Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the vary...Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.展开更多
Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other...Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.展开更多
Spectrum analysis of the plasma has over the years been growing both in methods and instrument, which makes it become a widely used non-contact detection method, without disturbing the arc plasma itself. With noticeab...Spectrum analysis of the plasma has over the years been growing both in methods and instrument, which makes it become a widely used non-contact detection method, without disturbing the arc plasma itself. With noticeable developments in the industry application of the method, a need for careful analysis of the plasma with both time and space identification is desirable. Therefore, a spectral measurement system is developed in this paper for diagnosing arc plasma with time and space identification. With a new hollow probe scanning method, the instrument can be used to provide information like energy distribution of plasma, temperature within the arc plasma, which are of great significance with the requirement of space identification. Furthermore, the system can also be used to capture the instant state of the arc plasma with the synchronic triggering system, which uses high speed photo and electrical signal as the time criterion. The industry applications prove that the system works well for online detection of the arc plasma.展开更多
Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot disti...Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot distinguish urban population during the daytime from that at night, existed research in this field are quite limited. This paper tries to advance studies at this aspect by establishing a relationship model for the three components of ＇population, land use and time （daytime or night）＇ to explore the temporal and spatial characteristics of different types of population, which is aimed to estimate urban population during the daytime and at night and to analyze their spatial characteristics at grid scale. Furthermore, an empirical case study has been carried out at the Haidian District in Beijing, China to test the model. The results are as follows： （1） The spatial structure of urban population during the daytime is significantly different from that at night. The spatial distribution of urban population during the daytime is more extensive and more agglomerated that that at night. （2） Several types of spatial coupling relationship between population during the daytime and that at night have been identified, such as sandwich mode, symmetry mode, convergence mode and single mode, etc. （3） The spatial distribution of daytime and nighttime population also reflects certain factors during the development of China, such as the distribution of old residential areas, the construction of new industrial districts, and the differences between urban and rural areas, which can provide reference points for studies in this field and other regional research.展开更多
In this research, effect of varying spatial orientations on the build time requirements for fused deposition modelling process is studied. Constructive solid geometry cylindrical primitive is taken as work piece and m...In this research, effect of varying spatial orientations on the build time requirements for fused deposition modelling process is studied. Constructive solid geometry cylindrical primitive is taken as work piece and modeling is accomplished for it. Response surface methodology is used to design the experiments and obtain statistical models for build time requirements corresponding to different orientations of the given primitive in modeller build volume. Contour width, air gap, slice height, raster width, raster angle and angle of orientation are treated as process parameters. Percentage contribution of individual process parameter is found to change for build time corresponding to different spatial orientations. Also, the average of build time requirement changes with spatial orientation. This paper attempts to clearly discuss and describe the observations with an aim to develop a clear understanding of effect of spatial variations on the build time for Fused Deposition Modelling process. This work is an integral part of process layout optimization and these results can effectively aid designers specially while tackling nesting issues.展开更多
A guidance policy for controller performance enhancement utilizing mobile sensor-actuator networks （MSANs） is proposed for a class of distributed parameter systems （DPSs）, which are governed by diffusion partial d...A guidance policy for controller performance enhancement utilizing mobile sensor-actuator networks （MSANs） is proposed for a class of distributed parameter systems （DPSs）, which are governed by diffusion partial differential equations （PDEs） with time-dependent spatial domains. Several sufficient conditions for controller performance enhancement are presented. First, the infinite dimensional operator theory is used to derive an abstract evolution equation of the systems under some rational assumptions on the operators, and a static output feedback controller is designed to control the spatial process. Then, based on Lyapunov stability arguments, guidance policies for collocated and non-collocated MSANs are provided to enhance the performance of the proposed controller, which show that the time-dependent characteristic of the spatial domains can significantly affect the design of the mobile scheme. Finally, a simulation example illustrates the effectiveness of the proposed policy.展开更多
Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stab...Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.展开更多
Location advantages of ports refer to the current developments of ports based on their conditions, such as geographic location, traffic accessibility and hinterland economy, etc., and the spatial pattern of ports’ lo...Location advantages of ports refer to the current developments of ports based on their conditions, such as geographic location, traffic accessibility and hinterland economy, etc., and the spatial pattern of ports’ location advantages reflects the spatial distributions, the regularities and the correlations among their conditions for development. A good understanding of the spatial patterns of ports’ location advantages can help to better identify the relative advantages of ports, position ports’ functions and make strategic plans for development. This paper selected 1259 ports from 63 countries along the Maritime Silk Road as research objects and builds an accessing model to analyze their location advantages on the bases of six factors: the influence of strategic shipping pivot, the competitiveness of port location potential, port network status, the influence of city, the influence of traffic trunk, and road network density in hinterland. The study has the following three findings. Firstly, the location advantages of ports show a 'high-low-high' distribution pattern from the west to the east, displaying an obvious 'core-periphery' regionalized distribution. Secondly, most ports have high location advantages, mainly located in Strait of Malacca, the United Arab Emirates, northern Mediterranean coastal region and China-Japan region, the top 10 ports are mainly located in Singapore, China, Malaysia and Japan, indicating that the shipping industry in Asia-Pacific region has stepped to the far front of the global competition;slow economic growths, wars, far away from the Belt and Road countries or bad climate have low location advantages, mainly located in African coastal areas, Oceania, Northeast Europe and Russia. Thirdly, compared with the landward location advantages, the seaward location advantages have a higher influence, and different indicators of location advantages have different influences on the evaluation results, the competitiveness of port location potential being the core indicator.展开更多
In this paper,we design a spatial modulation based orthogonal time frequency space(SMOTFS)system to achieve improved transmission reliability and meet the high transmission rate and highspeed demands of future mobile ...In this paper,we design a spatial modulation based orthogonal time frequency space(SMOTFS)system to achieve improved transmission reliability and meet the high transmission rate and highspeed demands of future mobile communications,which fully utilizes the characteristics of spatial modulation(SM)and orthogonal time frequency space(OTFS)transmission.The detailed system design and signal processing of the SM-OTFS system have been presented.The closed-form expressions of the average symbol error rate(ASER)and average bit error rate(ABER)of the SM-OTFS system have been derived over the delay-Doppler channel with the help of the union bounding technique and moment-generating function(MGF).Meanwhile,the system complexity has been evaluated.Numerical results verify the correctness of the theoretical ASER and ABER analysis of the SM-OTFS system in the high signal-to-noise ratio(SNR)regions and also show that the SM-OTFS system outperforms the traditional SM based orthogonal frequency division multiplexing(SM-OFDM)system with limited complexity increase under mobile conditions,especially in high mobility scenarios.展开更多
Construction of road infrastructure is fundamental to city operation and development, as well as an important pathway and focus in physical urban-rural integration. The long-term implementation of a system of ring roa...Construction of road infrastructure is fundamental to city operation and development, as well as an important pathway and focus in physical urban-rural integration. The long-term implementation of a system of ring roads plus radiating roads in Beijing has strongly impacted urban infrastructure construction and space-time accessibility. Particularly, recent rapid growth of private car ownership in Beijing has imposed greater loads on its road system, seriously hampering urban commuting efficiency and negatively impacting quality of life. To address such challenges and enhance the rapid development of transport infrastructure, Beijing has accelerated rail transit construction since 2008 in an effort to improve commuting capacity. This paper aims to measure time accessibility and its spatial characteristics in urban areas of Beijing by applying a comprehensive method that combines vector and raster attribute data generated from road network and subway transport infrastructure. By using a dual index of accessibility and road density, the study further reveals the features of and differences in spatial accessibility and the construction of road systems in urban areas of the northern and southern parts of Beijing. The findings of this study can provide a scientific basis for future urban planning and road system construction both in general and with respect to Beijing, given its aspirations to become a world city.展开更多
Associated alpha particle imaging based on the time-of-flight(API-TOF) technique is an advanced neutron analysis method, which is capable of discriminating material nuclides and three-dimensional imaging of the spatia...Associated alpha particle imaging based on the time-of-flight(API-TOF) technique is an advanced neutron analysis method, which is capable of discriminating material nuclides and three-dimensional imaging of the spatial distribution of material nuclei. In this paper, the spatial resolution of API-TOF and its effects are studied using mathematical analysis and Monte Carlo numerical simulation. The results can provide guidance and assist in designing of API-TOF detection devices. First, a mathematical analysis of the imaging principles of the API-TOF was carried out, and the calculation formulas of the spatial resolution of API-TOF were deduced. Next, the relationship between the device layout and the spatial resolution of the API-TOF detection device was studied. The concept of a typical API-TOF detection device with an optimized structure was proposed. Then, the spatial distribution of the spatial resolution of the typical API-TOF detection device was analyzed, and the effects of the time resolution and the neutron emission angle resolution on the spatial resolution were studied. The results show that spatial resolutions better than 1 cm can be achieved by improving the time resolution and the neutron emission angle resolution to appropriate levels. Finally, a Monte Carlo numerical simulation program was developed for the study of the APITOF and was used to calculate the spatial resolutions of the API-TOF. The comparison of the results shows that thespatial resolutions calculated based on the Monte Carlo numerical simulation are in good agreement with those calculated based on the mathematical analysis. This verifies the mathematical analysis and the evaluation of the effects of the spatial resolution of the API-TOF in this study.展开更多
This study explored spatial explicit multiple cropping efficiency （MCE） of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis （SFA）. We firstly extra...This study explored spatial explicit multiple cropping efficiency （MCE） of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis （SFA）. We firstly extracted multiple cropping index （MCI） on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer （MODIS） enhanced vegetation index （EVI） value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% double- cropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.展开更多
Bus arrival time prediction contributes to the quality improvement of public transport services.Passengers can arrange departure time effectively if they know the accurate bus arrival time in advance.We proposed a mac...Bus arrival time prediction contributes to the quality improvement of public transport services.Passengers can arrange departure time effectively if they know the accurate bus arrival time in advance.We proposed a machine⁃learning approach,RTSI⁃ResNet,to forecast the bus arrival time at target stations.The residual neural network framework was employed to model the bus route temporal⁃spatial information.It was found that the bus travel time on a segment between two stations not only had correlation with the preceding buses,but also had common change trends with nearby downstream/upstream segments.Two features about bus travel time and headway were extracted from bus route including target section in both forward and reverse directions to constitute the route temporal⁃spatial information,which reflects the road traffic conditions comprehensively.Experiments on the bus trajectory data of route No.10 in Shenzhen public transport system demonstrated that the proposed RTSI⁃ResNet outperformed other well⁃known methods(e.g.,RNN/LSTM,SVM).Specifically,the advantage was more significant when the distance between bus and the target station was farther.展开更多
Competition of spatial and temporal instabilities under time delay near the codimension-two Turing-Hopfbifurcations is studied in a reaction-diffusion equation.The time delay changes remarkably the oscillation frequen...Competition of spatial and temporal instabilities under time delay near the codimension-two Turing-Hopfbifurcations is studied in a reaction-diffusion equation.The time delay changes remarkably the oscillation frequency,theintrinsic wave vector,and the intensities of both Turing and Hopf modes.The application of appropriate time delaycan control the competition between the Turing and Hopf modes.Analysis shows that individual or both feedbacks canrealize the control of the transformation between the Turing and Hopf patterns.Two-dimensional numerical simulationsvalidate the analytical results.展开更多
In monoculture, crop failure due to biotic or abiotic causes can result in partial or total output failure. The yield, socio-economic, and environmental effects of intercropping on the farmer and the environment as a ...In monoculture, crop failure due to biotic or abiotic causes can result in partial or total output failure. The yield, socio-economic, and environmental effects of intercropping on the farmer and the environment as a whole have not received much attention. There is a dearth of knowledge on the productivity of maize-groundnut intercrops in Ghana regarding the relative timing of planting and spatial arrangement of component crops. Therefore, the objective of the study was to determine the effects of spatial row arrangement and the time of planting intercrops on the productivity of groundnut under maize-groundnut intercropping. The 5 × 3 factorial field experiment was undertaken at the Miminaso community in the Ejura-Sekyedumase municipality of the Ashanti Region of Ghana during the 2020 cropping seasons. Treatments were evaluated in a Randomized Complete Block Design (RCBD) with three replicates. The levels of row arrangement of intercrops were: one row of maize and one row of groundnut (1M1G), one row of maize and two rows of groundnut (1M2G), two rows of maize and one row of groundnut (2M1G), two rows of maize and two rows of groundnut (2M2G), sole maize and sole groundnut (M/G). The levels of time of introducing groundnut included simultaneous planting of intercrops (0 WAP), planting groundnut one week after planting maize (1 WAP) and planting groundnut two weeks after planting maize (2 WAP). There were significant (P 0.05) treatment interactions for pod and seed yields of groundnut throughout the study. The highest groundnut pod yields of 1815.00 kg/ha and 2359.00 kg/ha were recorded by the 0WAP × 1M2G treatment in the major and minor seasons of 2020, respectively, while the highest groundnut seed yields of 741.00 kg/ha and 726.00 kg/ha were recorded in the major and minor rainy seasons of 2020 by 1WAP × G and 0WAP × G treatments, respectively. The highest seed yields of groundnut (404 kg/ha and 637 kg/ha for major and minor rainy seasons, respectively) were produced by 1WAP × 2M2G.展开更多
The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial charact...The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.展开更多
Spatially distributed systems （SDSs） are usually infinite-dimensional spatio-temporal systems with unknown nonlinearities. Therefore, to model such systems is difficult. In real applications, a low-dimensional model...Spatially distributed systems （SDSs） are usually infinite-dimensional spatio-temporal systems with unknown nonlinearities. Therefore, to model such systems is difficult. In real applications, a low-dimensional model is required. In this paper, a time/space separation based 3D fuzzy modeling approach is proposed for unknown nonlinear SDSs using input-output data measurement. The main characteristics of this approach is that time/space separation and time/space reconstruction are fused into a novel 3D fuzzy system. The modeling methodology includes two stages. The first stage is 3D fuzzy structure modeling which is based on Mamdani fuzzy rules. The consequent sets of 3D fuzzy rules consist of spatial basis functions estimated by Karhunen-Love decomposition. The antecedent sets of 3D fuzzy rules are used to construct temporal coefficients. Going through 3D fuzzy rule inference, each rule realizes time/space synthesis. The second stage is parameter identification of 3D fuzzy system using particle swarm optimization algorithm. After an operation of defuzzification, the output of the 3D fuzzy system can reconstruct the spatio-temporal dynamics of the system. The model is suitable for the prediction and control design of the SDS since it is of low-dimension and simple nonlinear structure. The simulation and experiment are presented to show the effectiveness of the proposed modeling approach.展开更多
In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.A...In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.展开更多
基金supported by the Collaborative Tackling Project of the Yangtze River Delta SciTech Innovation Community(Nos.2024CSJGG01503,2024CSJGG01500)Guangxi Key Research and Development Program(No.AB24010317)Jiangxi Provincial Key Laboratory of Electronic Data Control and Forensics(Jiangxi Police College)(No.2025JXJYKFJJ002).
文摘Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.
文摘Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.
基金Research Project Supported by Shanxi Scholarship Council of China(No.2012-69)Selected Research Project by Department of Human Resources and Social Security of Shanxi
文摘Spectrum analysis of the plasma has over the years been growing both in methods and instrument, which makes it become a widely used non-contact detection method, without disturbing the arc plasma itself. With noticeable developments in the industry application of the method, a need for careful analysis of the plasma with both time and space identification is desirable. Therefore, a spectral measurement system is developed in this paper for diagnosing arc plasma with time and space identification. With a new hollow probe scanning method, the instrument can be used to provide information like energy distribution of plasma, temperature within the arc plasma, which are of great significance with the requirement of space identification. Furthermore, the system can also be used to capture the instant state of the arc plasma with the synchronic triggering system, which uses high speed photo and electrical signal as the time criterion. The industry applications prove that the system works well for online detection of the arc plasma.
基金National Natural Science Foundation of China, No.41271174 National Science and Technology Support Program, No.2012BAI32B07
文摘Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot distinguish urban population during the daytime from that at night, existed research in this field are quite limited. This paper tries to advance studies at this aspect by establishing a relationship model for the three components of ＇population, land use and time （daytime or night）＇ to explore the temporal and spatial characteristics of different types of population, which is aimed to estimate urban population during the daytime and at night and to analyze their spatial characteristics at grid scale. Furthermore, an empirical case study has been carried out at the Haidian District in Beijing, China to test the model. The results are as follows： （1） The spatial structure of urban population during the daytime is significantly different from that at night. The spatial distribution of urban population during the daytime is more extensive and more agglomerated that that at night. （2） Several types of spatial coupling relationship between population during the daytime and that at night have been identified, such as sandwich mode, symmetry mode, convergence mode and single mode, etc. （3） The spatial distribution of daytime and nighttime population also reflects certain factors during the development of China, such as the distribution of old residential areas, the construction of new industrial districts, and the differences between urban and rural areas, which can provide reference points for studies in this field and other regional research.
文摘In this research, effect of varying spatial orientations on the build time requirements for fused deposition modelling process is studied. Constructive solid geometry cylindrical primitive is taken as work piece and modeling is accomplished for it. Response surface methodology is used to design the experiments and obtain statistical models for build time requirements corresponding to different orientations of the given primitive in modeller build volume. Contour width, air gap, slice height, raster width, raster angle and angle of orientation are treated as process parameters. Percentage contribution of individual process parameter is found to change for build time corresponding to different spatial orientations. Also, the average of build time requirement changes with spatial orientation. This paper attempts to clearly discuss and describe the observations with an aim to develop a clear understanding of effect of spatial variations on the build time for Fused Deposition Modelling process. This work is an integral part of process layout optimization and these results can effectively aid designers specially while tackling nesting issues.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61174021 and 61473136)
文摘A guidance policy for controller performance enhancement utilizing mobile sensor-actuator networks （MSANs） is proposed for a class of distributed parameter systems （DPSs）, which are governed by diffusion partial differential equations （PDEs） with time-dependent spatial domains. Several sufficient conditions for controller performance enhancement are presented. First, the infinite dimensional operator theory is used to derive an abstract evolution equation of the systems under some rational assumptions on the operators, and a static output feedback controller is designed to control the spatial process. Then, based on Lyapunov stability arguments, guidance policies for collocated and non-collocated MSANs are provided to enhance the performance of the proposed controller, which show that the time-dependent characteristic of the spatial domains can significantly affect the design of the mobile scheme. Finally, a simulation example illustrates the effectiveness of the proposed policy.
基金supported by the National Natural Science Foundation of China(Grant No.52308340)the Innovative Projects of Universities in Guangdong(Grant No.2022KTSCX208)Sichuan Transportation Science and Technology Project(Grant No.2018-ZL-01).
文摘Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.
基金Major Program of National Social Science Fund of China,No.20&ZD070。
文摘Location advantages of ports refer to the current developments of ports based on their conditions, such as geographic location, traffic accessibility and hinterland economy, etc., and the spatial pattern of ports’ location advantages reflects the spatial distributions, the regularities and the correlations among their conditions for development. A good understanding of the spatial patterns of ports’ location advantages can help to better identify the relative advantages of ports, position ports’ functions and make strategic plans for development. This paper selected 1259 ports from 63 countries along the Maritime Silk Road as research objects and builds an accessing model to analyze their location advantages on the bases of six factors: the influence of strategic shipping pivot, the competitiveness of port location potential, port network status, the influence of city, the influence of traffic trunk, and road network density in hinterland. The study has the following three findings. Firstly, the location advantages of ports show a 'high-low-high' distribution pattern from the west to the east, displaying an obvious 'core-periphery' regionalized distribution. Secondly, most ports have high location advantages, mainly located in Strait of Malacca, the United Arab Emirates, northern Mediterranean coastal region and China-Japan region, the top 10 ports are mainly located in Singapore, China, Malaysia and Japan, indicating that the shipping industry in Asia-Pacific region has stepped to the far front of the global competition;slow economic growths, wars, far away from the Belt and Road countries or bad climate have low location advantages, mainly located in African coastal areas, Oceania, Northeast Europe and Russia. Thirdly, compared with the landward location advantages, the seaward location advantages have a higher influence, and different indicators of location advantages have different influences on the evaluation results, the competitiveness of port location potential being the core indicator.
基金in part by the National Natural Science Foundation of China under Grant 61771291,Grant 61671278in part by the Key Research and Development Project of Shandong Province under Grant 2018GGX101009,Grant 2019TSLH0202,Grant 2020CXGC010109+1 种基金in part by the National Nature Science Foundation of China for Excellent Young Scholars under Grant 61622111in part by the Project of International Cooperation and Exchanges NSFC under Grant 61860206005.
文摘In this paper,we design a spatial modulation based orthogonal time frequency space(SMOTFS)system to achieve improved transmission reliability and meet the high transmission rate and highspeed demands of future mobile communications,which fully utilizes the characteristics of spatial modulation(SM)and orthogonal time frequency space(OTFS)transmission.The detailed system design and signal processing of the SM-OTFS system have been presented.The closed-form expressions of the average symbol error rate(ASER)and average bit error rate(ABER)of the SM-OTFS system have been derived over the delay-Doppler channel with the help of the union bounding technique and moment-generating function(MGF).Meanwhile,the system complexity has been evaluated.Numerical results verify the correctness of the theoretical ASER and ABER analysis of the SM-OTFS system in the high signal-to-noise ratio(SNR)regions and also show that the SM-OTFS system outperforms the traditional SM based orthogonal frequency division multiplexing(SM-OFDM)system with limited complexity increase under mobile conditions,especially in high mobility scenarios.
基金National Natural Science Foundation of China,No.41601164,No.41601427Key Program of National Natural Science Foundation of China,No.71433008Cultivate Project of Institute of Geographic Sciences and Natural Resources Research,CAS,No.TSYJS03
文摘Construction of road infrastructure is fundamental to city operation and development, as well as an important pathway and focus in physical urban-rural integration. The long-term implementation of a system of ring roads plus radiating roads in Beijing has strongly impacted urban infrastructure construction and space-time accessibility. Particularly, recent rapid growth of private car ownership in Beijing has imposed greater loads on its road system, seriously hampering urban commuting efficiency and negatively impacting quality of life. To address such challenges and enhance the rapid development of transport infrastructure, Beijing has accelerated rail transit construction since 2008 in an effort to improve commuting capacity. This paper aims to measure time accessibility and its spatial characteristics in urban areas of Beijing by applying a comprehensive method that combines vector and raster attribute data generated from road network and subway transport infrastructure. By using a dual index of accessibility and road density, the study further reveals the features of and differences in spatial accessibility and the construction of road systems in urban areas of the northern and southern parts of Beijing. The findings of this study can provide a scientific basis for future urban planning and road system construction both in general and with respect to Beijing, given its aspirations to become a world city.
文摘Associated alpha particle imaging based on the time-of-flight(API-TOF) technique is an advanced neutron analysis method, which is capable of discriminating material nuclides and three-dimensional imaging of the spatial distribution of material nuclei. In this paper, the spatial resolution of API-TOF and its effects are studied using mathematical analysis and Monte Carlo numerical simulation. The results can provide guidance and assist in designing of API-TOF detection devices. First, a mathematical analysis of the imaging principles of the API-TOF was carried out, and the calculation formulas of the spatial resolution of API-TOF were deduced. Next, the relationship between the device layout and the spatial resolution of the API-TOF detection device was studied. The concept of a typical API-TOF detection device with an optimized structure was proposed. Then, the spatial distribution of the spatial resolution of the typical API-TOF detection device was analyzed, and the effects of the time resolution and the neutron emission angle resolution on the spatial resolution were studied. The results show that spatial resolutions better than 1 cm can be achieved by improving the time resolution and the neutron emission angle resolution to appropriate levels. Finally, a Monte Carlo numerical simulation program was developed for the study of the APITOF and was used to calculate the spatial resolutions of the API-TOF. The comparison of the results shows that thespatial resolutions calculated based on the Monte Carlo numerical simulation are in good agreement with those calculated based on the mathematical analysis. This verifies the mathematical analysis and the evaluation of the effects of the spatial resolution of the API-TOF in this study.
基金supported by the National Natural Science Foundation of China (41001277)the National 973 Program of China (2010CB95090102)
文摘This study explored spatial explicit multiple cropping efficiency （MCE） of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis （SFA）. We firstly extracted multiple cropping index （MCI） on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer （MODIS） enhanced vegetation index （EVI） value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% double- cropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.
基金Sponsored by the Transportation Science and Technology Planning Project of Henan Province,China(Grant No.2019G-2-2).
文摘Bus arrival time prediction contributes to the quality improvement of public transport services.Passengers can arrange departure time effectively if they know the accurate bus arrival time in advance.We proposed a machine⁃learning approach,RTSI⁃ResNet,to forecast the bus arrival time at target stations.The residual neural network framework was employed to model the bus route temporal⁃spatial information.It was found that the bus travel time on a segment between two stations not only had correlation with the preceding buses,but also had common change trends with nearby downstream/upstream segments.Two features about bus travel time and headway were extracted from bus route including target section in both forward and reverse directions to constitute the route temporal⁃spatial information,which reflects the road traffic conditions comprehensively.Experiments on the bus trajectory data of route No.10 in Shenzhen public transport system demonstrated that the proposed RTSI⁃ResNet outperformed other well⁃known methods(e.g.,RNN/LSTM,SVM).Specifically,the advantage was more significant when the distance between bus and the target station was farther.
基金Supported by the Fundamental Research Funds for the Central Universities under Grant No. 09ML56the Foundation for Young Teachers of the North China Electric Power University, China under Grant No. 200611029
文摘Competition of spatial and temporal instabilities under time delay near the codimension-two Turing-Hopfbifurcations is studied in a reaction-diffusion equation.The time delay changes remarkably the oscillation frequency,theintrinsic wave vector,and the intensities of both Turing and Hopf modes.The application of appropriate time delaycan control the competition between the Turing and Hopf modes.Analysis shows that individual or both feedbacks canrealize the control of the transformation between the Turing and Hopf patterns.Two-dimensional numerical simulationsvalidate the analytical results.
文摘In monoculture, crop failure due to biotic or abiotic causes can result in partial or total output failure. The yield, socio-economic, and environmental effects of intercropping on the farmer and the environment as a whole have not received much attention. There is a dearth of knowledge on the productivity of maize-groundnut intercrops in Ghana regarding the relative timing of planting and spatial arrangement of component crops. Therefore, the objective of the study was to determine the effects of spatial row arrangement and the time of planting intercrops on the productivity of groundnut under maize-groundnut intercropping. The 5 × 3 factorial field experiment was undertaken at the Miminaso community in the Ejura-Sekyedumase municipality of the Ashanti Region of Ghana during the 2020 cropping seasons. Treatments were evaluated in a Randomized Complete Block Design (RCBD) with three replicates. The levels of row arrangement of intercrops were: one row of maize and one row of groundnut (1M1G), one row of maize and two rows of groundnut (1M2G), two rows of maize and one row of groundnut (2M1G), two rows of maize and two rows of groundnut (2M2G), sole maize and sole groundnut (M/G). The levels of time of introducing groundnut included simultaneous planting of intercrops (0 WAP), planting groundnut one week after planting maize (1 WAP) and planting groundnut two weeks after planting maize (2 WAP). There were significant (P 0.05) treatment interactions for pod and seed yields of groundnut throughout the study. The highest groundnut pod yields of 1815.00 kg/ha and 2359.00 kg/ha were recorded by the 0WAP × 1M2G treatment in the major and minor seasons of 2020, respectively, while the highest groundnut seed yields of 741.00 kg/ha and 726.00 kg/ha were recorded in the major and minor rainy seasons of 2020 by 1WAP × G and 0WAP × G treatments, respectively. The highest seed yields of groundnut (404 kg/ha and 637 kg/ha for major and minor rainy seasons, respectively) were produced by 1WAP × 2M2G.
基金Projects(LQ16E080012,LY14F030012)supported by the Zhejiang Provincial Natural Science Foundation,ChinaProject(61573317)supported by the National Natural Science Foundation of ChinaProject(2015001)supported by the Open Fund for a Key-Key Discipline of Zhejiang University of Technology,China
文摘The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.
基金supported by National Science Foundation of China(Nos.61273182,31570998,51375293 and 61374112)
文摘Spatially distributed systems （SDSs） are usually infinite-dimensional spatio-temporal systems with unknown nonlinearities. Therefore, to model such systems is difficult. In real applications, a low-dimensional model is required. In this paper, a time/space separation based 3D fuzzy modeling approach is proposed for unknown nonlinear SDSs using input-output data measurement. The main characteristics of this approach is that time/space separation and time/space reconstruction are fused into a novel 3D fuzzy system. The modeling methodology includes two stages. The first stage is 3D fuzzy structure modeling which is based on Mamdani fuzzy rules. The consequent sets of 3D fuzzy rules consist of spatial basis functions estimated by Karhunen-Love decomposition. The antecedent sets of 3D fuzzy rules are used to construct temporal coefficients. Going through 3D fuzzy rule inference, each rule realizes time/space synthesis. The second stage is parameter identification of 3D fuzzy system using particle swarm optimization algorithm. After an operation of defuzzification, the output of the 3D fuzzy system can reconstruct the spatio-temporal dynamics of the system. The model is suitable for the prediction and control design of the SDS since it is of low-dimension and simple nonlinear structure. The simulation and experiment are presented to show the effectiveness of the proposed modeling approach.
基金This work is partly supported by the National Key Research and Development Program of China(Grant No.2020YFB1805403)the National Natural Science Foundation of China(Grant No.62032002)the 111 Project(Grant No.B21049).
文摘In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.
