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Mobility in China, 2020: a tale of four phases

National Science Review 2021年第11期8卷 110-120页

作者： Suoyi Tan Shengjie Lai Fan Fang Ziqiang Cao Bin Sai Bing Song Bitao Dai Shuhui Guo Chuchu Liu Mengsi Cai Tong Wang Mengning Wang Jiaxu Li Saran Chen Shuo Qin Jessica R.Floyd Zhidong Cao Jing Tan Xin Sun Tao Zhou Wei Zhang Andrew J.Tatem Petter Holme Xiaohong Chen Xin Lu School of Business Central South University Institute of Big Data and Internet Innovations Hunan University of Technology and Business College of Systems Engineering National University of Defense Technology WorldPop School of Geography and Environmental ScienceUniversity of Southampton School of Mathematics and big data Foshan University State Key Laboratory on Blind Signal Processing State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Chinese Evidence-Based Medicine Center National Clinical Research Center for Geriatrics West China Hospital Sichuan University big data Research Center University of Electronic Science and Technology of China West China Biomedical big data Center West China Hospital Sichuan University Tokyo Tech World Hub Research Initiative Institute of Innovative Research Tokyo Institute of Technology

2020 was an unprecedented year,with rapid and drastic changes in human mobility due to the COVID-19 pandemic.To understand the variation in commuting patterns among the Chinese population across stable and unstable periods,we used nationwide mobility data from 318 million mobile phone users in China to examine the extreme fluctuations of population movements in 2020,ranging from the Lunar New Year travel season(chunyun), to the exceptional calm of COVID-19 lockdown,and then to the recovery period.We observed that cross-city movements,which increased substantially in chunyun and then dropped sharply during the lockdown,are primarily dependent on travel distance and the socio-economic development of cities.Following the Lunar New Year holiday,national mobility remained low until mid-February,and COVID-19 interventions delayed more than 72.89 million people returning to large cities.Mobility network analysis revealed clusters of highly connected cities,conforming to the social-economic division of urban agglomerations in China.While the mass migration back to large cities was delayed,smaller cities connected more densely to form new clusters.During the recovery period after travel restrictions were lifted,the netflows of over 55% city pairs reversed in direction compared to before the lockdown.These findings offer the most comprehensive picture of Chinese mobility at fine resolution across various scenarios in China and are of critical importance for decision making regarding future public-health-emergency response,transportation planning and regional economic development,among others.

关键词： human mobility travel restrictions COVID-19 mobile phone data behavioral response

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新型缓释磷酸盐固定剂对镉和铅污染的土壤的修复效果

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Journal of Central South University 2022年第4期29卷 1185-1196页

作者：姚文斌黄磊赵飞平杨志辉刘奕苏长青 School of Metallurgy and Environment Central South UniversityChangsha 410083China Guangzhou University-Linköping University Research Center on Urban Sustainable Development Guangzhou UniversityGuangzhou 510006China School of Energy Science and Engineering Central South UniversityChangsha 410083China Institute of Big Data and Internet Innovations Hunan University of Technology and BusinessChangsha 410205China

磷酸盐通过不溶性金属磷酸盐沉淀而被广泛应用于镉、铅污染土壤的稳定修复。但是,环境中磷含量的增加会引起新的污染,而缓释磷酸盐因兼具稳定重金属和降低二次污染风险的特性而备受关注。本文制备了一种新型的缓释磷酸盐固定剂(SRPA),... 详细信息

磷酸盐通过不溶性金属磷酸盐沉淀而被广泛应用于镉、铅污染土壤的稳定修复。但是,环境中磷含量的增加会引起新的污染,而缓释磷酸盐因兼具稳定重金属和降低二次污染风险的特性而备受关注。本文制备了一种新型的缓释磷酸盐固定剂(SRPA),对其进行了BET,SEM,FTIR,溶胀率,磷含量等表征。结果表明,SRPA是一种内部具有网状结构的球体,除磷酸盐外,还含有羟基,羧基和其他官能团,比表面积为5~7.18 m^(2)/g。SRPA的磷酸盐含量从5%增加到8%,Korsmeyer-Peppus模型表明,non-Fickian扩散过程对磷酸盐的释放起着主要控制作用。将SRPA应用于土壤后,我们发现与传统的磷酸盐改良剂相比,土壤中水溶性磷的浓度大大降低。SRPA比传统的磷酸盐改良剂对土壤的修复效果更好。水溶性镉(Cd)和铅(Pb)的修复效率分别从68.57%提高到97.09%,和从76.9%提高到97.89%。可生物利用的Cd和Pb分别从63.09%增加到71.85%,和从66.21%增加到76.47%。提取物的实验结果表明,随着残留重金属的增加,修复后土壤中重金属的可交换和碳酸盐结合的含量显着降低,表明重金属的稳定性增加。

关键词：重金属磷酸盐缓释固定剂土壤修复

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Multi‐task framework of precipitation nowcasting

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1350-1363页

作者： Zheng Zhang Chuyao Luo Baoquan Zhang Hao Jiang Bowen Zhang Department of Computer Science Shenzhen Key Laboratory of Internet Information CollaborationHarbin Institute of TechnologyShenzhenChina College of big data and internet Shenzhen Technology UniversityShenzhenChina

Precipitation forecasting plays an important role in disaster warning,agricultural production,and other fields.To solve this issue,some deep learning methods are proposed to forecast future radar echo images and convert them into rainfall distributions.Prevailing spatiotemporal sequence prediction methods are usually based on a ConvRNN structure that combines a Convolutional Neural Network and Recurrent Neural Network.However,these existing methods ignore the image change prediction,which causes the coherence of the predicted image has deteriorated.Moreover,these approaches mainly focus on complicating model structure to exploit more historical spatiotemporal representations.Nevertheless,they ignore introducing other valuable information to improve predictions.To tackle these two issues,we propose GCMT‐ConvRNN,a multi‐ask framework of ConvRNN.Except for precipitation nowcasting as the main task,it combines the motion field estimation and sub‐regression as auxiliary tasks.In this framework,the motion field estimation task can provide motion information,and the sub‐regression task offers future information.Besides,to reduce the negative transfer between the auxiliary tasks and the main task,we propose a new loss function based on the correlation of gradients in different tasks.The experiments show that all models applied in our framework achieve stable and effective improvement.

关键词： deep neural networks motion estimation

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The development trend and practical innovation of smart cities under the integration of new technologies

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Frontiers of Engineering Management 2019年第4期6卷 485-502页

作者： Xiaohong CHEN institute of big data and internet Innovation Hunan University of Technology and BusinessChangsha 410205China Business School Central South UniversityChangsha 410083China

Smart cities have rapidly developed in the context of the integration of new digital technologies such as big data,internet of Things,artificial intelligence,blockchains,and virtual reality.These cities have conducted practical innovations and typical cases in many sectors,such as in government,transportation,environmental protection,energy,medical care,and logistics,and have produced many social,economic,and ecological benefits.However,there are still some problems that continue to hinder the construction of smart cities.This paper examines such problems in depth and proposes some relevant countermeasures and suggestions.

关键词： new technology integration smart city big data practical innovation

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Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1695-1712页

作者： Xiaodong Yang Runze Diao Tao Liu Haoqi Wen Caifen Wang College of Computer Science and Engineering Northwest Normal UniversityLanzhou730070China institute of China TelecomWanwei China TelecomWanwei Information Technology Co.Ltd.Lanzhou730030China College of big data and internet Shenzhen Technology UniversityShenzhen518118China Key Laboratory of Cryptography and data Analytics Northwest Normal UniversityLanzhou730070China

The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading market.Certificateless signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrowbased on identity cryptography.However,most certificateless signatures still suffer fromvarious security flaws.We present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature schemes.To ensure the integrity and verifiability of electricity carbon quota trading,we propose an electricity carbon quota trading scheme based on a certificateless signature and blockchain.Our scheme utilizes certificateless signatures to ensure the validity and nonrepudiation of transactions and adopts blockchain technology to achieve immutability and traceability in electricity carbon quota transactions.In addition,validating electricity carbon quota transactions does not require time-consuming bilinear pairing operations.The results of the analysis indicate that our scheme meets existential unforgeability under adaptive selective message attacks,offers conditional identity privacy protection,resists replay attacks,and demonstrates high computing and communication performance.

关键词： Electricity carbon trading certificateless signature blockchain forgery attack carbon quota

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Improved Dota2 Lineup Recommendation Model Based on a Bidirectional LSTM

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Tsinghua Science and Technology 2020年第6期25卷 712-720页

作者： Lei Zhang Chenbo Xu Yihua Gao Yi Han Xiaojiang Du Zhihong Tian Henan Key Laboratory of big data Analysis and Processing Kaifeng 457004China institute of data and Knowledge Engineering Henan UniversityKaifeng 475004.China National internet Emergency Center Zhengzhou 450000China Department of Computer and Information Sciences Temple UniversityPhiladelphiaPA 19122-6008USA Cyberspace institute of Advanced Technology Guangzhou UniversityGuangzhou 510006China

In recent years,e-sports has rapidly developed,and the industry has produced large amounts of data with specifications,and these data are easily to be obtained.Due to the above characteristics,data mining and deep learning methods can be used to guide players and develop appropriate strategies to win games.As one of the world’s most famous e-sports events,Dota2 has a large audience base and a good game system.A victory in a game is often associated with a hero’s match,and players are often unable to pick the best lineup to compete.To solve this problem,in this paper,we present an improved bidirectional Long Short-Term Memory(LSTM)neural network model for Dota2 lineup recommendations.The model uses the Continuous Bag Of Words(CBOW)model in the Word2 vec model to generate hero vectors.The CBOW model can predict the context of a word in a sentence.Accordingly,a word is transformed into a hero,a sentence into a lineup,and a word vector into a hero vector,the model applied in this article recommends the last hero according to the first four heroes selected first,thereby solving a series of recommendation problems.

关键词： Word2vec mutiplayer online battle arena games Continuous Bag Of Words(CBOW)model Long Short-Term Memory(LSTM)

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Demand Learning and Cooperative Deployment of UAV Networks

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Chinese Journal of Electronics 2022年第3期31卷 408-415页

作者： ZHANG Xiao WANG Xuehe XU Xinping ZHAO Yingchao South-Central University for Nationalities Caritas institute of Higher Education Sun Yat-sen University & Guangdong Key Laboratory of big data Analysis and Processing Nanyang Technological University

Unmanned aerial vehicle(UAV) as a powerful tool has found its applicability in assisting mobile users to deal with computation-intensive and delaysensitive applications(e.g., edge computing, high-speed internet access, and local caching). However, deployment of UAV-aided mobile services(UMS) faces challenges due to the UAV limitation in wireless coverage and energy storage. Aware of such physical limitations, a future UMS system should be intelligent enough to self-plan trajectories and best offer computational capabilities to mobile users. There are important issues regarding the UAV-user interaction, UAV-UAV cooperation for sustainable service provision, and dynamic UMS pricing. These networking and resource management issues are largely overlooked in the literature and this article presents intelligent solutions for cooperative UMS deployment and operation. Mobile users’ locations are generally private information and changing over time. How to learn on-demand users’ truthful location reporting is important for determining optimal UAV deployment in serving all the users fairly. After addressing the truthful UAV-user interaction issue via game theory, we further study the UAV network sustainability for UMS provision by minimizing the energy consumption cost during deployment and seeking UAV-UAV cooperation. Finally, for profit-maximizing purpose, we analyze the cooperative UAVs’ deployment, capacity allocation, and dynamic service pricing.

关键词： Unmanned aerial vehicle networks Wireless coverage Dynamic pricing Capacity allocation

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On the time-independent Hamiltonian in real-time and imaginary-time quantum annealing

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Chinese Physics B 2020年第10期29卷 167-171页

作者：孙杰路松峰 Hubei Engineering Research Center on big data Security School of Cyber Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China School of internet Anhui UniversityHefei 230039China Shenzhen Huazhong University of Science and Technology Research institute Shenzhen 518063China

We present the analog analogue of Grover's problem as an example of the time-independent Hamiltonian for applying the speed limit of the imaginary-time Schrödinger equation derived by Okuyama and Ohzeki and the new class of energy-time uncertainty relation proposed by Kieu. It is found that the computational time of the imaginary-time quantum annealing of this Grover search can be exponentially small, while the counterpart of the quantum evolution driven by the real-time Schrödinger equation could only provide square root speedup, compared with classic search. The present results are consistent with the cases of the time-dependent quantum evolution of the natural Grover problem in previous works. We once again emphasize that the logarithm and square root algorithmic performances are generic in imaginary-time quantum annealing and quantum evolution driven by real-time Schrödinger equation, respectively. Also, we provide evidences to search deep reasons why the imaginary-time quantum annealing can lead to exponential speedup and the real-time quantum annealing can make square root speedup.

关键词： time-independent Hamiltonian imaginary-time quantum annealing quantum speed limit the energy-time uncertainty relation continuous Grover's search

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A Survey on Emerging Computing Paradigms for big data

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Chinese Journal of Electronics 2017年第1期26卷 1-12页

作者： ZHANG Yaoxue REN Ju LIU Jiagang XU Chugui GUO Hui LIU Yaping School of Information Science and Engineering Central South University Research institute of Information Security and big data Central South University

The explosive growth of data volume and the ever-increasing demands of data value extraction have driven us into the era of big data. The "5V"(Variety,Velocity, Volume, Value, and Veracity) characteristics of big data pose great challenges to traditional computing paradigms and motivate the emergence of new solutions.Cloud computing is one of the representative technologies that can perform massive-scale and complex data computing by taking advantages of virtualized resources, parallel processing and data service integration with scalable data storage. However, as we are also experiencing the revolution of internet-of-things(IoT), the limitations of cloud computing on supporting lightweight end devices significantly impede the flourish of cloud computing at the intersection of big data and IoT era. It also promotes the urgency of proposing new computing paradigms. We provide an overview on the topic of big data, and a comprehensive survey on how cloud computing as well as its related technologies can address the challenges arisen by big data.Then, we analyze the disadvantages of cloud computing when big data encounters IoT, and introduce two promising computing paradigms, including fog computing and transparent computing, to support the big data services of IoT. Finally, some open challenges and future directions are summarized to foster continued research efforts into this evolving field of study.

关键词： Computing paradigm big data Cloud computing Transparent computing Fog computing internet-of-things(IoT)

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A deep convolutional neural network for diabetic retinopathy detection via mining local and long-range dependence

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 153-166页

作者： Xiaoling Luo Wei Wang Yong Xu Zhihui Lai Xiaopeng Jin Bob Zhang David Zhang Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of TechnologyShenzhenChina Peng Cheng Laboratory ShenzhenChina Shenzhen institute of Artificial Intelligence and Robotics for Society ShenzhenChina College of big data and internet Shenzhen Technology UniversityShenzhenChina The Department of Computer and Information Science University of MacaoMacaoMacaoChina The Chinese University of Hong Kong(Shenzhen) ShenzhenChina

Diabetic retinopathy(DR),the main cause of irreversible blindness,is one of the most common complications of diabetes.At present,deep convolutional neural networks have achieved promising performance in automatic DR detection tasks.The convolution operation of methods is a local cross-correlation operation,whose receptive field de-termines the size of the local neighbourhood for processing.However,for retinal fundus photographs,there is not only the local information but also long-distance dependence between the lesion features(e.***.hemorrhages and exudates)scattered throughout the whole image.The proposed method incorporates correlations between long-range patches into the deep learning framework to improve DR detection.Patch-wise re-lationships are used to enhance the local patch features since lesions of DR usually appear as plaques.The Long-Range unit in the proposed network with a residual structure can be flexibly embedded into other trained networks.Extensive experimental results demon-strate that the proposed approach can achieve higher accuracy than existing state-of-the-art models on Messidor and EyePACS datasets.

关键词： image classification medical image processing pattern recognition

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