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39th IEEE International Conference on data engineering, ICDE 2023

作者： Qiu, Rui Ming, Yi Hong, Yisen Li, Haoyu Yang, Tong Peking University School of Computer Science National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peking University Academy for Advanced Interdisciplinary Studies China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350322279

Graphs are good at presenting relational and structural information, making it powerful in the representation of various data. For the efficient storage and processing of graph-like data, graph databases have been rapidly developed and extensively studied. However, graph databases mostly use adjacency lists as their basic data structure (e.g., Neo4j), which could result in poor performance of edge due to the skewed degree distribution of *** design the Wind-Bell Index to address this problem. Wind-Bell Index is a memory-efficient index data structure, which can be attached to existing graph databases to speed up the edge. We have fully implemented our data structure in Neo4j, the most popular graph database today, and conduct theoretical and experimental analysis to evaluate the performance. Theoretical results prove the high query efficiency of our algorithm. And experimental results show that the average edge query speed is increased by hundreds of times compared with the original query interface of Neo4j. We believe that the excellent performance and scalability of Wind-Bell Index make it suitable for the application in a variety of graph databases. © 2023 IEEE.

关键词： Graph databases

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Visual-semantic network: a visual and semantic enhanced model for gesture recognition

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Visual Intelligence 2023年第1期1卷 1-13页

作者： Wang, Yizhe Cao, Congqi Zhang, Yanning National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an 710129 China

Gesture recognition has attracted considerable attention and made encouraging progress in recent years due to its great potential in applications. However, the spatial and temporal modeling in gesture recognition is still a problem to be solved. Specifically, existing works lack efficient temporal modeling and effective spatial attention capacity. To efficiently model temporal information, we first propose a long- and short-term temporal shift module (LS-TSM) that models the long-term and short-term temporal information simultaneously. Then, we propose a spatial attention module (SAM) that focuses on where the change primarily occurs to obtain effective spatial attention capacity. In addition, the semantic relationship among gestures is helpful in gesture recognition. However, this is usually neglected by previous works. Therefore, we propose a label relation module (LRM) that takes full advantage of the relationship among classes based on their labels’ semantic information. To explore the best form of LRM, we design four different semantic reconstruction methods to incorporate the semantic relationship information into the class label’s semantic space. We perform extensive ablation studies to analyze the best settings of each module. The best form of LRM is utilized to build our visual-semantic network (VS Network), which achieves the state-of-the-art performance on two gesture datasets, i.e., EgoGesture and NVGesture. © The Author(s) 2023.

关键词： Gesture recognition Semantic relationship Spatial attention Temporal modeling

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Continuous and generalized visual odometry based on FLANN_PSC-RANSAC_LSTM

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Journal of Intelligent and Fuzzy Systems 2024年第1-2期47卷 15-28页

作者： Li, Dengao Feng, Ran Wu, Fanming Zhao, Jinhua Zhao, Jumin College of Computer Science and Technology College of Data Science Taiyuan University of Technology Shanxi Taiyuan China College of Electronic Information and Optical Engineering Taiyuan University of Technology Shanxi Taiyuan China Key Laboratory of Big Data Fusion Analysis and Application of Shanxi Province Taiyuan University of Technology Shanxi Taiyuan China Intelligent Perception Engineering Technology Center of Shanxi Taiyuan China

In the field of simultaneous localization and mapping (SLAM), visual odometry (VO) always has great application prospects. In recent years, with the progress in the field of machine learning, methods based on neural networks are constantly being updated and applied. In this paper, we propose a continuous and generalized monocular visual odometry method based on features and neural networks. First, the feature information of adjacent image sequences is extracted by matching and troubleshooting algorithm (FLANN_PSC-RANSAC), then it and the corresponding six-degree-of-freedom information are simultaneously input into the long short-term memory artificial neural network (LSTM) for model construction, which not only ensures the reliability of the mode but also eliminates the influence of illumination on the data. In the real environment test, it has been effectively proved in terms of trajectory recovery accuracy and generalization ability to different environments and different illuminations. © 2024 - IOS Press. All rights reserved.

关键词： Long short-term memory

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A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Capability Evaluation of Manufacturing Enterprises 9th

A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Cap...

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19th International Conference on Advanced data Mining and applications, ADMA 2023

作者： Liu, Tingting Ding, Xuefeng Jiang, Yuming Hu, Dasha College of Computer Science Sichuan University Chengdu610065 China Big Data Analysis and Fusion Application Technology Engineering Laboratory of Sichuan Province Chengdu610065 China

ISBN: (纸本)9783031466731

In the collaborative production environment of manufacturing tasks, the evaluation of enterprise technical capability in advance has a direct impact on the high-performance collaboration between the supplier and the demander of production tasks. In order to solve the problem of efficiency and accuracy in the past evaluation methods, this paper applies the adaptive neuro fuzzy inference system (ANFIS) to the field of enterprise technical capability evaluation for the first time, and proposes an improved hybrid intelligent model SFAHP-ANFIS-PSO based on fuzzy theory. The model takes the four key indexes which have the deepest impact on enterprise technical capability evaluation as the input variables of the model, and the input data are evaluated by ANFIS with high accuracy. Spherical fuzzy analytic hierarchy process (SFAHP) calculated the weight of each evaluation index to preprocess the ANFIS model. Particle swarm optimization algorithm (PSO) continuously optimized the model parameters in the training process, shortened the model training time, improved the evaluation efficiency, and further improved the accuracy of the evaluation results. The experimental results show that the SFAHP-ANFIS-PSO model has high convergence speed and accuracy of results, and can be used to evaluate the technical capability of enterprises with high efficiency and high accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Analytic hierarchy process

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A Method for Identifying the Timeliness of Manufacturing data Based on Weighted Timeliness Graph 9th

A Method for Identifying the Timeliness of Manufacturing Dat...

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19th International Conference on Advanced data Mining and applications, ADMA 2023

作者： Liu, Zehua Ding, Xuefeng Jiang, Yuming Hu, Dasha College of Computer Science Sichuan University Chengdu610065 China Big Data Analysis and Fusion Application Technology Engineering Laboratory of Sichuan Province Chengdu610065 China

ISBN: (纸本)9783031466601

Timeliness is one of the important indicators of data quality. In industrial production processes, a large amount of dependent data is generated, often resulting in unclear timestamps. Therefore, this article combines the conclusion dependency graph into a process dependency graph to determine the identification order of the timeliness of each process data;By constructing a weighted timeliness graph (WTG) and path single flux, a data timeliness identification method that does not completely rely on timestamps is proposed. Finally, a time-effectiveness identification method based on weighted time-effectiveness graph was discussed through an example and 9 dependency rules, and the effectiveness of the method was verified through a set of experiments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： big data

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RT3DHVC: A Real-time Human Holographic Video Conferencing System with a Consumer RGB-D Camera Array

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IEEE Transactions on Circuits and Systems for Video technology 2024年第5期35卷 4226-4241页

作者： Jiang, Yuqi Li, Jing Dai, Yanran Qin, Haidong Zhou, Xiaoshi Zhang, Yong Liu, Hongwei Yan, Kefan Yang, Tao The School of Telecommuni cations Engineering Xidian University Xi’an710071 China The National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology SAIIP School of Computer Science Northwestern Polytechnical University Xi’an710129 China

In this paper, we present an end-to-end holographic video conferencing system that enables real-time high-quality free-viewpoint rendering of participants in different spatial regions, placing them in a unified virtual space for a more immersive display. Our system offers a cost-effective, complete holographic conferencing process, including multiview 3D data capture, RGB-D stream compression and transmission, high-quality rendering, and immersive display. It employs a sparse set of commodity RGB-D cameras that capture 3D geometric and textural information. We then remotely transmit color and depth maps via standard video encoding and transmission protocols. We propose a GPU-parallelized rendering pipeline based on an image-based virtual view synthesis algorithm to achieve real-time and high-quality scene rendering. This algorithm uses an on-the-fly Truncated Signed Distance Function (TSDF) approach, which marches along virtual rays within a computed precise search interval to determine surface intersections. We then design a multiweight projective texture mapping method to fuse color information from multiple views. Furthermore, we introduce a method that uses a depth confidence map to weight the rendering results from different views, which mitigates the impact of sensor noise and inaccurate measurements on the rendering results. Finally, our system places conference participants from different spaces into a virtual conference environment with a global coordinate system through coordinate transformation, which simulates a real conference scene in physical space, providing an immersive remote conferencing experience. Experimental evaluations confirm our system’s real-time, low-latency, high-quality, and immersive capabilities. ©1991-2012 IEEE.

关键词： Video conferencing

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The impact of COVID-19 on subway passenger flow in Chicago: A study of spatial variation of influencing factors 6

The impact of COVID-19 on subway passenger flow in Chicago: ...

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

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

ISBN: (纸本)9781665497138

At the beginning of 2020, with the rapid spread of COVID-19 around the world, the passenger flow of subway has suffered from a serious impact. Based on the subway passenger flow data in Chicago, this article analyzes the impact of COVID-19 on rail transit passenger flow. ArcGIS is used to visualize the spatial-temporal distribution of the passenger flow of different stations during different time periods. Based on the fluctuation characteristics of passenger flow before and after the outbreak of COVID-19, one of the deep learning methods, the LSTM (Long-Short Term Memory) neural network model, is constructed to predict the passenger flow of each station in the scenario of no virus. The decline of passenger flow is calculated for each station. Stepwise regression model is constructed to determine factors that explain the decline in passenger flow, and significant factors are obtained: the original passenger flow, number of houses and jobs within 800m buffer zone, number of bus stops within 800m buffer zone, whether the station is a transfer station, distance from the station to the city center, and the number of low-income people. The results of the study show that after the outbreak of COVID-19, the passenger flow of the subway in Chicago experience a 'cliff-like' decline in the short term. The passenger flow in most areas dropped by more than 80%, and the passenger flow of some severely impacted stations dropped by more than 90%. Characteristics of the station and built environment factors of different stations influence the decline of passenger flow. © 2021 IEEE.

关键词： COVID-19

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The difference between customers and subscribers in Boston tourists using shared bicycles under COVID-19: Trip frequency and its determinants 6

The difference between customers and subscribers in Boston t...

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

作者： Jiang, Lanzhen Yang, Hongtai Zheng, Rong Huo, Jinghai Southwest Jiaotong University School of Transportation and Logistics National United Engineering Laboratory of Integrated and Intelligent Transportation National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9781665497138

The COVID-19 pandemic has changed the frequency of tourists using shared bicycles to a certain extent. This paper uses the cycling data of Boston, USA from June 2020 to December 2020, taking users in areas without bicycle sites as tourists. Using customers and subscribers among tourists to share bicycle trip data on a daily basis, taking into account the weather, the built environment of bicycle sites, and the number of COVID-19 cases per week, a negative binomial regression model is used to explore these factors during the epidemic. The relationship between regional customers and subscribers using shared bicycle trips and influencing factors. The results show that, first of all, during the pandemic, there is a double-peak tide phenomenon in the usage of shared bicycles by subscribers among tourists, and customers use more in the evening peak. Secondly, the population density and employment density around bicycle sites have a significant positive impact on the shared bicycle use of customers and subscribers. For every 1% increase in the population, subscriber usage increases by 4.55%, and every 1 % increase in employment Density, customer usage increased by 4.22 %. In addition, the number of bus stations and subway stations has a restraining effect on the use of shared bicycles. Finally, the number of epidemics will increase the usage of customers and subscribers to a certain extent, with subscribers increasing by 0.25% and customer usage increasing by 2.92 %. The research results can timely analyze the usage of bicycles shared by different users among tourists during the pandemic, and can help transportation agencies adjust services in different regions to better control the spread of the virus. © 2021 IEEE.

关键词： Bicycles

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An aggregate flow based scheduler in multi-task cooperated UAVs network

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Chinese Journal of Aeronautics 2020年第11期33卷 2989-2998页

作者： Xiaohuan LI Ziqi XIE Jin YE Xin TANG Chunhai LI Fengzhu TANG Rong YU School of Information and Communication Guilin University of Electronic TechnologyGuilin 541004China Guangxi Key Laboratory of Multimedia Communications and Network Technology School of ComputerElectronics and InformationGuangxi UniversityNanning 530004China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology(Guangxi) Nanning 530001China School of Automation Guangdong University of TechnologyGuangzhou 510006China

Unmanned Aerial Vehicles(UAVs)cooperative multi-task system has become the research focus in recent ***,the existing network frameworks of UAVs are not flexible and efficient enough to deal with the complex multi-task scheduling,because they are not able to perceive the different *** this paper,a novel cooperated UAVs network framework for multi-task scheduling is *** is a three-layer network including a core layer,an aggregation layer and an execution layer,which enhances the efficiency of multi-task distribution,aggregation and ***,an Aggre Gate Flow(AGFlow)based scheduler is dedicatedly designed to maximize the task completion rate,whose key point is to aggregate flows belonging to one task during the multi-task transmission of UAVs network and to allocate priority by calculating the urgency-level of each *** results demonstrate that,compared with that of state-of-the-art scheduler,the average task completion rate of AGFlow based scheduler is raised by 0.278.

关键词： Mixed-flow scheduling Multi-task Task completion rate Unmanned Aerial Vehicles(UAVs) Urgency-level

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Determine Lane Function of Variable Approach Lane at the Signalized Intersection Based on Real-time Traffic Status 6

Determine Lane Function of Variable Approach Lane at the Sig...

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

作者： Tang, Liying Liu, Yugang National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9781665497138

How to determine the lane function of Variable Approach Lane (VAL) is critical for satisfying the turning traffic demand and decreasing vehicle delay. Though a lot of scholars have studied this topic, most of them ignore the cycle-by-cycle traffic demand fluctuation at a signalized intersection. This paper proposes a dynamic offline lane assignment scheme to determine the lane function of VAL based on real-time traffic status identification. Firstly, the Fuzzy C- Means Algorithm is utilized to identify the traffic status based on three indicators: volume, occupancy, and speed in a cycle. Then, a rapid traffic status identification system focusing on through and left-turn traffic is built. A dynamic lane assignment model is established to determine the lane function of VAL in a real-time manner. An example is introduced to better illustrate how the method works. The result shows that the number of vehicles released increases by 9.8% while the delay per vehicle is reduced by 9.2%. In addition, the performance of dynamic lane, fixed left-turn lane, and fixed through lane under different traffic volumes is compared and results show dynamic lane has the best performance. Finally, this paper compares the proposed dynamic lane optimization method with two other optimization methods. Results reveal that the proposed method works better. © 2021 IEEE.

关键词： Vehicles

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