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4th IEEE International Conference on Electronics and Communication Engineering, ICECE 2021

作者： Xue, Junjie Zhou, Junhua Shi, Guoqiang Feng, Chaoqun Liu, Penghua Quan, Hongyan Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing China Institute of Electronic System Engineering Beijing China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (纸本)9781728194226

In order to make full use of the concept of model-based systems engineering (MBSE) and the collaborative design capability of the open model-based engineering environment (OpenMBEE) in establishing complex product development platform, we propose an effective method to solve the problem of unified identity authentication in OpenMBEE integration. The proposed method is based on the Model View Controller(MVC) architecture in OpenMBEE, which has the characteristics strong plasticity and can be benefit for expanding the function in the controller layer. In our research, we make full use of the Software Development Kit (SDK) of OpenMBEE to expand the existing functions in the controller layer, and increase the function of communicating with the application development platform, then realize the function of sharing user authentication information between the development platform and OpenMBEE. After expansion, the system includes three modules, including the Front-end Service Module(FSM), MQ based Information Receiving Service Module(IFRSM), and the OpenMBEE Back-end Server Module(BSM). The effectiveness of the proposed strategies is verified by some practical instances, which verifies that our study can provide an effective design idea for the identity authentication in OpenMBEE integration. ©2021 IEEE

关键词： Integration

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A Client Selection Method Based on Loss Function Optimization for Federated Learning

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Computer modeling in Engineering & Sciences 2023年第10期137卷 1047-1064页

作者： Yan Zeng Siyuan Teng Tian Xiang Jilin Zhang Yuankai Mu Yongjian Ren Jian Wan School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Key Laboratory of Complex System Modeling and Simulation Ministry of EducationHangzhou310018China Zhejiang Engineering Research Center of Data Security Governance Hangzhou310018China Intelligent Robotics Research Center Zhejiang LabHangzhou311100China HDU-ITMO Joint Institute Hangzhou Dianzi UniversityHangzhou310018China

Federated learning is a distributedmachine learningmethod that can solve the increasingly serious problemof data islands and user data privacy,as it allows training data to be kept locally and not shared with other *** trains a globalmodel by aggregating locally-computedmodels of clients rather than their ***,the divergence of local models caused by data heterogeneity of different clients may lead to slow convergence of the global *** this problem,we focus on the client selection with federated learning,which can affect the convergence performance of the global model with the selected local *** propose FedChoice,a client selection method based on loss function optimization,to select appropriate local models to improve the convergence of the global *** firstly sets selected probability for clients with the value of loss function,and the client with high loss will be set higher selected probability,which can make them more likely to participate in ***,it introduces a local control vector and a global control vector to predict the local gradient direction and global gradient direction,respectively,and calculates the gradient correction vector to correct the gradient direction to reduce the cumulative deviationof the local gradient causedby *** experiments to verify the validity of FedChoice on CIFAR-10,CINIC-10,MNIST,EMNITS,and FEMNIST datasets,and the results show that the convergence of FedChoice is significantly improved,compared with FedAvg,FedProx,and FedNova.

关键词： Federated learning model aggregation Non-IID

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Analysis of overload-based cascading failure in multilayer spatial networks

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Chinese Physics B 2020年第9期29卷 404-414页

作者： Min Zhang Xiao-Juan Wang Lei Ji Mei Song Zhong-Hua Liao School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation CenterBeijing 100854China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China

Many complex networks in real life are embedded in space and most infrastructure networks are interdependent,such as the power system and the transport *** this paper,we construct two cascading failure models on the multilayer spatial *** our research,the distance l between nodes within the layer obeys the exponential distribution P(l)~exp(-l/ζ),and the length r of dependency link between layers is defined according to node *** entropy approach is applied to analyze the spatial network structure and reflect the difference degree between *** metrics,namely dynamic network size and dynamic network entropy,are proposed to evaluate the spatial network robustness and *** the cascading failure process,the spatial network evolution is analyzed,and the numbers of failure nodes caused by different reasons are also counted,***,we discuss the factors affecting network *** demonstrate that the larger the values of average degree,the stronger the network *** the length r decreases,the network performs *** the probability p is small,asζdecreases,the network robustness becomes more *** p is large,the network robustness manifests better performance asζ*** results provide insight into enhancing the robustness,maintaining the stability,and adjusting the difference degree between nodes of the embedded spatiality systems.

关键词： cascading failure multilayer network load distribution spatial network entropy

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A probe into the acid deposition mitigation path in China over the last four decades and beyond

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National Science Review 2024年第4期11卷 84-92页

作者： Qian Yu Xiaodong Ge Haotian Zheng Jia Xing Lei Duan Dongwei Lv Dian Ding Zhaoxin Dong Yisheng Sun Posch Maximilian Danni Xie Yu Zhao Bin Zhao Shuxiao Wang Jan Mulder Thorj?rn Larssen Jiming Hao State Key Laboratory of Environmental Simulation and Pollution Control School of EnvironmentTsinghua University State Key Laboratory of Pollution Control &Resource Reuse and School of the Environment Nanjing University State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex School of EnvironmentTsinghua University International Institute for Applied System Analysis(IIASA) School of Land Engineering Chang'an University Faculty of Environmental Sciences and Natural Resource Management Norwegian University of Life Sciences Norwegian Institute for Water Research

China currently has the highest acid deposition globally, yet research on its status, impacts, causes and controls is lacking. Here, we compiled data and calculated critical loads regarding acid deposition. The results showed that the abatement measures in China have achieved a sharp decline in the emissions of acidifying pollutants and a continuous recovery of precipitation p H, despite the drastic growth in the economy and energy consumption. However, the risk of ecological acidification and eutrophication showed no significant decrease. With similar emission reductions, the decline in areas at risk of acidification in China(7.0%) lags behind those in Europe(20%) or the USA(15%). This was because, unlike Europe and the USA, China's abatement strategies primarily target air quality improvement rather than mitigating ecological impacts. Given that the area with the risk of eutrophication induced by nitrogen deposition remained at 13%of the country even under the scenario of achieving the dual targets of air quality and carbon dioxide mitigation in 2035, we explored an enhanced ammonia abatement pathway. With a further 27% reduction in ammonia by 2035, China could largely eliminate the impacts of acid deposition. This research serves as a valuable reference for China's future acid deposition control and for other nations facing similar challenges.

关键词： acid deposition critical loads acidification eutrophication ammonia abatement

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Multi-objective Optimization of Electromagnetic Launch system Based on Improved RVEA-IGNG Algorithm 1

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19th International Conference of Intelligent Unmanned systems, ICIUS 2023

作者： Li, Xiaoyu Guo, Ke Chao, Tao Ma, Ping Yang, Ming Wang, Songyan Harbin Institute of Technology Harbin150001 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin China Beijing Institute of Space Long March Vehicle Beijing100076 China

ISBN: (数字)9789819765911

ISBN: (纸本)9789819765904

For analyzing the influences of discharge sequence of each pulsed power supply and discharge voltage on the performance of the electromagnetic launch system, intelligent optimization algorithms are carried out based on the simulation model of the electromagnetic launch system. Based on the maximum rail current, projectile exit velocity and energy conversion efficiency, the corresponding multi-objective optimization model is established, and the Pareto front (PF) is acquired in RVEA-iGNG algorithm. The algorithm combines an evolutionary optimization algorithm with the reference vector adaptive adjustment by growing neural gas network. It can handle the multi-objective optimization of the electromagnetic launch system with complex irregular PF and achieve fast convergence. In order to provide decision makers with more diversified solutions, this paper proposes an improved RVEA-iGNG algorithm where the archive maintenance strategy is improved. The simulation results not only show that the RVEA-iGNG algorithm can effectively solve the electromagnetic launch system multi-objective optimization problem, but also show that the improved archive maintenance strategy is significantly better than the archive in the original RVEA-iGNG in terms of enhancing the diversity of solutions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electromagnetic launchers

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Zhou, Renjie Jin, Zhenming Wan, Jian Zhang, Jilin Guo, Xingyu Liu, Qiang Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou China Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education Itmo Joint Institute Hangzhou China Zhejiang University of Science and Technology School of Information and Electronic Engineering Hangzhou China Zhejiang Police College Dept. of Computer and Information Technology Hangzhou China

ISBN: (纸本)9798350304855

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user's shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods. © 2023 IEEE.

关键词： Forecasting

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On the Fifth-Order Stokes Solution for Steady Water Waves

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China Ocean Engineering 2016年第5期30卷 794-810页

作者： ZHAO Hong-jun SONG Zhi-yao LI Ling KONG Jun WANG Le-qiang YANG Jie Key Laboratory of Coastal Disasters and Defence Ministry of Education College of Harbor Coastal and Offshore Engineering Hohai University Nanjing 210098 China Key Laboratory of Virtual Geographic Environment Ministry of Education Jiangsu Key Laboratory for Numerical Simulation of Large-Scale Complex System Nanjing Normal University Nanjing 210023 China School of Engineering The University of Queensland Brisbane St Lucia QLD 4072 Australia Xiamen Branch of CCCC Third Harbor Consultants Co. Ltd. Xiamen 361005 China

This paper presents a universal fifth-order Stokes solution for steady water waves on the basis of potential theory. It uses a global perturbation parameter, considers a depth uniform current, and thus admits the flexibilities on the definition of the perturbation parameter and on the determination of the wave celerity. The universal solution can be extended to that of Chappelear （1961）, confirming the correctness for the universal theory. Furthermore, a particular fifth-order solution is obtained where the wave steepness is used as the perturbation parameter. The applicable range of this solution in shallow depth is analyzed. Comparisons with the Fourier approximated results and with the experimental measurements show that the solution is fairly suited to waves with the Ursell number not exceeding 46.7.

关键词： steady water waves universal Stokes solution fifth-order global perturbation parameter uniform current wave steepness

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Research on key Technologies of Cross-domain Guidance 8

Research on Key Technologies of Cross-domain Guidance

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8th Symposium on Novel Photoelectronic Detection Technology and Applications

作者： Guo, Xiaoyun Wu, Chengfeng Fang, Xueli Xu, Cheng Li, Hui Beijing Institute of Mechanical and Electrical Engineering Beijing China Beijing Institute of Mechanical and Electrical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Institute of Mechanical and Electrical Engineering Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

Cross-domain synergy and intelligence will become important features of future warfare. Cross-domain guidance is one of the typical forms of cross-domain synergy. It can significantly improve the ability to respond quickly to random targets and time-sensitive targets and enhance the anti-jamming ability in the case of confrontation. This article introduces the concept and winning mechanism of cross-domain guidance, analyzes the research progress of cross-domain guidance at home and abroad, combs the key technologies of cross-domain guidance, summarizes the current challenges and problems in cross-domain guidance research, and proposes development suggestions. © 2022 SPIE

关键词： Optical engineering

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key indexes identifying approach of weapon equipment system-of-systems effectiveness integrating Bayes method and dynamic grey incidence analysis model

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Journal of systems Engineering and Electronics 2024年第6期35卷 1482-1490页

作者： ZHANG Jingru FANG Zhigeng YE Feng CHEN Ding College of Economics and Management Nanjing University of Aeronautics and AstronauticsNanjing 210006China National Key Laboratory for Complex Systems Simulation Institute of System EngineeringAcademy of Military ScienceBeijing 100020China Shanghai Electro-Mechanical Engineering Institute Shanghai 201109China

Aiming at the characteristics of multi-stage and(extremely)small samples of the identification problem of key effectiveness indexes of weapon equipment system-of-systems(WESoS),a Bayesian intelligent identification and inference model for system effectiveness assessment indexes based on dynamic grey incidence is *** method uses multi-layer Bayesian techniques,makes full use of historical statistics and empirical information,and determines the Bayesian estima-tion of the incidence degree of indexes,which effectively solves the difficulties of small sample size of effectiveness indexes and difficulty in obtaining incidence rules between ***-ondly,The method quantifies the incidence relationship between evaluation indexes and combat effectiveness based on Bayesian posterior grey incidence,and then identifies key system effec-tiveness evaluation ***,the proposed method is applied to a case of screening key effectiveness indexes of a missile defensive system,and the analysis results show that the proposed method can fuse multi-moment information and extract multi-stage key indexes,and has good data extraction capability in the case of small samples.

关键词： weapon equipment system-of-systems(WESoS) effectiveness index system effectiveness key index Bayes theo-rem grey incidence analysis (extremely)small samples

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Semantic segmentation of track image based on deep neural network

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The Journal of China Universities of Posts and Telecommunications 2020年第5期27卷 23-33页

作者： Wang Zhaoying Zhou Junhua Liao Zhonghua Zhai Xiang Zhang Lianping School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Complex Product Advanced Manufacturing Kngineering Research Center Beijing Simulation CenterBeijing 100854China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China Alibaba Cloud Computing Beijing 100020China

In this paper,deep learning technology was utilited to solve the railway track recognition in intrusion detection *** railway track recognition can be viewed as semantic segmentation task which extends image processing to pixel level *** encoder-decoder architecture DeepLabv3+model was applied in this work due to its good performance in semantic segmentation *** images of the railway track collected from the video surveillance of the train cab were used as experiment dataset in this work,the following improvements were made to the *** first aspect deals with over-fitting problem due to the limited amount of training *** augmentation and transfer learning are applied consequently to rich the diversity of data and enhance model robustness during the training ***,different gradient descent methods are compared to obtain the optimal optimizer for training model *** third problem relates to data sample imbalance,cross entropy(CE)loss is replaced by focal loss(FL)to address the issue of serious imbalance between positive and negative *** of the improved DeepLabv3+model with above solutions is demonstrated by experiment results with different system parameters.

关键词： railway track recognition convolutional neural networks semantic segmentation DeepLabv3+

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