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Corrigendum to Anthropogenic emission inventories in China: a review

National Science Review 2018年第4期5卷 603-603页

作者： Meng Li Huan Liu Guannan Geng Chaopeng Hong Fei Liu Yu Song Dan Tong Bo Zheng Hongyang Cui Hanyang Man Qiang Zhang Kebin He Ministry of Education Key Laboratory for Earth System Modeling Department for Earth System Science Tsinghua University Max-Planck Institute for Chemistry State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University State Key Joint Laboratory of Environmental Simulation and Pollution Control Department of Environmental Science Peking University

In the Figure 4 of‘Anthropogenic emission inventories in China:a review’(National Science Review,Volume 4,Issue 6,2017,Pages 834–866,doi:10.1093/nsr/nwx150),the data for the MEIC v1.2 was incorrectly *** corrected ... 详细信息

关键词： a review Figure Corrigendum to Anthropogenic emission inventories in China

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Evaluating environmental tax rates for power plants in BTH area based on marginal damage estimation: An Integrated Assessment

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Energy Procedia 2019年 158卷 3923-3929页

作者： Shihui Zhang Robert Mendelsohn Can Wang Wenjia Cai State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC) and School of Environment Tsinghua University Beijing 100084 China School of Forestry and Environmental Studies Yale University 205 Prospect Street New Haven CT 06511 USA Ministry of Education Key Laboratory for Earth System Modeling and Center for Earth System Science Room S925 Meng Minwei Science Building Tsinghua University Beijing 100084 China

As China started to collect environmental tax on pollutant emitters, local governments were given autonomy to set tax rates that reflects regional differences to increase the policy efficiency. Previous studies have argued for efficient environmental regulations that equate the marginal damage of pollution to marginal abatement costs across space. Nevertheless, barely no study in China has estimated the source-specific marginal damages, preventing regulators from considering efficient environmental taxing regimes that exhibit spatial heterogeneity. Therefore, this paper measures the marginal health damage of air pollutant emissions from coal-fired power plants in BTH area (Beijing-Tianjin-Hebei area, which will be referred to as BTH area in the following text) using a sophisticated integrated assessment model. The results show that marginal damages varies a great deal across space: the range between the lowest and highest emission source is $1999 to $31185 per ton for SO2, $283 to $4416 per ton for NOx and $2102 - $131886 per ton for PM2.5, respectively. The marginal damages are driven by proximity to highly populated areas and meteorological conditions, which means coal-fired power plants located in downtown areas and upwind of highly populated areas have larger marginal damages than other sources. Then based on the marginal damage estimation, the relative taxing ratios are calculated. In this way, his study provides a marginal pollution damage evaluation approach that builds the base for efficient source-specific environmental taxing regimes that reflects spatial variation.

关键词： Integrated Assessment health impacts air pollution environmental tax marginal damage

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Research on Active Participation of Distributed Photovoltsics in Power Grid Primary Frequency Control Strategy

SSRN

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SSRN 2024年

作者： Zhang, Runtao Wang, Lei Zeng, Siming Cheng, Ziwei Su, Can Li, Zhiwei Zhang, Hao State Grid Hebei Electric Power Research Institute Shijiazhuang China Hebei Key Laboratory of Simulation Modeling and Control for Energy Internet Shijiazhuang China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding071003 China

Distributed photovoltaic systems can actively contribute to the primary frequency regulation of the power grid by reserving capacity. Traditional power reduction methods often employ fixed load reduction ratios, potentially resulting in inadequate frequency regulation capacity and unnecessary reserve power. This paper centers on optimizing power reserve control, starting with the construction of a two-stage model for a photovoltaic grid-connected inverter power generation system. It includes the design of a maximum power estimation method and the implementation of photovoltaic power reduction operation. The article proposes a strategy to utilize photovoltaic backup capacity for achieving primary frequency modulation effects in a short time scale. Additionally, it adopts a variable power reserve ratio operation strategy over the long term, aiming to enhance photovoltaic power generation and optimize solar energy utilization without compromising the grid's frequency and quality. Finally, a MATLAB/Simulink model is developed to validate the effectiveness of the control strategy. simulation results indicate that the proposed strategy satisfies frequency regulation requirements, enhances power generation efficiency, and improves the economic viability of photovoltaic operations. © 2024, The Authors. All rights reserved.

关键词： Frequency modulation

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NWD-YOLOv5: A YOLOv5 Model for Small Target Detection Based on NWD Loss

NWD-YOLOv5: A YOLOv5 Model for Small Target Detection Based ...

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

Power Characterization of Memory Intensive Applications: Ana...

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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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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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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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