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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 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 School of Business Central South University Institute of Big Data and Internet Innovations Hunan University of Technology and Business

2020 was an unprecedented year,with rapid and drastic changes in human mobility due to the COVID-19 *** 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 *** 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 *** 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 *** network analysis revealed clusters of highly connected cities,conforming to the social-economic division of urban agglomerations in *** the mass migration back to large cities was delayed,smaller cities connected more densely to form new *** the recovery period after travel restrictions were lifted,the netflows of over 55% city pairs reversed in direction compared to before the *** 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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An Efficient Evolutionary Algorithm for High-Speed Train Rescheduling Under a Partial Station Blockage

SSRN

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SSRN 2023年

作者： Wang, Rongsheng Zhang, Qi Dai, Xuewu Yuan, Zhiming Zhang, Tao Ding, Shuxin Jin, Yaochu China Academy of Railway Sciences Corporation Limited Beijing100081 China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Train Operation Control Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing100081 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Faculty of Technology Bielefeld University BielefeldD-33615 Germany Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

This paper investigates the high-speed train rescheduling (HSTR) problem under a partial station blockage and proposes an efficient problem-specific strengthen elitist genetic algorithm (PS-SEGA) for HSTR. An HSTR model that is subject to train operation constraints is established to minimize the total train delay. The PS-SEGA framework consists of the following main steps. Firstly, a permutation-based encoding method is developed to define an efficient search space based on a train departure sequence. A decoding method is employed to output the rescheduled timetable and objective value based on the departure sequence. Moreover, a hybrid initialization method involving an efficient heuristic strategy (EHS) is put forward to accelerate the convergence speed of Evolutionary algorithms (EAs). Using problem-specific knowledge, EHS generates an efficient and feasible solution for the initial population. Finally, a restart strategy is presented to maintain genetic diversity. Compared with other advanced EAs and their improved variants also using the PS-SEGA framework, experimental results demonstrate the effectiveness of the proposed PS-SEGA for addressing HSTR scenarios under the partial station blockage. As for the scenarios that CPLEX can not obtain optimal solutions within 10 minutes, PS-SEGA can all provide quasi-optimal solutions in real-time. Furthermore, compared with the other two strategies (i.e., First-Scheduled-First-Served and EHS), PS-SEGA can find the best departure sequence that can output the timetable with a quasi-optimal solution. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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The Importance of Gender Specification for Detection of Driver Fatigue using a Single EEG Channel

The Importance of Gender Specification for Detection of Driv...

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Biomedical Engineering International Conference (BMEiCON)

作者： Mohammad Shahbakhti Matin Beiramvand Erfan Nasiri Wei Chen Jordi Solé-Casals Michal Wierzchon Anna Broniec-Wójcik Piotr Augustyniak Vaidotas Marozas Biomedical Engineering Institute Kaunas University of Technology Kaunas Lithuania Faculty of Information Technology and Communication Tampere University Tempere Finland Faculty of Statistics Mathematics and Computer Allameh Tabataba’i University Tehran Iran Center for Intelligent Medical Electronics School of Information Science and Technology the Human Phenome Institute Fudan University Shanghai China Data and Signal Processing Research Group University of Vic-Central University of Catalonia Vic Spain Institute of Psychology Jagiellonian University Krakow Poland Department of Biocybernetics and Biomedical Engineering AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9781665489041

Although detection of the driver fatigue using a single electroencephalography (EEG) channel has been addressed in literature, the gender differentiation for applicability of the model has not been investigated heretofore. Motivated accordingly, we address the detection of driver fatigue based the gender-segregated datasets, where each of them contains 8 subjects. After splitting the EEG signal into its sub-bands (delta, theta, alpha, beta, and gamma) using discrete wavelet transform, the log energy entropy of each band is computed to form the feature vector. Afterwards, the feature vector is randomly split into 50% for training and 50% for the unseen testing, and fed to a support vector machine model. When comparing the classification results of fatigue driving detection between the gender segregated and non-gender segregated datasets, the former achieved the accuracy 78% and 77% for male and female subjects, respectively, than the latter (71%). The obtained results show the importance of gender-specification for the driver fatigue detection.

关键词： Training Support vector machines Computational modeling Transforms Fatigue Brain modeling Electroencephalography

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Anonymizing Communication in VANets by Applying I2P Mechanisms

Anonymizing Communication in VANets by Applying I2P Mechanis...

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2019 IEEE Global Communications Conference (GLOBECOM)

作者： Tayeb Diab Marc Gilg Frederic Drouhin Pascal Lorenz Institute of Research in Computer Science Mathematics Automation and Signal (IRIMAS) University of Haute Alsace Colmar France

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Anonymizing communication becomes a substantial issue to enhance security and facing attacks. Huge researches are made in this field aiming to ensure a secure and anonymous communication. In vehicular ad hoc networks (VANets), this concept is used in different application areas like military domains, in which hiding destinations identities is necessary to avoid consequences attacks. In this paper, we propose a model of security to ensure anonymity in vehicular ad-hoc network. We inspire this model from the Invisible Internet project (I2P) in which we continue our previous work by adapting some of I2P mechanisms and algorithms in VANets. We adapt the I2P protocol to respond to several requirements of VANets. The proposed model is based on tunnels and encryption algorithms that use digital signatures and authentication mechanisms. We aim to make the proposed protocol more secure by ensuring anonymity, integrity, non- repudiation and confidentiality. We prove the effectiveness and the security of our proposed model by analysing different cases of anonymity and showing performance results. We have launched our simulations using NS3 platform.

关键词： Encryption Protocols Authentication Logic gates Internet

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Application of Entropy Filter in the Analysis of X-Ray Images

Application of Entropy Filter in the Analysis of X-Ray Image...

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2019 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019

作者： Likhachov, N.A. Likhachov, A.V. Department of Structural Mechanics Novosibirsk Russia Institute of Automation and Electrometry IAE SB RAS Research Group of Computer Science and Applied Mathematics Novosibirsk Russia

ISBN: (纸本)9781728100616

The problem of automatic analysis of X-ray images of large reinforced concrete structures is considered. The aim is to improve the accuracy of the evaluation of the shape and size of projections of internal cracks in the armature. The analysis is based on the classification of image elements by brightness threshold. In this case, it is complicated by the fact that the image has low contrast. To increase it, it is proposed to use an entropy filter whose window size is consistent with the noise level in the image. The study, including a computational experiment, confirmed the effectiveness of the proposed method. © 2019 IEEE.

关键词： Luminance

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A Reliable Method to Estimate the Bispectral Index Value Using a Single Frontal EEG Channel for Intra and Inter Subject Variability

A Reliable Method to Estimate the Bispectral Index Value Usi...

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Mohammad Shahbakhti Matin Beiramvand Roza Krycinska Erfan Nasiri Wei Chen Jordi Solé-Casals Michal Wierzchon Anna Broniec-Wójcik Piotr Augustyniak Vaidotas Marozas Biomedical Engineering Institute Kaunas University of Technology Kaunas Lithuania Faculty of Information Technology and Communication Tampere University Tempere Finland Doctoral School in Medical and Health Sciences Jagiellonian University Medical College Krakow Poland Department of Interdisciplinary Intensive Care Jagiellonian University Collegium Medicum Krakow Poland Faculty of Statistics Mathematics and Computer Allameh Tabataba’i University Tehran Iran Center for Intelligent Medical Electronics School of Information Science and Technology Fudan University Shanghai China Data and Signal Processing Research Group University of Vic-Central University of Catalonia Vic Spain Institute of Psychology Jagiellonian University Krakow Poland Department of Biocybernetics and Biomedical Engineering AGH University of Science and Technology Krakow Poland

Objective: Monitoring the depth of anesthesia (DoA) plays an important role for administering the drug injection during a surgery, i.e., preventing undesired awareness and inordinate anesthetic depth. Although the bispectral index (BIS) monitor is the golden standard system for the DoA monitoring, it is still not affordable for the developing countries. Alternatively, a low-cost electroencephalogram (EEG) headband can be used. The objective of this paper is to present a new algorithm for estimating the BIS values using a single frontal EEG channel. Method: In the first step, the EEG signal is filtered for the elimination of artifacts and is split into its sub-bands. In the second step, several linear and nonlinear features are extracted from each sub-band and fed to a random forest regression model in order to estimate the BIS. The performance of the proposed algorithm is assessed using EEG data recorded from twenty-four subjects during the general anesthesia and is validated in terms of correlation coefficient (CC) and absolute error (AE) between the reference and estimated BIS values. Results: The proposed algorithm achieved the mean CC of 0.83 and AE of 6.5 for intra subject variability and mean CC of 0.87 and AE of 5.5 for inter subject variability. Significance: Given the similar results for both intra and inter subject variability, the proposed algorithm has the potential to be used in the real-world scenario.

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Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation

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Journal of computer science & Technology 2019年第2期34卷 476-493页

作者： Xiang-Chu Feng Chen-Ping Zhao Si-Long Peng Xi-Yuan Hu Zhao-Wei Ouyang School of Mathematics and Statistics Xidian University Xi’an 710126 China School of Mathematical Science Henan Institute of Science and Technology Xinxiang 453003 China Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100190 China Research Center of Beijing Visystem Co. Ltd. Beijing 100190 China

Different from a general density estimation,the crime density estimation usually has one important factor:the geographical *** this paper,a new crime density estimation model is formulated,in which the regions where crime is impossible to happen,such as mountains and lakes,are *** further optimize the estimation method,a learning-based algorithm,named Plug-and-Play,is implanted into the augmented Lagrangian scheme,which involves an off-the-shelf filtering *** selections of the filtering operator make the algorithm correspond to several classical estimation ***,the proposed Plug-and-Play optimization based estimation algorithm can be regarded as the extended version and general form of several classical *** the experiment part,synthetic examples with different invalid regions and samples of various distributions are first *** under complex geographic constraints,we apply the proposed method with a real crime dataset to recover the density *** state-of-the-art results show the feasibility of the proposed model.

关键词： crime density estimation augmented Lagrangian strategy Plug-and-Play filtering operator

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Accurate Discharge Coefficient Prediction of Streamlined Weirs by Coupling Linear Regression and Deep Convolutional Gated Recurrent Unit

arXiv

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arXiv 2022年

作者： Chen, Weibin Sharifrazi, Danial Liang, Guoxi Band, Shahab S. Chau, Kwok Wing Mosavi, Amir College of Computer Science and Artificial Intelligence Wenzhou University Zhejiang Wenzhou325035 China Department of Computer Engineering Shiraz Branch Islamic Azad University Shiraz Iran Department of Artificial Intelligence Wenzhou Polytechnic Wenzhou325035 China Future Technology Research Center College of Future National Yunlin University of Science and Technology Yunlin County Taiwan Department of Civil and Environmental Engineering Hong Kong Polytechnic University Hong Kong John von Neumann Faculty of Informatics Obuda University Budapest Hungary Institute of Information Engineering Automation and Mathematics Slovak University of Technology Bratislava Slovakia

Streamlined weirs, as a nature-inspired type of weirs, has gained tremendous attention among hydraulic engineers mainly due to their well-known performance with high discharge coefficient. Computational fluid dynamic (CDF) is considered as a robust tool to predict discharge coefficient. To bypass the computational cost of CFD-based assessment, the present study proposes data-driven modelling techniques, as an alternative to CFD simulation, to predict discharge coefficient based on an experimental dataset. To this end, after splitting the dataset by k-fold cross-validation technique, the performance assessment of classical and hybrid machine-deep learning (ML-DL) algorithms is undertaken. Amongst ML techniques, linear regression (LR), random forest (RF), support vector machine (SVM), k-nearest neighbours (KNN), and decision tree (DT) algorithms are studied . In the context of DL, long short-term memory (LSTM), convolutional neural network (CNN), gated recurrent unit (GRU) and their hybrid forms such as LSTM-GRU, CNN-LSTM and CNN-GRU techniques are compared by different error metrics. It is found that the proposed three-layer hierarchical DL algorithm consisting of a convolutional layer coupled with two subsequent GRU levels, which is also hybridized by LR method (i.e., LR-CGRU), leads to lower error metrics. This paper paves the way for data-driven modelling of streamlined *** Codes 68T05 © 2022, CC BY.

关键词： Deep neural networks

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FBSNet: A fast bilateral symmetrical network for real-time semantic segmentation

arXiv

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arXiv 2021年

作者： Gao, Guangwei Xu, Guoan Li, Juncheng Yu, Yi Lu, Huimin Yang, Jian Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo Japan College of Automation Nanjing University of Posts and Telecommunications Nanjing China Center for Mathematical Artificial Intelligence Department of Mathematics The Chinese University of Hong Kong Hong Kong Hong Kong Kyushu Institute of Technology Kitakyushu804-8550 Japan School of Computer Science and Technology Nanjing University of Science and Technology Nanjing China

Real-time semantic segmentation, which can be visually understood as the pixel-level classification task on the input image, currently has broad application prospects, especially in the fast-developing fields of autonomous driving and drone navigation. However, the huge burden of calculation together with redundant parameters are still the obstacles to its technological development. In this paper, we propose a Fast Bilateral Symmetrical Network (FBSNet) to alleviate the above challenges. Specifically, FBSNet employs a symmetrical encoder-decoder structure with two branches, semantic information branch and spatial detail branch. The semantic information branch is the main branch with deep network architecture to acquire the contextual information of the input image and meanwhile acquire sufficient receptive field. While spatial detail branch is shallow and simple network used to establish local dependencies of each pixel for preserving details, which is essential for restoring the original resolution during the decoding phase. Meanwhile, a feature aggregation module (FAM) is designed to effectively combine the output features of the two branches. The experimental results of Cityscapes and CamVid show that the proposed FBSNet can strike a good balance between accuracy and efficiency. Specifically, it obtains 70.9% and 68.9% mIoU along with the inference speed of 90 fps and 120 fps on these two test datasets, respectively, with only 0.62 million parameters on a single RTX 2080Ti GPU. Copyright © 2021, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Dynamics of the competition between two languages

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SeMA Journal 2020年第4期77卷 351-373页

作者： Tchendjeu, A. E. Tchahou Bowong, S. Tchitnga, R. Fotsin, H.B. Department of Computer Engineering National Higher Polytechnic Institute University of Bamenda PO Box 39 Bambili Cameroon Laboratory of Condensed Matters Electronics and Signal Processing (LAMACETS) Department of Physics Faculty of Science University of Dschang PO Box 63 Dschang Cameroon Research Group on Experimental and Applied Physics for Sustainable Development (EAPhySuD) Department of Physics Faculty of Science University of Dschang PO Box 63 Dschang Cameroon Laboratory of Applied Mathematics Department of Mathematics and Computer Science Faculty of Science University of Douala PO Box 24157 Douala Cameroon UMI 209 IRD/UPMC UMMISCO Bondy France LIRIMA Project Team GRIMCAPE Yaounde Cameroon The African Center of Excellence in Information and Communication Technologies (CETIC) University of Yaounde 1 Yaounde Cameroon Institute of Surface Chemistry and Catalysis University of Ulm Albert-Einstein-Allee 47 Ulm 89081 Germany

This paper reports a new kind of mathematical model for language competition dynamics using compartmental epidemiological modeling approach. The model describes the competition between two languages, say the predominant one called language 1, and the less spoken language 2, both in the same community. We distinguish three groups of population building the concerned community: one majority speaking language 1, one minority speaking language 2 and a last minority speaking neither language 1 nor language 2. The study of the proposed model includes an analysis of the evolution of the number of speakers over time. This model predicts that language 2 can inevitably disappear if the threshold parameter R is less than one. We show that our model is well-posed mathematically and linguistically. We also show that the model has basically two linguistic equilibrium points. A monolingual equilibrium point that corresponds to the case where only one language is spoken: some individuals speak only the language 1 and some others do speak neither language 1, nor language 2. A bilingual equilibrium point which corresponds to the case where all the languages are spoken: some individuals speak both languages 1 and 2, some others speak only language 1, while a third group does speak only language 2, and the last group speaks none of the two languages. In this bilingual equilibrium point, both languages coexist. Depending on the threshold parameter, we demonstrate the stability of these equilibria. The model presents on one hand, a direct bifurcation phenomenon, in which we have a stable equilibrium point without bilingual speakers when the associated basic reproduction number is less than one. On the other hand, it presents a stable bilingual equilibrium point when the number of associated basic reproductions is greater than one. The analysis of the overall sensitivity of the model is performed and the impact of the system parameters on the basic reproduction number was performed using

关键词： Bilingualism Compartmental modeling Dynamical system Language competition Stability

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