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2019 International Joint Conference on Information, Media, and Engineering, IJCIME 2019

作者： Su, Zhibin Qian, Yahong Ren, Hui Lv, Chaohui Zhang, Xiaoyi Li, Weiwei Key Laboratory of Acoustic Visual Technology and Intelligent Controla System Communication University of China Ministry of Culture and Tourism School of Information and Communication Engineering Communication University of China Beijing China CITVC KEHUA CO. LTD. Technology Service Branch Beijing China

ISBN: (纸本)9781728155869

The purpose of the research on emotion classification of film and television (TV) scene images is to hope that the computer can simulate the audience's emotional perception to judge positive or negative emotional trends of the image. In this paper, from the perspective of emotional semantics, a method of the emotion classification about the film and TV scene image is proposed. Firstly, the film and TV scene image dataset were established and assessed based on the subjective evaluation experiment. Then the theory of psychology and photographic art was used to extract image emotional features. Finally, particle swarm optimization (PSO)-support vector machine (SVM) algorithm based on feature importance dimension reduction was used for building the classifier. The experimental results show that the image dataset initially established in this paper can be helpful to the subsequent study on emotion classification of the film and TV scene image, and the accuracy of the positive and negative emotion classifier on this dataset is 0.87, which conforms to audience's emotional perception of the film and TV scene image. © 2019 IEEE.

关键词： Support vector machines

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Generalized association and deep understanding method for big video data processing

Generalized association and deep understanding method for bi...

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2019 IEEE International Conferences on Ubiquitous computing and Communications and Data Science and Computational Intelligence and Smart computing, Networking and services, IUCC/DSCI/SmartCNS 2019

作者： Xu, Lin Wu, Wei Lv, Wanghan Wang, Dong Science and Technology in Information System Engineering Lab Nanjing Research Institute of Electronic Engineering Nanjing China School of Information Science and Engineering University of Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China

ISBN: (纸本)9781728152097

In Big Data Era, it is becoming more and more important to timely and efficient processing of massive videos, and mining of the value information contained in them. This paper studies chaotic compressed sensing theory and uses Long-term and short-term memory networks (LSTM) algorithm to generate a summary of the content of video behavior track. It has already to apply the proposed method in target recognition and tracking, and the recognition rate achieves more than 86%. © 2019 IEEE.

关键词： Big data

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Research on China’s technology lists for addressing climate change

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Chinese Journal of Population,Resources and Environment 2021年第2期19卷 151-161页

作者： Can Wang Jianhui Cong Ke Wang Yue Qi Wenjian Cai Yulong Li Sha Fu Wentao Wang Yuanyuan Wei Xinzhu Zheng Jiani Jiang Mingpeng Chen Wenling Liu Yongxiang Zhang Zhibing Tian Ji Chen Rui Li Haiqing Zuo School of Environment Tsinghua UniversityBeijing100084China School of Economics and Management Shanxi UniversityTaiyuan030006China School of Environment and Natural Resources Renmin University of ChinaBeijing100872China National Center for Climate Change Strategy and International Cooperation Beijing100038China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing100084China School of Management Science and Engineering Central University of Finance and EconomicsBeijing100081China AdministrativeCenter for China’s Agenda 21 Beijing100038China Beijing Technology Innovation Service Center Beijing 101101China School of Economics and Management China University of PetroleumBeijing 102249China Law School Minzu University of ChinaBeijing 100081China School of Agriculture and Rural Development Renmin University of ChinaBeijing100872China School of Management and Economics Beijing Institute of TechnologyBeijing100081China National Climate Center China Meteorological AdministrationBeijing 100081China China Energy Saving Consulting Co. LtdBeijing100142China Rocky Mountain Institute Beijing100020China School of Foreign studies Guangxi University of Science and TechnologyLiuzhou545006China

The compilation of technology lists addressing climate change has a guiding effect on promoting technological research and development,demonstration,and *** is also crucial for China to strengthen ecological civilization construction,achieve the carbon emission peak and carbon neutrality target,and enhance global climate governance *** study first proposes the existing classification outline of the technology promotion lists,technology demand lists,and future technology ***,different methodologies are integrated on the basis of the existing outline of four technology lists:China’s existing technological promotion list for addressing climate change,China’s demand list for climate change mitigation technology,China’s key technology list for addressing climate change,and China’s future technology list for addressing climate ***’s more,core technologies are analyzed in the aspects of technology maturity,carbon reduction cost,carbon reduction potential,economic benefits,social influence,uncertainty,*** results show that:key industries and sectors in China already have relatively mature mitigation/adaptation technologies to support the achievement of climate change *** multi-sectoral system of promoting climate friendly technologies has been established,which has played an active role in tackling climate ***,climate technology needs are concentrated in the traditional technology and equipment upgrading,renewable energy technology,and management decision-making support *** key technologies are concentrated in 3 major areas and 12 technological directions that urgently need a *** carbon emmission peak and nentrality,carbon depth reduction and zero carbon emissions and geoengineering technology(CDR and SRM)have played an important role in forming the structure of global emissions and achieving carbon neutrality in the ***,the uncertainty assessment for the comprehensive techno

关键词： technology for addressing climate change technology list Carbon emission peak Carbon neutrality key technology

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An HSR Data Model for Cyborg Insect Research Experiments

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Chinese Journal of Electronics 2018年第4期27卷 680-686页

作者： HONG Hui WANG Xiaoyu ZHU Zhengfei MA Qian GUAN Nan ZHENG Nenggan Key Laboratory of Radio Frequency Circuit and System Hangzhou Dianzi University Qiushi Academy for Advanced Studies Zhejiang University College of Computer Science and Technology Zhejiang University Department of Computing Hong Kong Polytechnic University

Research on cyborg intelligent insects requires the experiment platform to collect data from the distributed sensing models and process the multi-modal signals in real-time. To overcome these issues, we present a novel data model, naming as the Hybrid-synchronizedrealtime(HSR) data model, which can synchronize the hybrid raw data channels by a meta data integration method and process them with a fixed priority scheduling algorithm. Real animal experiments show that the insect-machine experiment platform based on the HSR data model can fully satisfy the requirements of cyborg intelligent insect research, especially in dealing with the technical challenges of data synchronization, real-time processing and hybrid data integration. It provides an efficient approach to implement the experiment platform and thus aid the frontier research on cyborg insects.

关键词： Cyborg intelligent insects Data model Hybrid-synchronized-realtime(HSR)

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Application of SIRUS in credit card fraud detection 1

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7th International Conference on Computational Data and Social Networks, CSoNet 2018

作者： Zhang, Yuwei Liu, Guanjun Luan, Wenjing Yan, Chungang Jiang, Changjun Department of Computer Science and Technology Tongji University Shanghai201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China

ISBN: (数字)9783030046484

ISBN: (纸本)9783030046477

Credit card fraud problem is very common in recent years. It not only causes economic loss to people, but also causes trust crisis to enterprises. Due to the imbalance of data, fraud detection has always been tricky. In our previous work, we proposed a method of dealing with the class imbalance problem based on stacking ensemble learning and inverse random undersampling method (SIRUS). First, the inverse random undersampling method is used to generate multiple data subsets from the original data set. Then we use the stacking ensemble learning method for each data subset to train several different learners (also called first-level learners), and then the results generated by each first-level learner are taken as features to train a meta learner. We apply SIRUS to detect the credit card fraud in this paper. Our dataset comes from a financial company in China. A variety of measurements such as recall, precision, accuracy, F-measure, and G-mean to illustrate the effectiveness of our method in fraud detection. © Springer Nature Switzerland AG 2018.

关键词： Learning systems

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The roles of urban buildings and vegetation in adjusting seasonal and daily air temperature 4

The roles of urban buildings and vegetation in adjusting sea...

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4th ISPRS Geospatial Week 2019

作者： Lan, Y. Huang, Z. Guo, R. Zhan, Q. Research Institute for Smart Cities School of Architecture and Urban Planning Shenzhen University Shenzhen China Shenzhen Key Laboratory of Spatial Information Smart Sensing and Services Shenzhen University China Guangdong Key Laboratory of Urban Informatics Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China School of Urban Design Wuhan University Wuhan China

Exploring the spatiotemporal patterns of the relationships between urban indicators and urban temperature is essential to improve the mitigation effectiveness when we intend to adjust built environment for moderating urban thermal environment. In this study, RS, GIS technology and statistical methods were involved to investigate the spatiotemporal patterns of the impacts of urban buildings and vegetation on Air Temperature (AT). Building Density (BD) and Normalized Difference Vegetation Index (NDVI) are the indicators for urban buildings and vegetation respectively. The objectives of this study are: 1) to determine an appropriate scale for examining the building-AT relationships and vegetation-AT relationships;2) to explore the seasonal and daily characteristics of these relationships;and 3) to compare the effects of urban buildings and vegetation. The results show that, for both summer and winter, a scale of 200–250 m is optimal for examining building-AT relationships, and 960–1020 m is the desirable scale for studying vegetation-AT relationships. Based on the optimal scales, we find that for both buildings and vegetation, they only significantly impact night-time temperature in both summer and winter. For seasonal comparison, the building-AT relationships and vegetation-AT relationships are relatively stronger in summer than in winter, which are indicated by R-square of the regression results. When comparing the effects of urban building and vegetation, we find that increasing vegetation is more effective than reduce buildings to achieve the same air temperature reduction. Our findings are conducive to generating space-time targeted Urban Heat Island (UHI) mitigation strategies. © Authors 2019.

关键词： Vegetation

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A NOMA Power Allocation Method Based on Greedy Algorithm 8th

A NOMA Power Allocation Method Based on Greedy Algorithm

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8th International Conference on Communications, Signal Processing, and systems, CSPS 2019

作者： Lu, Yin Chen, Shuai Mao, Kai Bian, Haowei Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing210003 China Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Nanjing University of Posts and Telecommunications Ministry of Education Nanjing210003 China Nanjing University of Posts and Telecommunications Nanjing210003 China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9789811394089

In the existing Non-Orthogonal Multiple Access power allocation algorithm, the iterative water-filling algorithm is a commonly used algorithm, which has good performance but high complexity. In order to reduce the complexity, this paper divides the power allocation problem of Non-Orthogonal Multiple Access into two steps. Firstly, the water-filling algorithm is used to complete the power allocation between sub-carriers, then the greedy algorithm is used to allocate power to the superimposed users in the carrier. Many elements in the candidate power allocation coefficient set that are impossible to be optimal solutions are deleted by using the sum of power distribution coefficients of each user and the product of throughput, which effectively reducing the complexity. The simulation results show that the proposed algorithm has a slightly lower performance than the iterative water injection algorithm, but it effectively reduces the complexity. The performance of the proposed algorithm is better than other traditional algorithms, and a good compromise between system performance and complexity is achieved. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Filling

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Corrigendum to “Impact of spring Tibetan Plateau snow cover on extreme precipitation in Pakistan in July and August 2022” [Atmospheric Research 295 (2023) 107007]

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Atmospheric Research 2023年 295卷

作者： Qianrong Ma Hongjia Lei Taichen Feng Rui Hu Miaomiao Niu Zhiyuan Hu Guolin Feng College of Physical Science and Technology Yangzhou University Yangzhou 225012 China Key Laboratory of Meteorological Disaster (KLME) Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD) Nanjing University of Information Science & Technology Nanjing 210044 China School of Atmospheric Sciences and Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Education Sun Yat-sen University Zhuhai 519082 China Southern Marine Science and Engineering Guangdong Laboratory Zhuhai 519082 China Shaanxi Meteorological Service Center Xian 710015 China National Climate Center Laboratory for Climate Studies China Meteorological Administration Beijing 100081 China

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Implementing the matrix multiplication with dfc on kunlun small scale computer 20

Implementing the matrix multiplication with dfc on kunlun sm...

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20th International Conference on Parallel and Distributed computing, Applications and Technologies, PDCAT 2019

作者： Du, Zheng Zhang, Jing Sha, Shihao Luo, Qiuming Department of Computer Science and Technology Tsinghua University China NHPCC/Guangdong Key Laboratory of Popular HPC Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728126166

In this paper, we demonstrate a new dataflow platform of DFC, which can handle the successive dataflow computing passes with tagged data. By implementing the matrix multiplication in DFC, we show that DFC can exploit the parallelism automatically with a much simple dataflow graph constructed by DF functions of DFC. Different from the other dataflow execution platform, DFC support multiple worker threads for one dataflow node of DF functions. By running the matrix multiplication program of DFC on Kunlun system, it was verified that DFC get a reasonable speedup for large scale computing for thread number up to 512. © 2019 IEEE.

关键词： Matrix algebra

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Transport complexity of data dissemination in large-scale online social networks 19

Transport complexity of data dissemination in large-scale on...

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2019 ACM Turing Celebration Conference - China, ACM TURC 2019

作者： Wang, Cheng Zhu, Hangyu Wang, Chaodong Zhao, Qin Zhang, Bo Key Laboratory of Embedded Systems Service Computing Ministry of Education Tongji University Shanghai China East China Branch China Academy of Information and Communications Technology Shanghai China Department of Computer Science Shanghai Normal University Tongji University Shanghai China

ISBN: (纸本)9781450371582

In this paper, we aim to measure the transport difficulty of data dissemination in online social networks (OSNs). We focus on a usual type of interest-driven social sessions in OSNs, called Social-InterestCast, under which users autonomously determine whether to view the content from their followees depending on their interest. We define the fundamental limit of transport load as a new metric, called transport complexity, i.e., the minimally required transport load for an OSN in a given carrier network. We derive the transport complexity for Social-InterestCast sessions in a large-scale OSN in the carrier network with optimal communication architecture. The results can act as the common lower bounds on transport load for Social-InterestCast in any carrier networks. To the best of our knowledge, this is the first work to measure the transport difficulty for data dissemination in OSNs by modeling session patterns with the interest-driven characteristics. © 2019 Association for computing Machinery.

关键词： Social networking (online)

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