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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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Online learning with sparse labels

Online learning with sparse labels

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作者： He, Wenwu Zou, Fumin Liang, Quan School of Mathematics and Physics Fujian University of Technology Fujian China Fujian Collaborative Innovation Center for Beidou Navigation and Intelligent Traffic Fujian China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fujian China School of Information Science and Engineering Fujian University of Technology Fujian China

In this paper, we consider an online learning scenario where the instances arrive sequentially with partly revealed labels. We assume that the labels of instances are revealed randomly according to some distribution, eg, Bernoulli distribution. Three specific algorithms based on different inspirations are developed. The first one performs the idea of Estimated gradient for which a strict high-probability regret guarantee in scale of (Formula presented.) can be derived, when the distributing parameter p is revealed. An empirical version is also developed for cases where the learner has to learn the parameter p when it is not revealed. Experiments on several benchmark data sets show the feasibility of the proposed method. To further improve the performance, two kinds of aggressive algorithms are presented. The first one is based on the idea of instances recalling, which tries to get the full use of the labeled instances. The second one is based on the idea of labels learning, and it tries to learn the labels for unlabeled instances. In particular, it includes the step of online co-learning, which aims to learn the labels, and the step of weighted voting, which aims to make the final decision. Empirical results confirm the positive effects of the two aggressive algorithms. © 2018 John Wiley & Sons, Ltd.

关键词： E-learning

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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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Border identification and spatial evolution of metropolitan areas by surface network analysis using nighttime light data

Information Geography

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Information Geography 2025年第1期1卷

作者： Congxiao Wang Zuoqi Chen Bin Wu Hong Zhang Honghuan Gu Yue Tu Wei Li Yuan Yuan Bailang Yu Key Laboratory of Geographic Information Science (Ministry of Education) East China Normal University Shanghai 200241 China School of Geographic Sciences East China Normal University Shanghai 200241 China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology Fuzhou University Fuzhou 350108 China The Academy of Digital China Fuzhou University Fuzhou 350108 China School of Geospatial Engineering and Science Sun Yat-sen University Zhuhai 519082 China Institute for Global Innovation and Development East China Normal University Shanghai 200241 China Institute of Urban and Demographic Studies Shanghai Academy of Social Sciences Shanghai 200020 China Research Center for China Administrative Division East China Normal University Shanghai 200241 China

Metropolitan areas are described as large population centers consisting of a central city and its surrounding suburbs and exurbs. Traditionally, metropolitan areas are delineated based on travel time to a fixed urban center, without considering the dynamic evolution of urban centers. As a result, long-term analyses of the spatial interactions of metropolitan areas within urban agglomerations may be biased. Therefore, we propose a surface network method to identify the evolving metropolitan areas. In this surface network, nodes and edges—representing urban centers and their connections—are identified from nighttime light (NTL) data, with edge weights representing travel times. We then divide the surface network into sub-networks based on edge weights, each of which is considered a metropolitan area. Using the Yangtze River Delta Region (YRDR) as a case study, we examined the development trajectories of its metropolitan areas over a 20-year period at five-year intervals, focusing on both agglomeration-oriented and diffusion-oriented pathways. We found a significant increase in the number and size of metropolitan areas within the YRDR, which experienced an evolutionary process of “agglomeration–diffusion–re-agglomeration” that closely aligns with the region's strategic development plan. This study provides complementary insights into the evolutionary dynamics of urban systems and may serve as a useful reference for regional-scale urban planning.

关键词： Metropolitan areas Nighttime light Urban network Urban dynamics

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Electric Vehicle Charging Control Based on Smart Grid Big data

Electric Vehicle Charging Control Based on Smart Grid Big Da...

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International Conference on Intelligent Computing, Automation and Systems (ICICAS)

作者： Kuo-Chi Chang Ze Xu Kai-Chun Chu Fu-Hsiang Chang Hsiao-Chuan Wang Tsui-Lien Hsu Yuh-Chung Lin Yuwen Zhou North Borneo University College Sabah Malaysia Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Fujian University of Technology Fuzhou China Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan

At the same time, the burning of a large amount of fossil fuels has aggravated environmental pollution and the greenhouse effect. In order to solve the problems of energy shortage and environmental pollution, electric vehicle technology has been highly valued by many countries. Electric vehicles are the most promising new energy vehicles. Therefore, on the basis of fully considering the charging load characteristics of electric vehicles, how to better establish charging facilities and adjust the impact of a large number of random loads on the grid. Therefore, it is of great significance and application value to study the charging strategy and control method of electric vehicles to improve the stable operation level of the power grid and the ability to accept new energy. Here, the frequency modulation control strategy of electric vehicles considering the restriction of electricity price is studied to ensure the regulation ability and charging demand of electric vehicles.

关键词： Industries Pollution Frequency modulation Greenhouse effect Electric vehicles Regulation Fossil fuels

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Design of Primary System for 110kV Smart Substation

Design of Primary System for 110kV Smart Substation

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International Conference on Intelligent Computing, Automation and Systems (ICICAS)

作者： Kuo-Chi Chang Hongkai Chen Kai-Chun Chu Fu-Hsiang Chang Hsiao-Chuan Wang Tsui-Lien Hsu Yuh-Chung Lin Yuwen Zhou North Borneo University College Sabah Malaysia Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Fujian University of Technology Fuzhou China Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan

Substation is the bridge between power plant and load, and it is the place where high-quality energy is transported. And China's power technology has been in the world's top level, because of the complex terrain in China, so the design of power station should consider the impact of terrain factors, economic factors, and future development factors and so on. Therefore, smart substation design is worthy of our research and innovation. Installation of lightning arrester can effectively reduce the threat of lightning.

关键词： Wiring Arresters Substations Short-circuit currents Lightning Stability analysis Circuit stability

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Modeling the contribution of the microbial carbon pump to carbon sequestration in the South China Sea

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Science China Earth Sciences 2018年第11期61卷 1594-1604页

作者： Wenfang LU Yawei LUO Xiaohai YAN Yuwu JIANG State Key Laboratory of Marine Environmental Science College of Ocean and Earth Sciences Xiamen University Center for Remote Sensing College of Earth Ocean and Environment University of Delaware Joint Institute for Coastal Research and Management Xiamen University Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National Engineering Research Centre of Geospatial Information Technology Fuzhou University

The two key mechanisms for biologically driven carbon sequestration in oceans are the biological pump(BP) and the microbial carbon pump(MCP); the latter is scarcely simulated and quantified in the China seas. In this study, we developed a coupled physical-ecosystem model with major MCP processes in the South China Sea(SCS). The model estimated a SCSaveraged MCP rate of 1.55 mg C m^(-2) d^(-1), with an MCP-to-BP ratio of 1:6.08 when considering the BP at a depth of 1000 ***, the ecosystem responses were projected in two representative global warming scenarios where the sea surface temperature increased by 2 and 4°C. The projection suggested a declined productivity associated with the increased near-surface stratification and decreased nutrient supply, which leads to a reduction in diatom biomass and consequently the suppression of the BP. However, the relative ratio of picophytoplankton increased, inducing a higher microbial activity and a nonlinear response of MCP to the increase in temperature. On average, the ratio of MCP-to-BP at a 1000-m depth increased to 1:5.95 with surface warming of 4°C, indicating the higher impact of MCP in future ocean carbon sequestration.

关键词： South China Sea Microbial Carbon Pump Global change Numerical model

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Analysis for the Change of Aquaculture Area and Water Quality in Sansha Bay During 2010-2018

Analysis for the Change of Aquaculture Area and Water Qualit...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： YunZhi Chen YuShuang Wang TingTing Xie MingHui Zhang Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology Fuzhou University

Using Landsat 8 OLI, GF-1, GF-2 and ALOS satellite images, the distribution of aquaculture in 2010-2018 in Sansha Bay were extracted through SVM and the spatial and temporal changes of aquaculture area were detected. Next, analyze the impact of the spatial changes on local water quality which was evaluated by C Chl-a , C COD , C DIP , C DIN . The results show that:(1). During 2010-2018, the area of cage culture remained stable while the algae culture's area has grown every year expect 2017 affected by algae growth time. (2). In 2010-2014, the algae culture was transferred from the western port area to the northeastern Dongwu Ocean and then move to the central sea area in the next three years. In 2017-2018, removal of large-scale culture from non-cultivation area of the central sea. (3). The distribution of culture is proportional to the concentration of Chl-a and COD, and C Chl-a of algae aquaculture area is higher than that of cage area.

关键词： Aquaculture Algae Remote sensing Support vector machines Artificial satellites Earth data mining

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A two-phase approach for locally differentially private fuzzy co-clustering

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Information Sciences 2025年 718卷

作者： Pengfei Zhang Jianlong An Xiang Cheng Youwen Zhu Ji Zhang Zhikun Zhang State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining No. 168 Shungeng Road Tianjiaan District 232001 Huainan China School of Computer Science and Engineering Anhui University of Science and Technology No. 168 Shungeng Road Tianjiaan District 232001 Huainan China Yunnan Key Laboratory of Service Computing Yunnan University of Finance and Economics No. 237 Longquan Road Kunming 650221 Yunnan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) No. 3501 Daxue Road Jinan 255020 Shandong China Key Laboratory of Equipment Data Security and Guarantee Technology Guilin University of Electronic Technology No. 1 Jinji Road Guilin 541010 Guangxi China State Key Laboratory of Networking and Switching Technology No. 10 Xitucheng Road Haidian District 100876 Beijing China Beijing University of Posts and Telecommunications No. 10 Xitucheng Road Haidian District 100876 Beijing China College of Computer and Data Science Nanjing University of Aeronautics and Astronautics No. 29 Yudao Street Qinhuai District Nanjing 210016 Jiangsu China School of Mathematics Physics and Computing University of Southern Queensland West Street Toowoomba 4350 Queensland Australia College of Computer Science and Technology Zhejiang University No. 38 Zheda Road Xihu District 310027 Hangzhou China

Clustering analysis is important for providing personalized services across various user experience optimization. As an advanced clustering technique, Fuzzy Co-Clustering ( FCC ) excels at handling high-dimensional data by simultaneously grouping both samples and attributes while allowing objects to belong to multiple clusters. To alleviate the potential privacy risks posed by directly using raw data, researchers often employ local differential privacy (LDP) techniques for protection. However, current clustering studies under LDP either directly perform clustering on the high-dimensional data, which necessitates splitting the privacy budget heavily, leading to excessive noise injection, or fail to adequately address the impact of Laplacian noise on both objective function modeling and distance metric selection, resulting in reduced clustering accuracy. To address these limitations, we present a two-phase approach SONY , which allocates part of the privacy budget to evaluate attribute importance and perform dimensionality reduction accordingly, and then utilizes the remaining budget to conduct noise-aware clustering on the pruned data. Our key technical contributions include: (1) a Noise-aware Similarity Calculation method ( NSC ) that replaces traditional Euclidean distance with a specialized metric which accounts for the statistical properties of Laplacian noise; (2) an importance-driven dimension reduction and budget allocation method ( IDRBA ) which optimizes both attribute selection and privacy budget allocation; and (3) an outlier-aware objective function calculation method ( OOC ) which enhances robustness against potential noise-induced outliers. We provide theoretical guarantees for SONY 's convergence, privacy preservation, utility bounds, and computational complexity. Experimental evaluations conducted on two real-world datasets and one synthetic dataset, demonstrate that SONY outperforms the state-of-the-arts by at least 14% in F-Measure and 10% in Entrop

关键词： Fuzzy co-clustering Local differential privacy Privacy protection Two phase

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Kernelized multiview subspace analysis by self-weighted learning

arXiv

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arXiv 2019年

作者： Wang, Huibing Wang, Yang Zhang, Zhao Fu, Xianping Wang, Meng College of Information and Science Technology Dalian Maritime University Dalian Liaoning116021 China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Hefei University of Technology China

—With the popularity of multimedia technology, information is always represented or transmitted from multiple views. Most of the existing algorithms are graph-based ones to learn the complex structures within multiview data but overlooked the information within data representations. Furthermore, many existing works treat multiple views discriminatively by introducing some hyperparameters, which is undesirable in practice. To this end, abundant multiview based methods have been proposed for dimension reduction. However, there are still no research to leverage the existing work into a unified framework. To address this issue, in this paper, we propose a general framework for multiview data dimension reduction, named Kernelized Multiview Subspace Analysis (KMSA). It directly handles the multi-view feature representation in the kernel space, which provides a feasible channel for direct manipulations on multiview data with different dimensions. Meanwhile, compared with those graph-based methods, KMSA can fully exploit information from multiview data with nothing to lose. Furthermore, since different views have different influences on KMSA, we propose a self-weighted strategy to treat different views discriminatively according to their contributions. A co-regularized term is proposed to promote the mutual learning from multi-views. KMSA combines self-weighted learning with the co-regularized term to learn appropriate weights for all views. We also discuss the influence of the parameters in KMSA regarding the weights of multi-views. We evaluate our proposed framework on 6 multiview datasets for classification and image retrieval. The experimental results validate the advantages of our proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Multimedia systems

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