Viruses' complete genomes classification based on geometrical learning

In this paper, we proposed a method of classification for viruses' complete genomes based on graph geometrical theory in order to viruses classification. Firstly, a model of triangular geometrical graph was put forward, and then constructed feature-space-samples-graphs for classes of viruses' complete genomes in feature space after feature extraction and normalization. Finally, we studied an algorithm for classification of viruses' complete genomes based on feature-space-samples-graphs. Compared with the BLAST algorithm, experiments prove its efficiency.

Cancer subtypes recognition and its gene expression profiles analysis based on geometrical learning

The accurate recognition of cancer subtypes is very significant in clinic. Especially, the DNA microarray gene expression technology is applied to diagnosing and recognizing cancer types. This paper proposed a method of that recognized cancer subtypes based on geometrical learning. Firstly, the cancer genes expression profiles data was pretreated and selected feature genes by conventional method; then the expression data of feature genes in the training samples was construed each convex hull in the high-dimensional space using training algorithm of geometrical learning, while the independent test set was tested by the recognition algorithm of geometrical learning. The method was applied to the human acute leukemia gene expression data. The accuracy rate reached to 100%. The experiments have proved its efficiency and feasibility.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

A geometrical model of GaN morphology in initial growth stage

Based on morphology observed by atomic force microscopy, a geometrical model was proposed in order to explain the statistical results obtained from morphology observation on GaN in initial growth stage. Four parameters were introduced to describe the morphology characteristics in this model. Least-square fitting of height distribution was performed. The height distribution derived from the model agreed well with that obtained from experimental records. It was also found that the model should be further advanced to understand the growth of GaN in initial growth stage. (C) 2002 Elsevier Science BY. All rights reserved.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

The new concepts and new developments in hte theory of polymer crystallization

Recently a debate about the initial crystallization process which has not been the hotspot for a long time since the theory proposed by Hoffman- Lauritzen (LH) dominated the field arose again. For a long time the Hoffman-Lauritzen model was always confronted by criticism,and some of the points were taken up and led to modifications, but the foundation remained unchanged which deemed that before the nucleation and crystallization the system was uniform. In this article the classical nucleation and growth theory of polymer crystallization was reviewed, and the confusion of the explanations to the polymer crystallization phenomenon was pointed out. LH theory assumes that the growth of lamellae is by the direct attachment of chain sequences from the melt onto smooth lateral sides.

SOME NEWER CONCEPTS OF ETHYLENE ALPHA-OLEFIN COPOLYMERIZATION ON HETEROGENEOUS ZIEGLER-NATTA CATALYSTS

Unsteady diffusion kinetic, recently advanced by this laboratory, is applied to the examination of some polymerization and molecular chain structure problems. Hitherto deemed "anomalous" phenomena, such as the faster rate of copolymerization of ethylene/alpha-olefin than the homopolymerization of ethylene and the enrichment in the incorporation of a higher alpha-olefin in its copolymerization with ethylene by a lower alpha-olefin, are reasonably explained by unsteady diffusion of monomers. Molecular chain structure of copolymers, such as compositional heterogeneity and its dependence on comonomer incorporation originates from the difference in diffusion coefficients of the monomers. A copolymer composition equation taking into consideration the unsteady diffusion was developed. In cases where simulated curves were compared with experimental curves, good agreements were found.

砂砾岩储层流动单元四维模型研究

This article is an important part of "95" technological subject of SINOPEC. It has a large number of difficulties and workloads, and has significant theoretical meanings and practical value. The study area is composed of sandstone & conglomerate reservoir of alluvial fan & fan delta, which belong to Sha3 lower member and Sha4 upper member of lower tertiary of Yong'an Town Oilfield in Dongying Depression. The target stataum develops in the hanging wall of the synsedimentary fault in the scarp zone of Dongying Depression. The frequently intense movements result in the variation of sandstone and conglomerate reservoir and the evolution of the time and space of Sha3 lower member and Sha4 upper member in Yong'an Town Oilfield. As a result, it is difficult for the individual reservoir correlation at the root of fan, which bring about a tackle problem for the exploitation of oilfield. In this background, the research of fluid units will be more difficult. In this article, the new concepts, the new methods, and the new techniques of sedimentology, petroleum geology, reservoir geology, physics of crystal surface, dynamic & static state reservoir description and well logging geology are synthetically applied, and the computer technology are made full uses of, and the identifying, dividing and appraising of the two-formation-type sandstone & conglomerate reservoir fluid units of Sha3 lower member and Sha4 upper member systemically analyzed in Yong'an Town Oilfield, Dongying Depression. For the first time, the single-well model, the section model, the plane model, the nuclear magnetism log model, the microcosmic network model, the 4-D geology model and the simulation model of the two-formation-type reservoir fluid units of the of sandstone & conglomerate reservoir of Sha3 lower member and Sha4 upper member are established, and the formative mechanism and distributing & enrichment laws of oil-gas of the two type of sandstone and conglomerate reservoir fluid units are revealed. This article established the optimizing, identifying, classifying and appraising standard of the two-formation-type reservoir fluid units of the of sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member, which settles the substantial foundations for static state model of the fluid units, reveals the macroscopic & microcosmic various laws of geometrical static state of the fluid units, and instructs the oil exploitation. This article established static state model of the two-formation-type sandstone and conglomerate reservoir fluid units by using the multi-subject theories, information and techniques, and reveals the geometrical configuration, special distribution and the oil-gas enrichment laws of the sandstone and conglomerate reservoir fluid units. For the first time, we established the nuclear magnetism log model of the two-formation-type sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member, which reveals not only the character and distributing laws of the porosity and permeability, bat also the formation and distribution of the movable fluid. It established six type of microcosmic net model of the two-formation-type sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member in the working area by using the advanced theories, such as rock thin section, SEM, image analysis, intrusive mercury, mold, rock C.T. measure & test image etc., which reveals the microcosmic characteristic of porosity & throat, filterate mode and microcosmic oil-gas enrichment laws of the sandstone and conglomerate reservoir. For the first time, it sets up the 4-D model and mathematic model of the sandstone and conglomerate reservoir, which reveals the distributing and evolving laws of macroscopic & microcosmic parameters of the two-formation-type sandstone and conglomerate reservoir and oil-gas in 4-D space. At the same time, it also forecasts the oil-gas distribution and instructs the oilfield exploitation. It established reservoir simulation model, which reveals the filterate character and distributing laws of oil-gas in different porosity & throat net models. This article established the assistant theories and techniques for researching, describing, indicating and forecasting the sandstone and conglomerate reservoir fluid units, and develops the theories and techniques of the land faces faulted basin exploitation geology. In instructing oilfield exploitation, it had won the notable economic & social benefits.