Novel method to construct a quality map for phase unwrapping based on modulation and the phase gradient

A novel method to construct a quality map, called modulation-phase-gradient variance (MPGV), is proposed, based on modulation and the phase gradient. The MPGV map is successfully applied to two phase-unwrapping algorithms - the improved weighted least square and the quality-guided unwrapping algorithm. Both simulated and experimental data testify to the validity of our proposed quality map. Moreover, the unwrapped-phase results show that the new quality map can have higher reliability than the conventional phase-derivative variance quality map in helping to unwrap noisy, low-modulation, and/or discontinuous phase maps. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

Phase-step calibration technique based on a two-run-times-two-frame phase-shift method

A novel phase-step calibration technique is presented on the basis of a two-run-times-two-frame phase-shift method. First the symmetry factor M is defined to describe the distribution property of the distorted phase due to phase-shifter miscalibration; then the phase-step calibration technique, in which two sets of two interferograms with a straight fringe pattern are recorded and the phase step is obtained by calculating M of the wrapped phase map, is developed. With this technique, a good mirror is required, but no uniform illumination is needed and no complex mathematical operation is involved. This technique can be carried out in situ and is applicable to any phase shifter, whether linear or nonlinear. (c) 2006 Optical Society of America.

Novel method to construct a quality map for phase unwrapping based on modulation and the phase gradient

A novel method to construct a quality map, called modulation-phase-gradient variance (MPGV), is proposed, based on modulation and the phase gradient. The MPGV map is successfully applied to two phase-unwrapping algorithms - the improved weighted least square and the quality-guided unwrapping algorithm. Both simulated and experimental data testify to the validity of our proposed quality map. Moreover, the unwrapped-phase results show that the new quality map can have higher reliability than the conventional phase-derivative variance quality map in helping to unwrap noisy, low-modulation, and/or discontinuous phase maps. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

A detection method for grass carp hemorrhagic virus (GCHV) based on a reverse transcription polymerase chain reaction

A rapid, sensitive and highly specific detection method for grass carp hemorrhagic virus (GCHV) based on a reverse transcription-polymerase chain reaction (RT-PCR) has been developed. Two pairs of PCR primers were synthesized according to the cloned cDNA sequences of the GCHV-861 strain. For each primer combination, only one specific major product was obtained when amplification was performed by using the genomic dsRNA of GCHV-861 strain. The lengths of their expected products were 320 and 223 bp, respectively. No products were obtained when nucleic acids other than GCHV-861 genomic RNA were used as RT-PCR templates. To assess the sensitivity of the method, dilutions of purified GCHV-861 dsRNA total genome (0.01 pg up to 1000 pg) were amplified and quantities of as little as 0.1 pg of purified dsRNA were detectable when the amplification product was analyzed by 1.5% agarose gel electrophoresis. This technique could detect GCHV-861 not only in infected cell culture fluids, but also in infected grass carp Ctenopharyngodon idellus and rare minnow Gobiocypris rarus with or without hemorrhagic symptoms. The results show that the RT-PCR amplification method is useful for the direct detection of GCHV.

Polymerization of ionic liquid-based microemulsions: A versatile method for the synthesis of polymer electrolytes

电子邮箱fyan@suda.edu.cn

A new method to reduce the dark current of GaN based Schottky barrier ultraviolet photodetector

A new method to reduce the dark current of GaN based Schottky barrier ultraviolet photodetector is proposed. In comparision with conventional i-CaN/n(+)-GaN structure, an additional thin p-GaN cap layer is introduced on the i-GaN(n(-)-GaN) in the new structure. The simulation results showed that the additional layer makes the dark current to decrease in the photodetector due to the increase of the Schottky barrier height. The effects of thickness and carrier concentration of p-GaN layer on the dark current of the photodetector were also studied. It is suggested that the dark current of the new structure device could be better reduced by employing p-GaN with higher carrier concentration as the cap layer.

A Cancer Recognition Method Based on DNA Microarray

The accurate cancer classification is of great importance in clinical treatment. Recently, the DNA microarray technology provides a promising approach to the diagnosis and prognosis of cancer types. However, it has no perfect method for the multiclass classification problem. The difficulty lies in the fact that the data are of high dimensionality with small sample size. This paper proposed an automatic classification method of multiclass cancers based on Biomimetic pattern recognition (BPR). To the public GCM data set, the average correct classification rate reaches 80% under the condition that the correct rejection rate is 81%.

Development of Swept Frequency Method for Measuring Frequency Response of Photodetectors Based on Harmonic Analysis

We develop a swept frequency method for measuring the frequency response of photodetectors; (PDs) based on harmonic analysis. In this technique, a lightwave from a laser source is modulated by a radio-frequency (RF) signal via a Mach-Zehnder LiNbO3 modulator, and detected by a PD under test. The measured second-order harmonic of the RF signal contains information of the frequency responses and nonlinearities of the RF source, modulator, and PD. The frequency response of the PD alone is obtained by deducting the known frequency responses and nonlinearities of the RF source and modulator. Compared with the conventional swept frequency method, the measurement frequency range can be doubled using the proposed method. Experiment results show a good agreement between the measured results and those obtained using other techniques.

An Automatic Classification Method of Metabolic Cycle Based on Biomimetic Pattern Recognition

Correct classification of different metabolic cycle stages to identification cell cycle is significant in both human development and clinical diagnostics. However, it has no perfect method has been reached in classification of metabolic cycle yet. This paper exploringly puts forward an automatic classification method of metabolic cycle based on Biomimetic pattern recognition (BPR). As to the three phases of yeast metabolic cycle, the correct classification rate reaches 90%, 100% and 100% respectively.

A new method based on the construction of hypothetical symmetrical networks for fixture calibration in network analyzers

At least three known standards are normally required for the full two-port test fixture calibration in vector network analyzers (VNA). In this paper, a calibration procedure using only one standard, based on establishing two hypothetical symmetrical fixtures using triple-through method, is shown. The results using the calibrating method to subtract the influence of fixtures are in accord with the directly measured data of the device-under-test (DUT) without the fixtures very well, which shows that the proposed method is very simple and accurate.

Method for improving classification performance of neural network based on fuzzy input and network inversion

In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.

Synthesis and characterization of ZnO nanorods and nanoflowers grown on GaN-based LED epiwafer using a solution deposition method

We report the growth of hexagonal ZnO nanorods and nanoflowers on GaN-based LED epiwafer using a solution deposition method. We also discuss the mechanisms of epitaxial nucleation and of the growth of ZnO nanorods and nanoflowers. A GaN-based LED epiwafer was first deposited on a sapphire substrate by MOCVD with no electrode being fabricated on it. Vertically aligned ZnO nanorods with an average height of similar to 2.4 mu m were then grown on the LED epiwafer, and nanoflowers were synthesized on the nanorods. The growth orientation of the nanorods was perpendicular to the surface, and the synthesized nanoflowers were composed of nanorods. The micro-Raman spectra of the ZnO nanorods and nanoflowers are similar and both exhibit the E-2 (high) mode and the second-order multiple-phonon mode. The photoluminescence spectrum of ZnO nanostructures exhibits ultraviolet emission centred at about 380 nm and a broad and enhanced green emission centred at about 526 nm. The green emission of the ZnO nanostructures combined with the emission of InGaN quantum wells provides a valuable method to improve the colour rendering index (CRI) of LEDs.

An algorithm for removing facial makeup disturbances based on high dimensional imaginal geometry

In this paper, a novel algorithm for removing facial makeup disturbances as a face detection preprocess based on high dimensional imaginal geometry is proposed. After simulation and practical application experiments, the algorithm is theoretically analyzed. Its apparent effect of removing facial makeup and the advantages of face detection with this pre-process over face detection without it are discussed. Furthermore, in our experiments with color images, the proposed algorithm even gives some surprises.

A novel face recognition method based on hypersausage neural networks

In this paper, we firstly give the nature of 'hypersausages', study its structure and training of the network, then discuss the nature of it by way of experimenting with ORL face database, and finally, verify its unsurpassable advantages compared with other means.