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IET International Radar Conference 2020, IET IRC 2020

作者： Zhou, Jian Pang, Chen Li, Yongzhen Wang, Xuesong State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System National University of Defense Technology Hunan Changsha410073 China College of Electronic Science and Engineering National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9781839535635

This paper aims to eliminate the polarimetric biases of V-dipole phased array antennas using lower measurement cost. We analyze the polarization characteristics of the V-dipole with the integration method. An alternate-arranged 8×8 V-dipole array is designed and simulated. Based on the analysis of mutual coupling, the polarimetric performance of the array is presented. To correct the polarimetric biases using lower measurement cost, a cluster-based method is proposed to reconstruct the array pattern. The method uses partial elements to design polarimetric correction and treats the selection of elements as a clustering problem. The results prove the method helpful to minimize the biases using limited measurement cost. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Polarimeters

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Improving the Performance of Lattice Boltzmann Method with Pipelined Algorithm on A Heterogeneous Multi-zone Processor 23rd

Improving the Performance of Lattice Boltzmann Method with...

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23rd International Conference on Parallel and Distributed Computing, Applications, and Technologies, PDCAT 2022

作者： Zhang, Qingyang Xu, Lei Chen, Rongliang Chen, Lin Chen, Xinhai Wang, Qinglin Liu, Jie Yang, Bo Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410000 China Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha410000 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9783031299261

Lattice Boltzmann method (LBM) has become a powerful method in computational fluid dynamics and has drawn more and more attention in high-performance computing due to its particulate nature and local dynamics, especially on recent multi-core or many-core platforms. This paper develops a parallel software framework for 3D LBM simulation on a heterogeneous multi-zone processor, MT-3000. An improved pipelined algorithm named Pencil-H is proposed, which can not only fully exploit the advantages of each component of MT-3000 but also overlap the time of calculation and communication. Moreover, an architecture-aware multi-level parallelization algorithm is developed to fully utilize the computational performance of MT-3000. A benchmark test is performed to verify the reliability and test the performance of the LBM code. Experimental results show that the optimized code achieves a 32.02 × speedup compared with using 16 CPU cores and achieves a performance of 286.03MLUPS which reaches 72.3% of the theoretical peak performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational fluid dynamics

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An improved functional dependency network model for information systems effectiveness analysis 2020

An improved functional dependency network model for informat...

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2020 International Conference on Wireless Communication and Sensor Networks, icWCSN 2020

作者： Luo, Aimin Yi, Shuanghui Liu, Junxian Kou, Yuxiao Gao, Lanlan Zhang, Mengmeng Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha Hunan410073 China National Key Laboratory for Complex System Simulation Beijing China Academy of Military Science of the PLA Beijing100000 China

ISBN: (纸本)9781450377638

To address the limitations of the FDNA approach, in this paper, we analyze the dependency of the receiver node on the feeder nodes as well as the impact of the node's operability level on the system effectiveness, and improve the FDNA approach. We also propose a computing method for system effectiveness based on an improved FDNA model, and conduct relevant case verification. © 2020 ACM.

关键词： Information systems

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Simplify Array Processing Loops for Efficient Program Verification

Simplify Array Processing Loops for Efficient Program Verifi...

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International Symposium on software Reliability engineering (ISSRE)

作者： Xiang Du Liangze Yin Wei Dong National University of Defense Technology Changsha China Laboratory of Software Engineering for Complex Systems

ISBN: (纸本)9781665425889

Verification of large array programs is a major challenge for current program verification techniques due to large state spaces. Traditional methods such as bounded model checking often run out of time when verifying large array programs. To overcome the state explosion problem in the analysis of array programs, this paper proposes to simplify array processing loops for efficient program verification. For each array processing loop in an array program, we present a static analysis method to obtain a simplified loop for construction of a simplified program. The property checking of the simplified program can be used to approximate the original property. To evaluate the effectiveness and soundness, we implemented a tool based on our approach and tested it on SV-COMP 2019 benchmarks. The experimental results show that our method can successfully verify most program and achieve a high precision and effectiveness.

关键词： Static analysis Model checking Benchmark testing Explosions software reliability Arrays

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Program Verification Enhanced Precise Analysis of Interrupt-Driven Program Vulnerabilities

Program Verification Enhanced Precise Analysis of Interrupt-...

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Asia-Pacific Conference on software engineering

作者： Xiang Du Liangze Yin Haining Feng Wei Dong National University of Defense Technology Changsha China Laboratory of Software Engineering for Complex Systems

ISBN: (纸本)9781665437851

Due to the non-deterministic occurring of interrupt service routines, vulnerabilities of interrupt-driven programs, such as data race and atomicity violation, are usually hard to discover. Static analysis is an effective method for vulnerability analysis of interrupt-driven programs. However, existing techniques usually produce a large number of false alarms, which limits the application of static analysis in practice. To achieve high precision in vulnerability analysis of interrupt-driven programs, this paper proposes a program verification enhanced precise analysis method. For each potential vulnerability detected by static analysis, we propose a vulnerability validation approach which employs program verification to further automatically verify its feasibility. We have implemented a prototype of our method on top of CBMC. Experimental results on both an academic benchmark and 24 real-world programs show that our method can successfully identify true vulnerabilities and achieve a high precise analysis.

关键词： Prototypes Static analysis Benchmark testing software engineering

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An Empirical Study on the Influence of Social Interactions for the Acceptance of Answers in Stack Overflow

An Empirical Study on the Influence of Social Interactions f...

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Asia-Pacific Conference on software engineering

作者： Zhang Zhang Xinjun Mao Yao Lu Shangwen Wang Jinyu Lu Key Laboratory of Software Engineering for Complex Systems Changsha China National University of Defense Technology Changsha China

ISBN: (数字)9781728195537

ISBN: (纸本)9781728195544

In knowledge-sharing communities like Stack Overflow (SO), users can post questions, give answers and choose one answer as an accepted answer. The accepted answers will be important references for users when they encounter similar questions. Essentially, posting questions and giving answers is an interactive process occurring among community users, and choosing accepted answers is actually a decision-making process involving multiple factors. Previous works examined the impact on this decision process from the user, question and answer viewpoints. Social interactions between the questioners and answerers, although being popular according to our pre-analysis, have never been considered as a factor that can influence the decisions. To fill this gap, this paper first proposes a comprehensive answer acceptance model that integrates the answer features established by social interactions as well as information of users, questions and answers. We then divide social interactions into two stages and propose a method to calculate the relationship between the questioner and the answerer by analyzing these social interactions. Finally, we investigate the influence of social interactions for the acceptance of answers by performing logistic regression analysis. The results reveal several findings: (1) social-based features explain 16.6 % of the variance explained together, indicating that social interactions have significant and important effects on the acceptance of answers; (2) social interactions that occur after the answer is posted are more influential than these occur before the answer is posted. Based on the findings, we further conduct an online study of 132 SO users, and the respondents report that social interactions have a greater impact on the acceptance of answers than other judgments of answers such as upvotes, downvotes and not accepting answers.

关键词： Analytical models Decision making Transforms Predictive models Regression analysis Logistics software engineering

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Complementary Learning system Based Intrinsic Reward in Reinforcement Learning

Complementary Learning System Based Intrinsic Reward in Rein...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zijian Gao Kele Xu Hongda Jia Tianjiao Wan Bo Ding Dawei Feng Xinjun Mao Huaimin Wang National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

Deep reinforcement learning has achieved encouraging performance in many realms. However, one of its primary challenges is the sparsity of extrinsic rewards, which is still far from solved. Complementary learning system theory suggests that effective human learning relies on two complementary learning systems utilizing short-term and long-term memories. Inspired by the fact that humans evaluate curiosity by comparing current observations with historical information, we propose a novel intrinsic reward, namely CLS-IR, which aims to address the problems caused by sparse extrinsic rewards. Specifically, we train a self-supervised predictive model with short-term and long-term memories via exponential moving averages. We employ the information gain between the two memories as the intrinsic reward, which does not incur additional training costs but leads to better exploration. To investigate the effectiveness of CLS-IR, we conduct extensive experimental evaluations; the results demonstrate that CLS-IR can achieve state-of-the-art performance on Atari games and DeepMind Control Suite.

关键词： Learning systems Training Deep learning Costs Reinforcement learning Games Signal processing

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Diversifying Message Aggregation in Multi-Agent Communication Via Normalized Tensor Nuclear Norm Regularization

Diversifying Message Aggregation in Multi-Agent Communicatio...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yuanzhao Zhai Kele Xu Bo Ding Dawei Feng Zijian Gao Huaimin Wang National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

The use of graph attention networks (GAT) in communication-enhanced multi-agent reinforcement learning (Comm-MARL) has become prevalent. While successful, GAT can lead to homogeneity in the strategies of message aggregation, which can severely limit multi-agent coordination. To address this challenge, we study the adjacency tensor of the communication graph. Then we define a new nuclear tensor rank and its convex surrogate, the normalized tensor nuclear norm to measure the homogeneity of message aggregation. Leveraging the norm, we further propose a plug-and-play regularizer on the adjacency tensor, named Normalized Tensor Nuclear Norm Regularization (NTNNR), to actively enrich the diversity of message aggregation during the training stage. NTNNR is agnostic to specific Comm-MARL algorithms and can be flexibly integrated with different graph-attention methods. Empirical results demonstrate that aggregating messages using NTNNR-enhanced GAT can improve the efficiency of the training and achieve higher asymptotic performance than existing message aggregation methods.

关键词： Training Tensors Signal processing algorithms Reinforcement learning Signal processing Acoustics Speech processing

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Progressive Diversifying Policy for Multi-Agent Reinforcement Learning

Progressive Diversifying Policy for Multi-Agent Reinforcemen...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shaoqi Sun Yuanzhao Zhai Kele Xu Dawei Feng Bo Ding National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

Multi-Agent Reinforcement Learning (MARL) has recently achieved promising performance in many collaborative decision making tasks. However, one of the main bottleneck challenges for MARL is the sparsity of the team reward, which can lead to the homogenization of agents’ behaviors. To address these issues, we propose a Progressive Diversifying Policy (PDP) algorithm in this paper. Specifically, we propose to actively amplify the diversity between agents’ policies during learning and exploit diversity as an additional intrinsic reward for MARL. Furthermore, we propose a progressive diversity boosting policy to find a better team policy. Leveraging the aforementioned improvements, our method can handle sparse team rewards and alleviate the homogeneous behaviors of agents. We conduct experiments on widely-used MARL environments and the results show that PDP can provide state-of-the-art performance while maintaining a competitive convergence speed.

关键词： Decision making Collaboration Signal processing algorithms Reinforcement learning Diversity methods Signal processing Boosting

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Theoretical models for irradiation hardening and embrittlement in nuclear structural materials:a review and perspective

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Acta Mechanica Sinica 2020年第2期36卷 397-411页

作者： Xiazi Xiao Dmitry Terentyev Haijian Chu Huiling Duan Department of Mechanics School of Civil EngineeringCentral South UniversityChangsha 410075China Structural Materials Group Institute of Nuclear Materials ScienceSCK-CEN2400 MolBelgium Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai Institute of Applied Mathematics and MechanicsSchool of Mechanics and Engineering ScienceShanghai UniversityShanghai 200444China State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China CAPT HEDPS and IFSA CollaborativeInnovation Center of MoEBIC-ESATPeking UniversityBeijing 100871China

The study of irradiation hardening and embrittlement is critically important for the development of next-generation structural materials tolerant to neutron irradiation,and could dramatically affect the approach to the design of components for advanced nuclear *** addition,a growing interest is observed in the field of research and development of irradiation-resistant *** review aims to provide an overview of the theoretical development related to irradiation hardening and embrittlement at moderate irradiation conditions achieved in recent years,which can help extend our fundamental knowledge on nuclear structural *** a general introduction to the irradiation effects on metallic materials,recent research progress covering theoretical modelling is summarized for different types of structural *** fundamental mechanisms are elucidated within a wide range of temporal and spatial *** review closes with the current understanding of irradiation hardening and embrittlement,and puts some perspectives deserving further study.

关键词： Irradiation hardening Irradiation embrittlement Theoretical models Fundamental mechanisms

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