for MASs under ideal conditions, this work investigates scenarios where all agents are vulnerable to various forms of attacks. The considered attacks comprise false-data injection (FDI) attacks and denial of service (DoS) attacks that affect the communication channels among agents to destabilize the MAS. Also, the unbounded actuator attacks which exist in practical environments to intentionally degrade the MAS performance is considered. To cope with these kinds of attacks, two novel resilient approaches are established aimed at estimating and following a mobile target under attacks. The proposed distributed attack-resilient control strategies are designed based on a dual-layer structure, guaranteeing effective DEMC with an ultimately bounded error. The results from two simulation examples are provided to validate the presented algorithms. © 2004-2012 IEEE.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Self-Adaptive Dynamic In-Band Network Telemetry Orchestration for Balancing Accuracy and Stability

引用

IEEE Transactions on Network and Service Management 2025年第2期22卷 1514-1530页

作者： Ouyang, Tianhao Yao, Haipeng He, Wenji Mai, Tianle Wang, Fu Yu, F. Richard Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Beijing Institute of Technology School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing University of Posts and Telecommunications School of Electronic and Engineering Beijing100876 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

In-band network telemetry (INT) is an emerging network measurement technique that offers real-time and fine-grained visualization capabilities for networks. However, the utilization of INT for network measurement introduces additional overheads to the network. The process of data collection consumes extra bandwidth resources, and adjustments to the data collection scheme can impact network stability. Additionally, the INT orchestration scheme requires adaptation to dynamics in the network to improve measurement accuracy. Therefore, striking a balance between accuracy and stability becomes a critical problem. In this paper, our focus lies in the trade-off between measurement accuracy and network stability. We consider the long-term orchestration of multiple telemetry tasks, rationally deploying distinct telemetry tasks to different application flows. To address the challenge, we propose a self-adaptive Dynamic INT Orchestration scheme, D-INTO. Specifically, we formulate a stochastic optimization problem for dynamic INT orchestration. Then we employ Lyapunov optimization to decouple the stochastic optimization problem and use surrogate Lagrangian relaxation to construct a polynomial-time approximation algorithm. Theoretical analysis and experimental results demonstrate that our proposed D-INTO outperforms existing schemes in terms of adaptability to the network dynamics. © 2004-2012 IEEE.

关键词： Polynomial approximation

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

A Zero-Sequence Current Analysis Approach for Rotating Machinery Fault Diagnosis of Induction Motor Drivetrain Based on Sparse Learning

引用

IEEE Transactions on Power Electronics 2025年第7期40卷 9800-9810页

作者： Liu, Zhao-Hua Long, Jun-Jie Wei, Hua-Liang Liu, Kan Zhang, Ying-Jie Li, Xiao-Hua Hunan University of Science and Technology School of Information and Electrical Engineering Xiangtan411201 China The University of Sheffield School of Electrical and Electronic Engineering Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Hunan University College of Mechanical and Vehicle Engineering Changsha410082 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

Fault diagnosis of rotating machinery driven by induction motors has received increasing attention. Current diagnostic methods, which can be performed on existing inverters or current transformers of three-phase induction machines, have become a more economical and reliable alternative to vibration diagnostic methods. Existing references mainly focus on the stator current analysis of single-phase, but most single-phase current analysis methods utilize only a fraction of the total information accessible in the three-phase system. Field experience shows that zero-sequence current (ZSC) has more distinctive fault characteristics compared to single-phase current, and therefore it is better to use in mechanical fault detection and diagnostic tasks. This article proposes a novel sparse learning-based method for ZSC analysis for induction rotating motor drive fault diagnosis. First, it elaborates and compares the effectiveness of ZSC in revealing fault characteristics compared with single-phase current by analyzing the fault diagnosis mechanism of ZSC. In addition, the method proposes a correlation entropy-enhanced sparse learning method for the problem of high-frequency noise and interference in the ZSC signals, so as to enhance the learning of the features of the noise-containing signals. The diagnostic efficacy of the proposed method has been verified through experiments on two real datasets. © 1986-2012 IEEE.

关键词： Induction motors

来源：评论

学校读者我要写书评

暂无评论

Bangla License Plate Detection and Recognition Approach Based on computer Vision for Authentic Vehicle Identification 3rd

Bangla License Plate Detection and Recognition Approach Base...

引用

3rd International Conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Dhar, Rajib Kumar Khanom, Fahmida Uddin, Khandaker Mohammad Mohi Imam, Md. Hasan Mostafiz, Rafid Institute of Information Technology Noakhali Science and Technology University Noakhali Bangladesh Department of Mathematics American International University—Bangladesh 408/1 Kuratoli Khilkhet Dhaka1229 Bangladesh Department of Computer Science and Engineering Southeast University Dhaka1208 Bangladesh

ISBN: (纸本)9789819739363

Vehicle license plates (LPs) detection and recognition is a fundamental technique in computer vision that plays a crucial role to extract, localize, and authenticate the information of a vehicle. This paper presents an efficient method for Bangla LPs recognition and vehicle authentication using edge analysis and pattern matching algorithm in real-time nature. This method performs four modules as: preprocessing, license plate identification, character recognition, vehicle authentication. A multi-step preprocessing technique has been applied to extract and understand the potential information in case of any uneven images. To identify edge connectivity and uniformity, Canny edge detector provides more promising in contour analysis and character localization. The segmented characters are converted into texts and verified using the pattern matching algorithm by a predefined database. For this research, a database consisting of 3000 automobile license plate photos captured under different climatic circumstances has been compiled. Additionally, we have curated two additional databases consisting of templates for recognition and registered automobiles for the purpose of authentication. The proposed model can achieve accuracy of 96% in LPs detection, 99% in character recognition, and 100% in vehicle authentication by extracted texts from LPs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Density-Clustering Aggregation for Personalized Federated Learning With AI-Enabled Aerial and Edge Computing in UAVs

引用

IEEE Internet of Things Journal 2025年第9期12卷 11220-11232页

作者： Chien, Wei-Che Lin, Chih-Hsun Zhu, Tianli Dai, Cheng Garg, Sahil Mukherjee, Amrit National Dong Hwa University Department of Computer Science and Information Engineering Hualien City974301 Taiwan Sichuan University College of Computer Science Sichuan Chengdu610017 China École de Technologie Supérieure Electrical Engineering Department MontrealH3C 1K3 Canada Applied Science and Technology Dubai United Arab Emirates Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact and Outcome Rajpura140401 India University of South Bohemia Faculty of Science Department of Computer Science České Budějovice370 05 Czech Republic

This research introduces the density-clustering-based aggregation for personalized federated learning (DCPFL) algorithm, which utilizes DBSCAN clustering to enhance model accuracy in AI-enabled aerial and edge computing contexts, particularly for uncrewed aerial vehicles (UAVs). The DCPFL framework promotes model sharing among clients, fostering the development of personalized and optimized models. DBSCAN is beneficial in automatically determining cluster numbers using EPS neighborhoods and MinPts, with parameter optimization achieved through cross-experimental analysis. We further refined the model exchange mechanism by integrating a moving average prediction model to optimize the timing of these exchanges. Tests conducted on three public datasets covering two different machine learning (ML) tasks show that DCPFL surpasses existing methods, offering greater accuracy and enhanced adaptability in varied data environments. Implementing this algorithm in UAV networks leverages AI capabilities in aerial and edge computing to efficiently balance personalized modeling requirements with high performance, showcasing its potential to push federated learning (FL) forward in complex and dynamic settings. © 2014 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

When Generative AI Meets Semantic Communication: Optimizing Radio Map Construction and Distribution in Future Mobile Networks

引用

IEEE Network 2025年第3期39卷 47-55页

作者： Zhou, Li Deng, Xinfeng Ning, Zhaolong Zhao, Haitao Wei, Jibo Leung, Victor C. M. National University of Defense Technology College of Electronic Science and Technology Changsha410073 China Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China Shenzhen MSU-BIT University AI Research Institute Shenzhen518000 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518000 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada

With the rapid development of the internet of things and smart cities, the demand for effective spectrum collaboration has grown *** maps play a crucial role in understanding the spatial radio environment, which is essential for wireless applications such as cell planning and radio resource management. However, generating radio maps is a resource-intensive task, as the construction process is complex and the distribution process consumes substantial bandwidth. This article proposes a method that combines semantic communication (SemCom) and generative artificial intelligence (GAI) to optimize the construction and distribution processes of radio maps. By incorporating SemCom, our method transmits only key semantic information during the distribution process, significantly reducing bandwidth usage while ensuring accurate and efficient information transfer. While the diverse generative capabilities of GAI introduce some instability, which could be a limitation in radio map construction, this article achieves precise content decoding through prompts based on multi-modal semantic information, enabling accurate construction and restoration of radio maps. By utilizing SemCom and GAI technologies, the cost of applications of radio maps can be significantly reduced, which is beneficial for stimulating the pace of intelligence evolution in future mobile networks. © 1986-2012 IEEE.

关键词： Bandwidth

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial: Special Issue of Selected Extended Papers From the IEEE International Conference on Flexible, Printable Sensors and Systems (FLEPS) 2024

IEEE Journal on Flexible Electronics

引用

IEEE Journal on Flexible Electronics 2025年第1期4卷 2-3页

作者： Mantysalo, Matti Marrocco, Gaetano Agarwale, Shweta Grau, Gerd Gao, Wei Tampere University Faculty of Information Technology and Communication Sciences Tampere33720 Finland University of Roma Tor Vergata Dipartimento di Ingegneria Civile ed ed Ingegneria Informatica Rome00133 Italy Aarhus University Department of Electrical and Computer Engineering Aarhus8200 Denmark York University Department of Electrical Engineering and Computer Science TorontoONM3J 1P3 Canada Caltech Department of Engineering and Applied Science PasadenaCA91125 United States

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：