On-line observation of interlaminar damage by ultrasonic inspection

This paper explores an on-line experimental method to highlight the process of internal damage development in composites by taking advantage of ultrasonic inspection. A loading device, which can work together with an ultrasonic inspection system, was designed, and the interlaminar shear damage of a double-sided grooved specimen of composite was examined on-line with the system. A full view of the progressive internal interlaminar damage, seen only with difficulty by common inspection methods, was successfully achieved.

Digits speech recognition based on 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 a 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 via the Hilbert transform. 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 method based on ICA and geometrical learning outperforms HMM in different number of train samples.

Application of ICA in on-line verification of the phase difference of the current sensor

The performance of the current sensor in power equipment may become worse affected by the environment. In this paper, based on ICA, we propose a method for on-line verification of the phase difference of the current sensor. However, not all source components are mutually independent in our application. In order to get an exact result, we have proposed a relative likelihood index to choose an optimal result from different runs. The index is based on the maximum likelihood evaluation theory and the independent subspace analysis. The feasibility of our method has been confirmed by experimental results.

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.

Application of ICA in on-line verification of the phase difference of the current sensor

The performance of the current sensor in power equipment may become worse affected by the environment. In this paper, based on ICA, we propose a method for on-line verification of the phase difference of the current sensor. However, not all source components are mutually independent in our application. In order to get an exact result, we have proposed a relative likelihood index to choose an optimal result from different runs. The index is based on the maximum likelihood evaluation theory and the independent subspace analysis. The feasibility of our method has been confirmed by experimental results.

An etched porous interface for on-line capillary electrophoresis-based two-dimensional separation system

The construction and evaluation of an on-column etched fused-silica porous junction for on-line coupling of capillary isoelectric focusing (CIEF) with capillary zone electrophoresis (CZE) are described. Where two separation columns were integrated on a single piece of fused-silica capillary through the etched similar to4 to 5-mm length porous junction along the capillary. The junction is easily prepared by etching a short section of the capillary wall with HF after removing the polyimide coating. The etched section becomes a porous glass membrane that allows only small ions related to the background electrolyte to pass through when high voltage is applied across the separation capillary. The primary advantages of this novel porous junction interface over previous designs (in which the interface is usually formed by fracturing the capillary followed by connecting the two capillaries with a section of microdialysis hollow fiber membrane) are no dead volume, simplicity, and ruggedness, which is particularly well suited for an on-line coupling capillary electrophoresis-based multiple dimensional separation system. The performance of the 2D CIEF-CZE system constructed by such an etched porous junction was evaluated by the analyses of protein mixtures.

On-line concentration of neutral and charged species in capillary electrochromatography with a methacrylate-based monolithic stationary phase

A method involving self-concentration, on-column enrichment and field-amplified sample stacking for on-line concentration in capillary electrochromatography with a polymer monolithic column is presented. Since monolithic columns eliminate the frit fabrication and the problems associated with frits, the experimental conditions could be more flexibly adjusted to obtain higher concentration factor in comparison with conventional particulate packed columns. With self-concentration effect, the detection sensitivity of benzene and hexylbenzene is improved by a factor of 4 and 8, respectively. With on-column enrichment and ultralong injection, improvement as high as 22 000 times in detection sensitivity of benzoin is achieved. Furthermore, a combination of the three above-mentioned methods yields up to a 24000-fold improvement in detection sensitivity for caffeine, a charged compound. Parameters affecting the efficiency of on-line concentration are investigated systematically. In addition, equations describing on-line concentration process are deduced.

On-line introduction of high-pressure gas-liquid sample for capillary gas chromatographic analysis

An on-line sample introduction technique in capillary gas chromatograph (CGC) for the analysis of high-pressure gas-liquid mixtures has been designed and evaluated. A sample loop of 0.05 muL and a washing solvent loop of 0.5 muL are mounted on a 10-port switching valve, which serves as the injection valve. A capillary resistor was connected to the vent of sample loop in order to maintain the pressure of the sample. Both the sample and the washing solvent are transferred into the split-injection port through a narrow bore fused silica capillary inserted into the injection liner through a septum. The volume of the liner is used both as the pressure-release damper and evaporation chamber of the sample. On-line analysis of both reactants and resultants in ethylene olimer reaction mixture at 5 MPa was carried out, which demonstrated the applicability of the technique. (C) 2004 Elsevier B.V. All rights reserved.