Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emp...Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.展开更多
This paper introduces MultiPHydro,an in-house computational solver developed for simulating hydrodynamic and multiphase fluid—body interaction problems,with a specialized focus on multiphase flow dynamics.The solver ...This paper introduces MultiPHydro,an in-house computational solver developed for simulating hydrodynamic and multiphase fluid—body interaction problems,with a specialized focus on multiphase flow dynamics.The solver employs the boundary data immersion method(BDIM)as its core numerical framework for handling fluid—solid interfaces.We briefly outline the governing equations and physical models integrated within MultiPHydro,including weakly-compressible flows,cavitation modeling,and the volume of fluid(VOF)method with piecewise-linear interface reconstruction.The solver’s accuracy and versatility are demonstrated through several numerical benchmarks:single-phase flow past a cylinder shows less than 10%error in vortex shedding frequency and under 4%error in hydrodynamic resistance;cavitating flows around a hydrofoil yield errors below 7%in maximum cavity length;water-entry cases exhibit under 5%error in displacement and velocity;and water-exit simulations predict cavity length within 7.2%deviation.These results confirm the solver’s capability to reliably model complex fluid-body interactions across various regimes.Future developments will focus on refining mathematical models,improving the modeling of phase-interaction mechanisms,and implementing GPU-accelerated parallel algorithms to enhance compatibility with domestically-developed operating systems and deep computing units(DCUs).展开更多
As the crypto-asset ecosystem matures,the use of high-frequency data has become increasingly common in decentralized finance literature.Using bibliometric analysis,we characterize the existing cryptocurrency literatur...As the crypto-asset ecosystem matures,the use of high-frequency data has become increasingly common in decentralized finance literature.Using bibliometric analysis,we characterize the existing cryptocurrency literature that employs high-frequency data.We highlighted the most influential authors,articles,and journals based on 189 articles from the Scopus database from 2015 to 2022.This approach enables us to identify emerging trends and research hotspots with the aid of co-citation and cartographic analyses.It shows knowledge expansion through authors’collaboration in cryptocurrency research with co-authorship analysis.We identify four major streams of research:(i)return prediction and measurement of cryptocurrency volatility,(ii)(in)efficiency of cryptocurrencies,(iii)price dynamics and bubbles in cryptocurrencies,and(iv)the diversification,safe haven,and hedging properties of Bitcoin.We conclude that highly traded cryptocurrencies’investment features and economic outcomes are analyzed predominantly on a tick-by-tick basis.This study also provides recommendations for future studies.展开更多
Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analy...Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.展开更多
Objectives:Somatosensory Interaction Technology(SIT)is used in various aspects of geriatric care.We aimed to conduct a bibliometric analysis to summarize relevant publications and visualize publication characteristics...Objectives:Somatosensory Interaction Technology(SIT)is used in various aspects of geriatric care.We aimed to conduct a bibliometric analysis to summarize relevant publications and visualize publication characteristics,current hotspots,and development trends,thereby inspiring subsequent researches.Methods:We searched theWeb of Science Core Collection database for publications on the application of SIT in geriatric care.Bibliometric visualization and clustering analysis were performed using VOSviewer V1.6.18 Software,while keywords burst detection analysis was conducted with CiteSpace 6.1.R6 Software.Results:After screening,a total of 1,019 publications were included.The number of publications on SIT in geriatric care is gradually increasing,exhibiting a rapid growth rate.The United States,Canada,and Australia led in terms of publication volume.Keyword clustering analysis identified major research hotspots:crisis warning,somatic abilities,rehabilitation training and psychosocial support.Initial studies primarily explored themes such as recovery,movement,systems,and later shifted towards gait analysis,muscle strength,parameters,and home-based care.More recently,research themes have evolved to dementia,machine learning,and gamification.Conclusions:SIT is innovative for promoting active aging,advancing intelligent healthcare,and elevating the daily quality of life for older adults in clinical and domestic settings.Applications of SIT can be categorized into early warning systems for crises,detailed analyses of physical conditions,rehabilitation enhancement,and support for psychosocial health.Research trends have transitioned from whole-body recognition to precise feedback,from a focus on physical health to mental health,and from technical feasibility to user-friendliness.Future research should focus on developing accessible and user-friendly devices,fostering interdisciplinary collaborations for innovation,expanding research to address both the physical and mental health needs of diverse older adults,and integrating emerging technologies to enhance data precision and accelerate the development of intelligent platforms.展开更多
The low-pass fi ltering eff ect of the Earth results in the absorption and attenuation of the high-frequency components of seismic signals by the stratum during propagation.Hence,seismic data have low resolution.Consi...The low-pass fi ltering eff ect of the Earth results in the absorption and attenuation of the high-frequency components of seismic signals by the stratum during propagation.Hence,seismic data have low resolution.Considering the limitations of traditional high-frequency compensation methods,this paper presents a new method based on adaptive generalized S transform.This method is based on the study of frequency spectrum attenuation law of seismic signals,and the Gauss window function of adaptive generalized S transform is used to fi t the attenuation trend of seismic signals to seek the optimal Gauss window function.The amplitude spectrum compensation function constructed using the optimal Gauss window function is used to modify the time-frequency spectrum of the adaptive generalized S transform of seismic signals and reconstruct seismic signals to compensate for high-frequency attenuation.Practical data processing results show that the method can compensate for the high-frequency components that are absorbed and attenuated by the stratum,thereby eff ectively improving the resolution and quality of seismic data.展开更多
Logic regression is an adaptive regression method which searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome, and thus, it reveals interaction effects which ar...Logic regression is an adaptive regression method which searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome, and thus, it reveals interaction effects which are associated with the response. In this study, we extended logic regression to longitudinal data with binary response and proposed “Transition Logic Regression Method” to find interactions related to response. In this method, interaction effects over time were found by Annealing Algorithm with AIC (Akaike Information Criterion) as the score function of the model. Also, first and second orders Markov dependence were allowed to capture the correlation among successive observations of the same individual in longitudinal binary response. Performance of the method was evaluated with simulation study in various conditions. Proposed method was used to find interactions of SNPs and other risk factors related to low HDL over time in data of 329 participants of longitudinal TLGS study.展开更多
In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to an...In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation data.Second,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and storage.In our context model,all the main animation elements in a scene are operated as a whole.Then sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user operations.Finally,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.展开更多
In view of the extensive growth of China's steel production in recent years, this paper analyzed the industrial development background and economic geography theory, and discussed the possible spatial interaction ...In view of the extensive growth of China's steel production in recent years, this paper analyzed the industrial development background and economic geography theory, and discussed the possible spatial interaction mechanism. Based on panel data of China's inter-provincial steel output from 2001 to 2015, using spatial econometric model, this paper also explored whether China's provincial steel production shows material orientation, market orientation and traffic orientation, and isolated spatial interactions of interprovincial steel output. The results showed that the inter-provincial steel production in China did show both material orientation, market orientation and traffic orientation and that there was a significant negative spatial interaction, indicating that there might be strong competition and a crowing-out effect between neighboring provinces, and that the smaller the spatial scope, the more significant the spatial interactions of steel production.展开更多
Detecting genotype-by-environment (GE) interaction effects or yield stability is one of the most important components for crop trial data analysis, especially in historical crop trial data. However, it is statisticall...Detecting genotype-by-environment (GE) interaction effects or yield stability is one of the most important components for crop trial data analysis, especially in historical crop trial data. However, it is statistically challenging to discover the GE interaction effects because many published data were just entry means under each environment rather than repeated field plot data. In this study, we propose a new methodology, which can be used to impute replicated trial data sets to reveal GE interactions from the original data. As a demonstration, we used a data set, which includes 28 potato genotypes and six environments with three replications to numerically evaluate the properties of this new imputation method. We compared the phenotypic means and predicted random effects from the imputed data with the results from the original data. The results from the imputed data were highly consistent with those from the original data set, indicating that imputed data from the method we proposed in this study can be used to reveal information including GE interaction effects harbored in the original data. Therefore, this study could pave a way to detect the GE interactions and other related information from historical crop trial reports when replications were not available.展开更多
As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynami...As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynamics.The high complexity of industrial big data poses challenges for the practical decision-making of domain experts,leading to ever-increasing needs for integrating computational intelligence with human perception into traditional data analysis.Industrial big data visualization integrates theoretical methods and practical technologies from multiple disciplines,including data mining,information visualization,computer graphics,and human-computer interaction,providing a highly effective manner for understanding and exploring the complex industrial processes.This review summarizes the state-of-the-art approaches,characterizes them with six visualization methods,and categorizes them based on analytical tasks and applications.Furthermore,key research challenges and potential future directions are identified.展开更多
Population migration data derived from location-based services has often been used to delineate population flows between cities or construct intercity relationship networks to reveal and explore the complex interactio...Population migration data derived from location-based services has often been used to delineate population flows between cities or construct intercity relationship networks to reveal and explore the complex interaction patterns underlying human activities.Nevertheless,the inherent heterogeneity in multimodal migration big data has been ignored.This study conducts an in-depth comparison and quantitative analysis through a comprehensive lens of spatial association.Initially,the intercity interactive networks in China were constructed,utilizing migration data from Baidu and AutoNavi collected during the same time period.Subsequently,the characteristics and spatial structure similarities of the two types of intercity interactive networks were quantitatively assessed and analyzed from overall(network)and local(node)perspectives.Furthermore,the precision of these networks at the local scale is corroborated by constructing an intercity network from mobile phone(MP)data.Results indicate that the intercity interactive networks in China,as delineated by Baidu and AutoNavi migration flows,exhibit a high degree of structure equivalence.The correlation coefficient between these two networks is 0.874.Both networks exhibit a pronounced spatial polarization trend and hierarchical structure.This is evident in their distinct core and peripheral structures,as well as in the varying importance and influence of different nodes within the networks.Nevertheless,there are notable differences worthy of attention.Baidu intercity interactive network exhibits pronounced cross-regional effects,and its high-level interactions are characterized by a“rich-club”phenomenon.The AutoNavi intercity interactive network presents a more significant distance attenuation effect,and the high-level interactions display a gradient distribution pattern.Notably,there exists a substantial correlation between the AutoNavi and MP networks at the local scale,evidenced by a high correlation coefficient of 0.954.Furthermore,the“spatial dislocations”phenomenon was observed within the spatial structures at different levels,extracted from the Baidu and AutoNavi intercity networks.However,the measured results of network spatial structure similarity from three dimensions,namely,node location,node size,and local structure,indicate a relatively high similarity and consistency between the two networks.展开更多
The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM （Capital Asset Pricing Model betas）, derivate pricing and risk management in general. Recent ...The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM （Capital Asset Pricing Model betas）, derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution （both distributional properties and temporal dependencies） of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.展开更多
This paper aims to explore urban geography with a new perspective. Endowed with the urban geography connotations, an improved data field model is employed to integrate temporal dimension into spatial process of cities...This paper aims to explore urban geography with a new perspective. Endowed with the urban geography connotations, an improved data field model is employed to integrate temporal dimension into spatial process of cities in a typical region in this article. Taking the Beijing-Shanghai Corridor including 18 cities as an example, the authors chose the city centricity index (CCI) and the spatial data field model to analyze the evolution process and features of sub-region and urban spatial interaction in this corridor based on the data of 1991, 1996 and 2002. Through the analy- sis, we found that: 1) with the improvement of the urbanization level and the development of urban economy, the cit- ies’ CCI grew, the urban spatial radiative potential enhanced and the radiative range expanded gradually, which reflects the urban spatial interaction’s intensity has been increasing greatly; 2) although the spatial interaction intensity among the cities and sub-regions in the Beijing-Shanghai Corridor was growing constantly, the gap of the spatial interaction strength among different cities and sub-regions was widening, and the spatial division between the developed areas and the less developed areas was obvious; and 3) the intensity of the spatial interaction of Beijing, Shanghai and their urban agglomerations was far greater than that in small cities of other parts of the corridor, and it may have a strong drive force on the choice of spatial location of the economic activities.展开更多
High-frequency surface wave radar（HFSWR） and automatic identification system（AIS） are the two most important sensors used for vessel tracking.The HFSWR can be applied to tracking all vessels in a detection area,wh...High-frequency surface wave radar（HFSWR） and automatic identification system（AIS） are the two most important sensors used for vessel tracking.The HFSWR can be applied to tracking all vessels in a detection area,while the AIS is usually used to verify the information of cooperative vessels.Because of interference from sea clutter,employing single-frequency HFSWR for vessel tracking may obscure vessels located in the blind zones of Bragg peaks.Analyzing changes in the detection frequencies constitutes an effective method for addressing this deficiency.A solution consisting of vessel fusion tracking is proposed using dual-frequency HFSWR data calibrated by the AIS.Since different systematic biases exist between HFSWR frequency measurements and AIS measurements,AIS information is used to estimate and correct the HFSWR systematic biases at each frequency.First,AIS point measurements for cooperative vessels are associated with the HFSWR measurements using a JVC assignment algorithm.From the association results of the cooperative vessels,the systematic biases in the dualfrequency HFSWR data are estimated and corrected.Then,based on the corrected dual-frequency HFSWR data,the vessels are tracked using a dual-frequency fusion joint probabilistic data association（JPDA）-unscented Kalman filter（UKF） algorithm.Experimental results using real-life detection data show that the proposed method is efficient at tracking vessels in real time and can improve the tracking capability and accuracy compared with tracking processes involving single-frequency data.展开更多
This paper presents a composite interaction formula based on the discrete-interaction operator of wave-wave nonlinear interaction for deriving its adjoint source function in the wave assimilation model. Assimilation e...This paper presents a composite interaction formula based on the discrete-interaction operator of wave-wave nonlinear interaction for deriving its adjoint source function in the wave assimilation model. Assimilation experiments were performed using the significant wave heights observed by the TOPES/POSEIDON satellite, and the gradient distribution in the physical space was also analyzed preliminarily.展开更多
Integration of soil information system (SIS) and interactive self-organizing data (ISODATA) was studied to establish proper agricultural developing zones in red soil region of southern China which are of crucial impor...Integration of soil information system (SIS) and interactive self-organizing data (ISODATA) was studied to establish proper agricultural developing zones in red soil region of southern China which are of crucial importance to farmers, researchers, and decision makers while utilizing and managing red soil resources. SIS created by using ARC/INPO was used to provide data acquisition, systematic model parameter assignment, and visual display of analytic results. Topography, temperature, soil component (e.g., organic matter and pH) and condition of agricultural production were selected as parameters of ISODATA model. Taking Longyou County, Zhejiang Province as the case study area, the effect of the integration and recommendations are discussed for future research.展开更多
It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social ...It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social benefits of transportation services,and incorporated it into the comprehensive transportation efficiency evaluation framework as an expected output.Based on the panel data of 30 regions in China from 2003-2018,the CTGE in China was measured using the slacks-based measure-data envelopment analysis(SBM-DEA)model.Further,the dynamic evolution trends of CTGE were determined using the spatial Markov model and exploratory spatio-temporal data analysis(ESTDA)technique from a spatio-temporal perspective.The results showed that the CTGE shows a U-shaped change trend but with an overall low level and significant regional differences.The state transition of CTGE has a strong spatial dependence,and there exists the phenomenon of“club convergence”.Neighbourhood background has a significant impact on the CTGE transition types,and the spatial spillover effect is pronounced.The CTGE has an obvious positive correlation and spatial agglomeration characteristics.The geometric characteristics of the LISA time path show that the evolution process of local spatial structure and local spatial dependence of China’s CTGE is stable,but the integration of spatial evolution is weak.The spatio-temporal transition results of LISA indicate that the CTGE has obvious transfer inertness and has certain path-dependence and spatial locking characteristics,which will become the major difficulty in improving the CTGE.展开更多
Identifying the spatiotemporal interaction pattern of agricultural product circulation(APC)is crucial for agricultural resource adjustment and food security.Current studies are mostly based on static statistical data ...Identifying the spatiotemporal interaction pattern of agricultural product circulation(APC)is crucial for agricultural resource adjustment and food security.Current studies are mostly based on static statistical data over an entire year or a specific period,which cannot describe the spatial pattern of APC and its seasonal variation on a fine spatiotemporal scale.Thus,this study extracts an APC trip chain based on national truck trajectory data and constructs the flow network of the Beijing APC with the city as the spatial unit and the season as the temporal unit.The spatial interaction pattern and seasonal variation in APC are then analyzed from the network spatial form,city node function role,and transportation corridors.The results are as follows:(1)Compared with methods based on static statistical data,the proposed method provides a more complete and refined depiction of the spatiotemporal interaction pattern of APC.(2)The flow network of the Beijing APC involves 316 cities in China,of which 143 cities play a major role with typical seasonal characteristics.These cities can be divided into perennial core cities,perennial major cities,core cities in winter-spring,major cities in winter-spring,core cities in summer-autumn,and major cities in summer-autumn,contributing 2.6%-40.3%to the Beijing APC.(3)There are 6 transportation corridors for the Beijing APC.The Beijing-Tianjin-Hebei corridor and coastal corridor contribute 53.5%and 12.8%of the annual supply,respectively,with a balanced supply in all seasons.The Beijing-Kunming corridor and Beijing-Guangzhou corridor contribute 14.3%and 9.0%,respectively,with much higher supplies in winter and spring.The northeast and northwest corridors contribute 7.3%and 3.3%,respectively,mainly in the summer and autumn.These results help deepen the understanding of agricultural product supply patterns and provide a reference for the design and optimization of agricultural product transportation routes.展开更多
With the increasing popularity of cloud computing, there is an increased de mand for cloud resources in cloud. It has be come even more urgent to find solutions to improve resource utilization. From the per spective o...With the increasing popularity of cloud computing, there is an increased de mand for cloud resources in cloud. It has be come even more urgent to find solutions to improve resource utilization. From the per spective of a cloud consumer, a cloud applica tion processes a large information flow in volving user actions that access resources, but little work has so far been devoted to research from the perspective of the interaction be tween the user and the cloud application. In this paper, we analyze the interaction in detail, and propose a general mathematical interac tion model to formulate the challenge pertain ing to storage resource allocation as an opti mization problem, focusing on minimizing both the user＇s cost and server＇s consumption. A potential response mechanism is then de signed based on the interaction model. Fur thermore, the proposed model is used to ex plore strategies when multiple users access the same file simultaneously. Additionally, an improved queuing system, namely M/ G~ oo queue with standby, is introduced. Finally, an evaluation is presented to verify the interac- tion model.展开更多
文摘Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.
文摘This paper introduces MultiPHydro,an in-house computational solver developed for simulating hydrodynamic and multiphase fluid—body interaction problems,with a specialized focus on multiphase flow dynamics.The solver employs the boundary data immersion method(BDIM)as its core numerical framework for handling fluid—solid interfaces.We briefly outline the governing equations and physical models integrated within MultiPHydro,including weakly-compressible flows,cavitation modeling,and the volume of fluid(VOF)method with piecewise-linear interface reconstruction.The solver’s accuracy and versatility are demonstrated through several numerical benchmarks:single-phase flow past a cylinder shows less than 10%error in vortex shedding frequency and under 4%error in hydrodynamic resistance;cavitating flows around a hydrofoil yield errors below 7%in maximum cavity length;water-entry cases exhibit under 5%error in displacement and velocity;and water-exit simulations predict cavity length within 7.2%deviation.These results confirm the solver’s capability to reliably model complex fluid-body interactions across various regimes.Future developments will focus on refining mathematical models,improving the modeling of phase-interaction mechanisms,and implementing GPU-accelerated parallel algorithms to enhance compatibility with domestically-developed operating systems and deep computing units(DCUs).
文摘As the crypto-asset ecosystem matures,the use of high-frequency data has become increasingly common in decentralized finance literature.Using bibliometric analysis,we characterize the existing cryptocurrency literature that employs high-frequency data.We highlighted the most influential authors,articles,and journals based on 189 articles from the Scopus database from 2015 to 2022.This approach enables us to identify emerging trends and research hotspots with the aid of co-citation and cartographic analyses.It shows knowledge expansion through authors’collaboration in cryptocurrency research with co-authorship analysis.We identify four major streams of research:(i)return prediction and measurement of cryptocurrency volatility,(ii)(in)efficiency of cryptocurrencies,(iii)price dynamics and bubbles in cryptocurrencies,and(iv)the diversification,safe haven,and hedging properties of Bitcoin.We conclude that highly traded cryptocurrencies’investment features and economic outcomes are analyzed predominantly on a tick-by-tick basis.This study also provides recommendations for future studies.
文摘Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.
基金funded by the Chinese Nursing Association(#ZHKYQ202322)the Shanghai Science and Technology Innovation Action Plan Sailing Project(#21YF1447700)the Shanghai Municipal Health Commission(#2024QN026).
文摘Objectives:Somatosensory Interaction Technology(SIT)is used in various aspects of geriatric care.We aimed to conduct a bibliometric analysis to summarize relevant publications and visualize publication characteristics,current hotspots,and development trends,thereby inspiring subsequent researches.Methods:We searched theWeb of Science Core Collection database for publications on the application of SIT in geriatric care.Bibliometric visualization and clustering analysis were performed using VOSviewer V1.6.18 Software,while keywords burst detection analysis was conducted with CiteSpace 6.1.R6 Software.Results:After screening,a total of 1,019 publications were included.The number of publications on SIT in geriatric care is gradually increasing,exhibiting a rapid growth rate.The United States,Canada,and Australia led in terms of publication volume.Keyword clustering analysis identified major research hotspots:crisis warning,somatic abilities,rehabilitation training and psychosocial support.Initial studies primarily explored themes such as recovery,movement,systems,and later shifted towards gait analysis,muscle strength,parameters,and home-based care.More recently,research themes have evolved to dementia,machine learning,and gamification.Conclusions:SIT is innovative for promoting active aging,advancing intelligent healthcare,and elevating the daily quality of life for older adults in clinical and domestic settings.Applications of SIT can be categorized into early warning systems for crises,detailed analyses of physical conditions,rehabilitation enhancement,and support for psychosocial health.Research trends have transitioned from whole-body recognition to precise feedback,from a focus on physical health to mental health,and from technical feasibility to user-friendliness.Future research should focus on developing accessible and user-friendly devices,fostering interdisciplinary collaborations for innovation,expanding research to address both the physical and mental health needs of diverse older adults,and integrating emerging technologies to enhance data precision and accelerate the development of intelligent platforms.
基金This research is supported by the National Science and Technology Major Project of China(No.2011ZX05024-001-03)the Natural Science Basic Research Plan in Shaanxi Province of China(No.2021JQ-588)Innovation Fund for graduate students of Xi’an Shiyou University(No.YCS17111017).
文摘The low-pass fi ltering eff ect of the Earth results in the absorption and attenuation of the high-frequency components of seismic signals by the stratum during propagation.Hence,seismic data have low resolution.Considering the limitations of traditional high-frequency compensation methods,this paper presents a new method based on adaptive generalized S transform.This method is based on the study of frequency spectrum attenuation law of seismic signals,and the Gauss window function of adaptive generalized S transform is used to fi t the attenuation trend of seismic signals to seek the optimal Gauss window function.The amplitude spectrum compensation function constructed using the optimal Gauss window function is used to modify the time-frequency spectrum of the adaptive generalized S transform of seismic signals and reconstruct seismic signals to compensate for high-frequency attenuation.Practical data processing results show that the method can compensate for the high-frequency components that are absorbed and attenuated by the stratum,thereby eff ectively improving the resolution and quality of seismic data.
文摘Logic regression is an adaptive regression method which searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome, and thus, it reveals interaction effects which are associated with the response. In this study, we extended logic regression to longitudinal data with binary response and proposed “Transition Logic Regression Method” to find interactions related to response. In this method, interaction effects over time were found by Annealing Algorithm with AIC (Akaike Information Criterion) as the score function of the model. Also, first and second orders Markov dependence were allowed to capture the correlation among successive observations of the same individual in longitudinal binary response. Performance of the method was evaluated with simulation study in various conditions. Proposed method was used to find interactions of SNPs and other risk factors related to low HDL over time in data of 329 participants of longitudinal TLGS study.
基金Supported by the National Key Research and Development Plan(2016YFB1001200)the National Natural Science Foundation of China(U1435220,61232013)
文摘In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation data.Second,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and storage.In our context model,all the main animation elements in a scene are operated as a whole.Then sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user operations.Finally,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.
文摘In view of the extensive growth of China's steel production in recent years, this paper analyzed the industrial development background and economic geography theory, and discussed the possible spatial interaction mechanism. Based on panel data of China's inter-provincial steel output from 2001 to 2015, using spatial econometric model, this paper also explored whether China's provincial steel production shows material orientation, market orientation and traffic orientation, and isolated spatial interactions of interprovincial steel output. The results showed that the inter-provincial steel production in China did show both material orientation, market orientation and traffic orientation and that there was a significant negative spatial interaction, indicating that there might be strong competition and a crowing-out effect between neighboring provinces, and that the smaller the spatial scope, the more significant the spatial interactions of steel production.
文摘Detecting genotype-by-environment (GE) interaction effects or yield stability is one of the most important components for crop trial data analysis, especially in historical crop trial data. However, it is statistically challenging to discover the GE interaction effects because many published data were just entry means under each environment rather than repeated field plot data. In this study, we propose a new methodology, which can be used to impute replicated trial data sets to reveal GE interactions from the original data. As a demonstration, we used a data set, which includes 28 potato genotypes and six environments with three replications to numerically evaluate the properties of this new imputation method. We compared the phenotypic means and predicted random effects from the imputed data with the results from the original data. The results from the imputed data were highly consistent with those from the original data set, indicating that imputed data from the method we proposed in this study can be used to reveal information including GE interaction effects harbored in the original data. Therefore, this study could pave a way to detect the GE interactions and other related information from historical crop trial reports when replications were not available.
基金supported in part by the National Key Research and Development Plan Project(2022YFB3304700)in part by the Xinliao Talent Program of Liaoning Province(XLYC2202002).
文摘As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynamics.The high complexity of industrial big data poses challenges for the practical decision-making of domain experts,leading to ever-increasing needs for integrating computational intelligence with human perception into traditional data analysis.Industrial big data visualization integrates theoretical methods and practical technologies from multiple disciplines,including data mining,information visualization,computer graphics,and human-computer interaction,providing a highly effective manner for understanding and exploring the complex industrial processes.This review summarizes the state-of-the-art approaches,characterizes them with six visualization methods,and categorizes them based on analytical tasks and applications.Furthermore,key research challenges and potential future directions are identified.
基金National Natural Science Foundation of China,No.42361040。
文摘Population migration data derived from location-based services has often been used to delineate population flows between cities or construct intercity relationship networks to reveal and explore the complex interaction patterns underlying human activities.Nevertheless,the inherent heterogeneity in multimodal migration big data has been ignored.This study conducts an in-depth comparison and quantitative analysis through a comprehensive lens of spatial association.Initially,the intercity interactive networks in China were constructed,utilizing migration data from Baidu and AutoNavi collected during the same time period.Subsequently,the characteristics and spatial structure similarities of the two types of intercity interactive networks were quantitatively assessed and analyzed from overall(network)and local(node)perspectives.Furthermore,the precision of these networks at the local scale is corroborated by constructing an intercity network from mobile phone(MP)data.Results indicate that the intercity interactive networks in China,as delineated by Baidu and AutoNavi migration flows,exhibit a high degree of structure equivalence.The correlation coefficient between these two networks is 0.874.Both networks exhibit a pronounced spatial polarization trend and hierarchical structure.This is evident in their distinct core and peripheral structures,as well as in the varying importance and influence of different nodes within the networks.Nevertheless,there are notable differences worthy of attention.Baidu intercity interactive network exhibits pronounced cross-regional effects,and its high-level interactions are characterized by a“rich-club”phenomenon.The AutoNavi intercity interactive network presents a more significant distance attenuation effect,and the high-level interactions display a gradient distribution pattern.Notably,there exists a substantial correlation between the AutoNavi and MP networks at the local scale,evidenced by a high correlation coefficient of 0.954.Furthermore,the“spatial dislocations”phenomenon was observed within the spatial structures at different levels,extracted from the Baidu and AutoNavi intercity networks.However,the measured results of network spatial structure similarity from three dimensions,namely,node location,node size,and local structure,indicate a relatively high similarity and consistency between the two networks.
文摘The modeling of volatility and correlation is important in order to calculate hedge ratios, value at risk estimates, CAPM （Capital Asset Pricing Model betas）, derivate pricing and risk management in general. Recent access to intra-daily high-frequency data for two of the most liquid contracts at the Nord Pool exchange has made it possible to apply new and promising methods for analyzing volatility and correlation. The concepts of realized volatility and realized correlation are applied, and this study statistically describes the distribution （both distributional properties and temporal dependencies） of electricity forward data from 2005 to 2009. The main findings show that the logarithmic realized volatility is approximately normally distributed, while realized correlation seems not to be. Further, realized volatility and realized correlation have a long-memory feature. There also seems to be a high correlation between realized correlation and volatilities and positive relations between trading volume and realized volatility and between trading volume and realized correlation. These results are to a large extent consistent with earlier studies of stylized facts of other financial and commodity markets.
基金Under the auspices of Key Project of National Natural Science Foundation of China (No. 40635026)National Natural Science Foundation of China (No. 40701045)
文摘This paper aims to explore urban geography with a new perspective. Endowed with the urban geography connotations, an improved data field model is employed to integrate temporal dimension into spatial process of cities in a typical region in this article. Taking the Beijing-Shanghai Corridor including 18 cities as an example, the authors chose the city centricity index (CCI) and the spatial data field model to analyze the evolution process and features of sub-region and urban spatial interaction in this corridor based on the data of 1991, 1996 and 2002. Through the analy- sis, we found that: 1) with the improvement of the urbanization level and the development of urban economy, the cit- ies’ CCI grew, the urban spatial radiative potential enhanced and the radiative range expanded gradually, which reflects the urban spatial interaction’s intensity has been increasing greatly; 2) although the spatial interaction intensity among the cities and sub-regions in the Beijing-Shanghai Corridor was growing constantly, the gap of the spatial interaction strength among different cities and sub-regions was widening, and the spatial division between the developed areas and the less developed areas was obvious; and 3) the intensity of the spatial interaction of Beijing, Shanghai and their urban agglomerations was far greater than that in small cities of other parts of the corridor, and it may have a strong drive force on the choice of spatial location of the economic activities.
基金The National Natural Science Foundation of China under contract No.61362002the Marine Scientific Research Special Funds for Public Welfare of China under contract No.201505002
文摘High-frequency surface wave radar（HFSWR） and automatic identification system（AIS） are the two most important sensors used for vessel tracking.The HFSWR can be applied to tracking all vessels in a detection area,while the AIS is usually used to verify the information of cooperative vessels.Because of interference from sea clutter,employing single-frequency HFSWR for vessel tracking may obscure vessels located in the blind zones of Bragg peaks.Analyzing changes in the detection frequencies constitutes an effective method for addressing this deficiency.A solution consisting of vessel fusion tracking is proposed using dual-frequency HFSWR data calibrated by the AIS.Since different systematic biases exist between HFSWR frequency measurements and AIS measurements,AIS information is used to estimate and correct the HFSWR systematic biases at each frequency.First,AIS point measurements for cooperative vessels are associated with the HFSWR measurements using a JVC assignment algorithm.From the association results of the cooperative vessels,the systematic biases in the dualfrequency HFSWR data are estimated and corrected.Then,based on the corrected dual-frequency HFSWR data,the vessels are tracked using a dual-frequency fusion joint probabilistic data association（JPDA）-unscented Kalman filter（UKF） algorithm.Experimental results using real-life detection data show that the proposed method is efficient at tracking vessels in real time and can improve the tracking capability and accuracy compared with tracking processes involving single-frequency data.
文摘This paper presents a composite interaction formula based on the discrete-interaction operator of wave-wave nonlinear interaction for deriving its adjoint source function in the wave assimilation model. Assimilation experiments were performed using the significant wave heights observed by the TOPES/POSEIDON satellite, and the gradient distribution in the physical space was also analyzed preliminarily.
文摘Integration of soil information system (SIS) and interactive self-organizing data (ISODATA) was studied to establish proper agricultural developing zones in red soil region of southern China which are of crucial importance to farmers, researchers, and decision makers while utilizing and managing red soil resources. SIS created by using ARC/INPO was used to provide data acquisition, systematic model parameter assignment, and visual display of analytic results. Topography, temperature, soil component (e.g., organic matter and pH) and condition of agricultural production were selected as parameters of ISODATA model. Taking Longyou County, Zhejiang Province as the case study area, the effect of the integration and recommendations are discussed for future research.
基金National Key Research and Development Program of China(2019YFB1600400)National Natural Science Foundation of China(72174035)+2 种基金National Natural Science Foundation of China(71774018)Liaoning Revitalization Talents Program(XLYC2008030)Liaoning Provincial Natural Science Foundation Shipping Joint Foundation Program(2020-HYLH-20)。
文摘It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social benefits of transportation services,and incorporated it into the comprehensive transportation efficiency evaluation framework as an expected output.Based on the panel data of 30 regions in China from 2003-2018,the CTGE in China was measured using the slacks-based measure-data envelopment analysis(SBM-DEA)model.Further,the dynamic evolution trends of CTGE were determined using the spatial Markov model and exploratory spatio-temporal data analysis(ESTDA)technique from a spatio-temporal perspective.The results showed that the CTGE shows a U-shaped change trend but with an overall low level and significant regional differences.The state transition of CTGE has a strong spatial dependence,and there exists the phenomenon of“club convergence”.Neighbourhood background has a significant impact on the CTGE transition types,and the spatial spillover effect is pronounced.The CTGE has an obvious positive correlation and spatial agglomeration characteristics.The geometric characteristics of the LISA time path show that the evolution process of local spatial structure and local spatial dependence of China’s CTGE is stable,but the integration of spatial evolution is weak.The spatio-temporal transition results of LISA indicate that the CTGE has obvious transfer inertness and has certain path-dependence and spatial locking characteristics,which will become the major difficulty in improving the CTGE.
基金Innovation Project of LREIS,No.KPI003National Natural Science Foundation of China,No.42101423Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA23010202。
文摘Identifying the spatiotemporal interaction pattern of agricultural product circulation(APC)is crucial for agricultural resource adjustment and food security.Current studies are mostly based on static statistical data over an entire year or a specific period,which cannot describe the spatial pattern of APC and its seasonal variation on a fine spatiotemporal scale.Thus,this study extracts an APC trip chain based on national truck trajectory data and constructs the flow network of the Beijing APC with the city as the spatial unit and the season as the temporal unit.The spatial interaction pattern and seasonal variation in APC are then analyzed from the network spatial form,city node function role,and transportation corridors.The results are as follows:(1)Compared with methods based on static statistical data,the proposed method provides a more complete and refined depiction of the spatiotemporal interaction pattern of APC.(2)The flow network of the Beijing APC involves 316 cities in China,of which 143 cities play a major role with typical seasonal characteristics.These cities can be divided into perennial core cities,perennial major cities,core cities in winter-spring,major cities in winter-spring,core cities in summer-autumn,and major cities in summer-autumn,contributing 2.6%-40.3%to the Beijing APC.(3)There are 6 transportation corridors for the Beijing APC.The Beijing-Tianjin-Hebei corridor and coastal corridor contribute 53.5%and 12.8%of the annual supply,respectively,with a balanced supply in all seasons.The Beijing-Kunming corridor and Beijing-Guangzhou corridor contribute 14.3%and 9.0%,respectively,with much higher supplies in winter and spring.The northeast and northwest corridors contribute 7.3%and 3.3%,respectively,mainly in the summer and autumn.These results help deepen the understanding of agricultural product supply patterns and provide a reference for the design and optimization of agricultural product transportation routes.
基金supported in part by the National Natural Science Foundation of China under Grant No. 61271199the Fundamental Research Funds in Beijing Jiaotong University under Grant No. W11JB00630
文摘With the increasing popularity of cloud computing, there is an increased de mand for cloud resources in cloud. It has be come even more urgent to find solutions to improve resource utilization. From the per spective of a cloud consumer, a cloud applica tion processes a large information flow in volving user actions that access resources, but little work has so far been devoted to research from the perspective of the interaction be tween the user and the cloud application. In this paper, we analyze the interaction in detail, and propose a general mathematical interac tion model to formulate the challenge pertain ing to storage resource allocation as an opti mization problem, focusing on minimizing both the user＇s cost and server＇s consumption. A potential response mechanism is then de signed based on the interaction model. Fur thermore, the proposed model is used to ex plore strategies when multiple users access the same file simultaneously. Additionally, an improved queuing system, namely M/ G~ oo queue with standby, is introduced. Finally, an evaluation is presented to verify the interac- tion model.
