A non-intrusive in situ method of optical beam profiling in LCOS-based optical fiber switches

This paper proposed a non-intrusive method of measuring the optical beam profile at the surface of the liquid crystal on silicon (LCOS) device in an optical fiber switch. This method is based on blazed grating and can be employed in situ (on-line) for two-dimensional beam profiling in the LCOS-based optical fiber switches without introducing additional components or rearranging the system. The measured beam radius was in excellent agreement with that measured by the knife-edge technique. © 2013 Elsevier Ltd.

A Bayesian framework to predict deformations during supported excavations based on a semi-empirical method

The ground movements induced by the construction of supported excavation systems are generally predicted by empirical/semi-empirical methods in the design stage. However, these methods cannot account for the site-specific conditions and for information that becomes available as an excavation proceeds. A Bayesian updating methodology is proposed to update the predictions of ground movements in the later stages of excavation based on recorded deformation measurements. As an application, the proposed framework is used to predict the three-dimensional deformation shapes at four incremental excavation stages of an actual supported excavation project. © 2011 Taylor & Francis Group, London.

A Bayesian framework to predict deformations during supported excavations based on a semi-empirical method

The ground movements induced by the construction of supported excavation systems are generally predicted in the design stage by empirical/semi-empirical methods. However, these methods cannot account for the site-specific conditions and for information that become available as an excavation proceeds. A Bayesian updating methodology is proposed to update the predictions of ground movements in the later stages of excavation based on recorded deformation measurements. As an application, the proposed framework is used to predict the three-dimensional deformation shapes at four incremental excavation stages of an actual supported excavation project. Copyright © ASCE 2011.

Estimation of soil properties and deformations in staged constructions based on mcmc method

This paper presents a Bayesian probabilistic framework to assess soil properties and model uncertainty to better predict excavation-induced deformations using field deformation data. The potential correlations between deformations at different depths are accounted for in the likelihood function needed in the Bayesian approach. The proposed approach also accounts for inclinometer measurement errors. The posterior statistics of the unknown soil properties and the model parameters are computed using the Delayed Rejection (DR) method and the Adaptive Metropolis (AM) method. As an application, the proposed framework is used to assess the unknown soil properties of multiple soil layers using deformation data at different locations and for incremental excavation stages. The developed approach can be used for the design of optimal revisions for supported excavation systems. © 2010 ASCE.

Transient crosstalk in LCOS based WSS and a method to suppress the crosstalk levels

The origin of the transient crosstalk (TC) in a phase-only LCOS based WSS using a Fourier transform setup was investigated and identified. Two methods were proposed to reduce the TC by at least 5dB without the need to modify the optics or electronics in use. © 2013 OSA.

Requirements-based development of an improved engineering change management method

Engineering changes (ECs) are essential in complex product development, and their management is a crucial discipline for engineering industries. Numerous methods have been developed to support EC management (ECM), of which the change prediction method (CPM) is one of the most established. This article contributes a requirements-based benchmarking approach to assess and improve existing methods. The CPM is selected to be improved. First, based on a comprehensive literature survey and insights from industrial case studies, a set of 25 requirements for change management methods are developed. Second, these requirements are used as benchmarking criteria to assess the CPM in comparison to seven other promising methods. Third, the best-in-class solutions for each requirement are investigated to draw improvement suggestions for the CPM. Finally, an enhanced ECM method which implements these improvements is presented. © 2013 © 2013 The Author(s). Published by Taylor & Francis.

Transient Crosstalk in LCOS Based WSS and a Method to Suppress the Crosstalk Levels

The origin of the transient crosstalk (TC) in a phase-only LCOS based WSS using a Fourier transform setup was investigated and identified. Two methods were proposed to reduce the TC by at least 5dB without the need to modify the optics or electronics in use. © 2013 OSA.

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.