A New Comb Circular Polarizer Suitable for Millimeter‐Band Application

This letter presents a new polarizer which has a simple comb structure inside a circular waveguide. The electrical performance of the proposed comb polarizer is optimized by a circular waveguide radius and by the physical parameters of the comb plates. This polarizer is suitable for providing good performance in millimeter‐band application because of its simple structure and low fabrication cost. In our experiments the dual‐band comb polarizer designed in band 1(K) and band 2(Ka) showed good electrical performance without any tuning elements.     

A practical SPICE model based on the physics and characteristics of realistic single-electron transistors

A practical model for a single-electron transistor (SET) was developed based on the physical phenomena in realistic Si SETs, and implemented into a conventional circuit simulator. In the proposed model, the SET current calculated by the analytic model is combined with the parasitic MOSFET characteristics, which have been observed in many recently reported SETs formed on Si nanostructures. The SPICE simulation results were compared with the measured characteristics of the Si SETs. In terms of the bias, temperature, and size dependence of the realistic SET characteristics, an extensive comparison leads to good agreement within a reasonable level of accuracy. This result is noticeable in that a single set of model parameters was used, while considering divergent physical phenomena such as the parasitic MOSFET, the Coulomb oscillation phase shift, and the tunneling resistance modulated by the gate bias. When compared to the measured data, the accuracy of the voltage transfer characteristics of a single-electron inverter obtained from the SPICE simulation was within 15%. This new SPICE model can be applied to estimating the realistic performance of a CMOS/SET hybrid circuit or various SET logic architectures.     

Growth and formation mechanism of sea urchin-like ZnO nanostructures on Si

Sea urchin-like nanostructures of ZnO consisting of ZnO nanowires with blunt faceted ends were grown on Si (100) substrates by oxidation of metallic Zn at 600 °C. ZnO nanowires having a diameter of 30–60 nm and length of 2–4 Μm were in similar shape with uniform diameter along its entire length with well faceted blunt ends. X-ray diffraction and transmission electron microscope analysis showed that the as-grown nanostructures were highly crystalline with wurtzite hexagonal structure having lattice constants of a=b=3.25 å and c=5.21 å. Room temperature photoluminescence (PL) measurements showed a weak near band-edge emission at 380 nm, but a strong green emission at 500–530 nm. A model for vapor-solid (VS) growth mechanism of ZnO nanowires was presented, in which nucleation of ZnO is crucial for the growth of the nanostructures.     

Application of a fibre-reactive chitosan derivative to cotton fabric as a zero-salt dyeing auxiliary

Cotton fabric has been treated with a fibre-reactive chitosan derivative containing quaternary ammonium groups, O -acrylamidomethyl- N -[(2-hydroxy-3-trimethylammonium)propyl]chitosan chloride (NMA-HTCC). Cotton treated with NMA-HTCC has been dyed with direct and reactive dyes without the addition of salt. The colour yield was higher than that on untreated cotton, despite the addition of a large amount salt in the latter case. After dyeing, cotton treated with NMA-HTCC gave better wash fastness than the untreated cotton. The light fastness was however inferior to that on untreated cotton. The antimicrobial activity of cotton treated with NMA-HTCC against Staphylococcus aureus was considerably lower after dyeing, probably due to the antimicrobial effect of the cationic group on NMA-HTCC being blocked by its combination with the anionic dye.     

Virtual target tracking of mobile robot and its application to formation control

A virtual target tracking approach is proposed for kinematic control of mobile robot. In the controller, linear and angular velocity inputs are generated by using the local data of robot position and orientation along with the estimated velocity of target object. Applying the proposed approach to a cooperative robot group with arbitrary number of multiple mobile robots, it is possible to create various robot formations for cooperative navigation and tracking of moving object. The developed controller is shown to be stable and convergent through theoretical proof and a series of experiments.     

Note: High speed optical profiler based on a phase-shifting technique using frequency-scanning lasers

We present a high speed optical profiler (HSOP) using frequency-scanning lasers for three-dimensional profile measurements of microscopic structures. To improve upon previous techniques for implementing the HSOP, we developed frequency-scanning lasers and a compact microscopic interferometer. The controller of the HSOP was also modified to generate proper phase-shifting steps. For measurements of step height specimens, the HSOP showed results comparable with a commercial optical profiler, even with much higher measurement speeds (up to 30 Hz). The typical repeatability of step height measurement was less than 1 nm. We also present measurements of microscopic structures to verify the HSOP's ability to perform high speed inline inspection for the semiconductor and flat-panel display industries.     

AptaCDSS-E: A classifier ensemble-based clinical decision support system for cardiovascular disease level prediction

Conventional clinical decision support systems are generally based on a single classifier or a simple combination of these models, showing moderate performance. In this paper, we propose a classifier ensemble-based method for supporting the diagnosis of cardiovascular disease (CVD) based on aptamer chips. This AptaCDSS-E system overcomes conventional performance limitations by utilizing ensembles of different classifiers. Recent surveys show that CVD is one of the leading causes of death and that significant life savings can be achieved if precise diagnosis can be made. For CVD diagnosis, our system combines a set of four different classifiers with ensembles. Support vector machines and neural networks are adopted as base classifiers. Decision trees and Bayesian networks are also adopted to augment the system. Four aptamer-based biochip data sets including CVD data containing 66 samples were used to train and test the system. Three other supplementary data sets are used to alleviate data insufficiency. We investigated the effectiveness of the ensemble-based system with several different aggregation approaches by comparing the results with single classifier-based models. The prediction performance of the AptaCDSS-E system was assessed with a cross-validation test. The experimental results show that our system achieves high diagnosis accuracy (>94%) and comparably small prediction difference intervals (<6%), proving its usefulness in the clinical decision process of disease diagnosis. Additionally, 10 possible biomarkers are found for further investigation.     

Effect of interlayer on structure and performance of anode-supported SOFC single cells

To lower the operating temperatures in solid oxide fuel cell (SOFC) operations, anode-supported SOFC single cells with a single dip-coated interlayer were fabricated and the effect of the interlayer on the electrolyte structure and the electrical performance was investigated. For the preparation of SOFC single cells, yttria-stabilized zirconia (YSZ) electrolyte, NiO-YSZ anode, and 50% YSZ-50% strontium-doped lanthanum manganite (LSM) cathode were used. In order to characterize the cells, scanning electron microscopy (SEM) and atomic force microscopy (AFM) were utilized and the gas (air) permeability measurements were conducted for gas tightness estimation. When the interlayer was inserted onto NiO-YSZ anode, the surface roughness of anode was diminished by about 40% and dense crack-free electrolytes were obtained. The electrical performance was enhanced remarkably and the maximum power density was 0.57W/cm(2) at 800 degrees C and 0.44W/cm(2) at 700 degrees C. On the other hand, the effect of interlayer on the gas tightness was negligible. The characterization study revealed that the enhancement in the electrical performance was mainly attributed to the increase of ion transmission area of anode/electrolyte interface and the increase of ionic conductivity of dense crack-free electrolyte layer.     

Polarization properties of cube-corner retroreflectors and their effects on signal strength and nonlinearity in heterodyne interferometers

The polarization properties of solid-state cube-corner retroreflectors, which are uncoated glass or metal-coated glass on the reflecting surfaces, are examined analytically and compared. Experimental verifications are presented for the case of linearly polarized incident light. When the uncoated cube-corner is used in a heterodyne interferometer, the polarization properties reveal that the axial orientation of the corner reflector has an effect on the strength of the beat signal and the nonlinearity error. A theoretical analysis of the effect is presented together with experimental results.     

Multiscale Bayesian texture segmentation using neural networks and Markov random fields

This paper presents a wavelet-based texture segmentation method using multilayer perceptron (MLP) networks and Markov random fields (MRF) in a multi-scale Bayesian framework. Inputs and outputs of MLP networks are constructed to estimate a posterior probability. The multi-scale features produced by multi-level wavelet decompositions of textured images are classified at each scale by maximum a posterior (MAP) classification and the posterior probabilities from MLP networks. An MRF model is used in order to model the prior distribution of each texture class, and a factor, which fuses the classification information through scales and acts as a guide for the labeling decision, is incorporated into the MAP classification of each scale. By fusing the multi-scale MAP classifications sequentially from coarse to fine scales, our proposed method gets the final and improved segmentation result at the finest scale. In this fusion process, the MRF model serves as the smoothness constraint and the Gibbs sampler acts as the MAP classifier. Our texture segmentation method was applied to segmentation of gray-level textured images. The proposed segmentation method shows better performance than texture segmentation using the hidden Markov trees (HMT) model and the HMTseg algorithm, which is a multi-scale Bayesian image segmentation algorithm.