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CW-YOLO: joint learning for mask wearing detection in low-light conditions

Frontiers of computer Science 2023年第6期17卷 191-193页

作者： Mingqiang GUO Hongting SHENG Zhizheng ZHANG Ying HUANG Xueye CHEN Cunjin WANG Jiaming ZHANG School of Computer Science China University of GeosciencesWuhan 430074China National Engineering Research Center of Geographic Information System Wuhan 430074China Wuhan Zondy Cyber Technology Co.Ltd. Wuhan 430074China Shenzhen Data Management Center of Planning and Natural Resources Shenzhen 518000China Key Laboratory of Urban Land Resources Monitoring and Simulation(Ministry of Natural Resources) Shenzhen 518000China College of Engineering Boston UniversityBoston 02215USA

1 Introduction With the rapid progress of Artificial Intelligence(AI)technology in object detection and face recognition,deep learning methods for face mask wearing detection have become increasingly mature and continuously take into account the needs of efficiency and ***,these conventional detection methods mostly ignore the complexity of real-world application scenarios,such as extremely darkness and gloomy *** unfavorable conditions lead to a series of image degradations that seriously hamper machine vision *** camera parameter adjustment,auxiliary lighting,or pre-processing enhancement[1]can weaken these negative effects to some extent to promote the detection,they will also result in increased hardware and time costs.

关键词： hardware lighting weather

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Parallel Optimization of Computational Fluid Dynamics application code_saturne Based on Next Generation Sunway Supercomputer 14

Parallel Optimization of Computational Fluid Dynamics Applic...

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14th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2023

作者： Liu, Anjun Liao, Yin Xu, Xihao Chen, YanYan Zhong, Hongjun Wu, Jianming Kong, Bo Raikov, Alexander Guo, Meng Jinan Institute of Supercomputing Technology Jinan Key Laboratory of High Performance Industrial Software Jinan China Zhejiang Yuansuan Technology Co. Ltd Jinan Supercomputing-Zhejiang Yuansuan Industrial Simulation System Joint Laboratory Hangzhou China Qilu University of Technology Shandong Academy of Sciences Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Key Laboratory of Computing Power Network and Information Security China Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Shandong Jinan China

ISBN: (纸本)9798350371024

code_saturne is an open-source general large-scale computational fluid dynamics software independently developed by Electricite de France since 1997. Due to its high computing performance, code_saturne has been widely used in the nuclear industry, heavy fuel and biomass combustion, particle tracking and other computational fluid dynamics fields. In this work, we implemented code_saturne on the new generation Sunway supercomputer (SW26010pro) at the first time. By applying the data value-taking technology of double cache, combined with Sunway shared memory technology, we have adapted the data structure and Modular programming of code_saturne conducively to the new generation Sunway supercomputer (SW26010pro) and accelerated the software hotspots the software hotspots by 1-2 times. After optimizing and porting, this software has successfully served in the numerical simulation of the lateral flow of fuel assemblies in the nuclear industry. © 2023 IEEE.

关键词： Supercomputers

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Chaotic Neural Network with Nonlinear Delayed Self-feedback and applications

Chaotic Neural Network with Nonlinear Delayed Self-feedback ...

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2023 International Conference on Applied Mathematics, Modelling and Statistics application, AMMSA 2023

作者： Zhang, Yu Xu, Liuyang Xu, Yaoqun Chen, Bin Liao, Qian School of Computer and Information Engineering Harbin University of Commerce Harbin150028 China Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing Harbin150028 China Heilongjiang Cultural Big Data Theory Application Research Center Harbin150028 China Institute of System Engineering Harbin University of Commerce Harbin150028 China

We propose a novel transient chaotic neural network model with a nonlinear delayed self-feedback term, aiming to leverage its complex dynamical behavior for algorithm optimization. To avoid the influence of chance, we conduct experiments using randomly generated data and analyze the model's chaotic dynamical behavior by visualizing the stability of the neurons through inverse bifurcation diagrams and maximum Lyapunov exponent diagrams. The simulation results demonstrate the remarkable effectiveness of this new model in network optimization, with a success rate even reaching 100%, surpassing previous chaotic neural network models. Notably, in the following sections, all nonlinear terms are represented using trigonometric functions. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Traveling salesman problem

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Paired regions for shadow removal approach based on multi-features

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High Technology Letters 2023年第2期29卷 174-180页

作者：张之政 GUO Mingqiang WU Liang HUANG Ying CHEN Xueye Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034P.R.China National Engineering Research Center of Geographic Information System China University of GeosciencesWuhan 430074P.R.China School of Computer Science China University of GeosciencesWuhan 430074P.R.China Wuhan Zondy Cyber Technology Co. Ltd.Wuhan 430074P.R.China

The existence of shadow leads to the degradation of the image qualities and the defect of ground object *** removal is therefore an essential research topic in image processing *** biggest challenge of shadow removal is how to restore the content of shadow areas correctly while removing the shadow in the *** regions for shadow removal approach based on multi-features is proposed, in which shadow removal is only performed on related sunlit *** distance between regions is calculated to find the optimal paired regions with considering of multi-features(texture, gradient feature, etc.) *** in different scenes with peak signal-to-noise ratio(PSNR) and structural similarity(SSIM) evaluation indexes are chosen for *** results are shown with six existing comparison methods by visual and quantitative assessments, which verified that the proposed method shows excellent shadow removal effect, the brightness, color of the removed shadow area, and the surrounding non-shadow area can be naturally fused.

关键词： paired region feature distance texture peak signal-to-noise ratio(PSNR) structural similarity(SSIM)

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Multi-Timescale Trading Strategy for Renewable Power to Ammonia Virtual Power Plant in the Electricity, Hydrogen, and Ammonia Markets

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2023年第4期1卷 322-335页

作者： Wu, Sirui Lin, Jin Li, Jiarong Liu, Feng Song, Yonghua Xu, Yanhui Cheng, Xiang Yu, Zhipeng Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing100087 China Tsinghua University Sichuan Energy Internet Research Institute Chengdu610213 China University of Macau Department of Electrical and Computer Engineering Macau999078 China Tsinghua University Department of Electrical Engineering Beijing100087 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China

Renewablepower to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on electricity exchange with the power grid. Participating in the electricity market as a virtual power plant (VPP) may help to reduce energy costs. However, the power profile of local photovoltaics and wind turbines is similar to those in the market, resulting in rising energy costs under the conventional strategy. Hence, we develop a multi-timescale trading strategy for the RePtA VPP in the electricity, hydrogen, and ammonia markets. By utilizing the hydrogen and ammonia buffer systems, the RePtA VPP can optimally coordinate production planning. Moreover, we find it possible to describe the trading of electricity, ammonia, and hydrogen in a unified timeframe. The two-stage robust optimization model of the electricity market is extended to multiple markets and solved by the column and constraint generation (CC&G) algorithm. The case is derived from an actual project in the Inner Mongolia Autonomous Region. Sensitivity analysis demonstrates the economic advantages of the RePtA VPP joining multiple markets over the conventional strategy and reveals the necessity of the hydrogen and ammonia buffer and reactor flexibility. © 2023 IEEE.

关键词： Ammonia

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Quantitative distinction of the relative actions of climate change and human activities on vegetation evolution in the Yellow River Basin of China during 1981-2019

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Journal of Arid Land 2023年第1期15卷 91-108页

作者： LIU Yifeng GUO Bing LU Miao ZANG Wenqian YU Tao CHEN Donghua School of Civil Architectural Engineering Shandong University of TechnologyZibo 255000China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518000China Key Laboratory of National Geographic Census and Monitoring Ministry of Natural ResourcesWuhan 430072China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100101China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Agricultural Remote Sensing Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China Zhongke Langfang Institute of Spatial Information Applications Langfang 065000China College of Computer and Information Engineering Chuzhou UniversityChuzhou 239000China

Under the combined influence of climate change and human activities,vegetation ecosystem has undergone profound *** can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical ***,it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change *** on the data of climate elements(sunshine hours,precipitation and temperature),human activities(population intensity and GDP intensity)and other natural factors(altitude,slope and aspect),this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method,a trend analysis,and a gravity center model,and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector *** results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to *** 1981-2019,the temporal variation of vegetation NDVI showed an overall increasing *** gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County,Gansu Province,and the center moved northeastwards from 1981 to *** 1981-2000 and 2001-2019,the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the *** the study period(1981-2019),the dominant factors influencing vegetation NDVI shifted from natural factors to human *** results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.

关键词： vegetation evolution driving mechanisms climate change human activities relative actions Geodetector Yellow River Basin

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Nanoscale Textural and Evolution of the Carbonate Fault Mirrors: Implication for Fault Lubrication during the 2014 Ludian Earthquakes， China

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Journal of Earth Science 2025年

作者： Yang Zhou Bichuan Cai Rongwei Zhu Lin Wang Weijie Zhang Junzhi Liu Yongjian Yao Shengchang Ding Hailing Liu Yonglei Zhang Wei Liu Qingsong Liu Yiwen Ju Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance， Beijing Normal University School of National Safety and Emergency Management， Beijing Normal University Guangzhou Marine Geological Survey，China Geological Survey Centre for Marine Magnetism (CM2)， Department of Ocean Science and Engineering， Southern University of Science and Technology Guangzhou Institute of Geochemistry， Chinese Academy of Sciences South China Sea Institute of Oceanography， Chinese Academy of Sciences National Key Laboratory of Earth System Numerical Modeling and Application， College of Earth and Planetary Sciences， University of Chinese Academy of Sciences

To study the dynamic weakening processes， we conducted micro to nano scale structures and mineral composition analysis of natural carbonate fault mirrors （FMs） from the Mw 6.2 Ludian earthquake. Several 2–5 μm wide micro-slip surfaces are quickly localized to cut the previously formed shear band （<20 μm） based on microstructural observations. The R1-Riedel shears and tension fracture occurred outside the micro-slip surfaces （2–5 μm） boundaries in the low-strain domain. The strain is distributed across the initial thin shear band. In the slide process， the calcite twins experienced mechanical milling， producing wear particles with much reduced grain size. These nanoparticles are considered as the triggering ingredient for fault lubrication. Followed by the rise of temperature recorded by the magnetic minerals， the nanoparticles are welded to nano-aggregates due to frictional heating over 700 °C and accompanied by the decarbonization. We suggest that the calcite aggregates and CO2degassing may be an important precursor for friction reduction in carbonate fault during the earthquake.

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Key Techniques on Unified Identity Authentication in OpenMBEE Integration 4

Key Techniques on Unified Identity Authentication in OpenMBE...

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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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Method for constructing multi-dimensional feature map of malicious code 5

Method for constructing multi-dimensional feature map of mal...

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2020 5th International Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2020

作者： Ma, Haocong Zhang, Ji Zhou, Junhua Zhai, Xiang Xue, Junjie Ji, Hang State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing100854 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing100854 China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing100854 China

Malicious code is characterized by a large number of types, rapid increase in number, continuous update of transmission routes, and continuous enhancement of back analysis and back detection methods. Therefore, how to effectively detect and analyze malicious code has been a problem of great concern. This paper studies the features of binary file and disassembly file of malicious code, introduces the concept of information gain, and proposes a method to construct the multi-dimensional characteristic graph of malicious code. Finally, the convolutional neural network is used to classify the multi-dimensional feature graph of malicious code, which provides a new idea for the feature extraction of malicious code. © Published under licence by IOP Publishing Ltd.

关键词： Malware

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SFDE-net: A Spatial-Frequency Domain Feature Enhancement Network for Cloud Detection

SFDE-net: A Spatial-Frequency Domain Feature Enhancement Net...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Baotong Su Siyan Li Wenguang Zheng Yao Chen The School of Computer Science and Engineering Tianjin University of Technology Tianjin China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences and Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Cloud detection is a crucial step in the preprocessing of satellite remote sensing images. Existing methods tend to have misjudgments when dealing with specific scenarios, such as challenges in distinguishing thin clouds from the background and addressing missing cloud boundaries. To solve this problem, we designed a novel Spatial–Frequency Domain Feature Enhancement Block (SFDE) embedded in a U-shaped network called SFDE-net. SFDE consists of three units: the Dual Frequency Feature Unit (DFF), the Spatial Domain Feature Unit (SDF), and the Cross-Domain Feature Fusion Unit (CDF). DFF globally learns the boundaries and overall structure of clouds in the frequency domain, SDF captures fine-grained information in the spatial domain, and CDF adaptively fuses features from both DFF and SDF. Our method’s effectiveness was evaluated on two public datasets, GF-1 WFV and LandSat8. Extensive experiments demonstrated that the proposed SFDE-net achieved accurate detection accuracy and outperformed several state-of-the-art methods.

关键词： Earth Accuracy Satellites Artificial satellites Fuses Frequency-domain analysis Merging

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