Numerical inversions of a source term in the FADE with a Dirichlet boundary condition using final observations

This paper deals with an inverse problem of determining a source term in the one-dimensional fractional advection-dispersion equation (FADE) with a Dirichlet boundary condition on a finite domain, using final observations. On the basis of the shifted Grünwald formula, a finite difference scheme for the forward problem of the FADE is given, by means of which the source magnitude depending upon the space variable is reconstructed numerically by applying an optimal perturbation regularization algorithm. Numerical inversions with noisy data are carried out for the unknowns taking three functional forms: polynomials, trigonometric functions and index functions. The reconstruction results show that the inversion algorithm is efficient for the inverse problem of determining source terms in a FADE, and the algorithm is also stable for additional data having random noises.     

Neural network based controller for Cr–Fe batch reduction process

An automated pilot plant has been designed and commissioned to carry out online/real-time data acquisition and control for the Cr⁶⁺–Fe²⁺ reduction process. Simulated data from the Cr⁶⁺–Fe²⁺ model derived are validated with online data and laboratory analysis using ICP-AES analysis method. The distinctive trend or patterns exhibited in the ORP profiles for the non-equilibrium model derived have been utilized to train neural network-based controllers for the process. The implementation of this process control is to ensure sufficient Fe²⁺ solution is dosed into the wastewater sample in order to reduce all Cr⁶⁺–Cr³⁺. The neural network controller has been utilized to compare the capability of set-point tracking with a PID controller in this process. For this process neural network-based controller dosed in less Fe²⁺ solution compared to the PID controller which hence reduces wastage of chemicals. Industrial Cr⁶⁺ wastewater samples obtained from an electro-plating factory has also been tested on the pilot plant using the neural network-based controller to determine its effectiveness to control the reduction process for a real plant. The results indicate the proposed controller is capable of fully reducing the Cr⁶⁺–Cr³⁺ in the batch treatment process with minimal dosage of Fe²⁺.     

Poly(brilliant cresyl blue) electrogenerated on single-walled carbon nanotubes modified electrode and its application in mediated biosensing system

Single-walled carbon nanotubes (SWCNTs) functionalized with carboxylic acid groups were cast to glassy carbon electrode (GCE) to construct a three-dimensional nano-micro structured scaffold. Brilliant cresyl blue (BCB) was electropolymerized on the above-mentioned SWCNTs/GCE using continuous cycling between −0.7 and 0.9 V vs. SCE. PolyBCB yielded on SWCNTs/GCE exhibited the enhanced electrochemical redox behavior compared with that electrogenerated on bare GCE. The apparent surface coverage of PolyBCB obtained by SWCNTs/GCE was at least 10 times higher than that obtained by bare GCE, namely 4.8 × 10⁻⁹ and 3.6 × 10⁻¹⁰ mol cm⁻². The cyclic voltammograms recorded by PolyBCB/SWCNTs/GCE exhibited well-defined two peaks located at −0.25 V and −0.06 V, respectively, with a surface-controlled mechanism. In addition, morphologies of PolyBCB electrogenerated on GCE and SWCNTS/GCE were characterized by atomic force microscopy. Finally, this proposed PolyBCB/SWCNTs/GCE was used in the construction of the second-generation biosensors to hydrogen peroxide and glucose, with the enhanced analytical performance.     

Micro-piezoelectric immunoassay chip for simultaneous detection of Hepatitis B virus and α-fetoprotein

In this paper, a piezoelectric diaphragm-based immunoassay chip was developed to simultaneously detect anti-Hepatitis B virus (HBV) and anti-alpha-fetoprotein (AFP). The chip was fabricated by micro-machining technology and consists of eight individual circular sensors with a diameter of 800 μm. Hepatitis B surface antigen (HBsAg), Hepatitis C core antigen (HBcAg) and AFP as the probe molecules were immobilized on different sensing spots on the chip. A solution containing anti-HBsAg and anti-AFP was applied into the reaction chambers in all sensors of the chip, and significant frequency shifts were only observed in the sensors with HBsAg and AFP for immunoassay detection. The fluorescence image further confirmed the successful detection of anti-HBsAg and anti-AFP. The total assay time was less than 2 h. The frequency shift-based calibration curves show a detection limit of 0.1 ng/ml and a dynamic detection range of 0.1-10,000 ng/ml for both anti-HBsAg and anti-AFP, respectively, thus demonstrating that the developed piezoelectric immunoassay chip has potential applications for rapid, specific, sensitive, and multiple detections of HBV.     

Research of neural network algorithm based on factor analysis and cluster analysis

Aiming at the large sample with high feature dimension, this paper proposes a back-propagation (BP) neural network algorithm based on factor analysis (FA) and cluster analysis (CA), which is combined with the principles of FA and CA, and the architecture of BP neural network. The new algorithm reduces the feature dimensionality of the initial data through FA to simplify the network architecture; then divides the samples into different sub-categories through CA, trains the network so as to improve the adaptability of the network. In application, it is first to classify the new samples, then using the corresponding network to predict. By an experiment, the new algorithm is significantly improved at the aspect of its prediction precision. In order to test and verify the validity of the new algorithm, we compare it with BP algorithms based on FA and CA.     

Fabrication of metallic micromirror using electroplating technology

A nickel micromirror array was designed and successfully fabricated using a thick photoresist as a sacrificial layer and as a mold for nickel electroplating. It was composed of two address electrodes, two support posts and a nickel mirror plate. The mirror plate, which is supported by two nickel posts, is overhung about 10 μm from the silicon substrate. The nickel mirror plate is actuated by an electrostatic force generated by electrostatic potential difference applied between the mirror plate and the address electrode. Optimized fabrication processes have been developed to reduce residual stress in mirror plate and prevent contact between the mirror plate and the substrate, which ensure a reasonable flat and smooth micromirror for operation at low actuation voltage.

     

Exploiting effective features for chinese sentiment classification

Features play a fundamental role in sentiment classification. How to effectively select different types of features to improve sentiment classification performance is the primary topic of this paper. Ngram features are commonly employed in text classification tasks; in this paper, sentiment-words, substrings, substring-groups, and key-substring-groups, which have never been considered in sentiment classification area before, are also extracted as features. The extracted features are then compared and analyzed. To demonstrate generality, we use two authoritative Chinese data sets in different domains to conduct our experiments. Our statistical analysis of the experimental results indicate the following: (1) different types of features possess different discriminative capabilities in Chinese sentiment classification; (2) character bigram features perform the best among the Ngram features; (3) substring-group features have greater potential to improve the performance of sentiment classification by combining substrings of different lengths; (4) sentiment words or phrases extracted from existing sentiment lexicons are not effective for sentiment classification; (5) effective features are usually at varying lengths rather than fixed lengths.     

A multi-strategy knowledge interoperability framework for heterogeneous learning objects

This paper presents a knowledge exchange framework that can leverage the interoperability among semantically heterogeneous learning objects. With the release of various e-Learning standards, learning contents and digital courses are easy to achieve cross-platform sharing, exchanging, and even reorganizing. However, knowledge sharing in semantic level is still a challenge due to that the learning materials can be presented in any form, such as audios, videos, web pages, and even flash files. The proposed knowledge exchange framework allows users to share their learning materials (also called “learning objects”) in semantic level automatically. This framework contains two methodologies: the first is a semantic mapping between knowledge bases (i.e. ontologies) which have essentially similar concepts, and the second is an ontology-based classification algorithm for sharable learning objects. The proposed algorithm adopts the IMS DRI standard and classifies the sharable learning objects from heterogeneous repositories into a local knowledge base by their inner meaning instead of keyword matching. Significance of this research lies in the semantic inferring rules for ontology mapping and learning objects classification as well as the full automatic processing and self-optimizing capability. Focused on digital learning materials and contrasted to other traditional technologies, the proposed approach has experimentally demonstrated significantly improvement in performance.     

基于肤色分割的视频人体检测

针对视频图像中人体运动形态多变、方向不确定等问题,提出了一种基于肤色分割的视频人体检测算法。采用改进的帧间差分方法求得自适应背景,与背景差相结合进行运动目标粗分割,在粗分割范围内进行肤色分割。在肤色分割时,利用YCbCr色彩空间的自适应亮度分段椭圆肤色模型及形态学操作、约束性条件等后处理确定人脸区域,得到人体目标。实验结果表明,该方法能有效地检测视频中的人体目标,与同类方法相比,该方法的时间复杂度更低,因而能更好地满足视频处理的实时性要求。     

木马隐藏技术与防范方法

为加固网络安全、防范木马攻击,结合实例研究了一种木马隐藏技术,实现了基于加载三级跳和线程守护的隐藏技术,增强了木马的隐蔽性与抗毁性,并提出了该技术相应的防范措施和清除方法。实验结果表明,融入该隐藏技术的木马程序完成了预期的隐藏功能并可以穿透最新的瑞星杀毒软件、瑞星防火墙及硬件防火墙,表明了该隐藏技术的可行性与有效性。