Zhen Hong Jia

Nano-Al2O3 Film Prepared on Porous Silicon by Sol-Gel Method

We report the structural and optical properties of a-Al2O3 film grown on porous silicon substrate using sol-gel method. The results indicated that a-Al2O3 film were grown after it sintering at 1200 °C for 1 hour and the scanning electron microscopy image shows the a-Al2O3 film has a nanostructure. From the photoluminescence spectrum, it shows that a narrow purple emission peak. This proved porous silicon is a good substrate to grow a-Al2O3 film.

Lattice Reduction Algorithm Based Uplink MC-CDMA

MC-CDMA integrates the advantages of OFDM with those of CDMA, it has high spectral efficiency, robustness against multi-path propagation and multiple access flexibility. Due to the above mentioned merits, it has been considered as a candidate for future wireless. In recent years, lattice reduction technique is discussed in multiple input multiple output communication systems, and has been shown with its better performance. The purpose of this paper is to express a model for uplink MC-CDMA systems in matrix form and then to propose a lattice reduction aided multiuser detection, in order to ameliorate the affects of inter-carrier interference and multi access interference. The effectiveness of the proposed method is evaluated by the bit error rate performance.

Research on Combined Prediction Model for Busy Telephone Traffic

In order to improve the prediction accuracy of busy telephone traffic, this study proposes a busy telephone traffic prediction method that combines wavelet transformation and least square support vector machine (lssvm) model which is optimized by particle swarm optimization (pso) algorithm. Firstly, decompose the pretreatment of busy telephone traffic data with mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use pso_lssvm model predict each reconfigured one. Then the busy telephone traffic can be achieved. The experimental results show that the prediction model has higher prediction accuracy and stability.

A Novel Level Set Method for Remote Sensing Image

Due to the characteristic of remote sensing image, we propose a novel method based on K-means algorithm also with the improved multi-phrase level set model. Comparing with the classical multi-phase C-V model, the improved model considers the region area information, gradient information and edge detection .Proper use of gradient information can overcome the inaccurate edge localization defects in image segmentation. The edge detection is used for keeping the boundary information better in the evolution process .For the reason of picking up the contour’s convergent speed and enable the avoidance of trap .Four stages are constructed. Firstly, a median filtering is applied to smooth the original image and reduce parts of noise. Secondly, the usage of K-means algorithm gains more obvious differences of characteristics. Next, the reconstruction of gradient is obtained by using Sobel operator. Finally, segmentation result is achieved by using an improved method of multi-phase level set image segmentation. Experimental results show that the proposed approach has advantages in rapid and efficient application of remote sensing image segmentation.

The Influence of Electrochemical Anodization for Porous Silicon Microcavity Fabrication

The present work reports the electrochemical anodization for porous silicon microcavity (PSM) fabrication, including the number of layers and electrochemical process effect in the optical response quality of PSM. These PSMs have been obtained by using PS technology. It is found that the electrochemical process limits the maximum number of layers because there is a chemical dissolution effect during electrochemical anodization. The reflectance spectra of the PSMs indicates that stop-band and the resonant peak of the PSM shift down with the increases of the number of layers due to the decrease of layers thickness. The value of the full width at half maximum (FWHM) dependents on the number of layers, and the number of layer increases when the FWHM decreases, which is due to the light scattering at roughness interface layer.

Influence of AgNO3 on Photoluminescence Properties of Porous Silicon

Porous silicon (PS) has the strong photoluminescence (PL) at room temperature and high specific surface. In this paper, we have fabricated the PS coated with silver nanoparticles as a substrate. The result shows that the substrate made in this way is stable for more than twenty days and the strong PL intensity of PS is around 584nm after immersed into solution of AgNO3. The formation of SiAg bond was demonstrated to be responsible for the improvement of PL properties.

Porous Silicon Biosensor for the Detection of Transgenic Cotton of Antifeezing Protein

Genetic engineering has been used extensively for improving cold resistance in plants. In this paper, an optical immunoassay was developed by the optic reflectance spectroscopy of the porous silicon biosensor to monitor the success of transgenic frost-resistant cotton. Transgenic cotton extract samples and anti- antifreeze protein (AFP) antibodies were employed as the target and probe, respectively. Porous silicon is functionalized by using oxidation and silanization, then anti- AFP antibodies were immobilized to the porous silicon pore used a crosslink method. The changes of reflectance spectrum before and after antigen-antibody react ion are observed. The results show that transgenic frost-resistant cotton extract samples caused obvious red shift in reflectance spectrum of porous silicon while common cotton was not. Control experiment with negative antibodies shows high specifcity and conventional ELASA and Western experiment were also carried for comparison. Compare to conventional ELASA and Western, porous silicon biosensor is quick and accurate determination for the detection of transgenic cotton of antifeezing protein.

A Non-Destructive Method Based on QPSO-RBF for the Measurement of Sugar Content in Cantaloupe

A nondestructive measurement approach is presented in this paper, which is capable of determining sugar content in cantaloupe from the dielectric property. The approach is based on measured equivalent capacitance and equivalent resistance of the cantaloupe, and on data analysis using quantum-behaved particle swarm optimization (QPSO) and Grey radial basis function (RBF) neural network. First, accumulated generating operation (AGO) in Grey forecasting is used to convert the initial observed data to obtain the accumulated data with strong regularity, which are employed to model and train the radial basis function neural network. Second, it adopted quantum-behaved particle swarm optimization algorithm to train the centers and widths of radial basis function. This model not only prevented the problem that the parameters of neural network are hard to be tuned, but also improved the network precision of prediction. Experimental results revealed that the predictive model as proposed has good predictive effect for the measurement of sugar in cantaloupes.

Photonic Band-Gaps in Porous Silicon Based Mirrors with a Ellipse Profile Refractive Index

We investigate the use of ellipse refractive index structure to enlarge photonic band-gap (PBG). The PBG structure was prepared on porous silicon with 10 unit cell. Each unit cell is consisting of 21 layers with the refractive index varying according to the envelope of the ellipse function. The width of this photonic band-gap is high to 451nm.

Preparation and characterization of CdTe/Porous silicon system

We report the structural and photoluminescence properties of CdTe/Porous silicon (PS) composite system prepared by chemical vapor deposition. The XRD pattern accord with the standard pattern of cadmium telluride of the samples was evaluated and the morphology of CdTe particles was characterized by scanning electron microscopy. The composite sample gives a strong luminescence and the mechanism of photoluminescence with CdTe/PS has also been discussed.