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Survey on Fake Information Generation,Dissemination and Detection

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Chinese Journal of Electronics 2024年第3期33卷 573-583页

作者： Wanqiu CUI Dawei WANG Na HAN School of national Security People's Public Security University of China big data center of The Ministry of Public Security

The current booming development of the Internet has put the public in an era of information overload,in which false information is mixed and spread unscrupulously.This phenomenon has seriously disturbed the social network order.Thus,a substantial amount of research is beginning to be devoted to the effective management of fake information.We analyze the abnormal characteristics of fake information from its mechanism of generation and dissemination.In view of different exceptional features,we systematically sort out and evaluate the existing studies on false content detection.The commonly used public datasets,metrics,and performance are categorized and compared,hoping to provide a basis and guidance for related research.The study found that the current active social platforms show different novelty.The future direction should point to mining platform features of multi-domain sources,multi-data forms,and multi-language heterogeneity to provide more valuable clues for fake information.

关键词： Fake information Abnormal characteristics Detection methods Public datasets

Media Power Measuring via Emotional Contagion

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Journal of Social computing 2024年第1期5卷 15-35页

作者： Xue Lin Hong Huang Zongya Li Hai Jin national Engineering Research center for big data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China School of Journalism Huazhong University of Science and TechnologyWuhan 430074China

Media power,the impact that media have on public opinion and perspectives,plays a significant role in maintaining internal stability,exerting external influence,and shaping international dynamics for nations/regions.However,prior research has primarily concentrated on news content and reporting time,resulting in limitations in evaluating media power.To more accurately assess media power,we use news content,news reporting time,and news emotion simultaneously to explore the emotional contagion between media.We use emotional contagion to measure the mutual influence between media and regard the media with greater impact as having stronger media power.We propose a framework called Measuring Media Power via Emotional Contagion(MMPEC)to capture emotional contagion among media,enabling a more accurate assessment of media power at the media and national/regional levels.MMPEC also interprets experimental results through correlation and causality analyses,ensuring explainability.Case analyses confirm the higher accuracy of MMPEC compared to other baseline models,as demonstrated in the context of COVID-19-related news,yielding compelling and interesting insights.

关键词： explainability media power emotional contagion

A Distributed computing Algorithm for Electricity Carbon Emission Flow and Carbon Emission Intensity

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Protection and Control of Modern Power Systems 2024年第2期9卷 138-146页

作者： Xingping Wu Wei Yang Ning Zhang Chunlei Zhou Jinwei Song Chongqing Kang big data center of China Network Chinese Society of Electrical Engineering State Network big data center Department of Electrical Engineering Tsinghua UniversityBeijingChina 不详 big data center State Grid Corporation of ChinaBeijing 100052China Department of Electrical Engi-neering Tsinghua UniversityBeijingChina

The calculation of the indirect carbon emis-sion is essential for power system policy making,carbon market development,and power grid planning.The em-bedded carbon emissions of the electricity system are commonly calculated by carbon emission flow theory.However,the calculation procedure is time-consuming,especially for a country with 500-1000 thousand nodes,making it challenging to obtain nationwide carbon emis-sions intensity precisely.Additionally,the calculation procedure requires to gather all the grid data with high classified levels from different power grid companies,which can prevent data sharing and cooperation among different companies.This paper proposes a distributed computing algorithm for indirect carbon emission that can reduce the time consumption and provide privacy protection.The core idea is to utilize the sparsity of the nodes’flow matrix of the nationwide grid to partition the computing procedure into parallel sub-procedures exe-cuted in multiple terminals.The flow and structure data of the regional grid are transformed irreversibly for pri-vacy protection,when transmitted between terminals.A 1-master-and-N-slave layout is adopted to verify the method.This algorithm is suitable for large grid compa-nies with headquarter and branches in provinces,such as the State Grid Corporation of China.

关键词： Carbon emission flow cooperative computing carbon emission intensity matrix block par-tition power flow tracing parallel computing privacy protection

Minimal Context-Switching data Race Detection with dataflow Tracking

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Journal of Computer Science & Technology 2024年第1期39卷 211-226页

作者：郑龙李洋辛杰刘海峰郑然廖小飞金海 national Engineering Research center for big data Technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services computing Technology and System Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Cluster and Grid computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

data race is one of the most important concurrent anomalies in multi-threaded programs.Emerging con-straint-based techniques are leveraged into race detection,which is able to find all the races that can be found by any oth-er sound race detector.However,this constraint-based approach has serious limitations on helping programmers analyze and understand data races.First,it may report a large number of false positives due to the unrecognized dataflow propa-gation of the program.Second,it recommends a wide range of thread context switches to schedule the reported race(in-cluding the false one)whenever this race is exposed during the constraint-solving process.This ad hoc recommendation imposes too many context switches,which complicates the data race analysis.To address these two limitations in the state-of-the-art constraint-based race detection,this paper proposes DFTracker,an improved constraint-based race detec-tor to recommend each data race with minimal thread context switches.Specifically,we reduce the false positives by ana-lyzing and tracking the dataflow in the program.By this means,DFTracker thus reduces the unnecessary analysis of false race schedules.We further propose a novel algorithm to recommend an effective race schedule with minimal thread con-text switches for each data race.Our experimental results on the real applications demonstrate that 1)without removing any true data race,DFTracker effectively prunes false positives by 68%in comparison with the state-of-the-art constraint-based race detector;2)DFTracker recommends as low as 2.6-8.3(4.7 on average)thread context switches per data race in the real world,which is 81.6%fewer context switches per data race than the state-of-the-art constraint based race detec-tor.Therefore,DFTracker can be used as an effective tool to understand the data race for programmers.

关键词： data race satisfiability modulo theory multi-threaded program dynamic detection

Federated Dynamic Client Selection for Fairness Guarantee in Heterogeneous Edge computing

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Journal of Computer Science & Technology 2024年第1期39卷 139-158页

作者：毛莺池沈莉娟吴俊平萍吴杰 Key Laboratory of Water big data Technology of Ministry of Water Resources Hohai UniversityNanjing 211100China College of Computer and Information Hohai UniversityNanjing 211100China center of Networked computing Temple UniversityPhiladelphiaPA 19122-6096U.S.A

Federated learning has emerged as a distributed learning paradigm by training at each client and aggregat-ing at a parameter server.System heterogeneity hinders stragglers from responding to the server in time with huge com-munication costs.Although client grouping in federated learning can solve the straggler problem,the stochastic selection strategy in client grouping neglects the impact of data distribution within each group.Besides,current client grouping ap-proaches make clients suffer unfair participation,leading to biased performances for different clients.In order to guaran-tee the fairness of client participation and mitigate biased local performances,we propose a federated dynamic client selec-tion method based on data representativity(FedSDR).FedSDR clusters clients into groups correlated with their own lo-cal computational efficiency.To estimate the significance of client datasets,we design a novel data representativity evalua-tion scheme based on local data distribution.Furthermore,the two most representative clients in each group are selected to optimize the global model.Finally,the DYNAMIC-SELECT algorithm updates local computational efficiency and data representativity states to regroup clients after periodic average aggregation.Evaluations on real datasets show that FedS-DR improves client participation by 27.4%,37.9%,and 23.3%compared with FedAvg,TiFL,and FedSS,respectively,tak-ing fairness into account in federated learning.In addition,FedSDR surpasses FedAvg,FedGS,and FedMS by 21.32%,20.4%,and 6.90%,respectively,in local test accuracy variance,balancing the performance bias of the global model across clients.

关键词： federated learning fairness computational efficiency data distribution client selection client grouping

Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective

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Journal of Computer Science & Technology 2024年第2期39卷 245-266页

作者：廖小飞赵文举金海姚鹏程黄禹王庆刚赵进郑龙张宇邵志远 national Engineering Research center for big data Technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China

Graph processing has been widely used in many scenarios,from scientific computing to artificial intelligence.Graph processing exhibits irregular computational parallelism and random memory accesses,unlike traditional workloads.Therefore,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a significantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a specialized single-thread graph algorithm.While domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software codesigns.This article presents a graph processing ecosystem from hardware to software.We start by introducing a series of hardware accelerators as the foundation of this ecosystem.Subsequently,the codesigned parallel graph systems and their distributed techniques are presented to support graph applications.Finally,we introduce our efforts on novel graph applications and hardware architectures.Extensive results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.

关键词： graph processing hardware accelerator software system high performance ecosystem

Benefit of aerosol reduction to winter wheat during China's clean air action:A case study of Henan Province

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Journal of Environmental Sciences 2024年第7期141卷 90-101页

作者： Yang Bai Pengfei Zhao Xueyang Chen Lijun Wang Wenjuan Chang Jianzhong Guo Jiayao Wang College of Geography and Environmental Science Henan UniversityKaifeng 475004China Henan Industrial Technology Academy of Spatio-Temporal big data Henan UniversityZhengzhou 475000China Henan Technology Innovation center of Spatio-Temporal big data Henan UniversityZhengzhou 450046China Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions(Henan University) Ministry of EducationKaifeng 475000China

A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action,yet its impact on wheat(Triticum aestivum L.)production remains unclear.We use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to 2018.After calibrating parameters with the extended Fourier Amplitude Sensitivity Test(EFAST)and the generalized likelihood uncertainty estimation(GLUE)method,the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more accurately.We found that the aerosol negatively impacted wheat biomass by 21.87%and yield by 22.48%from 2006 to 2018,and the biomass effects from planting to anthesis were more significant compared to anthesis to maturity.Due to the strict clean air action,under all-sky conditions,the surface solar shortwave radiation(SSR)in 2018 increased by about 7.08%over 2006-2013 during the wheat growing seasons.As a result of the improvement of crop photosynthesis,winter wheat biomass and yield increased by an average of 5.46%and 2.9%,respectively.Our findings show that crop carbon uptake and yield will benefit from the clean air action in China,helping to ensure national food and health security.

关键词： Haze pollution Clean air action Aerosol-induced radiative perturbation Wheat production DSSAT model

Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers:A Life Course Perspective

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China CDC weekly 2024年第11期6卷 219-224,I0014-I0017页

作者： Cedric Zhang Bo Lua Yajie Gao Jinming Li Xingqi Cao Xinwei Lyu Yinuo Tu Shuyi Jin Zuyun Liu center for Clinical big data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Healththe Key Laboratory of Intelligent Preventive Medicine of Zhejiang ProvinceZhejiang University School of MedicineHangzhou CityZhejiang ProvinceChina Institute of Epidemiology and Health Care University College LondonLondonUK College of Chemical and Biological Engineering Zhejiang UniversityHangzhou CityZhejiang ProvinceChina

Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of research.In this study,we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English databases.Previous studies have predominantly used single biomarkers,such as C-reactive protein,or focused on specific life course stages and factors such as socioeconomic status,mental health,educational levels,and unhealthy lifestyles.By summarizing the progress in this field,our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.

关键词： such insight directions

Recent Advances in Asymmetric Structural Composites for Excellent Electromagnetic Interference Shielding: A Review

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Chinese Journal of Polymer Science 2024年第6期42卷 693-710页

作者： Ying Zhou Bai Xue Lan Xie Chang-Mei Wu Qiang Zheng Department of Polymer Materials and Engineering College of Materials and Metallurgy Guizhou University national Engineering Research center for Compounding and Modification of Polymer Materials National and Local Joint Engineering Research Center for Functional Polymer Membrane Materials and Membrane Processes State Key Laboratory of Public big data Guizhou University Department of Polymer Science and Engineering Zhejiang University

Since electromagnetic pollution is detrimental to human health and the environment, numerous efforts have been successively made to achieve excellent electromagnetic interference shielding effectiveness(EMI SE) via designing the hierarchical structures for electromagnetic interference(EMI) shielding polymer composites. Among the plentiful structures, the asymmetric structures are currently a hot spot, principally categorizing into multi-layered, porous, fibrous, and segregated asymmetric structures, which endows the high EMI shielding performance for polymer composites incorporated with magnetic, conductive, and/or dielectric micro/nano-fillers, due to the “absorption-reflection-reabsorption” shielding mechanism. Therefore, this review provides the retrospection and summary of the efforts with respect to abundant asymmetric structures and multifunctional micro/nano-fillers for enhancing EMI shielding properties, which is conducive to the booming development of polymeric EMI shielding materials for the promising prospect in modern electronics and 5-generation(5G) technology.

关键词： Asymmetric structure Microano functional filler Polymer composite Electromagnetic interference shielding