Composite of Au nanoparticles and molecularly imprinted polymer as a sensing material

A molecularly imprinted polymer with immobilized Au nanoparticles (Au-MIP) is reported as a novel type of sensing material. The sensing mechanism is based upon the variable proximity of the Au nanoparticles immobilized in the imprinted polymer, which exhibits selective binding of a given analyte accompanied by swelling that causes a blue-shift in the plasmon absorption band of the immobilized Au nanoparticles. Using adrenaline as the model analyte, it was shown that molecular imprinting effectively enhanced the sensitivity and selectivity, and accordingly, Au-MIP selectively detects the analyte at 5 microM. The combination of molecular imprinting and the Au nanoparticle-based sensing system was shown to be a general strategy for constructing sensing materials in a tailor-made fashion due to wide applicability of the imprinting technique and the independence of the sensing mechanism from the analyte recognition system.     

Sentence alignment using P-NNT and GMM

Parallel corpora have become an essential resource for work in multilingual natural language processing. However, sentence aligned parallel corpora are more efficient than non-aligned parallel corpora for cross-language information retrieval and machine translation applications. In this paper, we present two new approaches to align English–Arabic sentences in bilingual parallel corpora based on probabilistic neural network (P-NNT) and Gaussian mixture model (GMM) classifiers. A feature vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuation score, and cognate score values. A set of manually prepared training data was assigned to train the probabilistic neural network and Gaussian mixture model. Another set of data was used for testing. Using the probabilistic neural network and Gaussian mixture model approaches, we could achieve error reduction of 27% and 50%, respectively, over the length based approach when applied on a set of parallel English–Arabic documents. In addition, the results of (P-NNT) and (GMM) outperform the results of the combined model which exploits length, punctuation and cognates in a dynamic framework. The GMM approach outperforms Melamed and Moore’s approaches too. Moreover these new approaches are valid for any languages pair and are quite flexible since the feature vector may contain more, less or different features, such as a lexical matching feature and Hanzi characters in Japanese–Chinese texts, than the ones used in the current research.     

Color displays and flexible displays using quick‐response liquid‐powder technology for electronic paper

Abstract— Color displays and flexible displays that use electronic liquid powder have been developed. Novel types of color displays using either a colored powder or a color filter are discussed. We have also developed a flexible display with low‐cost substrate films with a high‐throughput roll‐to‐roll manufacturing method. These technologies enable a QR‐LPD to be widely used as an electronic‐paper display.     

Development of a high‐resolution RGBW flexible display using a white organic light‐emitting diode with microcavity structure and that of a side‐roll touch panel

In this study, white organic electroluminescent devices with microcavity structures were developed. A flexible high‐resolution active‐matrix organic light‐emitting diode display with low power consumption using red, green, blue, and white sub‐pixels formed by a color‐filter method was fabricated. In addition, a side‐roll touch display was developed in combination with a capacitive flexible touch screen.     

Fundamental study of high Q‐factor RF spiral inductor using carbonyl‐iron/epoxy composite magnetic core

In order to increase the Q‐factor of an RF spiral inductor used in the RF front‐end circuit of smartphone handsets, we introduced a carbonyl‐iron/epoxy composite magnetic core in the air‐core spiral inductor. The composite magnetic core, which was made by metal‐mask printing, consisted of carbonyl‐iron powder of 1.1 μm mean diameter and an epoxy resin matrix. We found that the 45 vol.% CIP composite magnetic core had a saturation magnetization of 0.9 T, relative permeability of ∼6, and loss tangent (tan δ) of ∼0.2 at 1 GHz. A two‐turn copper spiral inductor fabricated with the composite magnetic core filled only in the spacing between the conductor lines showed a clear Q‐factor increase of ∼29% compared to the air‐core spiral inductor at 1 GHz. Thus we obtained a substantial increase in the Q‐factor by the embedded composite magnetic core in the spacing between the conductor lines. The main reason for this is that the magnetic flux passing through the conductor lines was decreased by the magnetic core embedded in the spacing between conductor lines as a result of the magnetic flux passing mainly through the embedded magnetic core. Therefore, proximity effect is suppressed in the conductor line of the spiral coil. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

An extended probabilistic model building genetic network programming using both of good and bad individuals

Classical estimation of distribution algorithms (EDAs) generally use truncation selection to estimate the distribution of the good individuals while ignoring the bad ones. However, various researches in evolutionary algorithms (EAs) have reported that the bad individuals may affect and help solving the problem. This paper proposes a new method to use the bad individuals by studying the substructures rather than the entire individual structures to solve reinforcement learning (RL) problems, which generally factorize their entire solutions to the sequences of state–action pairs. This work was studied in a recent graph‐based EDA named probabilistic model building genetic network programming (PMBGNP), which could solve RL problems successfully, to propose an extended PMBGNP. The effectiveness of this work is verified in an RL problem, namely robot control. Compared to other related work, results show that the proposed method can significantly speed up the evolution efficiency. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Acquisition of optimal attribute subset through genetic algorithm using GNP‐based class association rule mining

Attribute selection is a technique to prune less relevant information and discover high‐quality knowledge. It is especially useful for the classification of a large database, because the preprocessing of data increases the possibility that predictor attributes given to the mining algorithm become more relevant to the class attribute. In this paper, a method to acquire the optimal attribute subset for the genetic network programming (GNP) based class association rule mining has been proposed, and this attribute selection process using genetic algorithm (GA) leads to a higher accuracy for classification. Class association rule mining through GNP is conducted with a small subset of data rather than the original large number of attributes; thus simple but important rules are obtained for classification while the local optimal problem is avoided. Simulation results with educational data show that the classification accuracy is largely improved from 52.73 to 74.54%, when classification is made using the optimal attribute subset. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Image denoising using pulse coupled neural network with an adaptive Pareto genetic algorithm

Recently, pulse coupled neural network (PCNN) attracts much attention in image denoising as a nonlinear filtering technique. The PCNN‐based anisotropic diffusion (PCNN‐AD) method has been proposed previously for flicker noise reduction and its effectiveness has been demonstrated. Using the visual characteristics of PCNN, PCNN‐AD has also solved the problem of AD that AD is not able to suppress the isolate noise. However, there are still two drawbacks in PCNN‐AD, that is, time consuming and PCNN parameters' estimation. In order to improve the efficiency and the denoising performance of PCNN‐AD, a PCNN‐based method with an adaptive Pareto genetic algorithm (GA‐PCNN) has been proposed to restrain from additive white Gaussian noise (AWGN) in this paper. GA‐PCNN firstly integrates the PCNN and AD as a parallel system, then, optimizes the parameters of a simplified PCNN by the adaptive Pareto GA. Experimental results indicate that GA‐PCNN has better performances than the previous denoising techniques, i.e. median filter, Wiener filter, AD filter, and PCNN‐AD. The effectiveness of GA‐PCNN on AWGN reduction and edge preservation are shown finally. The results will also contribute to denoising in CMOS image sensors in the future. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于操作功最优的永磁机构参数控制优化

以永磁机构分、合闸操作功与真空断路器开断性能要求匹配最优为目标,基于四连杆传动规律将12 kV真空断路器本体及传动机构的反力特性归算至永磁机构的运动部件动铁芯上,构建永磁机构操动特性数学模型。利用ANSYS-Maxwell仿真得到配永磁机构真空断路器的动铁芯位移、线圈电流、电容电压变化曲线等操动特性,计算出机构平均合闸速度、操作功等参数。以真空断路器操作功最优为目标函数,以线圈匝数、线径、操动电流为约束条件,在仿真的基础上建立正交回归实验,利用遗传算法对线圈参数进行优化设计,并通过实验进行验证。结果表明,在保证永磁机构操动特性满足真空断路器动作特性需求条件下,线圈优化设计后的永磁机构操作功从970.41 J降低到362.26 J,降低了动铁芯碰撞速度,提高了机构的稳定性。     

Highly anisotropic thermal conductivity of mesogenic epoxy resin film through orientation control

To develop insulating materials with a high thermally conductive anisotropy, planarly aligned mesogenic epoxy (ME) resin film was fabricated by uniaxial coating on a hydrophobic polyethylene terephthalate substrate. Grazing incidence small-angle X-ray scattering (GISAXS) and transmission SAXS measurements exhibited that the films spontaneously formed uniaxially aligned monodomain-like smectic structures by curing on the hydrophobic substrate. Then, an in- and out-of-plane thermal conductivity of 10 and 0.048 W m⁻¹ K⁻¹ and outstanding thermal conductivity anisotropy of 208 have been confirmed, respectively. The ME resin films with high thermal conductivity can be applied as insulating materials for multiple-layer electrical and electronic devices.