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Robotics, Intelligent Control and Artificial Intelligence (RICAI), International Conference on

作者： Liliang Zhou Huaming Ran Rongling Xiong Ruijie Tan National Key Laboratory of Complex Aviation System Simulation Chengdu China The 10th Research Institute of China Electronics Technology Group Corporation Chengdu China School of Mathematics Southwest Jiaotong University Chengdu China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

Target detection technology is vital in modern social management and urban security, with small target detection— accurately identifying tiny objects in large scenes—posing a key challenge for improving surveillance system accuracy and real-time performance. The YOLO series is still the mainstream target detection model, for the YOLOv5 model, as the IoU metric it adopts still uses the geometrical overlap of the detection frame as the basis of the loss calculation, while the experiments have proved that this metric is unable to effectively utilize the small-scale characteristics of small targets. Therefore, improving the loss metric in the existing framework can help the model to pay more attention to the spatial semantic features of small targets in the image in the training phase of the network, respectively, and thus improve the detection effect. In this paper, we propose the NWD-YOLOv5 model, i.e., we introduce the NWD loss that measures the difference in the distribution of the detection frames for the existing target detection framework YOLOv5, which ensures that the loss of the small targets is not neglected in the calculation of the forward propagation loss of the model, and we purposefully modify the structure of the feature extraction network in the original framework by adding a feature extraction layer for the detection of the small targets, which enhances the ability of the model to capture the subtle features thus improving the accuracy of small target detection. Through comparative experiments, we evaluated the detection performance of the original YOLOv5 model, the YOLOv5 model using only the NWD loss, the YOLOv5 model with only the additional small-target detection layer, and the full NWD-YOLOv5 model for small-targeted human bodies on the screened COCO2017 public dataset, respectively. The experimental results show that compared to the original YOLOv5 model, the model with only the NWD loss improves the mAP@.5 metrics on small-target detection by 16

关键词： YOLO Training Analytical models Accuracy Surveillance Semantics Feature extraction Propagation losses Loss measurement Security

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Reliability Assessment of LCC-HVDC links Using Protection Devices

Reliability Assessment of LCC-HVDC links Using Protection De...

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Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition (ICRSEtoSET), International Conference on

作者： Abdelhadi Hameurlaine Larbi Boukezzi Salah Karef Haouari Sayah Laboratory of Applied Automation & Industrial Diagnostics University of Djelfa Djelfa Algeria Materials Science and Informatics Laboratory MSIL University of Djelfa Djelfa Algeria Com Laboratory of Modeling Optimization and Simulation of Real Complex Systems University of Djelfa Djelfa Algeria Intelligent Control and Electrical Power System Laboratory University of SidiBel-Abbes SidiBel-Abbes Algeria

ISBN: (数字)9798350346336

ISBN: (纸本)9798350346343

the DC/AC interaction and the presence of the high nonlinearity in the HVDC links, these problems needs to examine the behavior of the system in steady-state and transient conditions in order to define the great role of protection functions and control parameters. Furthermore, Control and protection systems are a vital part of an HVDC system to guarantee the safety, reliability, and stability of its operation. This research aim is to provide the solutions for control and protection problems that can occur in HVDC link. In this paper, we study how we mitigate this serious malfunction of commutation failure process in the operation of HVDC converters. Indeed some protection functions like the commutation failure prevention. Furthermore, HVDC transmission systems are vulnerable to DC faults and its protection becomes ever more important with the fast growth in the number of installations. Finally, the dynamics of the studied power system including the HVDC link is thoroughly investigated through various simulation scenarios.

关键词： Performance evaluation HVDC transmission Power system dynamics Power system stability Stability analysis Power system reliability Steady-state

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ActivityNet-QA: A dataset for understanding complex web videos via question answering

arXiv

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arXiv 2019年

作者： Yu, Zhou Xu, Dejing Yu, Jun Yu, Ting Zhao, Zhou Zhuang, Yueting Tao, Dacheng Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China College of Computer Science Zhejiang University Hangzhou China UBTECH Sydney AI Centre SIT FEIT University of Sydney Australia

Recent developments in modeling language and vision have been successfully applied to image question answering. It is both crucial and natural to extend this research direction to the video domain for video question answering (VideoQA). Compared to the image domain where large scale and fully annotated benchmark datasets exists, VideoQA datasets are limited to small scale and are automatically generated, etc. These limitations restrict their applicability in practice. Here we introduce ActivityNet-QA, a fully annotated and large scale VideoQA dataset. The dataset consists of 58,000 QA pairs on 5,800 complex web videos derived from the popular ActivityNet dataset. We present a statistical analysis of our ActivityNet-QA dataset and conduct extensive experiments on it by comparing existing VideoQA baselines. Moreover, we explore various video representation strategies to improve VideoQA performance, especially for long videos. The dataset is available at https://***/MILVLG/ activitynet-qa. Copyright © 2019, The Authors. All rights reserved.

关键词： modeling languages

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Privacy Setting Recommendation for Image Sharing

Privacy Setting Recommendation for Image Sharing

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International Conference on Machine Learning and Applications (ICMLA)

作者： Jun Yu Zhenzhong Kuang Zhou Yu Dan Lin Jianping Fan Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China Dept. of Computer Science Missouri University of S & T Rolla MO USA Dept. of Computer Science UNC-Charlotte Charlotte NC USA

This paper aims to simultaneously consider two inseparable issues for privacy setting recommendation: (1) sensitiveness of visual content of the images being shared; and (2) trustworthiness of users being granted. First, an object-based approach is developed for image content sensitiveness (privacy) representation. Secondly, the users on a social network are clustered into a set of representative social groups to generate a discriminative dictionary for user trustworthiness characterization. Finally, a tree classifier is trained hierarchically to recommend appropriate privacy settings for image sharing.

关键词： Privacy Social groups Visualization Object recognition Social network services Dictionaries Training

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Scalability Evaluation of Big Data Processing Services in Clouds 1st

Scalability Evaluation of Big Data Processing Services in Cl...

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1st International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018

作者： Zhou, Xin Jiang, Congfeng Qiu, Yeliang Fan, Tiantian Wang, Yumei Zhang, Liangbin Wan, Jian Shi, Weisong Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou310037 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310037 China College of Big Data and Software Engineering Zhejiang Wanli University Ningbo China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China Department of Computer Science Wayne State University DetroitMI48202 United States

ISBN: (纸本)9783030328122

Currently, many cloud providers deploy their big data processing systems as cloud services, which helps users conveniently manage and process their data in clouds. Among different service providers’ big data processing services, how to evaluate and compare their scalability is an interesting and challenging work. Most traditional benchmark tools focus on performance evaluation of big data processing systems, such as aggregated throughput and IOPS, but fail to conduct a quantitative analysis of their scalability. In this paper, we propose a measurement methodology to quantify the scalability of big data processing services, which makes the cloud services scalability comparable. We conduct a group of comparative experiments on AliCloud E-MapReduce and Baidu MRS, and collect their respective scalability characteristics under Hadoop and Spark workloads. The scalability characteristics observed in our work could help cloud users choose the best cloud service platform to set up an optimized big data processing system to achieve their specific goals more successfully. © 2019, Springer Nature Switzerland AG.

关键词： Big data

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on the Tibetan Plateau

SSRN

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SSRN 2025年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Department of Geography Faculty of Arts and Sciences Beijing Normal University Zhuhai519087 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Geography South China Normal University Shipai Campus Guangzhou510631 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Study region: The Tibetan Plateau in China, the Third Pole of the *** focus: Accurate descriptions of spatial variation in evapotranspiration (ET) and its components on the Tibetan Plateau (TP) are crucial for understanding the dynamics of the regional water cycle and energy balance. However, how various environmental factors affect ET and its components remains unclear. This study addresses this gap using observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and underlying *** hydrological insights for the region: The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory model performance with an average R² of 0.75. The ratio of transpiration to ET was generally higher in alpine meadows (0.55) than alpine steppes (0.39). Across the TP, precipitation and the leaf area index together shaped spatial variation in ET and transpiration. Precipitation emerged as the primary driver of interannual variation in ET, while the leaf area index strongly regulated the proportion of ET accounted for by transpiration. Furthermore, above aridity index values of 0.73, grassland ecosystems transitioned from water to energy. This finding is significant as it challenges the common application of an aridity index value of 0.65 to distinguish arid from humid regions. It suggests that TP grasslands, with an AI of 0.65-0.73, remain primarily water-limited. © 2025, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Power Characterization of Memory Intensive Applications: Analysis and Implications 1st

Power Characterization of Memory Intensive Applications: Ana...

引用

1st International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018

作者： Qiu, Yeliang Jiang, Congfeng Fan, Tiantian Wang, Yumei Zhang, Liangbin Wan, Jian Shi, Weisong Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou310037 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310037 China College of Big Data and Software Engineering Zhejiang Wanli University Ningbo China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China Department of Computer Science Wayne State University DetroitMI48202 United States

ISBN: (纸本)9783030328122

DRAM is a significant source of server power consumption especially when the server runs memory intensive applications. Current power aware scheduling assumes that DRAM is as energy proportional as other components. However, the non-energy proportionality of DRAM significantly affects the power and energy consumption of the whole server system when running memory intensive applications. Thus good knowledge of server power characterization under memory intensive workloads can help better workload placement with power reduction. In this paper, we investigate the power characteristics of memory intensive applications on real rack servers of different generations. Through comprehensive analysis we find that (1) Server power consumption changes with workload intensity and concurrent execution threads. However, fully utilized memory systems are not the most energy efficient. (2) Powered memory modules of installed memory capacity, i.e. the memory capacity per processor core has significant impact on the application’s performance and server power consumption even if the memory system is not fully utilized. (3) Memory utilization is not always a good indicator for server power consumption when it is running memory intensive applications. Our experiments show that hardware configuration, workload types, as well as concurrently running threads have significant impact on a server’s energy efficiency when running memory intensive applications. Our findings presented in this paper provide useful insights and guidance to system designers, as well as data center operators for energy efficiency aware job scheduling and power reductions. © 2019, Springer Nature Switzerland AG.

关键词： Energy efficiency

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Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multiple Data Sources

arXiv

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arXiv 2021年

作者： Geng, Guannan Xiao, Qingyang Liu, Shigan Liu, Xiaodong Cheng, Jing Zheng, Yixuan Tong, Dan Zheng, Bo Peng, Yiran Huang, Xiaomeng He, Kebin Zhang, Qiang State Key Joint Laboratory of Environment 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 Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System Science Tsinghua University Beijing100084 China Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental Planning Beijing100012 China Institute of Environment and Ecology Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China

Air pollution has altered the Earth’s radiation balance, disturbed the ecosystem and increased human morbidity and mortality. Accordingly, a full-coverage high-resolution air pollutant dataset with timely updates and historical long-term records is essential to support both research and environmental management. Here, for the first time, we develop a near real-time air pollutant database known as Tracking Air Pollution in China (TAP, http://***/) that combines information from multiple data sources, including ground measurements, satellite retrievals, dynamically updated emission inventories, operational chemical transport model simulations and other ancillary data. Daily full-coverage PM2.5 data at a spatial resolution of 10 km is our first near real-time product. The TAP PM2.5 is estimated based on a two-stage machine learning model coupled with the synthetic minority oversampling technique and a tree-based gap-filling method. Our model has an averaged out-of-bag cross-validation R2 of 0.83 for different years, which is comparable to those of other studies, but improves its performance at high pollution levels and fills the gaps in missing AOD on daily scale. The full coverage and near real-time updates of the daily PM2.5 data allow us to track the day-to-day variations in PM2.5 concentrations over China in a timely manner. The long-term records of PM2.5 data since 2000 will also support policy assessments and health impact studies. The TAP PM2.5 data are publicly available through our website for sharing with the research and policy communities. © 2021, CC BY.

关键词： Air pollution

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Toward activity mapping for Artifact-Centric business process

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International Journal of u- and e- Service, Science and Technology 2016年第6期9卷 421-432页

作者： Yin, Yuyu Zhu, Zhengshuang Gao, Min Song, Aihua College of Electrical Engineering Zhejiang University HangzhouZhejiang310027 China School of Computer Science and Technology Hangzhou Dianzi University HangzhouZhejiang310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education HangzhouZhejiang310018 China

The existing method of task mapping between process models is mostly based on the similarity of labels to get the similarity between tasks, which is affected by a single factor and easy to cause errors. This paper proposes a task mapping method for Artifact-Centric business process analyzes the data operation in business process execution. At first we add the description of data operation to EZ-Flow model. Secondly select the similar artifact attributes of the two business artifact by whole artifacts similarity calculation and based them to calculate two tasks’ similarity by label similarity, artifact operation similarity and context similarity calculations. Finally, the task mapping comes from the optimal selection of tasks’ similarities. Experimental results verify the effectiveness of the method, and show that the method reflects the data operation characteristics of business process model, as artifact task mapping of the process model provides a feasible method. © 2016 SERSC.

关键词： Mapping

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Theoretical analysis and simulation of phase separation in a driven bidirectional two-lane system

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Physical Review E 2019年第3期100卷 032133-032133页

作者： Qing-Yi Hao Rui Jiang Mao-Bin Hu Yunxin Zhang Chao-Yun Wu Ning Guo Key Laboratory of Modeling Simulation and Control of Complex Ecosystem in Dabie Mountains of Anhui Higher Education Institutes School of Mathematics and Computational Science Anqing Normal University Anqing 246133 China School of Mathematical Sciences Fudan University Shanghai 200433 China MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Beijing 100044 China School of Engineering Science University of Science and Technology of China Hefei 230026 China School of Automotive and Transportation Engineering Hefei University of Technology Hefei 230009 China

The two-lane driven system is a type of important model to research some transport systems, and also a powerful tool to investigate properties of nonequilibrium state systems. This paper presents a driven bidirectional two-lane model. The dynamic characteristics of the model with periodic boundary are investigated by Monte Carlo simulation, simple mean field, and cluster mean field methods, respectively. By simulations, phase separations are observed in the system with some values of model parameters. When the phase separation does not occur, cluster mean field results are in good agreement with simulation results. According to the cluster mean field analysis and simulations, a conjecture about the condition that the phase separation happens is proposed. Based on the conjecture, the phase boundary distinguishing phase separation state and homogeneous state is determined, and a corresponding phase diagram is drawn. The conjecture is validated through observing directly the spatiotemporal diagram and investigating the coarsening process of the system by simulation, and a possible mechanism causing the phase separation is also discussed. These outcomes maybe contribute to understand deeply transport systems including the congestion and efficiency of the transport, and enrich explorations of nonequilibrium state systems.

关键词： Dynamical phase transitions Phase diagrams Phase separation Phase transitions Transport phenomena

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