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3rd IEEE International Conference on Big Data Analysis, ICBDA 2018

作者： Liu, Jinxin Jiao, Xu Jin, Youzhi Liu, Xinyu Liu, Li Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

ISBN: (纸本)9781538647936

Point-of-Interest is an interesting research topic of personalized recommendation. In this paper, a new position-based recommendation framework is proposing by using the time attribute. We establish a user matrix with user check-in data sets that contain time and location information. The user matrix is divided into the sub-matrices according to the set period and then every sub-matrix is decomposed into the user checking preference matrix and position feature matrix by using the non-negative matrix factorization. The user's attendance preferences at each time are integrated to get the user's final check-in preference for the candidate location to make recommendations more consistent with the needs of users. © 2018 IEEE.

关键词： Non-negative matrix factorization

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A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

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IEEE/CAA Journal of Automatica Sinica 2018年第5期5卷 934-945页

作者： Liang Qi Mengchu Zhou Wenjing Luan IEEE Department of Computer Scicnce and Technology Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Tongji UniversityShanghai 201804China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102USA Key Laboratory of Embedded System and Service Computing Ministry of EducationShanghai Electronic Transactions and Information Service Collaborative Innovation CenterDepartment of Com-puter ScienceTongji UniversityShanghai 201804China

Advanced information and communication technolo-gies can be used to facilitate traffic incident *** an incident is detected and blocks a road link,in order to reduce the incident-induced traffic congestion,a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this ***-dependent shortest path algorithms are used to generate a subnetwork where vehicles should receive such information.A simulation approach based on an extended cell transmission model is used to describe traffic flow in urban networks where path information and traffic flow at downstream road links are well *** results reveal the influences of some major parameters of an incident-induced congestion dissipation process such as the ratio of route-changing vehicles to the total vehicles,operation time interval of the proposed strategy,traffic density in the traffic network,and the scope of the area where traffic incident information is *** results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents.

关键词： Cell transmission model(CTM) intelligent transportation systems(ITS) traffic incident management(TIM) urban traffic congestion

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Optimal Power Allocation of Cooperative NOMA with Finite Blocklength Codes

Optimal Power Allocation of Cooperative NOMA with Finite Blo...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Siling Liu Zhengchuan Chen Jinfeng Xie Liang Liang Min Wang Yunjian Jia The Key Laboratory of Dependable Service Computing in Cyber-Physical Society Ministry of Education and School of Microelectronics and Communication Engineering Chongqing University Chongqing China Chongqing Academy of Informatioon and Communications Technology Chongqing China School of Optoelectronics Engineering Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

Compared with orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA) has enormous advantages in enhancing fairness and spectral efficiency for downlink transmission. To further improve the performance of NOMA, cooperative NOMA (C-NOMA) has attracted attention while power allocation of C-NOMA is of great importance to ameliorate the system performance. To guarantee the requirements of ultra-reliable and low-latency communication (URLLC) nowadays, the code length is supposed to be short enough where finite blocklength (FBL) codes are adopted. This paper presents a two-user half-duplex downlink C-NOMA scheme with low latency constraint. To minimize the error probability, power allocation problems are formulated. For this purpose, the properties of power allocation to objective functions are investigated. First, the error probability is analysed in terms of signal-to-noise ratio. Afterwards, the convexity of the power allocation problems under certain conditions are shown and optimal algorithms that solve the problems are proposed. Numerical results demonstrate that the proposed C-NOMA with finite blocklength codes successfully achieve lower error probability with regard to the conventional NOMA.

关键词： Wireless communication Signal processing Conferences

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Projection of Climate Change Impacts on Rice Water Footprint Under Arid Climate Conditions Based on Cmip6

SSRN

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SSRN 2024年

作者： Elsadek, Elsayed Ahmed Elshikha, Diaa Eldin M. Awad, Ahmed Hamoud, Yousef Alhaj Elsheikha, Ahmed Williams, Clinton F. Orr, Ethan Shaghaleh, Hiba Hamad, Amar Ali Adam Thorp, Kelly R. Elbeltagi, Ahmed Biosystems Engineering Department University of Arizona TucsonAZ85721 United States Agricultural and Biosystems Engineering Department College of Agriculture Damietta University Damietta34517 Egypt Department of Food Agricultural and Biological Engineering College of Food Agricultural and Environmental Sciences The Ohio state University ColumbusOH43210 United States Giza11925 Egypt Key Laboratory of Hydrologic-Cycle and Hydrodynamic-System of Ministry of Water Resources Hohai University Jiangsu Nanjing210024 China College of Hydrology and Water Resources Hohai University Jiangsu Nanjing210024 China USDA-ARS Arid Land Agricultural Research Center MaricopaAZ85138 United States Agriculture Education Technology and Innovation The University of Arizona TucsonAZ85721 United States College of Environment Hohai University Jiangsu Nanjing210098 China USDA Agricultural Research Service Grassland Soil & Water Research Laboratory TX76502 United States Agricultural Engineering Department College of Agriculture Mansoura University Mansoura35516 Egypt USDA-ARS Arid Land Agricultural Research Center United States

The present study was conducted to project the effect of climate change on rice yield (Y), evapotranspiration(ET), and total water footprint (WFT) in *** emission scenarios of Shared Socioeconomic Pathways(SSP) were applied as climate projections: SSP2-4.5 and ***, four statistical evaluation metrics, namely, Pearson’s correlation coefficient (R), the index of agreement (Dindex), the mean absolute error (MAE), and the bias of temperature (BIAST) and precipitation (BIASPr), were used to evaluate five global climate models (GCMs) with respect to the baseline temperatures(T)and precipitation(Pr)over the study area under the two SSP scenarios. Then, AquaCrop-GIS, integrated with the ensemble downscaled GCMs data, was used to project the future climate change impacts on rice Y, ET, and WF under the 3-day irrigation frequency regime(3IF)and the two SSP and CO2 emission scenarios during 2021–2099. Our results demonstrated a moderate-to-strong correlation between all GCMs and historical average annual Pr and T(0.52>R>0.99)over the study area. Moreover, MAE less than 7.04 mm and 5.19°C, with a Dindex between 0.57 and 0.99, were recorded for Pr and T variables, respectively, indicating an acceptable degree of agreement between predicted and observed climate variables during the baseline period. Without CO2 effects, rice yields would slightly increase (1.07%–3.03%) during the 2030s and 2050s. In contrast, it would significantly decline (4.55%–18.94%) during the 2070s and 2090s under the two SSP scenarios. With CO2 effects, rice yields would significantly increase(14.19%–28.31%)under the two SSP scenarios over time. Projected ET, by AquaCrop-GIS, would decline (1.42%–18.98%) under the two SSP and CO2 scenarios over time. Meanwhile, without CO2 effects, the WFT would increase by 5.55% to 17.13% during the ***, with CO2 effects, the WFT would decrease significantly(15.45%–34.50%)under the two SSP scenarios over time. Our findings are helpful for grow

关键词： Carbon dioxide

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Point adversarial self mining: A simple method for facial expression recognition

arXiv

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arXiv 2020年

作者： Liu, Ping Lin, Yuewei Meng, Zibo Lu, Lu Deng, Weihong Zhou, Joey Tianyi Yang, Yi Institute of High Performance Computing Agency for Science Technology and Research Singapore Singapore Centre for Artificial Intelligence University of Technology Sydney Sydney Australia Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Brookhaven National Laboratory UptonNY United States InnoPeak Technology Inc. Palo AltoCA United States Key Laboratory of Medical Molecular Virology School of Basic Medical Sciences Fudan University Shanghai China

In this paper, we propose a simple yet effective approach, named Point Adversarial Self Mining (PASM), to improve the recognition accuracy in facial expression recognition. Unlike previous works focusing on designing specific architectures or loss functions to solve this problem, PASM boosts the network capability by simulating human learning processes: providing updated learning materials and guidance from more capable teachers. Specifically, to generate new learning materials, PASM leverages a point adversarial attack method and a trained teacher network to locate the most informative position related to the target task, generating harder learning samples to refine the network. The searched position is highly adaptive since it considers both the statistical information of each sample and the teacher network capability. Other than being provided new learning materials, the student network also receives guidance from the teacher network. After the student network finishes training, the student network changes its role and acts as a teacher, generating new learning materials and providing stronger guidance to train a better student network. The adaptive learning materials generation and teacher/student update can be conducted more than one time, improving the network capability iteratively. Extensive experimental results validate the efficacy of our method over the existing state of the arts for facial expression recognition. Copyright © 2020, The Authors. All rights reserved.

关键词： Iterative methods

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Conceptual model of real-time IoT systems

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Frontiers of Information technology & Electronic Engineering 2019年第11期20卷 1457-1464页

作者： Bo YUAN De-ji CHEN Dong-mei XU Ming CHEN Department of Computer Science and Technology Tongji UniversityShanghai 201804China School of Electronics and Information Engineering Jinggangshan UniversityJi'an 343009China MOE Key Laboratory of Embedded System and Service Computing Tongji UniversityShanghai 201804China China Electronics Standardization Institute Beijing 100007China Chinesisch-Deutsche Hochschule for Angewandte Wissenschaften Tongji UniversityShanghai 201804China

We address a special kind of Internet of Things (IoT) systems that are also real-time. We call them real-time IoT (RT-IoT) systems. An RT-IoT system needs to meet timing constraints of system delay, clock synchronization, deadline, and so on. The timing constraints turn to be more stringent as we get closer to the physical things. Based on the reference architecture of IoT (ISO/IEC 30141), the RT-IoT conceptual model is established. The idea of edge subsystem is introduced. The sensing & con-trolling domain is the basis of the edge subsystem, and the edge subsystem usually must meet the hard real-time constraints. The model includes four perspectives, the time view, computation view, communication view, and control view. Each view looks, from a different angle, at how the time parameters impact an RT-IoT system.

关键词： Internet of Things(IoT) Real-time system Conceptual model View Hard/Soft real-time

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Deep Domain Adaptation for Pavement Crack Detection

arXiv

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arXiv 2021年

作者： Liu, Huijun Yang, Chunhua Li, Ao Huang, Sheng Feng, Xin Ruan, Zhimin Ge, Yongxin College of Computer Science Chongqing University Chongqing400044 China School of Big Data and Software Engineering Chongqing University Chongqing401331 China Chongqing City Management College Chongqing401331 China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University Chongqing400044 China College of Computer Science And Engineering Chongqing University of Technology Chongqing400054 China Co. Ltd Chongqing400060 China

Deep learning-based pavement cracks detection methods often require large-scale labels with detailed crack location information to learn accurate predictions. In practice, however, crack locations are very difficult to be manually annotated due to various visual patterns of pavement crack. In this paper, we propose a Deep Domain Adaptation-based Crack Detection Network (DDACDN), which learns domain invariant features by taking advantage of the source domain knowledge to predict the multi-category crack location information in the target domain, where only image-level labels are available. Specifically, DDACDN first extracts crack features from both the source and target domain by a two-branch weights-shared backbone network. And in an effort to achieve the cross-domain adaptation, an intermediate domain is constructed by aggregating the three-scale features from the feature space of each domain to adapt the crack features from the source domain to the target domain. Finally, the network involves the knowledge of both domains and is trained to recognize and localize pavement cracks. To facilitate accurate training and validation for domain adaptation, we use two challenging pavement crack datasets CQU-BPDD and RDD2020. Furthermore, we construct a new large-scale Bituminous Pavement Multi-label Disease Dataset named CQU-BPMDD, which contains 38994 high-resolution pavement disease images to further evaluate the robustness of our model. Extensive experiments demonstrate that DDACDN outperforms state-of-the-art pavement crack detection methods in predicting the crack location on the target domain. Copyright © 2021, The Authors. All rights reserved.

关键词： Crack detection

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Joint Channel Estimation and Decoding Design for 5G-Enabled V2V Channel

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China Communications 2018年第7期15卷 39-46页

作者： Xuanfan Shen Yong Liao Xuewu Dai Ming Zhao Kai Liu Dan Wang Center of Communication and TT&C Chongqing University The State Key Laboratory of Integrated Services Networks Xidian University Faculty of Engineering and Environment Northumbria University Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Ministry of Education Chongqing Key Laboratory of Mobile Communication Technology Chongqing University of Posts and Telecommunication

This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular(V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing(OFDM) system, we perform extended Kalman filter(EKF) for channel estimation in conjunction with Iterative Detector & Decoder(IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.

关键词： orthogonal frequency division multiplexing（OFDM）non-stationary channel estimation extended Kalman filter（EKF）Iterative Detector ＆ Decoder（IDD）vehicular-to-vehicular（V2V）

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Emergency analysis based on affective computing in universities forum 5th

Emergency analysis based on affective computing in universit...

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5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Zhang, Lu Wu, Xu Xie, Xiaqing Xu, Jin Zhang, Tianle Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing100876 China School of Cyberspace Security BUPT Beijing100876 China Beijing University of Posts and Telecommunications Library Beijing100876 China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou510006 China

ISBN: (纸本)9783030242701

Emergency analysis for social networking sites have gained increased attention. In order to detect emergencies in University Forums, we present an emergency analysis method based on affective computing. The method detects the emergency and calculates the scores in real-time based on affective computing and the University Public Opinion Ontology (UPO_Ontology) established manually. The method is evaluated on two test datasets. The results show that the UPO_Ontology and affective computing greatly improved the accuracy, recall and F-measure. The method proposed in this paper meets the requirement of real-time detection. What's more, It gain of 1.24% in F-measure over the "event-specific detection" proposed by Laylavi et al. and outperforms emergency detect using contextual semantics by nearly 7.1% in F-measure. The analysis of the emergencies in University Forums will help Universities deal with emergencies more effectively and provide students with better service. © Springer Nature Switzerland AG 2019.

关键词： Semantics

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Design, performance and in-orbit evaluation results of Tiangong-2 wide-band imaging spectrometer

Design, performance and in-orbit evaluation results of Tiang...

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Tiangong-2 Remote Sensing Application Conference on technology, Method and Application

作者： Wei, Jun Ding, Lei He, Xianqiang Tang, Yuyu Feng, Xin Lin, Mingsen Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai200083 China State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography SOA Hangzhou310012 China National Satellite Ocean Application Service SOA Beijing100081 China Key Laboratory of Infrared System Detection and Imaging Technology Chinese Academy of Sciences Shanghai200083 China

ISBN: (纸本)9789811335006

The system design, performance and in-orbit evaluations of a push-broom wide-band imaging spectrometer (WIS) on Tiangong-2 space laboratory is introduced. The WIS has 100 m spatial resolution in ocean color bands (FOV is around 42°), which is the highest compared to other in-orbit ocean color sensors (GOCI, MODIS, VIIRS, and OLCI). Besides, WIS includes visible and near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) channels and has excellent performance in ocean color monitoring, and SNR in 0.4–0.8 μm is more than 400 at typical oceanic radiance. Average SNR at SWIR is more than 550 at typical atmosphere radiance. Moreover, the instrument’s average NE⊿T at TIR is lower than 20 mK, which is one of the best. The in-orbit tests reveal that the ocean color components retrieved by WIS are highly consistent with the results from the typical ocean color satellite sensors (MODIS, VIIRS and GOCI), but have finer structures due to higher spatial resolution. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Dewars

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