Noninvasive glucose monitoring in vivo with an optical heterodyne polarimeter

An amplitude-sensitive optical heterodyne polarimeter was set up to monitor noninvasively the aqueous glucose concentration in a rabbit's eye. A Zeeman laser in conjunction with a Glan-Thompson analyzer was used to generate an optical heterodyne signal. The amplitude of the heterodyne signal linearly related to the optical rotation angle of the aqueous glucose. The concentration of the aqueous glucose in a rabbit's eyeball was measured in vivo. There was a 30-min time delay between observations of aqueous glucose and blood glucose. The detection capability and the reproducibility of the experiment are demonstrated and discussed.     

Random-iteration algorithm-based optical parallel architecture for fractal-image decoding by use of iterated-function system codes

An optical parallel architecture for the random-iteration algorithm to decode a fractal image by use of iterated-function system (IFS) codes is proposed. The code value is first converted into transmittance in film or a spatial light modulator in the optical part of the system. With an optical-to-electrical converter, electrical-to-optical converter, and some electronic circuits for addition and delay, we can perform the contractive affine transformation (CAT) denoted in IFS codes. In the proposed decoding architecture all CAT's generate points (image pixels) in parallel, and these points then are joined for display purposes. Therefore the decoding speed is improved greatly compared with existing serial-decoding architectures. In addition, an error and stability analysis that considers nonperfect elements is presented for the proposed optical system. Finally, simulation results are given to validate the proposed architecture.     

Pressure infiltration of sol/gel processed short fibre ceramic matrix composites

Using pressure infiltration short fibre-reinforced ceramic matrix composites with uniform and dense microstructure can be made. Based upon this processing technique, composites composed of silica sol, alumina particles, and alumina short fibres were fabricated. The related processing parameters studied in this work include infiltration rate, fibre volume fraction Vf, particle size, and infiltrate viscosity. An optimal infiltration rate was 4 mm min-1, at which rate the composite with Vf of 8.1% and particle size of 3 m has the highest green density. An equilibrium between particle packing strength and applied load must be obtained during the infiltration to obtain high green density and composite strength. The influence of fibre volume fraction and particle size on composite green density is in a synergistic manner because it involves particle–fibre interactions, fibre–fibre interactions, and sedimentation. Furthermore, the increase of sol viscosity results in more sedimentation in the infiltrate and lower composite green density. The fracture toughness of composites is 38% higher than that of monolithic alumina. © 1998 Chapman & Hall     

Ho:CaF(2) solid-state saturable-absorber Q switch for the 2-µm Tm,Cr:Y(3)Al(5)O(12) laser

The holmium-doped calcium fluoride (Ho:CaF(2)) crystal was shown to be an effective solid-state saturable-absorber Q-switch for a flash-lamp-pumped Tm,Cr:Y(3)Al(5)O(12) laser at 2.017 μm. With a 1-cm-thick Ho(0.5%),Er(5%):CaP(2) saturable absorber and a 6.3% output coupler, a single Q-switched laser pulse of 51 mJ in energy and 60 ns in duration was obtained at a flash-lamp input energy of 85 J. With a 14.6% output coupler, a typical Q-switched laser pulse of 84 mJ and 82 ns was observed.     

高速数据采集系统的设计与实现

由于雷达数据处理的要求,需要对雷达数据进行实时地存储记录。本文介绍了一种基于光纤通道的高速数据采集系统,以FPGA为平台,PCIExpress为接口,链式DMA为传输模式,实现了最高速率为6Gbps的数据采集系统。     

A template-based baseball video scene classification using efficient playfield segmentation

In this paper, we present an effective and efficient framework for baseball video scene classification. The results of scene classification can be able to provide the ground for baseball video abstraction and high-level event extraction. In general, most conventional approaches are shot-based, which shot change detection and key-frame extraction are necessary prerequisite procedures. On the contrary, we propose a frame-based approach. In our scene classification framework, an efficient playfield segmentation technique is proposed, and then the reduced field maps are utilized as scene templates. Because the shot change detection and the key-frame extraction are not required in proposed method, the new framework is very simple and efficient. The experimental results have demonstrated that the effectiveness of our proposed framework for baseball videos scene classification, and it can be easily extended the template-based approach to other kinds of sports videos.     

Simulation optimization using particle swarm optimization algorithm with application to assembly line design

Assembly line design is an important part of production system. Some processes need to undergo changes in order to increase in efficiency. Computer simulation has been applied on process design for many decades. Traditionally, simulation had to run all possible alternatives of assembly line and was not considered as an optimization technique. Thus, this study employs particle swarm optimization (PSO) algorithm which is with mutation based on similarity for simulation optimization in order to optimize the managerial parameters in production system. Through experimentation designs and statistics tests, the simulation results show that the proposed method is better than other algorithms, like genetic algorithm and conventional PSO algorithm for solving assembly line design problem.     

An econometric analysis of SARS and Avian Flu on international tourist arrivals to Asia

This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu are compared directly according to the number of human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.     

Gene selection and sample classification on microarray data based on adaptive genetic algorithm/k-nearest neighbor method

Recently, microarray technology has widely used on the study of gene expression in cancer diagnosis. The main distinguishing feature of microarray technology is that can measure thousands of genes at the same time. In the past, researchers always used parametric statistical methods to find the significant genes. However, microarray data often cannot obey some of the assumptions of parametric statistical methods, or type I error may be over expanded. Therefore, our aim is to establish a gene selection method without assumption restriction to reduce the dimension of the data set. In our study, adaptive genetic algorithm/k-nearest neighbor (AGA/KNN) was used to evolve gene subsets. We find that AGA/KNN can reduce the dimension of the data set, and all test samples can be classified correctly. In addition, the accuracy of AGA/KNN is higher than that of GA/KNN, and it only takes half the CPU time of GA/KNN. After using the proposed method, biologists can identify the relevant genes efficiently from the sub-gene set and classify the test samples correctly.