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Fusing Spatio-Temporal Contexts into DeepFM for Taxi Pick-Up Area Recommendation

Computer Systems Science & engineering 2023年第6期45卷 2505-2519页

作者： Yizhi Liu Rutian Qing Yijiang Zhao Xuesong Wang Zhuhua Liao Qinghua Li Buqing Cao School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan411201China Northwestern Institute on Complex Systems Northwestern UniversityEvanstonIL60208USA Key Laboratory of Knowledge Processing and Networked Manufacturing in Hunan Province Xiangtan411201China

Short-term GPS data based taxi pick-up area recommendation can improve the efficiency and reduce the *** how to alleviate sparsity and further enhance accuracy is still *** at these issues,we propose to fuse spatio-temporal contexts into deep factorization machine(STC_DeepFM)offline for pick-up area recommendation,and within the area to recommend pick-up points online using factorization machine(FM).Firstly,we divide the urban area into several grids with equal ***-temporal contexts are destilled from pick-up points or points-of-interest(POIs)belonged to the preceding ***,the contexts are integrated into deep factorization machine(DeepFM)to mine high-order interaction relationships from *** a novel algorithm named STC_DeepFM is presented for offline pick-up area ***,we devise the architecture of offline-to-online(O2O)recommendation respectively based on DeepFM and FM model in order to tradeoff the accuracy and *** experiments are designed on the DiDi dataset to evaluate step by step the performance of spatio-temporal contexts,different recommendation models,and the O2O *** results show that the proposed STC_DeepFM algorithm exceeds several state-of-the-art methods,and the O2O architecture achieves excellent real-time performance.

关键词： Location-based service(LBS) trajectory data mining offline-toonline(O2O)recommendation deep factorization machine(DeepFM) spatiotemporal context

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Kubernetes-based Scripted Remote Sensing Process Service Platform 6

Kubernetes-based Scripted Remote Sensing Process Service Pla...

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6th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2023

作者： Zhou, Liming Liu, Mengyu Yang, Wencheng Liu, Zhehao Zhao, Hang Han, Hongyu Henan University Henan Key Laboratory of Big Data Analysis and Processing Kaifeng China Henan University School of Computer and Information Engineering Kaifeng China

ISBN: (纸本)9781665460033

With the formation of the high-resolution satellite system, the information carried in remote sensing data is becoming more and more abundant, and the types of data are also increasing. In order to realize the efficient processing of remote sensing data, the construction of remote sensing process is very important. At the same time, higher requirements are put forward for the remote sensing system in terms of dynamic resource scheduling, easy maintenance, elastic expansion, controllable complexity, and flexible deployment. In response to the above problems, this paper first designs a scripted process construction technology, which realizes the efficient construction of various complex processes. And introduce Docker container technology and Kubernetes container cluster management technology, split the remote sensing system into different micro-service modules, run independently in mutually isolated containers, so that the system has the characteristics of flexible load scheduling and elastic scaling. © 2023 IEEE.

关键词： Containers

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Dual Branch PnP Based Network for Monocular 6D Pose Estimation

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Intelligent Automation & Soft Computing 2023年第6期36卷 3243-3256页

作者： Jia-Yu Liang Hong-Bo Zhang Qing Lei Ji-Xiang Du Tian-Liang Lin Department of Computer Science and Technology Huaqiao UniversityXiamen361000China Xiamen Key Laboratory of Computer Vision and Pattern Recognition Huaqiao UniversityXiamen361000China Fujian Key Laboratory of Big Data Intelligence and Security Huaqiao UniversityXiamen361000China College of Mechanical Engineering and Automation Xiamen361000China

Monocular 6D pose estimation is a functional task in the field of com-puter vision and *** recent years,2D-3D correspondence-based methods have achieved improved performance in multiview and depth data-based ***,for monocular 6D pose estimation,these methods are affected by the prediction results of the 2D-3D correspondences and the robustness of the per-spective-n-point(PnP)*** is still a difference in the distance from the expected estimation *** obtain a more effective feature representation result,edge enhancement is proposed to increase the shape information of the object by analyzing the influence of inaccurate 2D-3D matching on 6D pose regression and comparing the effectiveness of the intermediate ***,although the transformation matrix is composed of rotation and translation matrices from 3D model points to 2D pixel points,the two variables are essentially different and the same network cannot be used for both variables in the regression ***,to improve the effectiveness of the PnP algo-rithm,this paper designs a dual-branch PnP network to predict rotation and trans-lation ***,the proposed method is verified on the public LM,LM-O and YCB-Video *** ADD(S)values of the proposed method are 94.2 and 62.84 on the LM and LM-O datasets,*** AUC of ADD(-S)value on YCB-Video is *** experimental results show that the performance of the proposed method is superior to that of similar methods.

关键词： 6D pose monocular RGB edge enhancement dual-branch PnP 2D-3D correspondence

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Reynosin protects neuronal cells from microglial neuroinflammation by suppressing NLRP3 inflammasome activation mediated by NADPH oxidase

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Chinese Journal of Natural Medicines 2024年第6期22卷 486-500页

作者： YANG Yanqiu CHE Yue FANG Mingxia YAO Xiaohu ZHOU Di WANG Feng CHEN Gang LIANG Dong LI Ning HOU Yue Key Laboratory of Bioresource Research and Development of Liaoning Province College of Life and Health SciencesNorth-eastern UniversityShenyang 110000China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Key Laboratory of Data Analytics and Optimization for Smart IndustryMinistry of EducationNortheastern UniversityShenyang 110000China School of Traditional Chinese Materia Medica Key Laboratory of Innovative Traditional Chinese Medicine for Major Chronic Diseases of Liaoning provinceKey Laboratory for TCM Material Basis Study and Innovative Drug Development of Shenyang CityShenyang Pharmaceutical UniversityShenyang 110000China State Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources School of Chemistry and Pharmaceutical SciencesGuangxi Normal UniversityGuilin 541000China

Neuroinflammation,mediated by the nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing-3(NLRP3)inflammasome,is a significant contributor to the pathogenesis of neurodegenerative diseases(NDDs).Reynos-in,a natural sesquiterpene lactone(SL),exhibits a broad spectrum of pharmacological effects,suggesting its potential therapeutic ***,the effects and mechanism of reynosin on neuroinflammation remain *** current study explores the effects and mechanisms of reynosin on neuroinflammation using mice and BV-2 microglial cells treated with lipopolysaccharide(LPS).Our findings reveal that reynosin effectively reduces microglial inflammation in vitro,as demonstrated by decreased CD11b expression and lowered interleukin-1 beta(IL-1β)and interleukin-18(IL-18)mRNA and protein ***,in vivo,results showed a re-duction in the number of Iba-1 positive cells and alleviation of morphological alterations,alongside decreased expressions of IL-1βand *** analysis indicates that reynosin inhibits NLRP3 inflammasome activation,evidenced by reduced transcription of NLRP3 and caspase-1,diminished NLRP3 protein expression,inhibited apoptosis-associated speck-like protein containing a CARD(ASC)oli-gomerization,and decreased caspase-1 ***,reynosin curtailed the activation of nicotinamide adenine dinuc-leotide phosphate(NADPH)oxidase,demonstrated by reduced NADP^(+)and NADPH levels,downregulation of gp91^(phox) mRNA,pro-tein expression,suppression of p47^(phox) expression and translocation to the ***,reynosin exhibited a neuroprotective effect against microglial inflammation in vivo and in *** collective findings underscore reynosin’s capacity to mitigate mi-croglial inflammation by inhibiting the NLRP3 inflammasome,thus highlighting its potential as a therapeutic agent for managing neuroinflammation.

关键词： Microglia NLRP3 inflammasome Reactive oxygen species NADPH oxidase Neuron Reynosin

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Forces of fully nonlinear interfacial periodic waves on a cylindrical pile in a two-layer fluid with free-surface boundary conditions

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Journal of Ocean engineering and Science 2023年第6期8卷 662-674页

作者： Jiyang Li Zeng Liu Jie Cui School of Naval Architecture and Ocean Engineering Jiangsu University of Science and TechnologyZhenjiangJiangsu 212000PR China School of Naval Architecture and Ocean Engineering Huazhong University of Science and TechnologyWuhan 430074PR China Hubei Key Laboratory of Naval Architecture and Ocean Engineering Hydrodynamics(HUST) Wuhan 430074China Hubei Provincial Engineering Research Center of Data Techniques and Supporting Software for Ships Wuhan 430074PR China

In the frame of fully nonlinear potential flow theory,series solutions of interfacial periodic gravity waves in a two-layer fluid with free surface are obtained by the homotopy analysis method(HAM),and the related wave forces on a vertical cylinder are *** solution procedure of the HAM for the interfacial wave model with rigid upper surface is further developed to consider the free surface *** forces of nonlinear interfacial periodic waves are estimated by both the classical and modified Mori-son *** is found that the estimated wave forces by the classical Morison equation are more conservative than those by the modified Morison’s formula,and the relative error between the total inertial forces calculated by these two kinds of Morison’s formulae remains over 25%for most cases unless the upper and lower layer depths are both large *** demonstrates that the convective acceleration neglected in the classical Morison equation is rather important for inertial force exerted by not only internal solitary waves but also interfacial periodic *** of these should further deepen our understanding of internal periodic wave forces on a vertical marine riser.

关键词： Interfacial periodic waves Wave force Cylindrical pile Homotopy analysis method Morison equation

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Integrated multi-dimensional communication system for dam and bank risk situations on the Yellow River

Integrated multi-dimensional communication system for dam an...

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2022 International Conference on Signal Processing, Computer Networks, and Communications, SPCNC 2022

作者： Dang, Lanxue Zhang, Miaoxin Xie, Yi Zuo, Xianyu Zhang, Lei Fan, Minghu Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China School of Computer and Information Engineering Henan University Kaifeng China

ISBN: (纸本)9781510664616

Due to the terrain, the frequent floods of the Yellow River have posed a great threat to the cities along the Yellow River. At present, although the danger alarm system and video surveillance system are widely installed along the Yellow River Basin, there is a lack of linkage between the two, which wastes monitoring resources. In addition, the push rules of different types of alarm signals are relatively complex, and the coupling between rules and system implementation is high, which is not conducive to rule modification and expansion;moreover, there are many cities along the Yellow River, if each city customizes its own system, it will lead to more overhead. Therefore, this problem can be solved by improving the hierarchical scalability of the system. So, based on the Drools framework, this paper uses the rule engine to realize the unified processing of different rules and the linkage integration of sensors and cameras, and designs a recursive model to simplify the development process, so as to realize the accurate positioning of alarm information at all levels of provinces, cities and counties, and the hierarchical processing of various alarm information. © 2023 SPIE.

关键词： Alarm systems

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Adaptive Fourier Decomposition of the First Three SARS-CoV-2 Infection Waves with Epidemic Intervention—London,UK,2020-2022

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China CDC weekly 2024年第21期6卷 478-486,I0006-I0008页

作者： Zige Liu Guibin Lu Cheokieng Vong Zhiqi Zeng Wei He Zhijie Lin Cuiyun Lin Kaichin Hsieh Zifeng Yang Arlindo L.Oliveira Chitin Hon Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao SARChina Queen Ethelburga’s Collegiate Thorpe Underwood EstateYorkUK State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory HealthThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou CityGuangdong ProvinceChina Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications Department of Engineering ScienceFaculty of Innovation EngineeringMacao University of Science and TechnologyMacao SARChina Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases KingMed School of Laboratory MedicineGuangzhou Medical UniversityGuangzhou CityGuangdong ProvinceChina Faculty of Innovation Engineering School of Computer Science and EngineeringMacao University of Science and TechnologyMacao SARChina University College London UCL Faculty of Engineering SciencesLondonUK Guangzhou Laboratory Guangzhou CityGuangdong ProvinceChina Instituto de Engenharia de Sistemas e Computadores:Investigação e Desenvolvimento em Lisboa LisboaPortugal Instituto Superior Técnico Universidade de LisboaLisboaPortugal

Background:This study provides a detailed analysis of the daily fluctuations in coronavirus disease 2019(COVID-19)case numbers in London from January 31,2020 to February 24,*** primary objective was to enhance understanding of the interactions among government pandemic responses,viral mutations,and the subsequent changes in COVID-19 case ***:We employed the adaptive Fourier decomposition(AFD)method to analyze diurnal changes and further segmented the AFD into novel multi-component groups consisting of one to three *** restructured components were rigorously evaluated using Pearson correlation,and their effectiveness was compared with other signal analysis *** study introduced a novel approach to differentiate individual components across various time-frequency scales using basis decomposition ***:Analysis of London’s daily COVID-19 data using AFD revealed a strong correlation between the“stay at home”directive and high-frequency components during the first epidemic *** indicates the need for sustained implementation of vaccination policies to maintain their ***:The AFD component method provides a comprehensive analysis of the immediate and prolonged impact of governmental policies on the spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).This robust tool has proven invaluable for analyzing COVID-19 pandemic data,offering critical insights that guide the formulation of future preventive and public health strategies.

关键词： offering sustained London

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Graph Neural Networks with Learnable and Optimal Polynomial Bases

arXiv

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arXiv 2023年

作者： Guo, Yuhe Wei, Zhewei Gaoling School of Articial Intelligence Renmin University of China China Peng Cheng Laboratory China Beijing Key Laboratory of Big Data Management and Analysis Methods China MOE Key Lab of Data Engineering and Knowledge Engineering China

Polynomial filters, a kind of Graph Neural Networks, typically use a predetermined polynomial basis and learn the coefficients from the training data. It has been observed that the effectiveness of the model is highly dependent on the property of the polynomial basis. Consequently, two natural and fundamental questions arise: Can we learn a suitable polynomial basis from the training data? Can we determine the optimal polynomial basis for a given graph and node features? In this paper, we propose two spectral GNN models that provide positive answers to the questions posed above. First, inspired by Favard’s Theorem, we propose the FavardGNN model, which learns a polynomial basis from the space of all possible orthonormal bases. Second, we examine the supposedly unsolvable definition of optimal polynomial basis from Wang & Zhang (2022) and propose a simple model, OptBasisGNN, which computes the optimal basis for a given graph structure and graph signal. Extensive experiments are conducted to demonstrate the effectiveness of our proposed models. Our code is available at https://***/yuziGuo/FarOptBasis. © 2023, CC BY.

关键词： Graph neural networks

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T2R-GAN: A CGAN-based model for rural thematic road extraction 27th

T2R-GAN: A CGAN-based model for rural thematic road extracti...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Ni, Zixiang Zhai, Weixin College of Information and Electrical Engineering China Agricultural University Beijing100083 China Key Laboratory of Agricultural Machinery Monitoring and Big Data Application Ministry of Agriculture and Rural Affairs Beijing100083 China

ISBN: (纸本)9783031783883

Rural roads extracted from agricultural machinery trajectories have significant research value. Due to the intricate network of rural roads and the large difference in the density of agricultural machinery trajectories, traditional road extraction methods struggle to perform effectively on rural roads with complex topology and on agricultural machinery trajectories with obscure road features. Therefore, this paper proposes a CGAN-based model named T2R-GAN (Trajectory to Road-GAN) for rural thematic road extraction, which learns the trajectory-to-road feature mapping through continuous adversarial training between the ELAU-Net generator and the PatchGAN discriminator to adapt to trajectories of various densities. ELAU-Net is an efficient network that utilizes an encoder-decoder structure and ELA modules to enhance the capture of obscure road features between sparse trajectories. To enhance model performance and reduce the risk of overfitting, bilateral hinge loss is designed to train our model to enhances the discriminator’s discriminative ability to facilitate the generator to generate more realistic roads improve the generalization of the model. To verify the effectiveness of T2R-GAN in extracting roads from agricultural trajectory data, this paper selects the real agricultural trajectory data from Henan Province, China in June 2021 as the dataset for verification. The experimental results show that the proposed method achieves 79.23% F1score, which is 5.53% higher than the previous state-of-art. The proposed T2R-GAN provides a novel and effective approach for extracting rural thematic roads from agricultural machinery trajectories for the first time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

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Multivariate Time Series Classification via Hierarchical Graph Embedding

Multivariate Time Series Classification via Hierarchical Gra...

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International Joint Conference on Neural Networks (IJCNN)

作者： Wenhao Niu Xingrui Zhuo Gongqing Wu JunWei Lv Zan Zhang Chenyang Bu Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China) School of Computer Science and Information Engineering Hefei University of Technology Anhui China

Multivariate time series classification aims to determine the labels for multivariate time series samples. Although variable interaction relationships and sample similarity relationships exist in multivariate time series, the available related methods usually ignore the rich relationships and are ineffective in exploiting these. To solve this problem, we propose a Hierarchical Graph Embedding for Multivariate Time Series Classification (MTSC-HGE), which consists of a variable-wise attentive graph pooling module and a sample-wise graph convolutional module to obtain the relationships of variables and samples. Specifically, we design an attentive graph pooling module based on self-attention, which can obtain sample features fusing temporal patterns and variable interaction relationships in samples. Furthermore, we propose a graph mapping criterion that converts the MTS dataset into a graph based on dynamic time warping to explicitly reflect the similarity relationships between samples. To capture latent sample relationships, a GCN module is utilized on the sample graph to integrate sample features obtained from the attentive graph pool module. In addition, a classifier takes the rich representation output by the model to get the final predicted class. Extensive experiments on 14 public datasets show that MTSC-HGE significantly outperforms state-of-the-art baselines.

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