All things in the universe possess a state and characteristics of state, resultantly in presence of space-time, which is perceived by human beings. An outlook of space-time is shaped in human by perceiving the existen...All things in the universe possess a state and characteristics of state, resultantly in presence of space-time, which is perceived by human beings. An outlook of space-time is shaped in human by perceiving the existence and change of objects. The state space is all state characteristics exhibited in objects whilst the state time refers to the duration of an object＇s state. The time is a spatial property and not an independent dimension. The state space-time is a unity of internal and external space-time. The internal space-time is stemmed from the overall internal forces and internal energies and is a covert space-time. The external space-time refers to a space-time manifested by the external characteristics and movement of an object and is an overt space-time. In physics, there are four kinds of forces and four state space-times： bonding force and three-dimensional space-time; strong interaction of exchangeable n meson and two-dimensional space-time; quark confinement and one-dimensional space-time; and weak interaction and zero-dimensional space-time. The universe is constituted by dissimilar state space-times. Newton space-time is a three-dimensional state space-time; Einstein＇s theory of relativity is a two-dimensional state space-time. Newton and Einstein were different observers. Temporal and spatial perception of human is dependent upon human＇s intemal energy and quality. Through Qigong exercises, the human is able to enter the three-dimensional, two-dimensional, one-dimensional and zero-dimensional space-times. The relativity theory of human body will solve the time problems at the interplanetary voyage of astronauts.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
This paper discusses the asymptotic stability and Riesz basis generation for a general tree-shaped network of vibrating strings. All exterior vertices are assumed to be fixed and interior vertices are imposed linear d...This paper discusses the asymptotic stability and Riesz basis generation for a general tree-shaped network of vibrating strings. All exterior vertices are assumed to be fixed and interior vertices are imposed linear damping feedbacks. This paper shows that the system is well-posed and asymptotically stable by C0-semigroup theory. With some additional conditions, the spectrum of the system is shown to be located in a strip that is parallel to the imaginary axis and the set of all generalized eigenfunctions is completed in the state space. These lead to the conclusion that there is a sequence of generalized eigenfunctions of the system, which forms a Riesz basis with parenthesis for the state space.展开更多
We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named ‘decomposed hidden Markov model’ (DHMM), combines spatial decomposition and hierarchical ab...We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named ‘decomposed hidden Markov model’ (DHMM), combines spatial decomposition and hierarchical abstraction to capture multi-modal, long-term dependent and multi-scale characteristics of activities. Decomposition in space and time offers conceptual advantages of compaction and clarity, and greatly reduces the size of state space as well as the number of parameters. DHMMs are efficient even when the number of persons is variable. We also introduce an efficient approximation algorithm for inference and parameter estimation. Experiments on multi-person activities and multi-modal individual activities demonstrate that DHMMs are more efficient and reliable than familiar models, such as coupled HMMs, hierarchical HMMs, and multi-observation HMMs.展开更多
We study for a class of symmetric Levy processes with state space R^n the transition density pt（x） in terms of two one-parameter families of metrics, （dt）t〉o and （δt）t〉o. The first family of metrics describes...We study for a class of symmetric Levy processes with state space R^n the transition density pt（x） in terms of two one-parameter families of metrics, （dt）t〉o and （δt）t〉o. The first family of metrics describes the diagonal term pt （0）; it is induced by the characteristic exponent ψ of the Levy process by dr（x, y） = √tψ（x - y）. The second and new family of metrics 6t relates to √tψ through the formula exp（-δ^2t（x,y））=F[e^-tψ/pt（0）]（x-y）,where Y denotes the Fourier transform. Thus we obtain the following ＂Gaussian＂ representation of the tran- sition density： pt（x） = pt（O）e^-δ^2t（x,0） where pt（O） corresponds to a volume term related to √tψ and where an ＂exponential＂ decay is governed by 5t2. This gives a complete and new geometric, intrinsic interpretation of pt（x）.展开更多
文摘All things in the universe possess a state and characteristics of state, resultantly in presence of space-time, which is perceived by human beings. An outlook of space-time is shaped in human by perceiving the existence and change of objects. The state space is all state characteristics exhibited in objects whilst the state time refers to the duration of an object＇s state. The time is a spatial property and not an independent dimension. The state space-time is a unity of internal and external space-time. The internal space-time is stemmed from the overall internal forces and internal energies and is a covert space-time. The external space-time refers to a space-time manifested by the external characteristics and movement of an object and is an overt space-time. In physics, there are four kinds of forces and four state space-times： bonding force and three-dimensional space-time; strong interaction of exchangeable n meson and two-dimensional space-time; quark confinement and one-dimensional space-time; and weak interaction and zero-dimensional space-time. The universe is constituted by dissimilar state space-times. Newton space-time is a three-dimensional state space-time; Einstein＇s theory of relativity is a two-dimensional state space-time. Newton and Einstein were different observers. Temporal and spatial perception of human is dependent upon human＇s intemal energy and quality. Through Qigong exercises, the human is able to enter the three-dimensional, two-dimensional, one-dimensional and zero-dimensional space-times. The relativity theory of human body will solve the time problems at the interplanetary voyage of astronauts.
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This research is supported in part by the Natural Science Foundation of China under Grant No. 60874035 and by the Scientific Research Initiation Foundation of Civil Aviation University of China （08QD09X）.
文摘This paper discusses the asymptotic stability and Riesz basis generation for a general tree-shaped network of vibrating strings. All exterior vertices are assumed to be fixed and interior vertices are imposed linear damping feedbacks. This paper shows that the system is well-posed and asymptotically stable by C0-semigroup theory. With some additional conditions, the spectrum of the system is shown to be located in a strip that is parallel to the imaginary axis and the set of all generalized eigenfunctions is completed in the state space. These lead to the conclusion that there is a sequence of generalized eigenfunctions of the system, which forms a Riesz basis with parenthesis for the state space.
基金Project (No. 60772050) supported by the National Natural Science Foundation of China
文摘We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named ‘decomposed hidden Markov model’ (DHMM), combines spatial decomposition and hierarchical abstraction to capture multi-modal, long-term dependent and multi-scale characteristics of activities. Decomposition in space and time offers conceptual advantages of compaction and clarity, and greatly reduces the size of state space as well as the number of parameters. DHMMs are efficient even when the number of persons is variable. We also introduce an efficient approximation algorithm for inference and parameter estimation. Experiments on multi-person activities and multi-modal individual activities demonstrate that DHMMs are more efficient and reliable than familiar models, such as coupled HMMs, hierarchical HMMs, and multi-observation HMMs.
文摘We study for a class of symmetric Levy processes with state space R^n the transition density pt（x） in terms of two one-parameter families of metrics, （dt）t〉o and （δt）t〉o. The first family of metrics describes the diagonal term pt （0）; it is induced by the characteristic exponent ψ of the Levy process by dr（x, y） = √tψ（x - y）. The second and new family of metrics 6t relates to √tψ through the formula exp（-δ^2t（x,y））=F[e^-tψ/pt（0）]（x-y）,where Y denotes the Fourier transform. Thus we obtain the following ＂Gaussian＂ representation of the tran- sition density： pt（x） = pt（O）e^-δ^2t（x,0） where pt（O） corresponds to a volume term related to √tψ and where an ＂exponential＂ decay is governed by 5t2. This gives a complete and new geometric, intrinsic interpretation of pt（x）.
