Knowledge about human beings is an integral part of any intelligent agent ofconsiderable significance. Delimiting, modeling and acquiring such knowledge are the centraltopics of this paper. Because of the tremendous c...
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Knowledge about human beings is an integral part of any intelligent agent ofconsiderable significance. Delimiting, modeling and acquiring such knowledge are the centraltopics of this paper. Because of the tremendous complexity in knowledge of human beings, weintroduce a top-level ontology of human beings from the perspectives of psychology, sociology,physiology and pathology. This ontology is not only an explicit conceptualization of humanbeings, but also an efficient way of acquiring and organizing relevant knowledge.
This paper presents the recent process in a long-term research project, calledNational Knowledge Infrastructure (or NKI). Initiated in the early 2000, the project aims todevelop a multi-domain shareable knowledge base...
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This paper presents the recent process in a long-term research project, calledNational Knowledge Infrastructure (or NKI). Initiated in the early 2000, the project aims todevelop a multi-domain shareable knowledge base for knowledge-intensive applications. Todevelop NKI, we have used domain-specific ontologies as a solid basis, and have built morethan 600 ontologies. Using these ontologies and our knowledge acquisition methods, we haveextracted about 1.1 millions of domain assertions. For users to access our NKI knowledge,we have developed a uniform multi-modal human-knowledge interface. We have also imple-mented a knowledge application programming interface for various applications to share theNKI knowledge.
Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art ...
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Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art in the field of simulated modeling of vibration systems using methods of computational intelligence, based on some relevant subjects and the authors' own research work. First, contributions to the applications of computational intelligence to the identification of nonlinear characteristics of packaging are reviewed. Subsequently, applications of the newly developed training algorithms for feedforward neural networks to the identification of restoring forces in multi-degree-of-freedom nonlinear systems are discussed. Finally, the neural-network-based method of model reduction for the dynamic simulation of microelectromechanical systems (MEMS) using generalized Hebbian algorithm (GHA) and robust GHA is outlined. The prospects of the simulated modeling of vibration systems using techniques of computational intelligence are also indicated.
There exists an enormous gap between low-level visual features and high-level semantic information and accuracy of content-based image classification. Retrieval depends largely on the description of low-level visual f...
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Knowledge Grid is a platform that enables uniform and effective knowledge sharing and management across the Internet. Based on this platform, this paper proposes a cooperative learning environment KGCL. It supports th...
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The main idea of SVM, i.e. Support Vector Machine, is mapping nonlinear separable data into higher dimension linear space where the data can be separated by hyper plane. Based on Jordan Curve Theorem, a general classi...
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The main idea of SVM, i.e. Support Vector Machine, is mapping nonlinear separable data into higher dimension linear space where the data can be separated by hyper plane. Based on Jordan Curve Theorem, a general classification method HSC, Classification based on Hyper Surface, is put forward in this paper. The separating hyper surface is directly made to classify large database. The data are classified according to whether the intersecting number is odd or even. It is a novel approach which has no need of either mapping from lower dimension space to higher dimension space or considering kernel function. It can directly solve the nonlinear classification problem. The experiments show that the new method can efficiently and accurately classify large data.
By introducing a discrete Frenet frame, this paper first proposes 3D discrete clothoid splines to extend the planar discrete clothoid splines of Schneider and Kobbelt. On the basis of 3D discrete clothoid spline curve...
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Recent years there is an urgent need for effective content-based image retrieval(CBIR) systems, and we believe the key to effective CBIR performance lies in the ability to access the image at the level of *** by these...
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Recent years there is an urgent need for effective content-based image retrieval(CBIR) systems, and we believe the key to effective CBIR performance lies in the ability to access the image at the level of *** by these considerations,we propose a region-based image retrieval system using max weighted bipartite matching,which can successfully solve the similarity measure of multi-region *** retrieval involves two stage:First,the images are segmented based on perceptual color homogeneity,for each color regions,color,texture,scale,location and shape characteristics are used to represent the content of ***,max weighted bipartite matching scheme is used to measure the similarity between *** results shows that a region-based approach can retrieve more relevant and more accurate images.
There is an urgent need for effective content-based image retrieval (CBIR) systems, and we believe the key to effective CBIR performance lies in the ability to access the image at the level of objects. Motivated by th...
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There is an urgent need for effective content-based image retrieval (CBIR) systems, and we believe the key to effective CBIR performance lies in the ability to access the image at the level of objects. Motivated by these considerations, we propose a region-based image retrieval system using max weighted bipartite matching, which can successfully solve the similarity measure of a multi-region image. The retrieval involves two stages: first, the images are segmented based on perceptual color homogeneity, for each color region, color, texture, scale, location and shape characteristics are used to represent the content of regions. Second, the max weighted bipartite matching scheme is used to measure the similarity between images. Experimental results show that a region-based approach can retrieve more relevant and more accurate images.
Virtual Museum of Chinese Nationalities is a multi-user shared virtual reality system developed to popularize the cultures and folk-customs of various ethnic groups for the public by means of cooperative work. We rega...
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ISBN:
(纸本)0660184931
Virtual Museum of Chinese Nationalities is a multi-user shared virtual reality system developed to popularize the cultures and folk-customs of various ethnic groups for the public by means of cooperative work. We regard the project as long-term research, in that there are many problems to be solved. Unlike existing systems, we should maintain scalab.e and interactive performance on a wide variety of computing platforms, not only high-end graphics workstations, and distribute the virtual world via a bandwidth-limited network. We introduce some architectures and algorithms realized in our current prototype, e.g., shared event mechanism, area of interest algorithm, distributed server architecture, etc.
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