检索结果-内蒙古大学图书馆

2nd International Conference on Image, Vision and Intelligent Systems, ICIVIS 2022

作者： Yu, Mengqi Wang, Shuai Wei, Yining Zhong, Zhenkun Peng, Hui School of Computer Science and Engineering Central South University Changsha410083 China School of Software Engineering Xinjiang University Xinjiang830008 China

ISBN: (纸本)9789819909223

The state of charge (SOC) of lithium-ion batteries is predicted by using neural network and random forest. According to the battery discharge state in different periods, the entire discharge process is divided into platform stage and non-platform stage, and the above two methods are used to predict each stage separately. On the basis of fully analyzing the charge and discharge mechanism of lithium-ion batteries, the back propagation (BP) neural network model of lithium-ion batteries is established by genetic algorithm. The result proves that the SOC prediction method based on neural network and random forest has high accuracy, so this method can be applied in predicting the battery SOC. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Lithium-ion batteries

来源：评论

学校读者我要写书评

暂无评论

FedEvalFair: A Privacy-Preserving and Statistically Grounded Federated Fairness Evaluation Framework 24

FedEvalFair: A Privacy-Preserving and Statistically Grounded...

引用

32nd ACM International Conference on Multimedia, MM 2024

作者： Wang, Zhongchi Sun, Hailong Zhao, Zhengyang School of Computer Science and Engineering Beihang University Beijing China Hangzhou Innovation Institute Beihang University Beijing China School of Software Beihang University Beijing China

ISBN: (纸本)9798400706868

Federated learning has rapidly gained attention in the industrial sector due to its significant advantages in protecting privacy. However, ensuring the fairness of federated learning models post-deployment presents a challenge in practical applications. Given that clients typically rely on limited private datasets to assess model fairness, this constrains their ability to make accurate judgments about the fairness of the model. To address this issue, we propose an innovative evaluation framework, FedEvalFair, which integrates private data from multiple clients to comprehensively assess the fairness of models in actual deployment without compromising data privacy. Firstly, FedEvalFair draws on the concept of federated learning to achieve a comprehensive assessment while protecting privacy. Secondly, based on the statistical concept of "estimating the population from the sample", FedEvalFair is capable of estimating the fairness performance of the model in real-world settings from a limited data sample. Thirdly, we have designed a flexible two-stage evaluation strategy based on statistical hypothesis testing. We verified the theoretical performance and sensitivity to fairness variations of FedEvalFair using Monte Carlo simulations, demonstrating the superior performance of its two-stage evaluation strategy. Additionally, we validated the effectiveness of the FedEvalFair method on real-world datasets, including UCI Adult and eICU, and demonstrated its stability in dealing with real-world data distribution changes compared to traditional evaluation methods. © 2024 ACM.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A Cost-Efficient Anonymous Authenticated and Key Agreement Scheme for V2I-Based Vehicular Ad-Hoc Networks

引用

IEEE Transactions on Intelligent Transportation Systems 2024年第9期25卷 12621-12630页

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Shamshad, Salman Alenazi, Mohammed J. F. Das, Ashok Kumar University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518000 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500032 India

The rise of smart cities is directly connected to the increasing use of vehicles. The growing vehicle utilization has driven the emergence of Vehicular Ad-hoc Networks (VANETs), facilitating instant information exchange among vehicles. The system provides essential information regarding road conditions, traffic patterns, and more relevant data. VANETs encompass two fundamental categories of communication exchanges, namely Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). V2I technology facilitates the integration of cars and transportation infrastructure, enabling effective communication between vehicles and infrastructure. Nevertheless, the potential of V2I communication has various security concerns arising from prevalent security threats. Current authentication techniques encounter challenges regarding complexity, security, and privacy considerations. We designed a hash-based lightweight and anonymous authentication scheme to address the aforementioned restrictions and enhance the effectiveness of authentication in V2I architecture. This scheme effectively combines identity, password, and bio-metric to enhance resistance against impersonation, denial of service, and privileged insider attacks. The devised scheme distinguishes itself by a comparative analysis and security proofs, highlighting its superior capability in guaranteeing secure authentication in V2I communication. The comprehensive security analysis conducted formally and informally showcases the robustness of the proposed solution against several threats. The performance evaluation results show that our scheme demonstrates a decrease in the computational cost of 51.40% approximately and a reduction in communication overhead of around 22.57%. These results establish the efficiency and scalability of the proposed scheme as a viable solution for V2I architecture. © 2000-2011 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

Two-stage image inpainting method based on transformer and Fast Fourier convolution 2

Two-stage image inpainting method based on transformer and F...

引用

2nd International Conference on Image Processing, computer Vision and Machine Learning, ICICML 2023

作者： Li, Changxing Chen, Zhuang Chongqing University of Posts and Telecommunications School of Software Engineering Chongqing China Chongqing University of Technology School of Computer Science and Engineering Chongqing China

ISBN: (纸本)9798350331417

In view of the insufficient ability of the currently existing deep learning-based methods to repair image high-frequency information and the small sensory field of the traditional convolutional methods. A two-stage image repair model is proposed. First, Transformer is used to repair the image initially;second, Fourier convolution is used to construct a generative network to refine the high-frequency details of the image;finally, the repair results are input into the discriminator for training to obtain the final image repair model. The experimental results on street view datasets show that the model in the paper has better restoration results in high-frequency details as well as semantic information;compared with mainstream methods, It achieves better results in peak signal-to-noise ratio and structural similarity. © 2023 IEEE.

关键词： Generative adversarial network image inpainting multiple attention Receptive field

来源：评论

学校读者我要写书评

暂无评论

A method of monitoring and locating eggs laid by breeding geese based on photoelectric sensing technology

引用

Information Processing in Agriculture 2022年第3期9卷 406-416页

作者： Yidan Xu Qiuju Xie Liwei Wang College of Mechanical and Automotive Engineering Zhaoqing UniversityZhaoqing526061China School of Computer Science and Software Zhaoqing UniversityZhaoqing 526061China

On the current breeding goose farm,the detection of individual egg laying mainly depends on some judgement experiences of farm *** present,there have been some egg laying detection systems developed with images and weighing sensors,which only signal the eggs being laid,but no egg position being ***,the detection rate of the system is not high due to environment limitations like dim light of the goose ***,to solve these problems mentioned above,an intelligent detection and positioning system is pro-posed by integrating technologies of the Radio Frequency(RF)and photoelectric sensors,together with the geometric calculation *** this research,individual egg laying information of breeding geese in a non-cage state was examined to improve the level of auto-matic detection and positioning in the field of breeder egg *** results showed that an accurate detection and positioning of an egg in a nest filled with the artificial turf could be achieved under some conditions:the height of sensor is 3.5 cm from the bottom plate of the egg laying nest,the spacing of the photoresistor module is 5 cm,and the external light intensity is less than 110 *** also shown that the error of the goose egg position recognition is 0.443 cm with a suitable level of straw in the ***,the monitoring system and positioningmethod that was developed in this research could provide a reference for the analysis of individual egg laying behavior,and could result in an improvement in the automatic egg collection for the breeding geese production.

关键词： Breeding geese Egg laying monitoring Goose egg location Photoelectric sensing technology RFID technology

来源：评论

学校读者我要写书评

暂无评论

A Novel Secure Scan Design Based on Delayed Physical Unclonable Function

引用

computers, Materials & Continua 2023年第3期74卷 6605-6622页

作者： Weizheng Wang Xingxing Gong Xiangqi Wang Gwang-jun Kim Fayez Alqahtani Amr Tolba School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China College of Information Science and Engineering Hunan Women’s UniversityChangsha410138China College of Mathematics and Computational Science Hunan First Normal UniversityChangsha410138China Department of Computer Engineering Chonnam National UniversityGwangju61186Korea Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia

The advanced integrated circuits have been widely used in various situations including the Internet of Things,wireless communication,*** its manufacturing process exists unreliability,so cryptographic chips must be rigorously *** to scan testing provides high test coverage,it is applied to the testing of cryptographic integrated ***,while providing good controllability and observability,it also provides attackers with a backdoor to steal *** the text,a novel protection scheme is put forward to resist scan-based attacks,in which we first use the responses generated by a strong physical unclonable function circuit to solidify fuseantifuse structures in a non-linear shift register(NLSR),then determine the scan input code according to the configuration of the fuse-antifuse structures and the styles of connection between the NLSR cells and the scan *** the key is right,the chip can be tested normally;otherwise,the data in the scan chain cannot be propagated normally,it is also impossible for illegal users to derive the desired scan *** proposed technique not only enhances the security of cryptographic chips,but also incurs acceptable overhead.

关键词： Cryptographic chips scan testing scan-based attacks hardware security PUF

来源：评论

学校读者我要写书评

暂无评论

LLMeLog: An Approach for Anomaly Detection based on LLM-enriched Log Events 35

LLMeLog: An Approach for Anomaly Detection based on LLM-enri...

引用

35th IEEE International Symposium on software Reliability engineering, ISSRE 2024

作者： He, Minghua Jia, Tong Duan, Chiming Cai, Huaqian Li, Ying Huang, Gang Peking University School of Software and Microelectronics Beijing China Peking University Institute for Artificial Intelligence Beijing China Peking University School of Computer Science Beijing China Peking University National Engineering Research Center for Software Engineering Beijing China

ISBN: (纸本)9798350353884

Log-based anomaly detection is an essential task in maintaining software reliability. Existing log-based anomaly detection approaches often consist of three key phases: log parsing, event embedding, and model construction. Event embedding efficiently extracts semantic information from log events and produces vector representations of log events. However, existing event embedding methods suffer from two key problems. First, semantic noises are buried in log events leading to inevitable gaps between the obtained semantics from log events and their essential meanings. Second, there exists a gap between general semantic embedding and the specific embedding requirement of anomaly detection tasks. To mitigate these problems and improve the quality of representations of log events, we propose a novel anomaly detection approach named LLMeLog. It leverages the capabilities of large language models (LLMs) to enrich the contents of log events with in-context learning techniques. Then it utilizes the enriched log events to fine-Tune a pre-Trained BERT model. At last, it trains a transformer-based anomaly detection model with the event representations produced by the pre-Trained BERT model. Evaluation results on three public log datasets show that LLMeLog achieves the best performance across all datasets, boasting F1-scores exceeding 99%. Besides, when using only 10% of labeled data as training data, our approach can still achieve over 90% F1-scores. © 2024 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Construction of PCOS Prediction Model based on BP Neural Network 6

Construction of PCOS Prediction Model based on BP Neural Net...

引用

6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Hu, Xianqing Yadav, Amit Khan, Asif Sah, Abhishek Pratap Azam, Sami School of Computer and Software Chengdu Neusoft University Chengdu China Faculty of Science and Technology Charles Darwin University NT Australia Department of Computer Application Integral University Lucknow India School of Management Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798331522667

Polycystic ovary syndrome (PCOS), a common endocrine-metabolic disorder affecting about 10-13% of women during reproductive age worldwide, often leads to irregular menstruation, infertility, obesity, and long-term health risks such as diabetes and cardiovascular disease. In this paper, clinical data from PCOS patients and healthy control group were collected from ten hospitals containing 37 key indicators such as age, weight, BMI, menstrual cycle, etc. BP (Back Propagation) Neural Network prediction models were constructed and compared using the collected data and the cross-validation method was used for parameter tuning. It was found that BP Neural Network performed particularly well on the test set, and both demonstrated high prediction accuracy and generalization ability which provided strong evidence for the early identification and early valuable intervention opportunities for PCOS patients. © 2025 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial: Special Issue on Human-Machine Fusion Decision-Making for Emergency Handling

引用

IEEE Transactions on Automation science and engineering 2025年 22卷 4427-4433页

作者： Wu, Edmond Q. Li, Jianqiang Chen, Guimin Yuce, Mehmet R. Islam, Shafiqul Ser, Javier Del Yu, Hui Liu, Peter Xiaoping Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China College of Computer and Software Engineering Shenzhen University Shenzhen518060 China State Key Laboratory for Manufacturing Xi'an Jiaotong University Xi'an710049 China Department of Electrical and Computer Systems Engineering Monash University MelbourneVIC3800 Australia Xavier University of Louisiana New OrleansLA70125 United States Tecnalia Institute Bizkaia48160 Spain School of Creative Technologies University of Portsmouth PortsmouthPO1 2UP United Kingdom Department of Systems and Computer Engineering Carleton University OttawaONKIS 5B6 Canada

来源：评论

学校读者我要写书评

暂无评论

Audio2AB:Audio-driven collaborative generation of virtual character animation

引用

虚拟现实与智能硬件（中英文） 2024年第1期6卷 56-70页

作者： Lichao NIU Wenjun XIE Dong WANG Zhongrui CAO Xiaoping LIU School of Computer Science and Information Engineering Hefei University of TechnologyHeifei 230009China School of Software Hefei University of TechnologyHeifei 230009China Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei University of TechnologyHefei 230601China

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of ***,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient *** Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body *** parameterization method can be used to drive full-body animations of virtual characters and improve their *** the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial *** Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio ***,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss *** By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape ***,different 3D virtual character animations could be created through *** The experimental results showed that the proposed method could generate significant gestures and facial animations.

关键词： Audio-driven Virtual character Full-body animation Audio2AB Blendshape GAN-GF

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：