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共 16681 条记录，以下是251-260 订阅

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Lightweight and Data-imbalance-aware Defect Detection Approach Based on Federated Learning in Industrial Edge networks 13

Lightweight and Data-imbalance-aware Defect Detection Approa...

引用

13th IEEE International conference on Electronics Information and Emergency Communication, ICEIEC 2023

作者： Bi, Congxian He, Shuo School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China

ISBN: (纸本)9798350331714

Accurate and timely defect detection in industrial edge networks is becoming increasingly important in intelligent manufacturing. However, the privacy concern and limited resources of edge devices hinder the applications of existing defect detection models. this paper presents a new defect detection approach based on federated learning (FL), where the transmission of privacy-sensitive data can be avoided and user privacy and data security can be well preserved. We first propose a lightweight defect detection model based on YOLOv5s. We use ShuffleNet as the backbone of YOLOv5s, use the SE attention mechanism and LRELU to improve the learning accuracy. We then develop a clustering-based device selection approach to address the degradation of accuracy caused by imbalanced data distributions of devices in FL. Corroborated by simulations, the accuracy of the proposed defect detection model increases by 26.86% as compared with existing models, and the proposed device selection approach is also superior to the benchmarks in terms of learning accuracy. © 2023 IEEE.

关键词： Sensitive data

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Fault Diagnosis of Quadrotor UAV Propeller with local-Global Attention-Based Graph Neural networks 13

Fault Diagnosis of Quadrotor UAV Propeller with Local-Global...

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13th IEEE Data Driven Control and Learning Systems conference, DDCLS 2024

作者： Wang, Zhiwei Liang, Shaojun Sun, Ye Yang, Yi Wang, Yanwei Zheng, Ying School of Artificial Intelligence and Automation Huazhong University of Science and Technology Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan430074 China School of Ordnance Sergeant Army Engineering University Wuhan430075 China School of Mechanical & Electrical Engineering Wuhan Institute of Technology Wuhan430073 China

ISBN: (纸本)9798350361674

With the wide application of Quadrotor Unmanned Aerial Vehicles (QUAV) in military and civilian fields, its flight reliability problem has become a hot research topic. the propellers, which are the important components relating to the performance of QUAV, play a central role in safe flight. Traditional data-driven fault diagnosis methods of QUAV are based on Euclidean distance, which cannot effectively capture the interrelationship of multiple variables. In this paper, we treat the fault diagnosis of QUAV propeller as a node classification problem in non-Euclidean infinite dimensional space by introducing the method of local-Global Attention-based Graph Neural Network (LGA-GNN). First, the graph topology is constructed using the KNN method based on the real flight log of the QUAV. then, the local and global attention strategies are integrated to form a graph-based collaborative feature extraction model. Finally, a unified end-to-end fault diagnosis framework tailored for QUAV is proposed. In the experiment section, real flight data of QUAV with different propeller fault conditions are collected, and the effectiveness and superiority of the proposed method are verified by comparing with other methods based on real data. © 2024 IEEE.

关键词： Graph neural networks

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Deep Reinforcement Learning to Enhance the Energy-efficient Performance of Unmanned Aerial Vehicles-enabled Fog Radio Access networks 21

Deep Reinforcement Learning to Enhance the Energy-efficient ...

引用

21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International conference on Big Data and Cloud Computing, 16th IEEE International conference on Social Computing and Networking and 13th International conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Liu, Chuanjie Ren, Siyu Du, Shuang Dai, Cheng Guo, Bing Fan, Runzhi Sichuan University School of Computer Science Chengdu China Uestc School of Aeronautic and Astronautic Chengdu China

ISBN: (纸本)9798350329223

Nowadays, the use of unmanned aerial vehicles (UAVs) as the fog access points (F-APs) is of high practical value to future fog radio access networks (F-RANs). Compared to the F-AP, UAV enabled F-AP possesses stronger line-of-sight links with the ground terminals (GTs) due to its high altitude as well as high and flexible mobility in 3D spaces. Nevertheless, unlike terrestrial F-AP that has reliable power supply, UAV- enabled F-AP in practice has limited on board power, but requires high propulsion power to stay air-borne and support high mobility. Motivated by the above considerations, this paper aims to explore how deep reinforcement learning (DRL) can be applied to enhance the energy-efficient performance of UAV- enabled F-RANs. Such DRL method supports UAV enabled F-AP to real-timely optimize the air-to-ground fog computing by reasoning network configuration in an online manner, which sheds new light on the existing works in UAV-enabled networks. In specific, the DRL based network configuration considers parameters including resource allocation, task offloading, cache deployment and 3D UAV trajectory, and get validated via simulation in this paper. In the end, the main design challenges and promising directions for future research are also discussed. © 2023 IEEE.

关键词： Reinforcement learning

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the Development of Physically Correct Reflectance Model Based on Logarithm Function 13

The Development of Physically Correct Reflectance Model Base...

引用

13th International conference on Advanced computer Information Technologies, ACIT 2023

作者： Romanyuk, Olexandr Zavalniuk, Yevhen Romanyuk, Oksana Snigur, Anatoliy Titova, Nataliia Maidaniuk, Volodymyr Vinnytsia National Technical University Faculty of Information Technologies and Computer Engineering Vinnytsia Ukraine Odessa National Polytechnic University Department of Biomedical Engineering Odessa Ukraine

关键词： Reflection

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Performance Comparison Between Docker Container and Virtual Machine Microservices 13

Performance Comparison Between Docker Container and Virtual ...

引用

13th IEEE International conference on Communication Systems and Network Technologies, CSNT 2024

作者： Verma, Ashok Kumar Patel, Ruchi Rai, Preeti Patel, Sharda Gyan Ganga Institute of Technology and Sciences Department of Computer Science & Engineering MP Jabalpur India

ISBN: (纸本)9798350305463

Currently, the microservice architecture is extensively employed in the creation and implementation of numerous time-sensitive, crucial, and expansive web services. Usually, these services are implemented on cloud platforms by utilizing Docker containers. Container technology offers superior portability, scalability, and performance in comparison to virtual machine-based services. Container-based services are recognized for their superior performance compared to virtual machine-based services. Nevertheless, our research demonstrates that services implemented through Amazon AWS ECS (EC2 Container Service) exhibit notably inferior performance compared to those implemented through Amazon EC2 VMs. We conducted a comprehensive analysis and measurement of the disparities in throughput, reaction time, and CPU use across different deployment situations. © 2024 IEEE.

关键词： Containers

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Improving Obesity Classification Accuracy Using SMOTE-based Dataset Balancing and Ensemble Machine Learning Approaches 13

Improving Obesity Classification Accuracy Using SMOTE-based ...

引用

13th International conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Agarwal, Ambuj Kumar Mishra, Amit Kumar Tiwari, Raj Gaurang Gupta, Neema Sharda University Sharda School of Engineering and Technology Department of Computer Science and Engineering Greater Noida India Graphic Era Hill University Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India University School of Business Chandigarh University Chandigarh India

ISBN: (纸本)9798350380583

Obesity categorization is a public health issue, especially when unbalanced datasets impair model performance. For obesity categorization, this research found XGBoost, CatBoost, and AdaBoost to be the most accurate machine-learning(ML) models. Stacking ensembles of these three models yielded 87.3% prediction accuracy. this research also uses the Synthetic Minority Over-sampling Technique (SMOTE) to balance the dataset by over-sampling the minority class. XGBoost, Random Forest, and CatBoost performed best on the balanced dataset, with a stacking ensemble method improving accuracy to 92.5%. Data balancing strategies improve model performance and ensemble methods improve obesity classification accuracy. For future health-related predictive analytics applications, the findings emphasize the need to overcome class imbalance in machine learning tasks. © 2024 IEEE.

关键词： Adversarial machine learning

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Research on the Design of Scaffolding for computer Network Technology Based on Higher-Order thinking Development 13

Research on the Design of Scaffolding for Computer Network T...

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13th International conference on Information Technology in Medicine and Education, ITME 2023

作者： Mao, Yongfang Du, Mingjie Luo, Minghui Xie, Fu Shandong Normal University School of Information Science and Engineering Jinan China

ISBN: (纸本)9798350319156

this paper presents a case study on teaching support for the cultivation of higher-order thinking skills in the context of secondary vocational education, specifically in the field of computer network technology. the study aims to enhance students' higher-order thinking skills using the zone of proximal development and constructivism theory. It aims to address the specific characteristics and requirements of computer network technology. the article proposes designing scaffolding that targets five dimensions: 'Analytical Ability', 'Comprehension Ability', 'Problem-Solving Ability', 'Evaluative Ability', and 'Creative Ability'. the objective is to address the issue of shallow thinking among secondary vocational students. the article concludes by presenting a teaching scaffolding designed for the 'Network Topology' course in secondary vocational schools. © 2023 IEEE.

关键词： Students

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A Real-Time local Binary Pattern-based Face Recognition System on Open CV using Boosted Cascade of Simple Features 13

A Real-Time Local Binary Pattern-based Face Recognition Syst...

引用

13th IEEE International conference on Communication Systems and Network Technologies, CSNT 2024

作者： Choudhary, Sarswati Pareyani, Silky Kourav, Sateesh Gyan Ganga College of Technology Department of Electronics and Communication Engineering Jabalpur India Department of Electronics and Communication Engineering MP Jabalpur India

ISBN: (纸本)9798350305463

Face recognition has grabbed the interest of biometrics, pattern recognition, and computer vision scientists. Face detection in photos has grown more significant during the last 10 years. Using OpenCV and a boosted cascade of basic features based on local Binary Pattern (LBP), we created a real-time face recognition system. Pre-processing the photographs improves their quality and normalizes them. You may wish to resize the photographs to a uniform size, convert them to grayscale, and do any other preparatory procedures that are required. Replace file locations and parameters with values appropriate to your dataset and project structure. the pre-processing step involves segmentation, filtering, thresholding, and picture quality enhancement. the BCSF Technique Face recognition is a critical stage in the recognition process. A Faces Database Each face in the database comprises an RTLBP computation and a correlation. the identity vectors in the covariance matrix are derived using a collection of fingerprint photos. Metrics of Performance the recognition method takes 10.18 seconds and has a 99.93% success rate. Face Recognition and Annotation on Multiple Faces Several faces can be recognized and annotated in a single run using traditional approaches. the detector runs in real-time at a frame rate of fifteen frames per second. It is not dependent on visual differences or skin color recognition. the name of the identified individual is shown in the upper left corner of a highlighted rectangle enclosing the face. Methods Evaluation summarizes the benefits and drawbacks of common strategies. this article looks into a variety of novel facial recognition systems. © 2024 IEEE.

关键词： local binary pattern

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Trusted Auditing of Data Operation Behaviors in Cloud based on Blockchain and TEE 21

Trusted Auditing of Data Operation Behaviors in Cloud based ...

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作者： Xu, Shujiang Wang, Fansheng Wang, Lianhai Mihaljevic, Miodrag J. Zhang, Shuhui Shao, Wei Huang, Qihao Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Mathematical Institute The Serbian Academy of Sciences and Arts Belgrade Serbia Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)9798350329223

With the rapid development of the new generation of information technologies, including cloud computing, 5G, and the Internet of things, data outsourcing storage in the cloud has brought great convenience to data storage or access anytime and anywhere. Due to the separation of ownership and management of outsourced stored data, it faces data security risks, including data loss and personal privacy disclosure. the third-party audit of data operational behavior by logs is often employed to strengthen the security of outsourced data. However, some privacy breach incidents in recent years show that third parties who may leak information about data and users' identities are not always trustworthy. To achieve data security and privacy protection, an operation behavior auditing scheme for outsourced data is proposed with the blockchain rather than third parties. the data operation behavior audit is carried out from three dimensions: integrity of the operation behavior log, the credibility of the operation behavior information, and compliance of operation behavior. the security analysis and experiment results indicate that this scheme is secure and feasible. © 2023 IEEE.

关键词： Blockchain

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Utilizing Artificial Intelligence in Telemedicine for Efficient Remote Diagnosis and Treatment Plan 13

Utilizing Artificial Intelligence in Telemedicine for Effici...

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13th IEEE International conference on Communication Systems and Network Technologies, CSNT 2024

作者： Asha, V. Sumalatha, Ippa Mishra, Anshoo thethi, H Pal Kalra, Ravi Almusawi, Muntather New Horizon College of Engineering Department of Computer Applications Bangalore India Institute of Aeronautical Engineering Hyderabad India Ies Insititute of Technology and Management Ies University Department of Computer Science & Engineering M. P Bhopal India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Uttar Pradesh Greater Noida201306 India The Islamic University Najaf Iraq

ISBN: (纸本)9798350305463

To facilitate dynamic and adaptive remote diagnosis and treatment planning, the 'Dynamic Adaptive Diagnosis and Treatment (DADT)' approach uses three fundamental AI algorithms that operate in tandem with one another. the cornerstone is the Intelligent Symptom Analysis Algorithm (ISAA), which uses patient-reported symptoms and medical history to make diagnostic determinations. the Adaptive Treatment Recommender (ATR) algorithm constantly adjusts prescribed treatments considering patient feedback, research findings, and new standards of care. In order to constantly learn from fresh data and update diagnostic and treatment models, the Continuous Learning Diagnostic Network (CLDN) makes use of a neural network. Accurate diagnosis and individualized treatment planning are the goals of the suggested technique, which is intended for use in distant healthcare settings. © 2024 IEEE.

关键词： Diagnosis

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