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Pedestrian wind flow prediction using spatial-frequency generative adversarial network

Building Simulation 2024年第2期17卷 319-334页

作者： Pengyue Wang Maozu Guo Yingeng Cao Shimeng Hao Xiaoping Zhou Lingling Zhao School of Architecture and Urban Planning Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building big data Beijing100044China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China School of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China

Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban *** pedestrian wind flow during the early design stages is essential but currently suffers from inefficiencies in numerical *** learning,particularly generative adversarial networks(GAN),has been increasingly adopted as an alternative method to provide efficient prediction of pedestrian wind ***,existing GAN-based wind flow prediction schemes have limitations due to the lack of considering the spatial and frequency characteristics of wind flow *** study proposes a novel approach termed SFGAN,which embeds spatial and frequency characteristics to enhance pedestrian wind flow *** the spatial domain,Gaussian blur is employed to decompose wind flow into components containing wind speed and distinguished flow edges,which are used as the embedded spatial *** information of wind flow is obtained through discrete wavelet transformation and used as the embedded frequency *** spatial and frequency characteristics of wind flow are jointly utilized to enforce consistency between the predicted wind flow and ground truth during the training phase,thereby leading to enhanced *** results demonstrate that SFGAN clearly improves wind flow prediction,reducing Wind_MAE,Wind_RMSE and the Fréchet Inception Distance(FID)score by 5.35%,6.52%and 12.30%,compared to the previous best method,*** also analyze the effectiveness of incorporating the spatial and frequency characteristics of wind flow in predicting pedestrian wind *** reduces errors in predicting wind flow at large error intervals and performs well in wake regions and regions surrounding *** enhanced predictions provide a better understanding of performance variability,bringing insights at the early design stage to improve pedestrian wind *** proposed spatial-frequen

关键词： pedestrian wind flow prediction generative adversarial network Gaussian kernel wavelet transform objective function

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Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

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Journal of Mountain Science 2024年第3期21卷 952-972页

作者： GUO Junqi XI Wenfei YANG Zhiquan SHI Zhengtao HUANG Guangcai YANG Zhengrong YANG Dongqing Faculty of Geography Yunnan Normal UniversityKunming 650500China Key Laboratory of Early Rapid Identification Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan ProvinceKunming 650093China Faculty of public safety and Emergency Management Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Geological Disaster Risk Prevention and Control and Emergency Disaster Reduction of Ministry of Emergency Management of the People’s Republic of China Kunming University of Science and TechnologyKunming 650093China Guizhou Geological Survey institute Guiyang 550081China College of big data and Intelligent Engineering Southwest Forestry UniversityKunming 650224China

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and *** order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network *** SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and *** Reservoir area is selected as a case study for *** indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard ***,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,***,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation *** area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation ra

关键词： Baihetan SBAS-InSAR SSA-BP Landslide hazard susceptibility evaluation

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Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1695-1712页

作者： Xiaodong Yang Runze Diao Tao Liu Haoqi Wen Caifen Wang College of Computer Science and Engineering Northwest Normal UniversityLanzhou730070China institute of China TelecomWanwei China TelecomWanwei Information Technology Co.Ltd.Lanzhou730030China College of big data and Internet Shenzhen Technology UniversityShenzhen518118China Key Laboratory of Cryptography and data Analytics Northwest Normal UniversityLanzhou730070China

The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading *** signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrowbased on identity ***,most certificateless signatures still suffer fromvarious security *** present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature *** ensure the integrity and verifiability of electricity carbon quota trading,we propose an electricity carbon quota trading scheme based on a certificateless signature and *** scheme utilizes certificateless signatures to ensure the validity and nonrepudiation of transactions and adopts blockchain technology to achieve immutability and traceability in electricity carbon quota *** addition,validating electricity carbon quota transactions does not require time-consuming bilinear pairing *** results of the analysis indicate that our scheme meets existential unforgeability under adaptive selective message attacks,offers conditional identity privacy protection,resists replay attacks,and demonstrates high computing and communication performance.

关键词： Electricity carbon trading certificateless signature blockchain forgery attack carbon quota

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Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation

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Computers, Materials & Continua 2024年第3期78卷 3021-3039页

作者： Shoukun Xu Lujun Zhang Guangqi Jiang Yining Hua Yi Liu School of Computer Science and Artificial Intelligence Aliyun School of Big Data and School of SoftwareChangzhou UniversityChangzhou213164China Department of Computer Science University of AberdeenKing’s CollegeAberdeenAB243FXUK

This paper focuses on the task of few-shot 3D point cloud semantic *** some progress,this task still encounters many issues due to the insufficient samples given,e.g.,incomplete object segmentation and inaccurate semantic *** tackle these issues,we first leverage part-whole relationships into the task of 3D point cloud semantic segmentation to capture semantic integrity,which is empowered by the dynamic capsule routing with the module of 3D Capsule Networks(CapsNets)in the embedding ***,the dynamic routing amalgamates geometric information of the 3D point cloud data to construct higher-level feature representations,which capture the relationships between object parts and their ***,we designed a multi-prototype enhancement module to enhance the prototype ***,the single-prototype enhancement mechanism is expanded to the multi-prototype enhancement version for capturing rich ***,the shot-correlation within the category is calculated via the interaction of different samples to enhance the intra-category *** studies prove that the involved part-whole relations and proposed multi-prototype enhancement module help to achieve complete object segmentation and improve semantic ***,under the integration of these two modules,quantitative and qualitative experiments on two public benchmarks,including S3DIS and ScanNet,indicate the superior performance of the proposed framework on the task of 3D point cloud semantic segmentation,compared to some state-of-the-art methods.

关键词： Few-shot point cloud semantic segmentation CapsNets

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Trends in the Incidence of High-Risk Newborns Based on a New Conceptual Framework-Beijing Municipality,China,2013-2022

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China CDC weekly 2024年第31期6卷 767-771页

作者： Yongxian Zhao Zhaoxia Jia Lei Wang Qingqing Wu Moning Guo Dong Han Lili Huang Junhua Wang Di Zhang Zhao Wang Minghui Wu Beijing Obstetrics and Gynecology Hospital Capital Medical UniversityBeijing Maternal and Child Health Care HospitalBeijingChina Beijing Municipal Health big data and Policy Research Center BeijingChina

Summary What is already known on this topic?A new conceptual term,small and vulnerable newborns(SVN),bringing preterm birth,small for gestational age(SGA),or low birth weight(LBW)together is being advocated for assessing whether a child is at high *** is added by this report?According to the new conceptual term,the increasing incidence of high-risk newborns(from 9.82%to 10.96%)has been observed among 2,005,408 newborns over the period from 2013 to 2022,which is higher than using any of the three definitions of *** age≥35,primiparity,and multiple births are high risks for *** are the implications for public health practice?The new conceptual framework should be used to better assess the number of high-risk *** should be paid to multiple births to prevent preterm-related *** reduce term newborns who are SGA,we need to be concerned not only with multiple pregnancies but also with first-time mothers.

关键词： Beijing bringing mother

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FADSF:A data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

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Computers, Materials & Continua 2024年第8期80卷 2351-2362页

作者： Yan Sun Caiyun Liu Jun Li Yitong Liu data Security institute China Industrial Control Systems Cyber Emergency Response TeamBeijing100040China

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage *** data of ICV(intelligent connected vehicles)is the key to organically maximizing their ***,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are *** study proposes FADSF(Fuzzy Anonymous data Share Frame),an automobile data sharing scheme based on *** data holder publishes the shared data information and forms the corresponding label storage on the *** data demander browses the data directory information to select and purchase data assets and verify *** data demander selects and purchases data assets and verifies them by browsing the data directory ***,this paper designs a data structure data Discrimination Bloom Filter(DDBF),making complaints about illegal *** the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing *** this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

关键词： Blockchain connected vehicles data sharing smart contracts credible traceability

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Ionic solid-like conductor-assisted polymer electrolytes for solid-state lithium metal batteries

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Science China Chemistry 2024年

作者： Shuaishuai Yan Hao Liu Xiaoxia Chen Yang Lu Qingbin Cao Kai Liu State Key Laboratory of Chemical Engineering Department of Chemical Engineering Tsinghua University Hefei institute for public safety Research Tsinghua University Beijing Huairou Laboratory

Solid polymer electrolytes（SPEs） have attracted extensive attention by virtue of lightweight and flexible processability for solidstate lithium metal batteries（LMBs） with high energy density and intrinsic safety. However, the SPEs suffer from the trade-off effect between ionic conductivity and mechanical strength. Herein, we report an ionic solid-like conductor with high Li+conductivity and good thermal stability as the conductive phase of polymer electrolytes for advanced LMBs. Using poly（vinylidene fluoride-co-hexafluoropropylene）(PVDF-HFP) as the polymer matrix, the ionic solid-like conductor can be regarded as a solid plasticizer due to its advantages of non-fluidity and non-leakage. It increases the amorphous region and the dissociation degree of lithium salts in SPEs, while minimizing the loss of mechanical properties. As a result, the Li+conductivity of SPEs incorporating the ionic solid-like conductor is enhanced by four orders of magnitude compared to the blank PVDF-HFPbased electrolyte. The optimized SPE membranes can be processed as thin as 50 μm with a high Young's modulus of 16.8 MPa,therefore ensuring stable long-term cycling of solid-state LMBs. The Li/Li symmetric cells stably cycled for more than 750 h without short circuits, and the LiFePO4/Li solid-state batteries demonstrate excellent electrochemical performance over 350cycles with a capacity retention of 82.5%. This work provides a new strategy for designing ionic solid-like conductors as solid plasticizers for high-performance polymer electrolytes.

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Combining prognostic value of serum carbohydrate antigen 19-9 and tumor size reduction ratio in pancreatic ductal adenocarcinoma

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World Journal of Gastrointestinal Oncology 2024年第3期16卷 798-809页

作者： Dong-Qin Xia Yong Zhou Shuang Yang Fang-Fei Li Li-Ya Tian Yan-Hua Li Hai-Yan Xu Cai-Zhi Xiao Wei Wang Oncology Treatment Center of Traditional Chinese Medicine Chongqing University Cancer HospitalChongqing 400030China Department of Oncology Chongqing Weisiteng Biotech Translational Research InstituteChongqing 430039China Chongqing Key Laboratory on big data for Bio Intelligence Chongqing University of Posts and TelecommunicationsChongqing 430065China

BACKGROUND Pancreatic ductal adenocarcinoma(PDAC)is a common cancer with increasing morbidity and mortality due to changes of social *** To evaluate the significance of serum carbohydrate antigen 19-9(CA19-9)and tumor size changes pre-and post-neoadjuvant therapy(NAT).METHODS This retrospective study was conducted at the Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment,Chongqing University Cancer *** study specifically assessed CA19-9 levels and tumor size before and after *** A total of 156 patients who completed NAT and subsequently underwent tumor resection were included in this *** average age was 65.4±10.6 years and 72(46.2%)patients were *** survival analysis,we defined the post-NAT serum CA19-9 level/pre-NAT serum CA19-9 level as the CA19-9 ratio(CR).The patients were divided into three groups:CR0.5 and*** regard to tumor size measured by both computed tomography and magnetic resonance imaging,we defined the post-NAT tumor size/pre-NAT tumor size as the tumor size ratio(TR).The patients were then divided into three groups:TR0.5 and*** on these groups divided according to CR and TR,we performed both overall survival(OS)and disease-free survival(DFS)***-rank tests showed that both OS and DFS were significantly different among the groups according to CR and TR(P<0.05).CR and TR after NAT were associated with increased odds of achieving a complete or near-complete pathologic ***,CR(hazard ratio:1.721,95%CI:1.373-3.762;P=0.006),and TR(hazard ratio:1.435,95%CI:1.275-4.363;P=0.014)were identified as independent factors associated with *** This study demonstrated that post-NAT serum CA19-9 level/pre-NAT serum CA19-9 level and post-NAT tumor size/pre-NAT tumor size were independent factors associated with OS in patients with PDAC who received NAT and subsequent surgical resection.

关键词： Pancreatic ductal adenocarcinoma Carbohydrate antigen 19-9 Tumor size Pathologic response Biomarkers

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Adaptive Successive POI Recommendation via Trajectory Sequences Processing and Long Short-Term Preference Learning

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Computers, Materials and Continua 2024年第1期81卷 685-706页

作者： Si, Yali Li, Feng Zhong, Shan Huo, Chenghang Chen, Jing Liu, Jinglian School of Computer Science and Engineering Changshu Institute of Technology Changshu 15500 China Suzhou Industrial Intelligence and big data Laboratory Suzhou 215000 China School of Information Science and Engineering Yanshan University Qinhuangdao 066004 China College of Electronic and Information Engineering Guangdong Ocean University Zhanjiang 524088 China

Point-of-interest (POI) recommendations in location-based social networks (LBSNs) have developed rapidly by incorporating feature information and deep learning methods. However, most studies have failed to accurately reflect different users' preferences, in particular, the short-term preferences of inactive users. To better learn user preferences, in this study, we propose a long-short-term-preference-based adaptive successive POI recommendation (LSTP-ASR) method by combining trajectory sequence processing, long short-term preference learning, and spatiotemporal context. First, the check-in trajectory sequences are adaptively divided into recent and historical sequences according to a dynamic time window. Subsequently, an adaptive filling strategy is used to expand the recent check-in sequences of users with inactive check-in behavior using those of similar active users. We further propose an adaptive learning model to accurately extract long short-term preferences of users to establish an efficient successive POI recommendation system. A spatiotemporal-context-based recurrent neural network and temporal-context-based long short-termmemory network are used to model the users' recent and historical checkin trajectory sequences, respectively. Extensive experiments on the Foursquare and Gowalla datasets reveal that the proposed method outperforms several other baseline methods in terms of three evaluation metrics. More specifically, LSTP-ASRoutperforms the previously best baselinemethod (RTPM)with a 17.15% and 20.62% average improvement on the Foursquare and Gowalla datasets in terms of the Fβ metric, respectively. © 2024 The Authors.

关键词： Contrastive Learning

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A deep convolutional neural network for diabetic retinopathy detection via mining local and long-range dependence

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 153-166页

作者： Xiaoling Luo Wei Wang Yong Xu Zhihui Lai Xiaopeng Jin Bob Zhang David Zhang Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of TechnologyShenzhenChina Peng Cheng Laboratory ShenzhenChina Shenzhen institute of Artificial Intelligence and Robotics for Society ShenzhenChina College of big data and Internet Shenzhen Technology UniversityShenzhenChina The Department of Computer and Information Science University of MacaoMacaoMacaoChina The Chinese University of Hong Kong(Shenzhen) ShenzhenChina

Diabetic retinopathy(DR),the main cause of irreversible blindness,is one of the most common complications of *** present,deep convolutional neural networks have achieved promising performance in automatic DR detection *** convolution operation of methods is a local cross-correlation operation,whose receptive field de-termines the size of the local neighbourhood for ***,for retinal fundus photographs,there is not only the local information but also long-distance dependence between the lesion features(*** and exudates)scattered throughout the whole *** proposed method incorporates correlations between long-range patches into the deep learning framework to improve DR ***-wise re-lationships are used to enhance the local patch features since lesions of DR usually appear as *** Long-Range unit in the proposed network with a residual structure can be flexibly embedded into other trained *** experimental results demon-strate that the proposed approach can achieve higher accuracy than existing state-of-the-art models on Messidor and EyePACS datasets.

关键词： image classification medical image processing pattern recognition

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