This paper introduces techniques in Gaussian process regression model for spatiotemporal data collected from complex systems.This study focuses on extracting local structures and then constructing surrogate models bas...This paper introduces techniques in Gaussian process regression model for spatiotemporal data collected from complex systems.This study focuses on extracting local structures and then constructing surrogate models based on Gaussian process assumptions.The proposed Dynamic Gaussian Process Regression(DGPR)consists of a sequence of local surrogate models related to each other.In DGPR,the time-based spatial clustering is carried out to divide the systems into sub-spatio-temporal parts whose interior has similar variation patterns,where the temporal information is used as the prior information for training the spatial-surrogate model.The DGPR is robust and especially suitable for the loosely coupled model structure,also allowing for parallel computation.The numerical results of the test function show the effectiveness of DGPR.Furthermore,the shock tube problem is successfully approximated under different phenomenon complexity.展开更多
The internal control process, which is designed to help an organization accomplish specific control objectives, is one of the most important processes, as it can determine whether or not the organization is in complia...The internal control process, which is designed to help an organization accomplish specific control objectives, is one of the most important processes, as it can determine whether or not the organization is in compliance with its internal or external requirements. Internal controls emerge from different perspectives. Currently, experts view and act on one control perspective at a time, which creates inefficiencies and duplication. This software engineering research is aimed at proposing a multiperspective framework for representing internal controls, in order to obtain a centralized and comprehensive view of all internal control mechanisms. To carry out this research, we also needed to represent the many different stakeholder perspectives of internal controls. Based on a literature review of mathematical and psychological analysis, we searched for the most suitable multiperspective representation of internal controls, and assessed the many representation options using the AHP (analytical hierarchical process) sensitivity analysis approach. This approach has been applied to a study group which has been called to answer to a questionnaire.展开更多
An approach to camera location determination based on the perspective projection geometry of three points is proposed, which is simple and straightforward. No rigid restrictions are placed on the original positional a...An approach to camera location determination based on the perspective projection geometry of three points is proposed, which is simple and straightforward. No rigid restrictions are placed on the original positional and orientational relationships between the camera and the mark. Experimental results verify the feasibility of the proposed approach.展开更多
在文旅深度融合背景下,旅游仪式虽承载着文化活化与促进游客留存的双重功能,却面临“流量难变留量”的实践困境。原因在于现有研究多基于静态视角,未能深入探究旅游者仪式感知的阶段性演化过程及其跨层次传导机制。为此,本研究提出“设...在文旅深度融合背景下,旅游仪式虽承载着文化活化与促进游客留存的双重功能,却面临“流量难变留量”的实践困境。原因在于现有研究多基于静态视角,未能深入探究旅游者仪式感知的阶段性演化过程及其跨层次传导机制。为此,本研究提出“设计−感知−行为”整合框架:确立商家仪式设计特征作为核心刺激源,解决感知生成的前置黑箱与“供给−需求割裂”问题;首创基于过程视角的旅游者仪式感知量表,探究仪式体验的阶段性演化规律;构建“个体−地方−群体”跨层次理论模型,系统解析仪式感知驱动逗留意愿(Intention to Extend Stay)的多元路径与边界条件。本研究推动旅游仪式研究从静态表征向过程性分析的深化,通过内在机制与边界条件探究,为目的地优化仪式设计、提升文化情境适配性提供创新性解决方案。展开更多
The growth of the software game development industry is enormous and is gaining importance day by day. This growth imposes severe pressure and a number of issues and challenges on the game development community. Game ...The growth of the software game development industry is enormous and is gaining importance day by day. This growth imposes severe pressure and a number of issues and challenges on the game development community. Game development is a complex process, and one important game development choice is to consider the developer＇s perspective to produce good-quality software games by improving the game development process. The objective of this study is to provide a better understanding of the developer＇s dimension as a factor in software game success. It focuses mainly on an empirical investigation of the effect of key developer＇s factors on the software game development process and eventually on the quality of the resulting game. A quantitative survey was developed and conducted to identify key developer＇s factors for an enhanced game development process. For this study, the developed survey was used to test the research model and hypotheses. The results provide evidence that game development organizations must deal with multiple key factors to remain competitive and to handle high pressure in the software game industry. The main contribution of this paper is to investigate empirically the influence of key developer＇s factors on the game development process.展开更多
A new representation of spatio-temporal random processes is proposed in this work.In practical applications,such processes are used to model velocity fields,temperature distributions,response of vibrating systems,to n...A new representation of spatio-temporal random processes is proposed in this work.In practical applications,such processes are used to model velocity fields,temperature distributions,response of vibrating systems,to name a few.Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations,for instance,in a computational mechanics problem.For a single-parameter process such as spatial or temporal process,the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Lo`eve(KL)decomposition.However,for multiparameter processes such as a spatio-temporal process,the covariance function itself can be defined in multiple ways.Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants.Then the spatial covariance matrix at different time instants are considered to define the covariance of the process.This set of square,symmetric,positive semi-definite matrices is then represented as a thirdorder tensor.A suitable decomposition of this tensor can identify the dominant components of the process,and these components are then used to define a closed-form representation of the process.The procedure is analogous to the KL decomposition for a single-parameter process,however,the decompositions and interpretations vary significantly.The tensor decompositions are successfully applied on(i)a heat conduction problem,(ii)a vibration problem,and(iii)a covariance function taken from the literature that was fitted to model a measured wind velocity data.It is observed that the proposed representation provides an efficient approximation to some processes.Furthermore,a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL,both in terms of computer memory and execution time.展开更多
基金co-supported by the National Natural Science Foundation of China(No.12101608)the NSAF(No.U2230208)the Hunan Provincial Innovation Foundation for Postgraduate,China(No.CX20220034).
文摘This paper introduces techniques in Gaussian process regression model for spatiotemporal data collected from complex systems.This study focuses on extracting local structures and then constructing surrogate models based on Gaussian process assumptions.The proposed Dynamic Gaussian Process Regression(DGPR)consists of a sequence of local surrogate models related to each other.In DGPR,the time-based spatial clustering is carried out to divide the systems into sub-spatio-temporal parts whose interior has similar variation patterns,where the temporal information is used as the prior information for training the spatial-surrogate model.The DGPR is robust and especially suitable for the loosely coupled model structure,also allowing for parallel computation.The numerical results of the test function show the effectiveness of DGPR.Furthermore,the shock tube problem is successfully approximated under different phenomenon complexity.
文摘The internal control process, which is designed to help an organization accomplish specific control objectives, is one of the most important processes, as it can determine whether or not the organization is in compliance with its internal or external requirements. Internal controls emerge from different perspectives. Currently, experts view and act on one control perspective at a time, which creates inefficiencies and duplication. This software engineering research is aimed at proposing a multiperspective framework for representing internal controls, in order to obtain a centralized and comprehensive view of all internal control mechanisms. To carry out this research, we also needed to represent the many different stakeholder perspectives of internal controls. Based on a literature review of mathematical and psychological analysis, we searched for the most suitable multiperspective representation of internal controls, and assessed the many representation options using the AHP (analytical hierarchical process) sensitivity analysis approach. This approach has been applied to a study group which has been called to answer to a questionnaire.
文摘An approach to camera location determination based on the perspective projection geometry of three points is proposed, which is simple and straightforward. No rigid restrictions are placed on the original positional and orientational relationships between the camera and the mark. Experimental results verify the feasibility of the proposed approach.
文摘在文旅深度融合背景下,旅游仪式虽承载着文化活化与促进游客留存的双重功能,却面临“流量难变留量”的实践困境。原因在于现有研究多基于静态视角,未能深入探究旅游者仪式感知的阶段性演化过程及其跨层次传导机制。为此,本研究提出“设计−感知−行为”整合框架:确立商家仪式设计特征作为核心刺激源,解决感知生成的前置黑箱与“供给−需求割裂”问题;首创基于过程视角的旅游者仪式感知量表,探究仪式体验的阶段性演化规律;构建“个体−地方−群体”跨层次理论模型,系统解析仪式感知驱动逗留意愿(Intention to Extend Stay)的多元路径与边界条件。本研究推动旅游仪式研究从静态表征向过程性分析的深化,通过内在机制与边界条件探究,为目的地优化仪式设计、提升文化情境适配性提供创新性解决方案。
文摘The growth of the software game development industry is enormous and is gaining importance day by day. This growth imposes severe pressure and a number of issues and challenges on the game development community. Game development is a complex process, and one important game development choice is to consider the developer＇s perspective to produce good-quality software games by improving the game development process. The objective of this study is to provide a better understanding of the developer＇s dimension as a factor in software game success. It focuses mainly on an empirical investigation of the effect of key developer＇s factors on the software game development process and eventually on the quality of the resulting game. A quantitative survey was developed and conducted to identify key developer＇s factors for an enhanced game development process. For this study, the developed survey was used to test the research model and hypotheses. The results provide evidence that game development organizations must deal with multiple key factors to remain competitive and to handle high pressure in the software game industry. The main contribution of this paper is to investigate empirically the influence of key developer＇s factors on the game development process.
基金Indian Institute of Science and the Board of Research in Nuclear Sciences(BRNS)grant no.2011/36/41-BRNS/1977 for their financial support.
文摘A new representation of spatio-temporal random processes is proposed in this work.In practical applications,such processes are used to model velocity fields,temperature distributions,response of vibrating systems,to name a few.Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations,for instance,in a computational mechanics problem.For a single-parameter process such as spatial or temporal process,the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Lo`eve(KL)decomposition.However,for multiparameter processes such as a spatio-temporal process,the covariance function itself can be defined in multiple ways.Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants.Then the spatial covariance matrix at different time instants are considered to define the covariance of the process.This set of square,symmetric,positive semi-definite matrices is then represented as a thirdorder tensor.A suitable decomposition of this tensor can identify the dominant components of the process,and these components are then used to define a closed-form representation of the process.The procedure is analogous to the KL decomposition for a single-parameter process,however,the decompositions and interpretations vary significantly.The tensor decompositions are successfully applied on(i)a heat conduction problem,(ii)a vibration problem,and(iii)a covariance function taken from the literature that was fitted to model a measured wind velocity data.It is observed that the proposed representation provides an efficient approximation to some processes.Furthermore,a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL,both in terms of computer memory and execution time.
