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Spatio-temporal evolution and topographic gradient effect of land use and ecosystem service value in the Lhasa River Basin
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作者 ZHOU Jianwei FENG Bin +8 位作者 WU Hua XU Tong CHEN Linna ZHAO Xinyong GUO Qiyun LI Jiatong ZHANG Chenguang ZHU Kangcheng KONG Yuzhong 《Journal of Mountain Science》 SCIE CSCD 2024年第6期2059-2074,共16页
The Lhasa River Basin forms an essential human settlement area in the southern part of the Qinghai-Tibet Plateau.This study employed ecosystem service value(ESV)evaluation model,terrain gradient grading,and Geodetecto... The Lhasa River Basin forms an essential human settlement area in the southern part of the Qinghai-Tibet Plateau.This study employed ecosystem service value(ESV)evaluation model,terrain gradient grading,and Geodetector to analyze land use and ESV in the Lhasa River Basin from 1985 to 2020.The findings reveal that:(1)From 1985 to 2020,grassland was the dominant land use.There was a trend of grassland reduction and the expansion of other land types.(2)ESV has increased over the research period(with a total increase of 0.84%),with higher values in the southeast and lower values in the northwest.Grassland contributed the most to ESV,and climate regulation and hydrological regulation were the ecosystem services that contribute the most to ESV.(3)Natural factors like NDVI and altitude,as well as economic factors like population density and distance from roads,influenced the spatial differentiation of ESV,the explanatory power of NDVI reached up to 0.47.The interaction between factors had a greater impact than individual factors.These research results can provide theoretical support for national spatial planning and ecological environment protection in the Lhasa River Basin and other similar areas. 展开更多
关键词 Ecosystem services value Land use Terrain gradient effect Lhasa River Basin Driving factors
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Improved spatio-temporal alignment measurement method for hull deformation
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作者 XU Dongsheng YU Yuanjin +1 位作者 ZHANG Xiaoli PENG Xiafu 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第2期485-494,共10页
In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Lar... In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist. 展开更多
关键词 inertial measurement spatio-temporal alignment hull deformation
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Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022
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作者 Ying Li Runze Lu +8 位作者 Liyan Dong Litao Sun Zongyi Zhang Yating Zhao Qing Duan Lijie Zhang Fachun Jiang Jing Jia Huilai Ma 《Biomedical and Environmental Sciences》 SCIE CAS CSCD 2024年第9期1015-1029,共15页
Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingda... Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious. 展开更多
关键词 Hemorrhagic fever with renal syndrome Epidemic characteristics spatio-temporal distribution
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Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting
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作者 Xiaojun Pu Jiaqi Zhu +3 位作者 Yunkun Wu Chang Leng Zitong Bo Hongan Wang 《CAAI Transactions on Intelligence Technology》 SCIE EI 2024年第3期769-786,共18页
Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning mode... Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting. 展开更多
关键词 ADAPTIVE COVID-19 forecasting dynamic INTERVENTION spatio-temporal graph neural networks
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An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism
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作者 Zhijun Guo Yun Sun +2 位作者 YingWang Chaoqi Fu Jilong Zhong 《Computers, Materials & Continua》 SCIE EI 2024年第5期2375-2398,共24页
Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanne... Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution. 展开更多
关键词 RESILIENCE cooperative mission FANET spatio-temporal node pooling multi-head attention graph network
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Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography
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作者 Pengyu Hu Jiangpeng Wu +3 位作者 Zhengang Yan Meng He Chao Liang Hao Bai 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第7期162-172,共11页
High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it... High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%. 展开更多
关键词 Warhead fragment measurement High speed photography Stereo vision Multi-object tracking spatio-temporal reconstruction
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A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion
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作者 Hanshan Li Xiaoqian Zhang Junchai Gao 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第10期48-64,共17页
To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage p... To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis. 展开更多
关键词 Target damage Cloud model Fragments dispersion Effectiveness assessment spatio-temporal sequence
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Self-Attention Spatio-Temporal Deep Collaborative Network for Robust FDIA Detection in Smart Grids
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作者 Tong Zu Fengyong Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第11期1395-1417,共23页
False data injection attack(FDIA)can affect the state estimation of the power grid by tampering with the measured value of the power grid data,and then destroying the stable operation of the smart grid.Existing work u... False data injection attack(FDIA)can affect the state estimation of the power grid by tampering with the measured value of the power grid data,and then destroying the stable operation of the smart grid.Existing work usually trains a detection model by fusing the data-driven features from diverse power data streams.Data-driven features,however,cannot effectively capture the differences between noisy data and attack samples.As a result,slight noise disturbances in the power grid may cause a large number of false detections for FDIA attacks.To address this problem,this paper designs a deep collaborative self-attention network to achieve robust FDIA detection,in which the spatio-temporal features of cascaded FDIA attacks are fully integrated.Firstly,a high-order Chebyshev polynomials-based graph convolution module is designed to effectively aggregate the spatio information between grid nodes,and the spatial self-attention mechanism is involved to dynamically assign attention weights to each node,which guides the network to pay more attention to the node information that is conducive to FDIA detection.Furthermore,the bi-directional Long Short-Term Memory(LSTM)network is introduced to conduct time series modeling and long-term dependence analysis for power grid data and utilizes the temporal selfattention mechanism to describe the time correlation of data and assign different weights to different time steps.Our designed deep collaborative network can effectively mine subtle perturbations from spatiotemporal feature information,efficiently distinguish power grid noise from FDIA attacks,and adapt to diverse attack intensities.Extensive experiments demonstrate that our method can obtain an efficient detection performance over actual load data from New York Independent System Operator(NYISO)in IEEE 14,IEEE 39,and IEEE 118 bus systems,and outperforms state-of-the-art FDIA detection schemes in terms of detection accuracy and robustness. 展开更多
关键词 False data injection attacks smart grid deep learning self-attention mechanism spatio-temporal fusion
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Multi-Scale Location Attention Model for Spatio-Temporal Prediction of Disease Incidence
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作者 Youshen Jiang Tongqing Zhou +2 位作者 Zhilin Wang Zhiping Cai Qiang Ni 《Intelligent Automation & Soft Computing》 2024年第3期585-597,共13页
Due to the increasingly severe challenges brought by various epidemic diseases,people urgently need intelligent outbreak trend prediction.Predicting disease onset is very important to assist decision-making.Most of th... Due to the increasingly severe challenges brought by various epidemic diseases,people urgently need intelligent outbreak trend prediction.Predicting disease onset is very important to assist decision-making.Most of the exist-ing work fails to make full use of the temporal and spatial characteristics of epidemics,and also relies on multi-variate data for prediction.In this paper,we propose a Multi-Scale Location Attention Graph Neural Networks(MSLAGNN)based on a large number of Centers for Disease Control and Prevention(CDC)patient electronic medical records research sequence source data sets.In order to understand the geography and timeliness of infec-tious diseases,specific neural networks are used to extract the geography and timeliness of infectious diseases.In the model framework,the features of different periods are extracted by a multi-scale convolution module.At the same time,the propagation effects between regions are simulated by graph convolution and attention mechan-isms.We compare the proposed method with the most advanced statistical methods and deep learning models.Meanwhile,we conduct comparative experiments on data sets with different time lengths to observe the predic-tion performance of the model in the face of different degrees of data collection.We conduct extensive experi-ments on real-world epidemic-related data sets.The method has strong prediction performance and can be readily used for epidemic prediction. 展开更多
关键词 spatio-temporal prediction infectious diseases graph neural networks
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Woody plant taxonomic,functional,and phylogenetic diversity decrease along elevational gradients in Andean tropical montane forests:Environmental filtering and arrival of temperate taxa
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作者 Guillermo Bañares-de-Dios Manuel J.Macía +6 位作者 Gabriel Arellano Íñigo Granzow-de la Cerda Julia Vega-álvarez Itziar Arnelas Carlos I.Espinosa Norma Salinas Luis Cayuela 《Plant Diversity》 SCIE CAS CSCD 2024年第4期491-501,共11页
Mountains are paramount for exploring biodiversity patterns due to the mosaic of topographies and climates encompassed over short distances.Biodiversity research has traditionally focused on taxonomic diversity when i... Mountains are paramount for exploring biodiversity patterns due to the mosaic of topographies and climates encompassed over short distances.Biodiversity research has traditionally focused on taxonomic diversity when investigating changes along elevational gradients,but other facets should be considered.For first time,we simultaneously assessed elevational trends in taxonomic,functional,and phylogenetic diversity of woody plants in Andean tropical montane forests and explored their underlying ecological and evolutionary causes.This investigation covered four transects(traversing ca.2200 m a.s.l.) encompassing 114 plots of 0.1 ha across a broad latitudinal range(ca.10°).Using Hill numbers to quantify abundance-based diversity among 37,869 individuals we observed a consistent decrease in taxonomic,functional,and phylogenetic diversity as elevation increased,although the decrease was less pronounced for higher Hill orders.The exception was a slight increase in phylogenetic diversity when dominant species were over-weighted.The decrease in taxonomic and functional diversity might be attributed to an environmental filtering process towards highlands,where the increasingly harsher conditions exclude species and functional strategies.Besides,the differences in steepness decrease between Hill orders suggest that rare species disproportionately contribute to functional diversity.For phylogenetic diversity the shifting elevational trend between Hill orders indicates a greater than previously considered influence in central Andean highlands of tropical lowlands originated species with strong niche conservatism relative to distantly related temperate lineages.This could be explained by a decreasing presence and abundance of temperate,extratropical taxa towards the central Andes relative to northern or southern Andes,where they are more prevalent. 展开更多
关键词 Altitudinal gradients ANDES Environmentalfiltering Out of the Tropical Lowlands Functional rarity Tropical Niche Conservatism
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Study on the dynamic contact relationship between layers under temperature gradients in CRTSⅢ ballastless track
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作者 Lei Zhao Guotang Zhao +2 位作者 Guotao Yang Hao Jin Chenxi Li 《High-Speed Railway》 2024年第3期133-142,共10页
In areas with large temperature differences,the uneven distribution of temperatures in the CRTS III ballastless track slab due to daytime sunlight can cause warpage deformation,leading to periodic rail irregularities ... In areas with large temperature differences,the uneven distribution of temperatures in the CRTS III ballastless track slab due to daytime sunlight can cause warpage deformation,leading to periodic rail irregularities that increase the wheel-rail impact of high-speed vehicles and accelerate track structure damage.Therefore,it is necessary to study the dynamic contact relationship between the composite slab and the base plate during vehicle running.The results of the study show that:1)Under the influence of temperature gradients,the composite slab tends to deform elliptically.With a positive temperature gradient,the middle part of the track slab bulges upward,causing the slab to be supported by its four corners.Conversely,with a negative temperature gradient,the four corners of the track slab bulge upward,resulting in the slab being supported by its center.2)Temperature gradients can lead to separation between the composite slab and the base plate,reducing the contact area between layers.During vehicle running,the contact area between layers gradually increases,but the separation cannot be completely closed.3)The temperature gradient significantly affects the vertical displacement of the track.The vertical displacement in the middle of the slab increases with a positive temperature gradient.In contrast,the vertical displacement at the ends of the slab increases with a negative temperature gradient.4)The stress of self-compacting concrete at the side position significantly increases under a positive temperature gradient,with the vertical stress increasing by 2.7 times when the temperature gradient increases from 0 to 90℃·m^(-1). 展开更多
关键词 High-speed railway Ballastless track Temperature gradient Periodic irregularities Interlayer contact
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Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya
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作者 Beatrice Chepkoech Cheserek George Morara Ogendi Paul Mutua Makenzi 《Open Journal of Ecology》 2024年第3期183-198,共16页
Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last... Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods. 展开更多
关键词 spatio-temporal Change Dispersal Greater Kudu (Tragelaphus Strepsiceros) Point Pattern Analysis (PPA) GIS
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Research on the Spatio-Temporal Evolution and Driving Forces of Green Spaces in the Central Urban Area of Zunyi City
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作者 Juan Du 《Journal of Architectural Research and Development》 2024年第4期8-16,共9页
Green space,as a medium for carrying out urban functions and guiding urban development,is becoming a scarce resource along with the urbanization process and the intensification of environmental problems.In the face of... Green space,as a medium for carrying out urban functions and guiding urban development,is becoming a scarce resource along with the urbanization process and the intensification of environmental problems.In the face of the spatial mismatch between high demand and low supply,it is of great significance to clarify the evolution mechanism of green space to undertake national spatial planning,protect the natural strategic resources in the urban fringe area,and promote the sustainable development of the“three living spaces.”The study focuses on the Zunyi City Center,selecting the 20 years of rapid development following its establishment as a city as the study period.It explores the dynamic evolution of green space and the main driving forces during different periods using remote-sensing image data.The study shows that from 2003 to 2023,the total scale of green space has an obvious decreasing trend along with the expansion of the urban built-up area.A large amount of arable land is being converted to construction land,resulting in a sudden decrease in arable land area.In the past 10 years,the comprehensive land use dynamics have accelerated.Still,the spatial difference has gradually narrowed,indicating that the overall development intensity of Zunyi City’s central urban area has increased.There is a gradual spread of the trend to the hilly areas.The limiting effect of the mountainous natural environment on the city’s development has gradually diminished under the superposition of external factors,such as economic development,industrial technological upgrading,and policy orientation so the importance of the effective protection and rational utilization of urban green space has become more prominent. 展开更多
关键词 Green space spatio-temporal evolution Driving force Zunyi city center
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Traveling Wave Solutions of a SIR Epidemic Model with Spatio-Temporal Delay
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作者 Zhihe Hou 《Journal of Applied Mathematics and Physics》 2024年第10期3422-3438,共17页
In this paper, we studied the traveling wave solutions of a SIR epidemic model with spatial-temporal delay. We proved that this result is determined by the basic reproduction number R0and the minimum wave speed c*of t... In this paper, we studied the traveling wave solutions of a SIR epidemic model with spatial-temporal delay. We proved that this result is determined by the basic reproduction number R0and the minimum wave speed c*of the corresponding ordinary differential equations. The methods used in this paper are primarily the Schauder fixed point theorem and comparison principle. We have proved that when R0>1and c>c*, the model has a non-negative and non-trivial traveling wave solution. However, for R01and c≥0or R0>1and 0cc*, the model does not have a traveling wave solution. 展开更多
关键词 Susceptible-Infected-Recovered Epidemic Model Traveling Wave Solutions spatio-temporal Delay Schauder Fixed Point Theorem
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Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences 被引量:1
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作者 Umair Muneer Butt Hadiqa Aman Ullah +3 位作者 Sukumar Letchmunan Iqra Tariq Fadratul Hafinaz Hassan Tieng Wei Koh 《Computers, Materials & Continua》 SCIE EI 2023年第3期5017-5033,共17页
Human Activity Recognition(HAR)is an active research area due to its applications in pervasive computing,human-computer interaction,artificial intelligence,health care,and social sciences.Moreover,dynamic environments... Human Activity Recognition(HAR)is an active research area due to its applications in pervasive computing,human-computer interaction,artificial intelligence,health care,and social sciences.Moreover,dynamic environments and anthropometric differences between individuals make it harder to recognize actions.This study focused on human activity in video sequences acquired with an RGB camera because of its vast range of real-world applications.It uses two-stream ConvNet to extract spatial and temporal information and proposes a fine-tuned deep neural network.Moreover,the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification information.Six state-of-the-art pre-trained models are exploited to find the best model for spatial feature extraction.For temporal sequence,this study uses dense optical flow following the two-stream ConvNet and Bidirectional Long Short TermMemory(BiLSTM)to capture longtermdependencies.Two state-of-the-art datasets,UCF101 and HMDB51,are used for evaluation purposes.In addition,seven state-of-the-art optimizers are used to fine-tune the proposed network parameters.Furthermore,this study utilizes an ensemble mechanism to aggregate spatial-temporal features using a four-stream Convolutional Neural Network(CNN),where two streams use RGB data.In contrast,the other uses optical flow images.Finally,the proposed ensemble approach using max hard voting outperforms state-ofthe-art methods with 96.30%and 90.07%accuracies on the UCF101 and HMDB51 datasets. 展开更多
关键词 Human activity recognition deep learning transfer learning neural network ensemble learning spatio-temporal
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Relationship between spatio-temporal evolution of soil pH and geological environment/surface cover in the eastern Nenjiang River Basin of Northeast China during the past 30 years 被引量:2
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作者 Guo-dong Liu Ming-hui Wei +3 位作者 Ze Yang Hong-ye Xiao Yi-he Zhang Na-na Fang 《China Geology》 CAS CSCD 2023年第3期369-382,共14页
To illuminate the spatio-temporal variation characteristics and geochemical driving mechanism of soil pH in the Nenjiang River Basin,the National Multi-objective Regional Geochemical Survey data of topsoil,the Second ... To illuminate the spatio-temporal variation characteristics and geochemical driving mechanism of soil pH in the Nenjiang River Basin,the National Multi-objective Regional Geochemical Survey data of topsoil,the Second National Soil Survey data and Normalized Difference Vegetation Index(NDVI)were analyzed.The areas of neutral and alkaline soil decreased by 21100 km^(2)and 30500 km^(2),respectively,while that of strongly alkaline,extremely alkaline,and strongly acidic soil increased by 19600 km^(2),18200 km^(2),and 15500 km^(2),respectively,during the past 30 years.NDVI decreased with the increase of soil pH when soil pH>8.0,and it was reversed when soil pH<5.0.There were significant differences in soil pH with various surface cover types,which showed an ascending order:Arbor<reed<maize<rice<high and medium-covered meadow<low-covered meadow<Puccinellia.The weathering products of minerals rich in K_(2)O,Na_(2)O,CaO,and MgO entered into the low plain and were enriched in different parts by water transportation and lake deposition,while Fe and Al remained in the low hilly areas,which was the geochemical driving mechanism.The results of this study will provide scientific basis for making scientific and rational decisions on soil acidification and salinization. 展开更多
关键词 Soil pH spatio-temporal variation Surface cover Soybean-maize-rice Woodland-grassland-wetland Saline-alkali land-sandy land Geological environment Land quality geochemical survey engineering Nenjiang River Basin
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A Methodology to Reduce Thermal Gradients Due to the Exothermic Reactions in Resin Transfer Molding Applications 被引量:1
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作者 Aouatif Saad Mohammed EL Ganaoui 《Fluid Dynamics & Materials Processing》 EI 2023年第1期95-103,共9页
Resin transfer molding(RTM)is among the most used manufacturing processes for composite parts.Initially,the resin cure is initiated by heat supply to the mold.The supplementary heat generated during the reaction can c... Resin transfer molding(RTM)is among the most used manufacturing processes for composite parts.Initially,the resin cure is initiated by heat supply to the mold.The supplementary heat generated during the reaction can cause thermal gradients in the composite,potentially leading to undesired residual stresses which can cause shrinkage and warpage.In the present numerical study of these processes,a one-dimensional finite difference method is used to predict the temperature evolution and the degree of cure in the course of the resin polymerization;the effect of some parameters on the thermal gradient is then analyzed,namely:the fiber nature,the use of multiple layers of reinforcement with different thermal properties and also the temperature cycle variation.The validity of this numerical model is tested by comparison with experimental and numerical results in the existing literature. 展开更多
关键词 CURE RTM finite difference method thermal gradients residual stresses
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Gradient coil design with enhanced shielding constraint for a cryogen-free superconducting MRI system 被引量:1
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作者 Yaohui Wang Weimin Wang +3 位作者 Hui Liu Shunzhong Chen Feng Liu Qiuliang Wang 《Magnetic Resonance Letters》 2024年第1期1-9,共9页
The relatively fragile low-temperature stability of cryogen-free superconducting magnetic resonance imaging(MRI)magnets requires the careful management of exogenous heat sources.A strongly shielded gradient magnetic f... The relatively fragile low-temperature stability of cryogen-free superconducting magnetic resonance imaging(MRI)magnets requires the careful management of exogenous heat sources.A strongly shielded gradient magnetic field is important for the optimal operation of cryogen-free MRI systems.In this study,we present an enhanced shielding method incorporating a regionalized stray field constraining strategy.By optimizing the constraint parameters,we could develop engineering-feasible gradient coil schemes without increasing system complexity but with the stray field intensity reduced by half.In real measurement in an integrated MRI system,the developed gradient assembly demonstrated good performance and supported to output images of excellent quality.Our findings suggested that the proposed method could potentially form a useful design paradigm for cryogen-free MRI magnets. 展开更多
关键词 MRI gradient coil Superconducting magnet Cryogen-free Magnetic shielding
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Climate-growth relationships of Pinus tabuliformis along an altitudinal gradient on Baiyunshan Mountain,Central China 被引量:1
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作者 Xiaoxu Wei Jianfeng Peng +5 位作者 Jinbao Li Jinkuan Li Meng Peng Xuan Li Yameng Liu Jiaxin Li 《Journal of Forestry Research》 SCIE EI CAS CSCD 2024年第1期202-212,共11页
A set of standard chronologies for tree-ring width(TRW),earlywood width(EWW)and latewood width(LWW)in Pinus tabuliformis Carr.along an altitudi-nal gradient(1450,1400,and 1350 m a.s.l.)on Baiyunshan Mountain,Central C... A set of standard chronologies for tree-ring width(TRW),earlywood width(EWW)and latewood width(LWW)in Pinus tabuliformis Carr.along an altitudi-nal gradient(1450,1400,and 1350 m a.s.l.)on Baiyunshan Mountain,Central China to analyze the effect of varying temperature and precipitation on growth along the gradi-ent.Correlation analyses showed that at all three altitudes and the TRW and EWW chronologies generally had signifi-cant negative correlations with mean and maximum tem-peratures in the current April and May and with minimum temperatures in the prior July and August,but significant positive correlations with precipitation in the current May.Correlations were generally significantly negative between LWW chronologies and all temperatures in the prior July and August,indicating that the prior summer temperature had a strong lag effect on the growth of P.tabuliformis that increased with altitude.The correlation with the standard-ized precipitation evapotranspiration index(SPEI)confirmed that wet conditions in the current May promoted growth of TR and EW at all altitudes.Significant altitudinal differences were also found;at 1400 m,there were significant positive correlations between EWW chronologies and SPEI in the current April and significant negative correlations between LWW chronologies and SPEI in the current September,but these correlations were not significant at 1450 m.At 1350 m,there were also significant negative correlations between the TRW and the EWW chronologies and SPEI in the prior October and the current July and between LWW chronology and SPEI in the current August,but these cor-relations were not significant at 1400 m.Moving correlation results showed a stable response of EWW in relation to the SPEI in the current May at all three altitudes and of LWW to maximum temperature in the prior July-August at 1400 m from 2002 to 2018.The EWW chronology at 1400 m and the LWW chronology at 1450 m were identified as more suitable for climate reconstruction.These results provide a strong scientific basis for forest management decisions and climate reconstructions in Central China. 展开更多
关键词 Tree rings Climate response Altitudinal gradient Baiyunshan Mountain Pinus tabuliformis Carr
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Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method 被引量:1
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作者 Xiaojia Yang Jinghuan Jia +5 位作者 Qing Li Renzheng Zhu Jike Yang Zhiyong Liu Xuequn Cheng Xiaogang Li 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2024年第6期1311-1321,共11页
Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for st... Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection. 展开更多
关键词 weathering steel stress-assisted corrosion gradient boosting decision tree machining learning
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