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3rd International Conference on Space Information Networks, SINC 2018

作者： Liu, Chengxiang Xiong, Wei Company of Postgraduate Management Space Engineering University Beijing China Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (纸本)9789811359361

The Internet of Things brings convenience to people’s lives and it is also vulnerable to external attacks due to its own vulnerability. For this reason, analyzing the vulnerability of the Internet of Things is very necessary and meaningful. The paper starts with the characteristics of the Internet of Things and firstly constructs its network attack model. And then we simulate the attack on the model according to the attack rules. Furthermore, an experimental analysis of the nodes vulnerability is conducted by the theory of complex networks, and indicators of network characteristics are quantified based on the removal of vulnerable nodes. The experimental results show that the vulnerability of the system will show different patterns of attenuation as the proportion of node deletion increases. © 2019, Springer Nature Singapore Pte Ltd.

关键词： complex networks

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Research on Integration Framework and Service Adaptation technology of Space system simulation Test-bed

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Journal of Physics: Conference Series 2021年第1期2133卷

作者： Desheng Liu Qing Chang Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

Aiming at the requirements of space system simulation test-bed in heterogeneous integration and co-simulation, the support capability of test-bed integration framework is analysed. A space system simulation test-bed integration framework based on bridging adaptation service is constructed, and adaptation services such as protocol adaptation, information publication, information subscription and service control for service oriented architecture are designed and implemented, which provide integration capability and co-simulation management capability for heterogeneous systems, models and components of space system simulation test-bed.

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A Multi-Objective Optimization Model for simulation-based Acquisition

A Multi-Objective Optimization Model for Simulation-based Ac...

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Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Xue Zhang Junjie Xue Junhua Zhou Guoqiang Shi Yan Yu School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (数字)9781728170862

ISBN: (纸本)9781728170879

Large-scale equipment presents the characteristics of technology-intensive, knowledge-intensive and complex, which brings high investment and high risk to equipment acquisition. This paper analyzes the various components of equipment acquisition to fully apply modeling and simulation technology to each stage of it. On the basis of multi-objective optimization theory, the objective function of the lowest risk and lowest cost of simulation-based acquisition (SBA) is proposed. Then establishing a multi-objective optimization model for simulation-based acquisition according to the corresponding constraints. The nondominated sorting genetic algorithm II (NSGA II) and multi-objective particle swarm optimization (MOPSO) algorithms are used to optimize the model, and the majority voting method is used for integration. The comparison of simulation examples proves that the multi-objective optimization model oriented to SBA designed in this paper can effectively realize the optimization of each objective of SBA under cost constraints. And the feasibility and efficiency of optimization solution are guaranteed.

关键词： Analytical models Linear programming Reliability Particle swarm optimization Optimization Sorting Investment

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A location method for ground moving target with azimuth spectrum aliasing in Geosynchronous Spaceborne-Airborne Bistatic multichannel SAR

A location method for ground moving target with azimuth spec...

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Zhang, Ying Xiong, Wei Dong, Xichao Hu, Cheng Liu, Chengxiang Sun, Yang Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China School of Information and Electronics Beijing Institute of Technology Beijing China Key Laboratory of Electronic and Information Technology in Satellite Navigation Ministry of Education Beijing China

ISBN: (纸本)9781728123455

Geosynchronous Spaceborne-Airborne Bistatic multichannel SAR (GEO-SABM SAR) maintains the fine temporal sampling and wide coverage characteristics of monostatic GEO SAR. But due to the PRF of GEO platform is very low, azimuth spectrum aliasing (ASA) will occur in GEO-SABM SAR which will make a moving target divided into several sub-targets. In this paper, a location method for ground moving target with ASA has given. From the simulation results, the moving target can be discriminated and located. © 2019 IEEE.

关键词： Synthetic aperture radar

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DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

arXiv

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arXiv 2025年

作者： Zeng, Jinzhe Zhang, Duo Peng, Anyang Zhang, Xiangyu He, Sensen Wang, Yan Liu, Xinzijian Bi, Hangrui Li, Yifan Cai, Chun Zhang, Chengqian Du, Yiming Zhu, Jia-Xin Mo, Pinghui Huang, Zhengtao Zeng, Qiyu Shi, Shaochen Qin, Xuejian Yu, Zhaoxi Luo, Chenxing Ding, Ye Liu, Yun-Pei Shi, Ruosong Wang, Zhenyu Bore, Sigbjørn Løland Chang, Junhan Deng, Zhe Ding, Zhaohan Han, Siyuan Jiang, Wanrun Ke, Guolin Liu, Zhaoqing Lu, Denghui Muraoka, Koki Oliaei, Hananeh Singh, Anurag Kumar Que, Haohui Xu, Weihong Xu, Zhangmancang Zhuang, Yong-Bin Dai, Jiayu Giese, Timothy J. Jia, Weile Xu, Ben York, Darrin M. Zhang, Linfeng Wang, Han School of Artificial Intelligence and Data Science Unversity of Science and Technology of China Hefei China AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing China Baidu Inc. Beijing China Department of Computer Science University of Toronto TorontoON Canada Department of Chemistry Princeton University PrincetonNJ08540 United States University of Chinese Academy of Sciences Beijing100871 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China College of Integrated Circuits Hunan University Changsha410082 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device Integration School of Material Science and Engineering Wuhan University of Technology Wuhan430070 China College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense Technology Changsha410073 China ByteDance Research Beijing100098 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Geosciences Princeton University PrincetonNJ08544 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States IKKEM Fujian Xiamen361005 China Graduate

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications. These packages, typically built on specific machine learning frameworks such as TensorFlow, PyTorch, or JAX, face integration challenges when advanced applications demand communication across different frameworks. The previous TensorFlow-based implementation of DeePMD-kit exemplified these limitations. In this work, we introduce DeePMD-kit version 3, a significant update featuring a multi-backend framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle backends, and demonstrate the versatility of this architecture through the integration of other MLPs packages and of Differentiable Molecular Force Field. This architecture allows seamless backend switching with minimal modifications, enabling users and developers to integrate DeePMD-kit with other packages using different machine learning frameworks. This innovation facilitates the development of more complex and interoperable workflows, paving the way for broader applications of MLPs in scientific research. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecular dynamics

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Diffusion mechanism simulation of cloud manufacturing complex network based on cooperative game theory

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Journal of systems Engineering and electronics 2018年第2期29卷 321-335页

作者： GENG Chao QU Shiyou XIAO Yingying WANG Mei SHI Guoqiang LIN Tingyu XUE Junjie JIA Zhengxuan Economics and Management School Harbin Institute of Technology at Weihai Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Science and Technology on Space System Simulation Laboratory Beijing Simulation Center

Cloud manufacturing is a specific implementation form of the "Internet + manufacturing" strategy. Why and how to develop cloud manufacturing platform(CMP), however, remains the key concern of both platform operators and users. A microscopic model is proposed to investigate advantages and diffusion forces of CMP through exploration of its diffusion process and mechanism. Specifically, a three-stage basic evolution process of CMP is innovatively proposed. Then, based on this basic process, a more complex CMP evolution model has been established in virtue of complex network theory, with five diffusion forces identified. Thereafter, simulations on CMP diffusion have been conducted. The results indicate that, CMP possesses better resource utilization,user satisfaction, and enterprise utility. Results of simulation on impacts of different diffusion forces show that both the time required for CMP to reach an equilibrium state and the final network size are affected simultaneously by the five diffusion forces. All these analyses indicate that CMP could create an open online cooperation environment and turns out to be an effective implementation of the "Internet + manufacturing" strategy.

关键词： complex network cloud manufacturing innovation diffusion network effect Gale-Shapley algorithm cooperative game theory

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A Model Based Heterogeneous Data Collaboration Method

A Model Based Heterogeneous Data Collaboration Method

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IEEE International Conference on electronics and Communication Engineering (ICECE)

作者： Junjie Xue Junhua Zhou Guoqiang Shi Yanhong Jiang Bowen Wei Hongyan Quan Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Beijing Simulation Center Science and Technology on Space System Simulation Laboratory Beijing China School of Software Engineering East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (数字)9781728192581

ISBN: (纸本)9781728192598

Model based heterogeneous data collaboration is important in the integrated design and manufacturing technology. In this work, we propose a systematic method of collaborative design method for heterogeneous data sources. In our method, we use the Open Model Based Engineering Environment (OpenMBEE) to study. In our work, we setup environment and construct the integrated multi-tools achieving consistency design, and then we successfully design and implement a reasonable scheme to parameterize the model in requirement analysis and store the extracted parameters in Model Management system (MMS) for transporting to the visualization tool for further simulation. We integrate the mathematical analysis tools of MATLAB, and successfully design the interface in the tool integration, and realize the model consistency in the problem of integrating multiple tools in the design based on model center. The effectiveness of the proposed integration strategies is verified by some practical instances. That is verified that our provided study can an effective design idea for complex production.

关键词： Analytical models Collaboration Production Tools Data models Mathematical model Matlab

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Preference-based Evolutionary Many-objective Optimization for Regional Coverage Satellite Constellation Design

Preference-based Evolutionary Many-objective Optimization fo...

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作者： Minghui Xiong Wei Xiong Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing

For the satellite constellation design problem, the computational complexity of regional coverage performance evaluation has posed great difficulty to classical Pareto dominance-based algorithms discovering the entire Pareto front of the problem, while the decision makers are often interested in a limited part of it. In this paper, a preference-based manyobjective evolutionary algorithm, HMOEA-T, is utilized to solve this problem. The optimization includes two steps. The first step describes the preference information of decision maker by target region, while the second step focuses the search process on the preferred region and maintaining well convergence and diversity within the region. A visualization method is applied to intuitively analysis the performance of different methods handling the problem. Experimental results have shown the advantage of integrating preference information into the optimization process, and the comparative study with other state-of-the-art preferencebased methods(T-MOEA/D and T-NSGA-III) indicate that the proposed method can achieve competitive and better performance.

关键词： evolutoinary algorithm preference articulation constellation design many-objective optimization

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Spectral-Driven Pansharpening Using Adaptive Image Segmentation to Reduce Color Distortion

Spectral-Driven Pansharpening Using Adaptive Image Segmentat...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Jiao Jiao Xiangwu Gong Lingda Wu Xiangli Meng Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

Extraction and injection of spatial details from the panchromatic (PAN) image and preservation of the spectral characteristics of the multispectral (MS) image are the key issues in pansharpening methods, which are of great significance for the application of image interpretation and target recognition. In this paper, a spectral-driven pansharpening method in which the injection detailed coefficients are estimated over each component segmented by the adaptive K-means algorithm is proposed. The pansharpening method relies on a multi-resolution framework, generalized Laplacian pyramid (GLP) technique, which is applied for the extraction of detail image. The fused image is used as the feedback element, its distance from the original MS image is used to adjust the number of segments adaptively so as to reduce the spectral distortion. Experiments carried out on GeoEye-1 and QuickBird data sets demonstrate the efficiency and effectiveness of our proposed method.

关键词： Image segmentation Spatial resolution Satellites Estimation Nonlinear distortion

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A multi-layer network topology visualization layout based on Louvain community detection 3

A multi-layer network topology visualization layout based on...

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3rd IEEE International Conference on Data science in Cyberspace, DSC 2018

作者： Zhang, Xitao Wu, Lingda Yao, Zhonghua Yu, Shaobo Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (纸本)9781538642108

Community is one of the most important structure features of complex networks. It has important research significance for topological structure analysis, behavior prediction, cascading failure, percolation and spreading of multi-layer networks. Aiming at the problem that the existing multi-layer network visualization can't clearly show the community structure, a multi-layer network topology visualization layout based on Louvain community detection is proposed. Firstly, a complex network community discovery algorithm (Louvain) is used to perform the multi-layer network nodes at each layer and the community affiliation of the nodes is obtained at each layer;then, based on the traditional force-directed layout, the community force is added to the internal nodes of the community, so that all the nodes that belong to the same community are gathered to the community center, so as to achieve the effect of displaying the network community structure. The simulation results show that the algorithm has the characteristics of faster convergence and clearer community structure than the traditional visual layout algorithm. © 2018 IEEE.

关键词： Network topology

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