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30th International Conference on Neural Information Processing, ICONIP 2023

作者： Yang, Tengxiao Lian, Song Jia, Qiong Hu, Chengyu Guo, Shanqing School of Cyber Science and Technology Shandong University Jinan China Beijing Institute of Computer Technology and Applications Beijing China

ISBN: (纸本)9789819981830

The significance of vulnerability detection has grown increasingly crucial due to the escalating cybersecurity threats. Investigating automated vulnerability detection techniques to avoid high false positives and false negatives is an important issue in the current software security field. In recent years, there has been a substantial focus on deep learning-based vulnerability detectors, which have achieved remarkable success. To fill the gap in multi-granularity program representation, we propose MulGraVD, a deep learning-based vulnerability detector at the function level. MulGraVD captures the continuity and structure of the programming language by considering information at word, statement, basic block, and function granularity respectively. To overcome the constraint posed by hyperparameter layers in the information aggregation process of graph neural networks, MulGraVD serially passes information from coarse to fine granularity, which facilitates the mining of vulnerability patterns. Our experimental evaluation on FFMPeg+Qemu and ReVeal datasets shows that MulGraVD significantly outperforms existing state-of-the-art methods in terms of precision, recall, and F1 score, with an average improvement of 11.62% in precision, 27.69% in recall, and 19.71% in F1 score. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Network security

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A Class of Parallel Implicit Runge-Kutta Formulas

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Journal of Systems Engineering and Electronics 1993年第4期4卷 53-63页

作者： Fei Jinggaobeijing institute of computer Application and simulation technology P.O. Box 3929, beijing 100854, China Beijing Institute of Computer Application and Simulation Technology P.O. Box 3929 Beijing 100854 China

A class of parallel implicit Runge-Kutta formulas is constructed for multiprocessor system. A family of parallel implicit two-stage fourth order Runge-Kutta formulas is given. For these formulas, the convergence is proved and the stability analysis is given. The numerical examples demonstrate that these formulas can solve an extensive class of initial value problems for the ordinary differential equations.

关键词： Multiprocessor system Parallel algorithm Ordinary differential equation Implicit Runge-Kutta formula.

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Design and implementation of virtual experiment system based on universal design 4th

Design and implementation of virtual experiment system based...

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4th International Conference on computer Engineering and Networks, CENet2014

作者： Liu, Yun Zhao, Guoan Gao, Dayong Ren, Zengxia Computer Simulation Technology Laboratory Network Education Institute Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9783319111032

This paper explores a kind of virtual-experiment system based on a universal design concept aimed at achieving the fast development of virtual experiments. This system provides a reference base for the design and development of the Internet and information products and services, which deserves further research and application. © Springer International Publishing Switzerland 2015.

关键词： Product design

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A Class of Parallel Runge-Kutta Methods for Differential-Algebraic Systems of Index 2

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Journal of Systems Engineering and Electronics 1999年第3期10卷 64-75页

作者： Fei Jinggao(beijing institute of computer Application and simulation technology, 100854, P. R. China) Beijing Institute of Computer Application and Simulation Technology 100854 P. R. China

A class of parallel Runge-Kutta Methods for differential-algebraic equations of index 2are constructed for multiprocessor system. This paper gives the order conditions and investigatesthe convergence theory for such m... 详细信息

关键词： Multiprocessor system Parallel algorithm Runges-Kutta method Differential-algebraic system

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A Class of Real-Time Parallel Combined Methods ofDigital simulation for Large Systems

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Journal of Systems Engineering and Electronics 2000年第2期11卷 25-31页

作者： Liu Degui & Chen Lirong(beijing institute of computer Application and simulation technology, 100854, P. R. China) Beijing Institute of Computer Application and Simulation Technology 100854 P. R. China

In this paper, a class of real-time parallel combined methods (RTPCM) of the digital simulation for a partitioned large system is presented. By means of combination of the parallelism across the system with the parallelism across the method, stiff and non-stiff subsystems are solved in parallel on parallel computer by a parallel Rosenbrock method and a parallel RK method, respectively. Their construction, convergence and numerical stability are discussed, and the digitalsimulation experiments are conducted.

关键词： Large system Real-time parallel combined method Parallel computer

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Real-time adversarial GAN-based abnormal crowd behavior detection

Real-time adversarial GAN-based abnormal crowd behavior dete...

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作者： Han, Qiulei Wang, Haofeng Yang, Lin Wu, Min Kou, Jinqiao Du, Qinsheng Li, Nianfeng School of Computer Science Changchun University Changchun130022 China Beijing Institute of Computer Technology and Applications Beijing110000 China

Detecting abnormal events in the crowd is a challenging problem. Insufficient samples make those traditional model-based methods cannot cope with sophisticated anomaly monitoring. Therefore, we design a real-time generative adversarial network plus an add-on encoder to deal with the continually changing environment. After the generator reconstructs the compressed pattern to generate the design to the latent vector, a discriminator is used to construct better videos by minimizing the adversarial loss function. We calculated the abnormal score by the distance between the two underlying patterns encoded by the first and the second encoders. The unusual event is detected when the anomaly score is above the threshold. To accelerate the processing efficiency, we introduced the grouped pointwise convolution method to decrease the computing complexity. The frame-level and video-level experiments on the benchmark dataset show the accuracy and reliance of our approach. The acceleration approach can increase the efficiency of the network with only limited accuracy loss. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Convolution

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Spectrum analysis of the stream cipher

Spectrum analysis of the stream cipher

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2013 International Conference on Vehicle and Mechanical Engineering and Information technology, VMEIT 2013

作者： Lin, Dai Mao Li, Xin Zhang, Lei Beijing Institute of Electronic Applications Technology Beijing 100091 China National Computer network Emergency Response technical Team/Coordination of China Beijing 100029 China Beijing Institute of Electronic Applications Technology Beijing 100091 China

ISBN: (纸本)9783037858202

Classical cryptography theory holds that the true random sequence is better than any pseudorandom sequence on the security of stream cipher. So people prefer the pseudorandom sequence with long-period to the pseudorandom sequence with short-period. In this paper, it is proved through power spectrum analysis that the pseudorandom sequence with long-period can't effectively conceal message characteristics in frequency-domain. To combine the pseudorandom sequences with long cycle and short cycle may be the better encryption key. © (2013) Trans Tech Publications, Switzerland.

关键词： Spectrum analysis

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The attitude control optimization of small rocket 12

The attitude control optimization of small rocket

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12th Asia Conference on Mechanical and Aerospace Engineering, ACMAE 2021

作者： Ni, Runfeng Wen, Chunyu Jia, Linhai Zhang, Yao Liu, Shiyu School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China Beijing Institute of Computer Technology and Applications Beijing100854 China

In this article, an optimization method for attitude calculation and vector control of small rocket is proposed, which reduces the performance requirements and costs of gyroscopes. Dynamic model parameters such as engine thrust curve and rocket body moment of inertia are added to the traditional filtering and control algorithm, which can reduce the hardware performance requirements of sensors and the cost of rocket control system. This method has achieved good results in the test, and is of great significance for the promotion of small rockets. © Published under licence by IOP Publishing Ltd.

关键词： Rockets

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Method for Processing Graph Degeneracy in Dynamic Geometry Based on Domain Design

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Journal of computer Science & technology 2021年第4期36卷 910-921页

作者： Hao Guan Yong-Sheng Rao Jing-Zhong Zhang Sheng Cao Xiao-Lin Qin Institute of Computing Science and Technology Guangzhou UniversityGuangzhou 510006China Chengdu Institute of Computer Applications Chinese Academy of SciencesChengdu 610041China University of Chinese Academy of Sciences Beijing 100049China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 61173China

A dynamic geometry system,as an important application in the field of geometric constraint solving,is widely used in elementary mathematics education;moreover,the dynamic geometry system is also a fundamental environment for automated theorem proving in *** a geometric constraint solving process,a situation involving a critical point is often encountered,and geometric element degeneracy may occur at this ***,the degeneracy situation must be substantively focused on during the learning and exploration ***,many degeneracy situations cannot be completely presented even by the well-known dynamic geometry *** this paper,the mechanisms causing the degeneracy of a geometric element are analyzed,and relevant definitions and formalized descriptions for the problem are provided according to the relevant modern Euclidean geometry *** solve the problem,the data structure is optimized,and a domain model design for the geometric element and the constraint relationships thereof in the dynamic geometry system are formed;furthermore,an update algorithm for the element is proposed based on the novel domain *** addition,instances show that the proposed domain model and the update algorithm can effectively cope with the geometric element degeneracy situations in the geometric constraint solving process,thereby achieving unification of the dynamic geometry drawing and the geometric intuition of the user.

关键词： dynamic geometry critical point degeneracy domain model

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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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