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6th International Conference on Transportation Information and Safety, ICTIS 2021

作者： Li, Juan Song, Yicheng Zhou, Xinan Yue, Jinjin Yang, Hongtai School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu China

ISBN: (纸本)9781665497138

The outbreak of COVID-19 has greatly impacted all industries of many countries in the world. As an important part of people's daily life, transportation is one of the most severely impacted industries. Taking New York City as an example, this paper explores the decline of taxi ridership due to the COVID-19. The decreased ratio of the actual taxi ridership to the taxi ridership predicted for the no COVID-19 scenario based on historical data is calculated as the dependent variable. The fractional response model is used to study the effect of built environment factors including demographic and socioeconomic, land use, and road-related on the decline of ridership. One model is constructed for each of the four periods, to explore the influence of influencing factors on the dependent variables in different periods. The model results show that the percentage of taxi trips decline is associated with the proportion of high-income people living in the area. The reason could be that these people have more flexible working hours and working places. They can choose to telecommute or travel by private cars to avoid contacting other people during transportation. The analysis of the other factors shows that industrial jobs are related to the low percentage of decline. The model results reveal to us the problem of equity exposed in New York City during the pandemic: limited by jobs(race/income), a portion of citizens are not fully free to choose their travel mode during the pandemic. According to the findings, this paper gives traffic management some policy suggestions. As a result, this study could provide an important reference for policymakers to develop appropriate measures to control the epidemic. © 2021 IEEE.

关键词： COVID-19

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REncoder: A Space-Time Efficient Range Filter with Local Encoder 39

REncoder: A Space-Time Efficient Range Filter with Local Enc...

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39th IEEE International Conference on data engineering, ICDE 2023

作者： Wang, Ziwei Zhong, Zheng Guo, Jiarui Wu, Yuhan Li, Haoyu Yang, Tong Tu, Yaofeng Zhang, Huanchen Cui, Bin Peking University School of Computer Science National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peng Cheng Laboratory Shenzhen China Zte Corporation Beijing China Tsinghua University Beijing China

ISBN: (纸本)9798350322279

A range filter is a data structure to answer range membership queries. Range queries are common in modern applications, and range filters have gained rising attention for improving the performance of range queries by ruling out empty range queries. However, state-of-the-art range filters, such as SuRF and Rosetta, suffer either high false positive rate or low throughput. In this paper, we propose a novel range filter, called REncoder. It organizes all prefixes of keys into a segment tree, and locally encodes the segment tree into a Bloom filter to accelerate queries. REncoder supports diverse workloads by adaptively choosing how many levels of the segment tree to store. We theoretically prove that the error of REncoder is bounded and derive the asymptotic space complexity under the bounded error. We conduct extensive experiments on both synthetic datasets and real datasets. The experimental results show that REncoder outperforms all state-of-the-art range filters. © 2023 IEEE.

关键词： data structures

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RANSACs for 3D Rigid Registration:A Comparative Evaluation

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1861-1878页

作者： Jiaqi Yang Zhiqiang Huang Siwen Quan Zhiguo Cao Yanning Zhang the National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer ScienceNorthwestern Polytechnical UniversityXi’an 710072China the School of Electronic and Control Engineering Chang’an UniversityXi’an 710064China the School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China IEEE

Estimating an accurate six-degree-of-freedom(6-Do F)pose from correspondences with outliers remains a critical issue to 3D rigid *** sample consensus(RANSAC)and its variants are popular solutions to this *** there have been a number of RANSAC-fashion estimators,two issues remain ***,it is unclear which estimator is more appropriate to a particular ***,the impacts of different sampling strategies,hypothesis generation methods,hypothesis evaluation metrics,and stop criteria on the overall estimators remain *** work fills these gaps by first considering six existing RANSAC-fashion methods and then proposing eight variants for a comprehensive *** objective is to thoroughly compare estimators in the RANSAC family,and evaluate the effects of each key stage on the eventual 6-Do F pose estimation *** have been carried out on four standard datasets with different application scenarios,data modalities,and *** provide us with input correspondence sets with a variety of inlier ratios,spatial distributions,and *** on the experimental results,we summarize remarkable outcomes and valuable findings,so as to give practical instructions to real-world applications,and highlight current bottlenecks and potential solutions in this research realm.

关键词： 3D rigid registration performance evaluation point cloud pose estimation

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KVSAgg: Secure Aggregation of Distributed Key-Value Sets 39

KVSAgg: Secure Aggregation of Distributed Key-Value Sets

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39th IEEE International Conference on data engineering, ICDE 2023

作者： Wu, Yuhan Dong, Siyuan Zhou, Yi Zhao, Yikai Fu, Fangcheng Yang, Tong Niu, Chaoyue Wu, Fan Cui, Bin Peking University School of Computer Science National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peng Cheng Laboratory Shenzhen China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China

ISBN: (纸本)9798350322279

In global data analysis, the central server needs the global statistic of the user data stored in local clients. In such cases, an Honest-but-Curious central server might put user privacy at risk in trying to collect individual statistics of each user. In response, the secure aggregation provides a solution for calculating global statistics without revealing users' privacy data. However, existing secure aggregation protocols only focus on the data in the form of vectors or common sets, which limits their application scope. We formalize a general problem - key-value set secure aggregation - that not only includes secure vector aggregation and private set union but also supports more applications. To address the proposed problem, we devise our solution (called the KVSAgg framework) that promises satisfactory performance in security, efficiency, and accuracy. Our key technique is a homomorphic transform algorithm (called HyperIBLT) that is not only capable of bidirectionally transforming data between key-value sets and vectors, but also able to transform sum operation of sets to addition of vectors. We implement KVSAgg on both CPU and GPU platforms and perform the evaluation on three use cases including federated learning, distributed data counting, and finding global hot items. Compared with our baselines, KVSAgg simultaneously achieves the best security, efficiency higher by orders of magnitude, and zero-error in nearly all cases. All codes are open-source anonymously. © 2023 IEEE.

关键词： Vectors

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A Framework for Multiclass Contour Visualization

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IEEE Transactions on Visualization and Computer Graphics 2023年第1期29卷 353-362页

作者： Li, Sihang Yu, Jiacheng Li, Mingxuan Liu, Le Zhang, Xiaolong Luke Yuan, Xiaoru Laboratory of Machine Perception Ministry of Education School of AI Peking University China Center for Data Science Academy for Advanced Interdisciplinary Studies Peking University China National Engineering Laboratory for Big Data Analysis and Application Peking University China School of Computer Science Northwestern Polytechnical University China College of Information Sciences and Technology Pennsylvania State University United States

Multiclass contour visualization is often used to interpret complex data attributes in such fields as weather forecasting, computational fluid dynamics, and artificial intelligence. However, effective and accurate representations of underlying data patterns and correlations can be challenging in multiclass contour visualization, primarily due to the inevitable visual cluttering and occlusions when the number of classes is significant. To address this issue, visualization design must carefully choose design parameters to make visualization more comprehensible. With this goal in mind, we proposed a framework for multiclass contour visualization. The framework has two components: a set of four visualization design parameters, which are developed based on an extensive review of literature on contour visualization, and a declarative domain-specific language (DSL) for creating multiclass contour rendering, which enables a fast exploration of those design parameters. A task-oriented user study was conducted to assess how those design parameters affect users' interpretations of real-world data. The study results offered some suggestions on the value choices of design parameters in multiclass contour visualization. © 2022 IEEE.

关键词： data visualization

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Visible-frequency nonvolatile reconfigurable Janus metasurfaces for dual-wavelength-switched and spin-asymmetric holograms

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Photonics Research 2024年第2期12卷 356-368页

作者： HUAN YUAN ZHEQIANG ZHONG BIN ZHANG College of Electronics and Information Engineering Sichuan UniversityChengdu 610064China Big Data Analysis and Fusion Application Technology Engineering Laboratory of Sichuan Province Chengdu 610065China

Janus metasurface holography with asymmetric transmission characteristics provides new degrees of freedom for multiplexing ***,earlier metasurfaces with asymmetrical transmission faced limitations in terms of tunability and *** this study,we propose a metasurface color holographic encryption scheme with dynamic switching and asymmetric transmission at visible frequencies using a low-loss nonvolatile optical phase-change material,Sb_(2)S_(3).Using a modified holographic optimization strategy,we achieved highfidelity asymmetric holographic imaging of a nanostructured *** controlling the incident direction and wavelength of visible light,as well as the level of crystallization of Sb_(2)S_(3),this reconfigurable metasurface enables the precise manipulation of tunable color holographic image *** particular,in the semi-crystalline state of Sb_(2)S_(3),the encoded information can be securely encrypted using a two-channel color-holographic image,whereas only a preset camouflaged image is displayed in the crystalline or amorphous state of Sb_(2)S_(3).The proposed multiencrypted Janus metasurface provides a potential approach for dynamic holographic displays with ultrahigh capacity,holographic encryption,and information storage.

关键词： holographic asymmetric visible

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Three-Dimensional Modeling of Maize Canopies Based on Computational Intelligence

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Plant Phenomics 2024年第2期6卷 349-363页

作者： Yandong Wu Weiliang Wen Shenghao Gu Guanmin Huang Chuanyu Wang Xianju Lu Pengliang Xiao Xinyu Guo Linsheng Huang National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230601China Information Technology Research Center Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China Beijing Key Lab of Digital Plant National Engineering Research Center for Information Technology in AgricultureBeijing 100097China Nongxin Science&Technology(Beijing)Co. LtdBeijing 100097China

The 3-dimensional(3D)modeling of crop canopies is fundamental for studying functional-structural plant *** studies often fail to capture the structural characteristics of crop canopies,such as organ overlapping and resource *** address this issue,we propose a 3D maize modeling method based on computational *** initial 3D maize canopy is created using the t-distribution method to reflect characteristics of the plant architecture.

关键词： intelligence modeling based canopies computational dimensional maize three

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Improvement in oxidation resistance of Cantor alloy through microstructure tailoring

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China Foundry 2022年第6期19卷 503-510页

作者： Bao-lin Pang Man Wang Yue-gang Shen Xiao-li Xi Zuo-ren Nie Collaborative Innovation Center of Capital Resource-Recycling Material Technology Faculty of Materials and ManufacturingBeijing University of TechnologyBeijing 100124China Key Laboratory of Advanced Functional Materials Ministry of EducationBeijing University of TechnologyBeijing 100124China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of TechnologyBeijing 100124China

A method of improving the oxidation resistance of Cantor alloy through microstructure tailoring was *** with distinctive microstructures were achieved by different annealing treatments on the cold-rolled Cantor *** test was then carried out on the various annealed samples at 800°C for 24 h in *** oxidation behavior was evaluated in terms of oxidation rate,surface and cross-section microstructure *** stratified oxide layers including outer Mn_(2)O_(3) and inner Cr_(2)O_(3) were observed in all the annealed samples,the thickness of Mn_(2)O_(3) and Cr_(2)O_(3) layers was ***,the samples exhibited different oxidation *** results indicate that the oxidation resistance of various annealed samples is closely related with grain size as well as twin density.

关键词： Cantor alloy annealing temperature grain size twins oxidation behavior

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analysis of anti-interference ability of hyperspectral sensitive features to wheat powdery mildew 8

Analysis of anti-interference ability of hyperspectral sensi...

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8th Annual International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2020

作者： Zhao, Jinling Chu, Guomin Yan, Hao Hu, Lei Xue, Yongan National Engineering Research Center for Analysis and Application of Agro-Ecological Big Data Anhui University Hefei230601 China College of Mining Engineering Taiyuan University of Technology Taiyuan030024 China

The development of ground-based, airborne and spaceborne remote sensing has greatly facilitated the identification and diagnosis of various objects. Corresponding algorithms and methods of removing interference from remotely sensed imagery have been proposed. Nevertheless, the studies on anti-interference ability of selected features have not been fully considered. In our study, the hyperspectral reflectance of leaf-scale powdery mildew (Erysiphe graminis) on winter wheat were collected as the testing dataset. A total of seven representative spectral features of Landsat-8 Operational Land Imager (OLI) and GaoFen-1 Wide-Field-View (WFV) was selected, namely, original blue, green, red, near-infrared (NIR) bands and normalized difference vegetation index (NDVI), normalized difference greenness index (NDGI), structure insensitive pigment index (SIPI). Four hyperspectral vegetation indices including red edge (MSR) simple ratio index, NDVI, green band and SIPI were also selected. Three primary background noises including soil, cloud and white poplar (Populus alba L.) were added into the spectral signal. The correlation coefficient (R) between disease severities (0, 1, 2, 3 and 4) and spectral features was used to estimate the anti-interference ability. The results show that there is a generally similar spectral performance for the two sensors, but Landsat-8 OLI is superior to GF-1 WVF in terms of spectral response. The green band was greatly affected with the R values decreasing from 0.77 to 0.35. The MSR and NDVI showed a gradual decrease with the increase of three background noises. The study shows that background noises must be removed when acquiring spectral data and stable spectral features should be also selected by evaluating the anti-interference ability. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Landsat

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The impact of selfish driving behavior of autonomous vehicles on mixed traffic flow

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Physica A: Statistical Mechanics and its applications 2025年 672卷

作者： Yunxia Wu Le Li Chenming Jiang Yangsheng Jiang Zhihong Yao National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu Sichuan 611756 China School of Transportation and Logistics Southwest Jiaotong University Chengdu Sichuan 610031 China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu Sichuan 611756 China China Institute of FTZ Supply Chain Shanghai Maritime University Shanghai 201306 China

With the development of automatic control and artificial intelligence technology, autonomous vehicles (AVs) are becoming more and more intelligent. However, this individual intelligence means that the driving behavior of AVs can be more aggressive and selfish. To investigate the impact of the selfish driving behavior of AVs on the characteristics of mixed traffic flow, this paper proposes a cellular automata model that considers the selfish driving behavior of AVs. First, we analyze the vehicle types‌ in the current mixed traffic flow and develop a universal safety distance model. Then, based on this, a cellular automata model is proposed. This model can not only describe the longitudinal car-following and lateral lane-changing behavior of human-driven vehicles and AVs, but also characterize the selfish degree in the driving behavior of AVs. Finally, simulation experiments are designed to analyze the impact of the selfish driving behavior of AVs on the performance indicators of mixed traffic flow. The results show that: (1) The increase in the penetration rate of AVs has a positive effect on the average velocity, traffic stability, and throughput of mixed traffic flow; (2) On the whole, the selfish lane-changing behavior of AVs has a relatively small impact on the average velocity of mixed traffic flow. The impact becomes smaller with the increase in traffic density. (3) In most scenarios, the selfish car-following behavior of AVs has an improving effect on the average velocity and throughput of mixed traffic flow. In summary, the relevant research results can provide theoretical support for the design of micro-behavioral control schemes for AVs.

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