Copula-based Kernel Dependency Measures

The paper presents a new copula based method for measuring dependence between random variables. Our approach extends the Maximum Mean Discrepancy to the copula of the joint distribution. We prove that this approach has several advantageous properties. Similarly to Shannon mutual information, the proposed dependence measure is invariant to any strictly increasing transformation of the marginal variables. This is important in many applications, for example in feature selection. The estimator is consistent, robust to outliers, and uses rank statistics only. We derive upper bounds on the convergence rate and propose independence tests too. We illustrate the theoretical contributions through a series of experiments in feature selection and low-dimensional embedding of distributions.

UEGO based measurement of EGR rate and residual gas fraction

A technique is presented for measuring the exhaust gas recirculation (EGR) and residual gas fraction (RGF) using a fast UEGO based O2 measurement of the manifold or in-cylinder gases, and of the exhaust gases. The technique has some advantages over the more common CO2-based method. In the case of an RGF measurement, fuel interference must be eliminated and special fuelling arrangements are is required. It is shown how a UEGO-based measurement, though sensitive to reactive species in the exhaust (such as H 2), as a system reports EGR/ RGF rates faithfully. Preliminary tests showed that EGR and RGF measurements using the O2 approach agreed well with CO2-based measurements. Copyright © 2011 SAE International.

Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering

Semi-supervised clustering is the task of clustering data points into clusters where only a fraction of the points are labelled. The true number of clusters in the data is often unknown and most models require this parameter as an input. Dirichlet process mixture models are appealing as they can infer the number of clusters from the data. However, these models do not deal with high dimensional data well and can encounter difficulties in inference. We present a novel nonparameteric Bayesian kernel based method to cluster data points without the need to prespecify the number of clusters or to model complicated densities from which data points are assumed to be generated from. The key insight is to use determinants of submatrices of a kernel matrix as a measure of how close together a set of points are. We explore some theoretical properties of the model and derive a natural Gibbs based algorithm with MCMC hyperparameter learning. The model is implemented on a variety of synthetic and real world data sets.

Rapid hologram generation utilizing layer-based approach and graphic rendering for realistic three-dimensional image reconstruction by angular tiling

An approach of rapid hologram generation for the realistic three-dimensional (3-D) image reconstruction based on the angular tiling concept is proposed, using a new graphic rendering approach integrated with a previously developed layer-based method for hologram calculation. A 3-D object is simplified as layered cross-sectional images perpendicular to a chosen viewing direction, and our graphics rendering approach allows the incorporation of clear depth cues, occlusion, and shading in the generated holograms for angular tiling. The combination of these techniques together with parallel computing reduces the computation time of a single-view hologram for a 3-D image of extended graphics array resolution to 176 ms using a single consumer graphics processing unit card. © 2014 SPIE and IS and T.

Continuous speech research based on HyperSausage Neuron

In this paper, we presents HyperSausage Neuron based on the High-Dimension Space(HDS), and proposes a new algorithm for speaker independent continuous digit speech recognition. At last, compared to HMM-based method, the recognition rate of HyperSausage Neuron method is higher than that of in HMM-based method.

Continuous speech research based on HyperSausage Neuron

In this paper, we presents HyperSausage Neuron based on the High-Dimension Space(HDS), and proposes a new algorithm for speaker independent continuous digit speech recognition. At last, compared to HMM-based method, the recognition rate of HyperSausage Neuron method is higher than that of in HMM-based method.

Sensitive detection of protein by an aptamer-based label-free fluorescing molecular switch

We report an aptamer-based method for the sensitive detection of proteins by a label-free fluorescing molecular switch (ethidium bromide), which shows promising potential in making protein assay simple and economical.

ZnO-based hollow microspheres: Biopolymer-assisted assemblies from ZnO nanorods

Many efforts have been made in fabricating three-dimensional (3D) ordered zinc oxide (ZnO) nanostructures due to their growing applications in separations, sensors, catalysis, bioscience, and photonics. Here, we developed a new synthetic route to 3D ZnO-based hollow microspheres by a facile solution-based method through a water-soluble biopolymer (sodium alginate) assisted assembly from ZnO nanorods. The products were characterized by X-ray diffraction, field emission scanning electron microscopy, transmission electron microscopy, selected area electron diffraction, and X-ray photoelectron spectroscopy. Raman and photoluminescence spectra of the ZnO-based hollow microspheres were obtained at room temperature to investigate their optical properties. The hollow microspheres exhibit exciting emission features with a wide band covering nearly all the visible region. The calculated CIE (Commission Internationale d'Eclairage) coordinates are 0.24 and 0.31, which fall at the edge of the white region (the 1931 CIE diagram). A possible growth mechanism of the 3D ZnO superstructures based on typical biopolymer-crystal interactions in aqueous solution is tentatively proposed, which might be really interesting because of the participation of the biopolymer.

Aggregation-based fabrication and assembly of roughened composite metallic nanoshells: Application in surface-enhanced Raman scattering

This paper reports an aggregation-based method for the fabrication of composite Au/Ag nanoshells with tunable thickness and surface roughness. It is found that the resultant roughened composite Au/Ag nanoshells can attract each other spontaneously to form films at the air-water interface. Importantly, such films can be transferred onto the solid substrates without being destroyed and show excellent surface-enhanced Raman scattering (SERS) enhancement ability. Their strong enhancement ability may stem from the unique two-dimensional structure itself.

非结构环境下基于人机合作技术的抓取作业研究

介绍了一种利用人机合作技术在非结构环境引导机械手抓取静态目标的方法.分别介绍了将激光—CCD摄像机系统与操作者的经验相结合获得抓取目标位置的方法,及将虚拟现实技术与操作者的经验相结合获得抓取目标姿态的方法.继而利用基于模型的视觉引导技术,引导手臂完成抓取操作.

基于CORBA的多机器人应用互操作系统的研究与实现

本文针对异构分布环境下的多机器人系统 ,提出了一种基于 CORBA规范和框架请求代理 (FRB)这一方式的应用系统集成模型 .为实现分布异构环境下的多机器人的通信、协同、编程 ,支持系统任务重组与重构、应用互操作提供一条有效途径 .并给出了一个自行设计的面向多机器人基于CORBA的对象互操作的方法、机制 .给出基于 CORBA的应用编程接口 (API)与扩展接口定义语言X- IDL,通过基于 CORBA的多机器人基本对象类的建立与对象的实现 ,实现基于 CORBA的多机器人互操作与开放分布处理原型系统 .

Rough set feature selection and rule induction for prediction of malignancy degree in brain glioma

X. Wang, J. Yang, R. Jensen and X. Liu, 'Rough Set Feature Selection and Rule Induction for Prediction of Malignancy Degree in Brain Glioma,' Computer Methods and Programs in Biomedicine, vol. 83, no. 2, pp. 147-156, 2006.

HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels

In this paper we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training based method with the same training information used, and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.

Design, optimisation and characterisation of polymeric microneedle arrays prepared by a novel laser-based micromoulding technique.

PURPOSE:
Design and evaluation of a novel laser-based method for micromoulding of microneedle arrays from polymeric materials under ambient conditions. The aim of this study was to optimise polymeric composition and assess the performance of microneedle devices that possess different geometries.
METHODS:
A range of microneedle geometries was engineered into silicone micromoulds, and their physicochemical features were subsequently characterised.
RESULTS:
Microneedles micromoulded from 20% w/w aqueous blends of the mucoadhesive copolymer Gantrez® AN-139 were surprisingly found to possess superior physical strength than those produced from commonly used pharma polymers. Gantrez® AN-139 microneedles, 600 µm and 900 µm in height, penetrated neonatal porcine skin with low application forces (>0.03 N per microneedle). When theophylline was loaded into 600 µm microneedles, 83% of the incorporated drug was delivered across neonatal porcine skin over 24 h. Optical coherence tomography (OCT) showed that drug-free 600 µm Gantrez® AN-139 microneedles punctured the stratum corneum barrier of human skin in vivo and extended approximately 460 µm into the skin. However, the entirety of the microneedle lengths was not inserted.
CONCLUSION:
In this study, we have shown that a novel laser engineering method can be used in micromoulding of polymeric microneedle arrays. We are currently carrying out an extensive OCT-informed study investigating the influence of microneedle array geometry on skin penetration depth, with a view to enhanced transdermal drug delivery from optimised laser-engineered Gantrez® AN-139 microneedles.

A rapid PCR-based assay for identification of cryptic Myotis spp (Myotis mystacinus, Myotis brandtii and Myotis alcathoe).

The development of a quick PCR-based method to distinguish European cryptic Myotis spp., Myotis mystacinus, Myotis brandtii and Myotis alcathoe is described. Primers were designed around species-specific single nucleotide polymorphisms (SNP’s) in the ND1 mitochondrial gene, and a pair of control primers was designed in the 12S mitochondrial gene. A multiplex of seven primer combinations produces clear species-specific bands using gel electrophoresis. Robustness of the method was tested on 33 M. mystacinus, 16 M. brandtii and 15 M. alcathoe samples from across the European range of these species. The method worked well on faecal samples collected from maternity roosts of M. mystacinus. The test is intended to aid collection of data on these species through a rapid and easy identification method with the ability to use DNA obtained from a range of sources including faecal matter.