10 resultados para 08 Information and Computing Sciences

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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National Basic Research Program of China; Chinese Academy of Sciences; Information Society Technologies; Institute of Computing Technology, Chinese Academy of Sciences; Zhuhai National Hi-tech Industrial Development Zone

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High dimensional biomimetic informatics (HDBI) is a novel theory of informatics developed in recent years. Its primary object of research is points in high dimensional Euclidean space, and its exploratory and resolving procedures are based on simple geometric computations. However, the mathematical descriptions and computing of geometric objects are inconvenient because of the characters of geometry. With the increase of the dimension and the multiformity of geometric objects, these descriptions are more complicated and prolix especially in high dimensional space. In this paper, we give some definitions and mathematical symbols, and discuss some symbolic computing methods in high dimensional space systematically from the viewpoint of HDBI. With these methods, some multi-variables problems in high dimensional space can be solved easily. Three detailed algorithms are presented as examples to show the efficiency of our symbolic computing methods: the algorithm for judging the center of a circle given three points on this circle, the algorithm for judging whether two points are on the same side of a hyperplane, and the algorithm for judging whether a point is in a simplex constructed by points in high dimensional space. Two experiments in blurred image restoration and uneven lighting image correction are presented for all these algorithms to show their good behaviors.

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To simplify the abstraction of descriptors, for the correlation analysis of the stability constants of gadolinium(III) complexes and their ligand structures, aiming at gadolinium(III) complexes, we only considered the ligands and ignored the common parts of the structures, i.e., the metal ions. Quantum-chemical descriptors and topological indices were calculated to describe the structures of the ligands. Multiple regression analysis and neural networks were applied to construct the models between the ligands and the stability constants of gadolinium(III) complexes and satisfactory results were obtained.

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In this research. we found CoMFA alone could not obtain sufficiently a strong equation to allow confident prediction for aminobenzenes. When some other parameter. such as heat of molecular formation of the compounds, was introduced into the CoMFA model, the results Were improved greatly. It gives us a hint that a better description for molecular structures will yield a better prediction model, and this hint challenged us to look for another method-the projection areas of molecules in 3D space for 3D-QSAR. It is surprising that much better results than that obtained by using CoMFA Were achieved. Besides the CoMFA analysis. multiregression analysis and neural network methods for building the models were used in this paper.

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A mathematical model on computation of molecular similarity was suggested, The algorithmic techniques for measuring the degree of similarity between pairs of three-dimensional chemical molecules was represented by modified interatomic distance matrices. Current work was carried out on Indigo 2 work station with Sybyl software. Four groups of molecules were used to compute the molecules similarity to testing the mathematical model with satisfactory results.

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The applications of new topological indices A(x1)-A(x3) suggested in our laboratory for the prediction of Gibbs energy values of phase transfer (water to nitrobenzene) of amine ions are described with satisfactory results. Multiple regression analysis and neural network were employed simultaneously in this study.

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The topological state and the total topological index, tau, have been tested systematically. Counterexamples are provided proving that the topological state method cannot determine classes of symmetrically equivalent atoms in a molecule fully correct. The

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In this paper, new topological indices, EA Sigma and EAmax, are introduced. They are based on the extended adjacency matrices of molecules, in which the influences of factors of heteroatoms and multiple bonds were considered. The results show that EA Sigm

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In this paper, three new topological indices, A(x1), A(x2), and A(x3), have been developed for use in multivariate analysis in structure-property relationship (SPR) and structure-activity relationship (SAR) studies. Good results have been obtained by using them to predict the physical and chemical properties and biological activities of some organic compounds.

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The CIAC (Changchun Institute of Applied Chemistry) Comprehensive information System of Rare Earths is composed of three subsystems, namely, extraction data, physicochemical properties, and reference data. This paper describes the databases pertaining to the extraction of rare earths and their physicochemical properties and discusses the relationships between data retrieval and optimization and between the structures of the extractants and the efficiency with which they are extracted. Expert systems for rare earth extraction and calculation of thermodynamic parameters are described, and an application of pattern recognition to the problems of classification of compounds of the rare earths and prediction of their properties is reported.