Phylogeny of SARS-CoV based on high-dimensional information geometry

We proposed a novel methodology, which firstly, extracting features from species' complete genome data, using k-tuple, followed by studying the evolutionary relationship between SARS-CoV and other coronavirus species using the method, called "High-dimensional information geometry". We also used the mothod, namely "caculating of Minimum Spanning Tree", to construct the Phyligenetic tree of the coronavirus. From construction of the unrooted phylogenetic tree, we found out that the evolution distance between SARS-CoV and other coronavirus species is comparatively far. The tree accurately rebuilt the three groups of other coronavirus. We also validated the assertion from other literatures that SARS-CoV is similar to the coronavirus species in Group I.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

Experimental investigation of intracavity absorber low temperature GaAs in diode-pumped Nd : GdVO4 laser

A passively Q-switched and mode-locked diode-pumped Nd:GdVO4 laser was demonstrated using a low-temperature-grown GaAs wafer (LT-GaAs) as an intracavity saturable absorber. The maximal Q-switched mode-locked average output power was 750 mW with the Q-switched envelop having a repetition rate of 167 kHz. The mode-locked pulse trains inside the Q-switched pulse envelope had a repetition rate of similar to 790 MHz.

Anti-Stokes photoluminescence in ZnO microcrystal

Low temperature (10 K) strong anti-Stokes photoluminescence (ASPL) of ZnO microcrystal excited by low power cw 532 nm laser is reported here. Energy upconversion of 1.1 eV is obtained in our experiment with no conventional nonlinear effect. Through the study of the normal photoluminescence and temperature dependence of ASPL we conclude that the green band luminescence in ZnO is related to deep donor to valance band transition. Using the two-step two-photon absorption model, we provide a plausible mechanism leading to the ASPL phenomenon in our experiment. (c) 2006 American Institute of Physics.

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.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

A novel image restoration algorithm based on high-dimensional space geometry

A novel image restoration approach based on high-dimensional space geometry is proposed, which is quite different from the existing traditional image restoration techniques. It is based on the homeomorphisms and "Principle of Homology Continuity" (PHC), an image is mapped to a point in high-dimensional space. Begin with the original blurred image, we get two further blurred images, then the restored image can be obtained through the regressive curve derived from the three points which are mapped form the images. Experiments have proved the availability of this "blurred-blurred-restored" algorithm, and the comparison with the classical Wiener Filter approach is presented in final.

Finite element analysis of stress and strain distributions in InAs/GaAs quantum dots

In this paper, we perform systematic calculations of the stress and strain distributions in InAs/GaAs truncated pyramidal quantum dots (QDs) with different wetting layer (WL) thickness, using the finite element method (FEM). The stresses and strains are concentrated at the boundaries of the WL and QDs, are reduced gradually from the boundaries to the interior, and tend to a uniform state for the positions away from the boundaries. The maximal strain energy density occurs at the vicinity of the interface between the WL and the substrate. The stresses, strains and released strain energy are reduced gradually with increasing WL thickness. The above results show that a critical WL thickness may exist, and the stress and strain distributions can make the growth of QDs a growth of strained three-dimensional island when the WL thickness is above the critical value, and FEM can be applied to investigate such nanosystems, QDs, and the relevant results are supported by the experiments.

Q-switched and mode-locked diode-pumped Nd : GdVO4 laser with low temperature GaAs saturable absorber

Low temperature GaAs (LT-GaAs) was successfully grown at the temperature of 550 degrees C by metal organic vapor phase epitaxy on a semi-insular GaAs substrate. With such an absorber as well as an output coupler we obtain Q-switched mode-locked (QML) 1064 nm Nd:GdVO4 laser pumped by diode laser with high repetition rate, formed with a simple flat-flat cavity. The repetition rate of the Q-switched envelope increased from 100 to 660 kHz as the pump power increased from 2.28 to 7.29 W. The mode-locked pulses inside the Q-switched pulse envelope had a repetition rate of similar to 1.36 GHz. A maximum average output power of 953 mW was obtained. The dependence of the operational parameters on the pump power was also investigated experimentally. (C) 2005 Elsevier B.V. All rights reserved.

Q-switched and mode-locked diode-pumped Nd : YAG laser with an LT-GaAs

Simultaneous Q-switching and mode-locking (QML) is accomplished in a diode-pumped Nd:YAG laser using low-temperature GaAs (LT-GaAs) as the saturable absorber, which also acts as an output coupler at the same time. The repetition rate of the Q-switched envelope increased from 25 to 40 kHz as the pump power increased from 2.2 to 6.9 W. The mode-locked pulses inside the Q-switched pulse envelope had a repetition rate of 714 MHz. A maximum average output power of 770 mW was obtained. (c) 2005 Elsevier GmbH. All rights reserved.

Continuous speech research based on HyperSausage Neuron

In this paper, we presents HyperSausage Neuron based on the High-Dimension Space(HDS), and proposes a new algorithm for speaker independent continuous digit speech recognition. At last, compared to HMM-based method, the recognition rate of HyperSausage Neuron method is higher than that of in HMM-based method.

An adaptive controller for a class of nonlinear system using direction basis function

For a class of nonlinear dynamical systems, the adaptive controllers are investigated using direction basis function (DBF) in this paper. Based on the criterion of Lyapunov' stability, DBF is designed which guarantees that the output of the controlled system asymptotically tracks the reference signals. Finally, the simulation shows the good tracking effectiveness of the adaptive controller.

Photoluminescence and microstructure of the Erbium-Doped hydrogenated amorphous SiOx(0 < x < 2)

The hydrogenated amorphous SiOx films (a-SiOx:H) with various oxygen contents have been prepared using plasma enhanced chemical vapor deposition technique. The films were implanted with erbium and annealed by rapid thermal annealing. An intense photoluminescence (PL) of Er at 1.54 mum has been observed at 77 K and at room temperature. The PL intensity depends strongly on both the oxygen content of the film and the rapid thermal annealing temperature and reaches its maximum if the ratio of O/Si in the film is approximately equal to 1.0 at 77 K and to 1.76 at room temperature. The microstructure of the film also has strong influences on the PL intensity. The PL intensity at 250 K is slightly more than a half of that at 15 K. It means that the temperature quenching effect of the PL intensity is very weak.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

Face recognition based on PCA and multi-degree of freedom neurons

An algorithm of PCA face recognition based on Multi-degree of Freedom Neurons theory is proposed, which based on the sample sets' topological character in the feature space which is different from "classification". Compare with the traditional PCA+NN algorithm, experiments prove its efficiency.