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27th European Modeling and simulation Symposium, EMSS 2015

作者： Liu, Zhizhao Li, Wei Yang, Ming Xu, Jun Qing, Duzheng Control and Simulation Center Harbin Institute of Technology Harbin150080 China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing100854 China

ISBN: (纸本)9788897999485

In order to utilize original sampling points as many as possible to construct a Latin Hypercube Sampling (LHS), a generation algorithm of LHS is proposed. The original sampling can be an arbitrary sampling and the new sampling is a LHS strictly. As the high structure of LHS, only part of original sampling points can be used for LHS. There are several problems including how to select the reserved original sampling points and generate the new ones if necessary. Matrices are used to describe the original sampling points and the original sampling points are reserved based on an adjacent matrix. The new sampling points are generated by a subtraction rule. Numerical experiments show that the generation algorithm is effective and saves a lot of running time for simulation systems.

关键词： Geometry

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Pin-Tool based execution backtracking 13th

Pin-Tool based execution backtracking

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13th Conference on Advanced Computer Architecture, ACA 2020

作者： Wei, Shuangjian Ji, Weixing Chen, Qiurui Wang, Yizhuo Beijing Institute of Technology Beijing100081 China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing100854 China

ISBN: (纸本)9789811581342

Checkpoint/restart is a common fault tolerant technique which periodically dump state to reliable storage and restart applications after failure. Most of existing checkpoint/restart implementations only handle volatile state and lack of support for persistence state of applications. Even the algorithm specifically designed for file checkpointing may not support complex operations and some need to modify source code. This paper presents a new checkpoint technique, which use dynamic instrumentation to temporarily cache disk operations in memory, and use existing memory checkpoint tool to dump or restore process state at runtime. We show that not only can this method create regular checkpoints for both volatile and persistence state, but also has important applications in execution backtracking. © Springer Nature Singapore Pte Ltd 2020.

关键词： Cache memory

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Full Polarization Radar Target Recognition Based on Ensemble Learning Algorithm 1

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19th Chinese Intelligent systems Conference, CISC 2023

作者： Yang, Zongkai Zhao, Jingcheng Li, Yanhan Xuan, Shiyang Zhang, Ke Song, Youbin Beihang University Beijing100083 China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing100854 China

ISBN: (数字)9789819968862

ISBN: (纸本)9789819968855

The polarization characteristic of radar targets is a significant research object in the fields of radar information processing and electronic countermeasures. The study aims to identify the targets by polarization information and machine learning. Points on the Poincaré sphere represent the polarization states. With the change of incident angle and frequency, polarization properties are mapped onto the curve of the Poincaré sphere. Combination of the individual classifiers in machine learning generated the final learning model with a determined strategy. The ensemble learning classifier recognized targets by analyzing the difference of polarization curve. The results indicate that the success rate of recognizing five aircraft targets up to 95.8 %. Full polarization information and ensemble learning algorithm is effective for classification of targets. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Polarization

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Long-term effects of PM2.5 constituents on childhood attention deficit hyperactivity disorder: evidence from a large population-based study in the Pearl River Delta Region, China

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Environmental Research 2025年 277卷 121641页

作者： Zeng, Hui-Xian Meng, Wen-Jie Zeng, Qing-Guo Wei, Jing Liu, Lu-Sheng Wu, Qi-Zhen Zhao, Bin Oudin, Anna Yang, Mo Jalava, Pasi Dong, Guang-Hui Zeng, Xiao-Wen Joint International Research Laboratory of Environment and Health Ministry of Education Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment Department of Occupational and Environmental Health School of Public Health Sun Yat-sen University Guangzhou510080 China Department of Atmospheric and Oceanic Science Earth System Science Interdisciplinary Center University of Maryland College ParkMD United States State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China Department of Public Health and Clinical Medicine Umeå University Umeå Sweden Department of Environmental and Biological Science University of Eastern Finland Kuopio Finland

Background: Evidence linking fine particulate matter (PM2.5) constituents to childhood attention deficit hyperactivity disorder (ADHD) was limited. Objectives: To investigate the individual and joint effects of exposure to PM2.5 constituents on ADHD. Methods: We conducted a large population-based survey involving 110,818 school children aged 6–18 years across six cities in the Pearl River Delta region, China. The three-year average concentrations of PM2.5 constituents (black carbon (BC), organic matter (OM), sulfate, nitrate, and ammonium) were estimated using the ChinaHighAirPollutants dataset. Parents completed an ADHD checklist using the Diagnostic and Statistical Manual of Mental Disorders-IV criteria. The individual and joint associations between PM2.5 components and ADHD were estimated using generalized linear mixed models and the quantile g-computation regression model, respectively. Results: The exposure-response relationships between PM2.5 constituents and ADHD primarily exhibited a nonlinear pattern. Compared with the lowest tertile, the highest tertiles of PM2.5 and its components were linked to greater odds for ADHD (e.g., the adjusted odds ratio (OR) was 1.37 (95 % confidential interval (CI): 1.27, 1.47) for PM2.5, 1.51 (95 %CI: 1.40, 1.63) for OM, 1.29 (95 %CI: 1.20, 1.39) for BC, and 1.20 (95 %CI:1.08, 1.34) for sulfate). Similar positive associations were observed between BC and sulfate exposure and ADHD subtypes. Moreover, joint exposure to PM2.5 components was associated with ADHD (OR = 1.14, 95 % CI:1.10, 1.18), with OM and BC contributing more to the observed associations. Conclusions: These findings highlight the varying contributions of PM2.5 constituents to ADHD and underscore the importance of reducing specific PM2.5 component emissions to mitigate the burden of PM2.5-associated neurodevelopmental diseases. © 2025 Elsevier Inc.

关键词： Regression analysis

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Research on weapon system portfolio selection based on combat network modeling 11

Research on weapon system portfolio selection based on comba...

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11th Annual IEEE International systems Conference, SysCon 2017

作者： Cheng, Cheng Li, Jichao Zhao, Qingsong Jiang, Jiang Yu, Lixin Shang, Huilin College of Information System and Management National University of Defense Technology Changsha China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9781509046225

Joint operations and combat system-of-systems encounter have become major developing trends of modern warfare. Weapon system portfolio selection attracts much attention, because it is closely related to the production, deployment and operation of weapons, which is a crucial factor determining the outcome of the war. This paper presents a portfolio selection model of the weapon systems based on the combat network. Firstly, we describe the portfolio selection problem of weapon systems based on the combat network, introduce the concept of operation loop, and analyze difficulties and strategies of the optimization problem. Then on this basis, the combat network of the weapon equipment system is modeled, and the operational capability evaluation index of weapon system-of-systems based on the operational loop is constructed. Portfolio selection model based on combat network is established to maximize the combined combat capability of the weapon as an optimization target, and the capacity demand and the expense restriction as constraints. Finally, we take the missile defense system as a example to demonstrate the whole calculation process and results of the weapon system portfolio selection based on the combat network model. It shows that our proposed method can achieve a very good performance to solve weapon system portfolio selection problems. © 2017 IEEE.

关键词： system of systems

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of Computer science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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A Runtime Verification Tool for Distributed simulation systems 5th

A Runtime Verification Tool for Distributed Simulation Syst...

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5th China Conference on Intelligent Networked Things, CINT 2022

作者： Zhang, Lianyi Qing, Duzheng Zhang, Han Wang, Qingyun Laili, Yuanjun Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China Beijing Institute of Electronic System Engineering Beijing China Beihang University Beijing China

ISBN: (纸本)9789811989148

Distributed simulation systems are complex systems that may suffer from runtime uncertainty or runtime errors. The core of defect detection in distributed simulation systems is to effectively traverse the state space of communication between nodes in the system. In a distributed simulation system, simulation nodes communicate and exchange data through event requests. Different event interaction sequences constitute different states of system behavior. Therefore, an efficient traversal of the state space can be transformed into sequential control of event requests in the system. This paper mainly studies the hybrid method based on software testing and model checking to perform runtime verification of the temporal properties of distributed simulation systems. We develop the runtime verification tool TempoRV. It monitors the distributed simulation system and responds immediately when the behavior of the system violated certain temporal properties. Finally, to illustrate the effectiveness of the proposed tool, we conduct a case study to show that TempoRV provides an important guarantee for the temporal correctness of distributed simulation systems. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Software testing

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One-Dimensional Photonic Crystal Filter with Multiple Defect Layers Based on Particle Swarm Optimization 21st

One-Dimensional Photonic Crystal Filter with Multiple Defect...

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21st Asia simulation Conference, AsiaSim 2022

作者： Hao, Kaizi Du, Jian Ma, Jing Zhang, Ying Ma, Yiyuan Wan, Chen Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing100854 China North University of China Taiyuan030051 China

ISBN: (纸本)9789811991974

In this paper, the defect mode of one-dimensional photonic crystal was studied. For photonic crystal with one defect layer, the effects of refractive index and thickness of defect layer, photon period number and incident angle on defect mode were discussed. Photonic crystal structure with multiple defect layers was constructed, and multiple defect modes were obtained in the forbidden band. Based on the photonic crystal structure with two defect layers, a dual-channel narrow-band filter operating at 480 nm and 532 nm was designed. Particle swarm optimization algorithm was introduced to optimize the position and transmittance of defect modes, which mainly depended on the thickness of defect layer. The calculation results showed that the transmittance of the two defect modes reached 97.52% and 97.55%, respectively, while the full width at half maximum was only 1.0 nm and 1.8 nm. The simulation of the electric field distribution further proved the correctness of the design results. The research results had important value in the field of underwater laser communication. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Photonic crystals

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Adaptive watermark generation mechanism based on time series prediction for stream processing

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Frontiers of Computer science 2021年第6期15卷 59-73页

作者： Yang SONG Yunchun LI Hailong YANG Jun XU Zerong LUAN Wei LI Sino-German Joint Software Institute Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing 100854China College of Life Sciences and Bioengineering Beijing University of TechnologyBeijing 100083China

The data stream processing framework processes the stream data based on event-time to ensure that the request can be responded to in *** reality,streaming data usually arrives out-of-order due to factors such as network *** data stream processing framework commonly adopts the watermark mechanism to address the data *** is a special kind of data inserted into the data stream with a timestamp,which helps the framework to decide whether the data received is late and thus be *** watermark generation strategies are periodic;they cannot dynamically adjust the watermark distribution to balance the responsiveness and *** paper proposes an adaptive watermark generation mechanism based on the time series prediction model to address the above *** mechanism dynamically adjusts the frequency and timing of watermark distribution using the disordered data ratio and other lateness properties of the data stream to improve the system responsiveness while ensuring acceptable result *** implement the proposed mechanism on top of Flink and evaluate it with realworld *** experiment results show that our mechanism is superior to the existing watermark distribution strategies in terms of both system responsiveness and result accuracy.

关键词： data stream processing watermark time series based prediction dynamic adjustment

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Structure characteristic-aware pruning strategy for convolutional neural networks 21

Structure characteristic-aware pruning strategy for convolut...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data science and systems, HPCC/SmartCity/DSS 2019

作者： Zuo, Peixuan Wang, Rui Fu, Xianya Yang, Hailong Liu, Yi Zhang, Lianyi Zhang, Han Qian, Depei BeiHang University Beijing China Secience and Technology on Special System Simulation Laboratory Beijing China Beijing Simulation Center Beijing China

ISBN: (纸本)9781728120584

Convolutional Neural Networks have received considerable attention over the past few years, and they are widely used in various fields. However, the computational complexity and excessive storage space caused by over-parameterized of these networks are also being serious. This will limit further development of deep learning in resource-constrained devices such as the mobile terminal. It has been proposed that pruning is a useful method to optimize networks, whereas there is no contribution focus on utilizing the traits of the network to guide pruning. The primary purpose of this paper is to research the different effects of layers with varying depth and the different number of parameters during the pruning process. By taking advantage of the characteristics of network structure itself, we propose a new pruning strategy with three variants to effectively prune CNNs which can automatically determine the most appropriate sparsity for each conv-layer. Using iterative pruning and retraining, we evaluated our strategy on InceptionV3 and ResNet50. We analyzed our three variants and made a comparison between each other. © 2019 IEEE.

关键词： Image classification

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