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Differences in single-vehicle motorcycle crashes caused by distraction and overspeed behaviors: considering temporal shifts and unobserved heterogeneity in prediction

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International Journal for Consumer and Product Safety 2023年第3期30卷

作者： Chenzhu Wang Muhammad Ijaz Fei Chen Dongdong Song Mingyu Hou Yunlong Zhang Jianchuan Cheng Muhammad Zahid a School of Transportation Southeast University Nanjing Jiangsu China b School of Transportation and Logistics Southwest Jiaotong University Chengdu Sichuan China c MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing China d Zachry Department of Civil Environmental Engineering Texas A&M University College Station TX USA e Department of Civil Geological and Mining Engineering École Polytechnique de Montréal Canada

Distraction and overspeed behaviors are acknowledged as two significant contributors to single-vehicle motorcycle crashes, injuries and fatalities resulting from which are severe and critical issues in Pakistan. To explore the temporal instability and differences in the factors determining the injury severities between single-vehicle motorcycle crashes caused by distraction and overspeed behaviors, this study estimated two groups of random parameter logit models with heterogeneity in means and variances. Single-vehicle motorcycle crash data in Rawalpindi city between 2017 and 2019 was used for model estimation, and a wide variety of explanatory variables relating to the rider, roadways, environments, and temporal attributes was simulated in the models. The current study considered three possible crash injury severity outcomes: minor injury, severe injury and fatal injury. Likelihood ratio tests were conducted to explore the temporal instability and non-transferability. Marginal effects were also calculated to further reveal temporal instability of the variables. Except for several variables, the most significant factors reported temporal instability and non-transferability, manifested as the effects varied from year to year and across different crashes. Moreover, out-of-sample prediction was also implemented to capture temporal instability and non-transferability between distraction and overspeed crash observations. The non-transferability between motorcycle crashes caused by distraction and overspeed behaviors provides insights into developing differentiated countermeasures and policies targeted at preventing and mitigating single-vehicle motorcycle crashes caused by the two risk-taking behaviors.

关键词： Temporal stability single-vehicle motorcycle crashes risk-taking behaviors injury severity out-of-sample prediction random parameters logit model

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Multi-view ontology alignment visualization (MOAV): A human-cognition based ontology alignment visualization technique

Journal of Network Intelligence

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Journal of Network Intelligence 2020年第4期5卷 198-210页

作者： Chen, Jie Zhang, Jie Xue, Xingsi Huang, Yikun Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No.33 Xueyuan Road University Town Minhou FuzhouFujian350118 China School of Computer Science and Engineering Yulin Normal University No.299 Education Middle Road Yulin CityGuanxi Province537000 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Intelligent Information Processing Research Center Fujian University of Technology No.33 Xueyuan Road University Town Minhou FuzhouFujian350118 China Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology No.1 Jinji Road Guangxi Guilin541004 China Department of Information Technology Concord University College Fujian Normal University No.68 Xueyuan Road University Town Minhou FuzhouFujian350117 China

To further improve the quality of ontology alignment, it is necessary for an ontology matcher to introduce a user’s knowledge into its automatic matching process, which yields the development of interactive ontology matching techniques. Since validating problematic entity correspondences is a difficult cognition task, user interaction based on Ontology Alignment Visualization (OAV) has become the critical component of an interactive ontology matcher, which directly affects the quality of validating result and the efficiency of validating process. The existing OAV tools are mainly developed based on their designers’ subjective feelings and experiences, which do not take into consideration the law of human cognition. To improve the efficiency of the ontology alignment validating process, in this paper, a Multi-view OAV (MOAV) is proposed, which synthetically utilizes the human cognitive theory-information visualization and human-computer inter-action. The experiment utilizes the Ontology Alignment Evaluation Initiative (OAEI)’s benchmark to test the performance of our proposal, and the experimental results show that MOAV can effectively improve a user’s validating efficiency. © 2020, Taiwan Ubiquitous Information. All rights reserved.

关键词： Visualization

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An Iteratively Optimized Patch Label Inference Network for Automatic Pavement Distress Detection

arXiv

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arXiv 2020年

作者： Tang, Wenhao Huang, Sheng Zhao, Qiming Li, Ren Huangfu, Luwen Ministry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing400044 China The School of Big Data and Software Engineering Chongqing University Chonqqing400044 China Chongqing Jiaotong University 400074 China Fowler College of Business San Diego State University San DiegoCA92182 United States

We present a novel deep learning framework named the Iteratively Optimized Patch Label Inference Network (IOPLIN) for automatically detecting various pavement distresses that are not solely limited to specific ones, such as cracks and potholes. IOPLIN can be iteratively trained with only the image label via the Expectation-Maximization Inspired Patch Label Distillation (EMIPLD) strategy, and accomplish this task well by inferring the labels of patches from the pavement images. IOPLIN enjoys many desirable properties over the state-of-the-art single branch CNN models such as GoogLeNet and EfficientNet. It is able to handle images in different resolutions, and sufficiently utilize image information particularly for the high-resolution ones, since IOPLIN extracts the visual features from unrevised image patches instead of the resized entire image. Moreover, it can roughly localize the pavement distress without using any prior localization information in the training phase. In order to better evaluate the effectiveness of our method in practice, we construct a large-scale Bituminous Pavement Disease Detection dataset named CQU-BPDD consisting of 60,059 high-resolution pavement images, which are acquired from different areas at different times. Extensive results on this dataset demonstrate the superiority of IOPLIN over the state-of-the-art image classification approaches in automatic pavement distress detection. The source codes of IOPLIN are released on https://***/DearCaat/ioplin, and the CQU-BPDD dataset is able to be accessed on https://***/CQU-BPDD/. © 2020, CC BY-NC-SA.

关键词： Large dataset

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Ball k-means

arXiv

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arXiv 2020年

作者： Xia, Shuyin Peng, Daowan Meng, Deyu Zhang, Changqing Wang, Guoyin Chen, Zizhong Wei, Wei Department of Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China National Engineering Laboratory for Algorithm and Analysis Technologiy on Big Data Xian Jiaotong University Xi'an710049 China College of Intelligence and Computing Tianjin University 300072 China Department of Computer Science and Engineering University of California Riverside 900 University Avenue RiversideCA92521 United States School of Computer Science and Engineering Xi'an University of Technology Xi'an710048 China

This paper presents a novel accelerated exact k-means algorithm called the Ball k-means algorithm, which uses a ball to describe a cluster, focusing on reducing the point-centroid distance computation. The Ball k-means can accurately find the neighbor clusters for each cluster resulting distance computations only between a point and its neighbor clusters centroids instead of all centroids. Moreover, each cluster can be divided into a stable area and an active area, and the later one can be further divided into annulus areas. The assigned cluster of the points in the stable area is not changed in the current iteration while the points in the annulus area will be adjusted within a few neighbor clusters in the current iteration. Also, there are no upper or lower bounds in the proposed Ball k-means. Furthermore, reducing centroid-centroid distance computation between iterations makes it efficient for large k clustering. The fast speed, no extra parameters and simple design of the Ball k-means make it an all-around replacement of the naive k-means algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： K-means clustering

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Contact lenses detection based on the Gaussian curvature

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Journal of Computers (Taiwan) 2019年第2期30卷 158-164页

作者： Wang, Junrui Tian, Qichuan School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing100044 China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044 China

Iris recognition is a kind of biometrics recognition with good stability, which is reliable, effective and safe. However, some attack means such as paper printed iris, iris images, simulated eyes, color contact lenses and the others are quite deceptive for iris recognition system. The recognition result of iris recognition system is meaningful only when the authenticity of the feature is guaranteed. At present, the iris anti-spoofing with contact lenses is seldom studied, and the recognition rate is not ideal. Based on the above background, aiming at the characteristics of gaussian curvature change of corneal outer surface caused by wearing contact lenses, this essay proposes a detection method of contact lenses based on depth feature. The effective depth information of cornea is obtained by depth camera, gaussian curvature of cornea is calculated, and features are extracted by sum of squared deviations. Experimental results show that this method can effectively identify whether to wear contact lenses, low error rate, high efficiency, which can meet the requirements of practical application. © 2019 Computer Society of the Republic of China. All rights reserved.

关键词： Contact lenses

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Micro-supervised disturbance learning: A perspective of representation probability distribution

arXiv

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arXiv 2020年

作者： Chu, Jielei Liu, Jing Wang, Hongjun Meng, Hua Gong, Zhiguo Li, Tianrui The School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China The School of Business Sichuan University Sichuan Chengdu610065 China The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China

The instability is shown in the existing methods of representation learning based on Euclidean distance under a broad set of conditions. Furthermore, the scarcity and high cost of labels prompt us to explore more expressive representation learning methods which depends on the labels as few as possible. To address these issues, the small-perturbation ideology is firstly introduced on the representation learning model based on the representation probability distribution. The positive small-perturbation information (SPI) which only depend on two labels of each cluster is used to stimulate the representation probability distribution and then two variant models are proposed to fine-tune the expected representation distribution of RBM, namely, Micro-supervised Disturbance GRBM (Micro-DGRBM) and Micro-supervised Disturbance RBM (Micro-DRBM) models. The Kullback-Leibler (KL) divergence of SPI is minimized in the same cluster to promote the representation probability distributions to become more similar in Contrastive Divergence (CD) learning. In contrast, the KL divergence of SPI is maximized in the different clusters to enforce the representation probability distributions to become more dissimilar in CD learning. To explore the representation learning capability under the continuous stimulation of the SPI, we present a deep Micro-supervised Disturbance Learning (Micro-DL) framework based on the Micro-DGRBM and Micro-DRBM models and compare it with a similar deep structure which has not any external stimulation. Experimental results demonstrate that the proposed deep Micro-DL architecture shows better performance in comparison to the baseline method, the most related shallow models and deep frameworks for clustering. © 2020, CC0.

关键词： Probability distributions

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Asymptotic properties of zeros for discrete-time linear systems with backward triangle sampled-and-hold using delta operator

Asymptotic properties of zeros for discrete-time linear syst...

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Chinese Automation Congress (CAC)

作者： Minghui Ou Shan Liang Xiaobin Wu Zhiyong Yang Hehuan Ran School of Big Data and Internet of Things of Chongqing Vocational Institute of Engineering College of Automation of Chongqing University Chongqing China College of Automation of Chongqing University The Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing China State Grid Chongqing Shiqu Electric Power Supply Branch Chongqing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

This article focuses on a well-studied theoretical problem that, for rapid sampling, a continuous-time system with minimum-phase properties may become a non-minimum phase discrete-time system in the discretization process. The properties of zeros for discrete-time linear models in the field of digital control when using the special shift operator was considered in this paper. From the former relevant studies one can know that the backward triangle sample-and-hold (BTSH) as an alternative hold method to discretize the continuous-time systems has an advantage over ZOH in stabilizing sampling zeros for linear system with classical forward shift operator. In this article, we deduce the exact sampled-data model of linear system using delta operator to replace forward shift operator in the case of BTSH. Furthermore, the expressions and properties of zeros for the corresponding discrete-time system are derived.

关键词： Control systems Linear systems Discrete-time systems Process control Numerical models Signal reconstruction Internet of Things

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Illuminating Recommendation by Understanding the Explicit Item Relations

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Journal of Computer Science & Technology 2018年第4期33卷 739-755页

作者： Qi Liu Hong-Ke Zhao Le Wu Zhi Li En-Hong Chen Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of China Hefei 230027 China School of Computer and Information Hefei University of Technology Hefei 230009 China School of Software Engineering University of Science and Technology of China Hefei 230051 China

Recent years have witnessed the prevalence of recommender systems in various fields, which provide a personalized recommendation list for each user based on various kinds of information. For quite a long time, most researchers have been pursing recommendation performances with predefined metrics, e.g., accuracy. However, in real-world applications, users select items from a huge item list by considering their internal personalized demand and external constraints. Thus, we argue that explicitly modeling the complex relations among items under domain-specific applications is an indispensable part for enhancing the recommendations. Actually, in this area, researchers have done some work to understand the item relations gradually from ＂implicit＂ to ＂explicit＂ views when recommending. To this end, in this paper, we conduct a survey of these recent advances on recommender systems from the perspective of the explicit item relation understanding. We organize these relevant studies from three types of item relations, i.e., combination-effect relations, sequence-dependence relations, and external-constraint relations. Specifically, the combination-effect relation and the sequence-dependence relation based work models the intra-group intrinsic relations of items from the user demand perspective, and the external-constraint relation emphasizes the external requirements for items. After that, we also propose our opinions on the open issues along the line of understanding item relations and suggest some future research directions in recommendation area.

关键词： recommender system item relation recommendation interpretability

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Distributed Local Bayesian Network for Gene Regulatory Network Reconstruction

Distributed Local Bayesian Network for Gene Regulatory Netwo...

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International Conference on big data Computing and Communications (bigCOM)

作者： Luxuan Qu Zhiqiong Wang Yueyang Huo Yuezhou Zhou Junchang Xin Wei Qian College of Medicine and Biological Information Engineering Northeastern University Shenyang China College of Medicine and Biological Information Engineering Northeastern University Neusoft Research of Intelligent Healthcare Technology Co. Ltd. Shenyang China School of Computer Science and Engineering Key Laboratory of Big Data Management and Analytics (Liaoning Province) Northeastern University Shenyang China College of Engineering The University of Texas at El Paso El Paso USA

ISBN: (数字)9781728182759

ISBN: (纸本)9781728182766

Gene regulatory network provides an effective way to study functional genomes. Reconstruction of gene regulatory network can better help us to reveal the regulatory relationship and complex mechanism between genes, thus exploring the essence of biological systems and lives. At present, the modeling methods of gene regulatory network either solve the problem of accuracy or scale of gene regulatory network by optimizing the model or combining various models. However, with the continuous increase of network scale and the computational complexity, the reconstruction of the network has exceeded the ability of single machine. Thus, we presented the Distributed Local Bayesian Network (D-LBN) method based on MapReduce framework to solve this problem. D-LBN is based on LBN algorithm which uses mutual information method, k-nearest neighbor algorithm, Bayesian network model and conditional mutual information method to reconstruct gene regulatory network. D-LBN realizes distributed computing using MapReduce framework at the step of regulatory direction learning with Bayesian network model to achieve the purpose of reconstructing large-scale gene regulatory network. Experiments based on two scales of dataset is done to verify the performance of D-LBN in reconstructing gene regulatory network at different scales. The results show that D-LBN is consistent with LBN in evaluation index and much more efficient than LBN on large-scale network reconstruction. And the scale of the network that can be reconstructed is also greatly improved.

关键词： Bayes methods Computational modeling Mutual information Mathematical model Biological system modeling Entropy

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Cellular automaton modeling of pedestrian movement behavior on an escalator

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Chinese Physics B 2018年第12期27卷 328-333页

作者： Fu-Rong Yue Juan Chen Jian Ma Wei-Guo Song Siu-Ming Lo School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong University Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention State Key Laboratory of Fire Science University of Science and Technology of China Department of Architectural and Civil Engineering City University of Hong Kong

As a convenient passenger transit facility between floors with different heights, escalators have been extensively used in shopping malls, metro stations, airport terminals, etc. Compared with other vertical transit facilities including stairs and elevators, escalators usually have large transit capacity. It is expected to reduce pedestrian traveling time and thus improve the quality of pedestrian’s experiences especially in jamming conditions. However, it is noticed that pedestrians may present different movement patterns, e.g., queuing on each step of the escalator, walking on the left-side and meanwhile standing on the right-side of the escalator. These different patterns affect the actual escalator traffic volume and finally the passenger spatiotemporal distribution in different built environments. Thus, in the present study, a microscopic cellular automaton(CA) simulation model considering pedestrian movement behavior on escalators is built. Simulations are performed considering different pedestrian movement speeds, queuing modes, and segregation on escalators with different escalator *** actual escalator capacities under different pedestrian movement patterns are investigated. It is found that walking on escalators will not always benefit escalator transit volume improvement, especially in jamming conditions.

关键词： cellular automaton pedestrian movement escalator capacity

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