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Rapid health estimation of in-service battery packs based on limited labels and domain adaptation

Journal of Energy Chemistry 2024年第2期89卷 345-354,I0009页

作者： Zhongwei Deng Le Xu Hongao Liu Xiaosong Hu Bing Wang Jingjing Zhou School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina School of Sustainability Stanford UniversityStanfordCA 94305USA College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400044China china Automotive Engineering Research Institute Co.Ltd. Chongqing 401122China

For large-scale in-service electric vehicles(EVs)that undergo potential maintenance,second-hand transactions,and retirement,it is crucial to rapidly evaluate the health status of their battery ***,existing methods often rely on lengthy battery charging/discharging data or extensive training samples,which hinders their implementation in practical *** address this issue,a rapid health estimation method based on short-time charging data and limited labels for in-service battery packs is proposed in this ***,a digital twin of battery pack is established to emulate its dynamic behavior across various aging levels and inconsistency ***,increment capacity sequences(△Q)within a short voltage span are extracted from charging process to indicate battery ***,data-driven models based on deep convolutional neural network(DCNN)are constructed to estimate battery state of health(SOH),where the synthetic data is employed to pre-train the models,and transfer learning strategies by using fine-tuning and domain adaptation are utilized to enhance the model ***,field data of 10 EVs exhibiting different SOHs are used to verify the proposed *** using the△Q with 100 m V voltage change,the SOH of battery packs can be accurately estimated with an error around 3.2%.

关键词： Lithium-ion battery Electric vehicles Health estimation Feature extraction Convolutional neural network Domain adapatation

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Automatic detection of breast nodule in the ultrasound images using CNN

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The Journal of china Universities of Posts and Telecommunications 2019年第2期26卷 9-16页

作者： Pang Hao Bu Yunyun Wang Cong Xiao Hui School of Software Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and service (BUPT) Ministry of EducationBeijing 100876China Department of Ultrasound Beijing Friendship HospitalCapital Medical University china electronic data service company limited

Breast cancer is the most common cancer among women *** is widely used as a harmless test for early breast cancer *** ultrasound network(USNet) model is *** is an improved object detection model specifically for breast nodule detection on ultrasound *** improved the backbone network,optimized the generation of feature maps,and adjusted the loss ***,USNet trained with real clinical *** evaluation results show that the trained model has strong nodule detection *** mean average precision(mAP) value can reach 0.734 *** nodule detection rate is 95.11%,and the in situ cancer detection rate is 79.65%.At the same time,detection speed can reach 27.3 frame per second(FPS),and the video data can be processed in real time.

关键词： convolutional neural network object detection ultrasound breast nodule

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Lattice-based autonomous path proxy re-encryption in the standard model

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Science china(Information Sciences) 2023年第10期66卷 184-195页

作者： Wenli XIE Jian WENG Yao TONG Xiaojian LIANG Lisha YAO Feixiang ZHAO College of Cyber Security Jinan University Guangzhou Fongwell data limited company

Autonomous path proxy re-encryption(AP-PRE) is a type of PRE that implements control on the delegation path in a multi-hop PRE. AP-PRE forces the proxy to perform the transformation along a predefined path without revealing the underlying plaintext. There are several applications of AP-PRE,including electronic medical systems, data sharing, and email systems. However, as far as we know, the existing AP-PRE scheme is provably secure in the random oracle model under the classical number-theoretic assumption, which might be vulnerable to quantum computers. Therefore, it raises the intriguing question of how to construct a quantum-resistant AP-PRE scheme. In this study, we proposed an AP-PRE scheme based on the widely accepted quantum-resistant learning with errors(LWE) assumptions. Our scheme supports the polynomial length of the delegation path. Furthermore, our scheme is proved to be selective-path CPA(sCPA) secure in the standard model under LWE assumptions.

关键词： autonomous path proxy re-encryption proxy re-encryption lattice-based cryptography learning with errors controlled delegation

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Research on Total Electric Field Prediction Method of Ultra-High Voltage Direct Current Transmission Line Based on Stacking Algorithm

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Computer Systems Science & Engineering 2024年第3期48卷 723-738页

作者： Yinkong Wei Mucong Wu Wei Wei Paulo R.F.Rocha Ziyi Cheng Weifang Yao Key Laboratory of Operation and Control of Terraced Hydropower Plants in Hubei Province Three Gorges UniversityYichang443002China School of Electricity and New Energy Three Gorges UniversityYichang443002China Marketing service Center(Metering Center) State Grid Hubei Electric Power Co.Ltd.Wuhan430072China Centre for Functional Ecology-Science for People&the Planet Associate Laboratory TERRADepartment of Life SciencesUniversity of CoimbraCoimbra3000-456Portugal Research Institute of Electric Power Science State Grid Anhui Electric Power Company LimitedHefei230601China

Ultra-high voltage(UHV)transmission lines are an important part of china’s power grid and are often surrounded by a complex electromagnetic *** ground total electric field is considered a main electromagnetic environment indicator of UHV transmission lines and is currently employed for reliable long-term operation of the power ***,the accurate prediction of the ground total electric field remains a technical *** this work,we collected the total electric field data from the Ningdong-Zhejiang±800 kV UHVDC transmission project,as of the Ling Shao line,and perform an outlier analysis of the total electric field *** show that the Local Outlier Factor(LOF)elimination algorithm has a small average difference and overcomes the performance of Density-Based Spatial Clustering of Applications with Noise(DBSCAN)and Isolated Forest elimination ***,the Stacking algorithm has been found to have superior prediction accuracy than a variety of similar prediction algorithms,including the traditional finite *** low prediction error of the Stacking algorithm highlights the superior ability to accurately forecast the ground total electric field of UHVDC transmission lines.

关键词： DC transmission line total electric field effective data multivariable outliers LOF algorithm Stacking algorithm

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Adaptive transfer learning framework for dense prediction of human activity recognition

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The Journal of china Universities of Posts and Telecommunications 2019年第5期26卷 1-10,21页

作者： Zhang Zhao Zhang Yong Teng Yinglei Guo Da Deng Haiqin School of electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Aldong Super AI(Beijing)company limited Beijing 100007China

Human activity recognition(HAR)for dense prediction is proven to be of good performance,but it relies on labeling every point in time series with the high *** addition,the performance of HAR model will show significant degradation when tested on the sensor data with different distribution from the training data,where the training data and the test data are usually collected from different sensor locations or sensor ***,the adaptive transfer learning framework for dense prediction of HAR is introduced to implement cross-domain transfer,where the proposed multi-level unsupervised domain adaptation(MLUDA)approach combines the global domain adaptation and the specific task adaptation to adapt the source and target domain in multiple *** multi-connected global domain adaptation architecture is proposed for the first time,which can adapt the output layer of the encoder and the decoder in dense prediction *** this,the specific task adaptation is proposed to ensure alignment of each class centroid in source domain and target domain by introducing the cosine distance loss and the moving average *** on three public HAR datasets demonstrate that the proposed MLUDA improves the prediction accuracy of target data by 20%compared to the source domain pre-trained model and it is more effective than the other three deep transfer learning methods with an improvement of 10%to 18%in accuracy.

关键词： transfer learning human activity recognition dense prediction global domain adaptation specific task adaptation

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Naive Echo-State-Network Based services Awareness Algorithm of Software Defined Optical Networks

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china Communications 2020年第4期17卷 11-18页

作者： Huifeng Bai Wenbin Chen Licheng Wang Chao Huo Beijing SmartChip Microelectronics Technology company limited Beijing 102200China

As internet services newly emerge with diversity and complexity, great challenges and demands are presented to the Open Flow controlled software defined optical networks(SDON) to achieve better match between services and SDON. With this aim, this paper proposes a naive Echo-State-Network(Naive-ESN) based services awareness algorithm of the software defined optical network, where the naive ESN model adopts the ring topology structure and generates the probability output result to determine the Qo S policy of SDON. Moreover, the Naive-ESN engine is also designed in controller node of SDON to perform services awareness by obtaining service traffic features from data plan, together with some necessary extension of the Open Flow protocol. Test results show that the proposed approach is able to improved services-oriented supporting ability of SDON.

关键词： software defined optical networks naive echo-state-network services awareness openflow protocol

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Logformer: Cascaded Transformer for System Log Anomaly Detection

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Computer Modeling in Engineering & Sciences 2023年第7期136卷 517-529页

作者： Feilu Hang Wei Guo Hexiong Chen Linjiang Xie Chenghao Zhou Yao Liu Information Center Yunnan Power Grid Company LimitedKunming650034China Network anddata Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu610054China

Modern large-scale enterprise systems produce large volumes of logs that record detailed system runtime status and key events at key *** logs are valuable for analyzing performance issues and understanding the status of the *** detection plays an important role in service management and system maintenance,and guarantees the reliability and security of online *** are universal semi-structured data,which causes difficulties for traditional manual detection and pattern-matching *** some deep learning algorithms utilize neural networks to detect anomalies,these approaches have an over-reliance on manually designed features,resulting in the effectiveness of anomaly detection depending on the quality of the *** the same time,the aforementioned methods ignore the underlying contextual information present in adjacent log *** propose a novel model called Logformer with two cascaded transformer-based heads to capture latent contextual information from adjacent log entries,and leverage pre-trained embeddings based on logs to improve the representation of the embedding *** proposed model achieves comparable results on HDFS and BGL datasets in terms of metric accuracy,recall and ***,the consistent rise in F1-score proves that the representation of the embedding spacewith pre-trained embeddings is closer to the semantic information of the log.

关键词： Anomaly detection system logs semi-structured data pre-trained embedding cascaded transformer

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A RANSAC based phase noise filtering method for the camera-projector calibration system

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Optoelectronics Letters 2022年第10期18卷 618-622页

作者： LI Wenjie ZHANG Zonghui JIANG Zhansi GAO Xingyu TAN Zhengdong WANG Hui School of Mechanical and Electrical Engineering Guilin University of Electronic TechnologyGuilin541004China Shenzhen Anewbest electronic Technology limited company Shenzhen518000China Communist Youth League Committee Guilin University of Electronic TechnologyGuilin541004China

Aiming at the noise disturbance of unwrapping phases of control points in the camera-projector calibration system, a random sample consensus(RANSAC) based plane fitting method is proposed to filter the phase noise in this paper. Different from the classical least squares method using all data, the points with noise will not be used to fit the plane in the proposed RANSAC method, which improves the accuracy of plane fitting. The proposed method suits for any two-dimensional(2D) calibration patterns, such as checkerboard or black dots with white background, which improves the flexibility of camera-projector system calibration.

关键词： system method phase

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Labeled Network Stack: A High-Concurrency and Low-Tail Latency Cloud Server Framework for Massive IoT Devices

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Journal of Computer Science & Technology 2020年第1期35卷 179-193页

作者： Wen-Li Zhang Ke Liu Yi-Fan Shen Ya-Zhu Lan Hui Song Ming-Yu Chen Yuan-Fei Chen State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China University of Chinese Academy of Sciences Beijing 100049China Peng Cheng Laboratory Shenzhen 518000China Zhongke Zhicheng electronic Technology company limited Jining 272000China

Internet of Things(IoT)applications have massive client connections to cloud servers,and the number of networked IoT devices is remarkably *** services require both low-tail latency and high concurrency in *** study aims to determine whether an order of magnitude improvement is possible in tail latency and concurrency in mainstream systems by proposing a hardware-software codesigned labeled network stack(LNS)for future *** key innovation is a cross-layered payload labeling mechanism that distinguishes different requests by payload across the full network stack,including application,TCP/IP,and Ethernet *** type of design enables prioritized data packet processing and forwarding along the full datapath,such that latency-insensitive requests cannot significantly interfere with high-priority *** build a prototype datacenter server to evaluate the LNS design against a commercial X86 server and the mTCP research,using a cloud-supported IoT application *** results show that the LNS design can provide an order of magnitude improvement in tail latency and concurrency.A single datacenter server node can support over 2 million concurrent long-living connections for IoT devices as a 99-percentile tail latency of 50 ms is *** addition,the hardware-software codesign approach remarkably reduces the labeling and prioritization overhead and constrains the interference of high-priority requests to low-priority requests.

关键词： tail latency high concurrency network stack cloud server Internet of Things(IoT)service

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Solution of false alarm and slow response in flame detector

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Journal of Southeast University(English Edition) 2019年第2期35卷 174-178页

作者： Song Wengang Zhang Lijun Zheng Zhanqi Wang Guanying Zhang Jianming Institute of Microelectronics Chinese Academy of SciencesBeijing 100029China School of Microelectronics University of Chinese Academy of SciencesBeijing 100190China Wuhan Binhu electronic limited Liability company Wuhan 430205China

A new flame detector with one ultraviolet and two infrared detectors is designed. The ultraviolet detector is of rapid response(≤10 μs) while the two infrared detectors usually have a response time of more than 5 ms. The ultraviolet detector is applied to deal with the flame of large scales. When facing the flame of mid or small scales, the three detectors cooperate. Employing the high-order derivatives of the sample data of the infrared circuits to improve the sensitivity, the response speed is greatly improved. The data of the temperature sensor is used to adjust circuit parameters in real time, thus reducing the effect of temperature drift. The flame detectors are tested at different distances and the response time is as rapid as 0.65 ms. The test results show that the new flame detector has the characteristics of high speed and a low rate of false alarms.

关键词： flame detector rapid response low false alarm rate derivative

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