Fabrication and application of a new modified electrochemical sensor using nano-silica and a newly synthesized Schiff base for simultaneous determination of Cd,Cu and Hg ions in water and some foodstuff samples

A new chemically modified carbon paste electrode was constructed and used for rapid, simple, accurate, selective and highly sensitive simultaneous determination of cadmium, copper and mercury using square wave anodic stripping voltammetry (SWASV). The carbon paste electrode was modified by N,N′-bis(3-(2-thenylidenimino)propyl)piperazine coated silica nanoparticles. Compared with carbon paste electrode, the stripping peak currents had a significant increase at the modified electrode. Under the optimized conditions (deposition potential, −1.100 V vs. Ag/AgCl; deposition time, 60 s; resting time, 10 s; SW frequency, 25 Hz; pulse amplitude, 0.15 V; dc voltage step height, 4.4 mV), the detection limit was 0.3, 0.1 and 0.05 ng mL⁻¹ for the determination of Cd²⁺, Cu²⁺ and Hg²⁺, respectively. The complexation reaction of the ligand with several metal cations in methanol was studied and the stability constants of the complexes were obtained. The effects of different cations and anions on the simultaneous determination of metal ions were studied and it was found that the electrode is highly selective for the simultaneous determination of Cd²⁺, Cu²⁺ and Hg²⁺. Furthermore, the present method was applied to the determination of Cd²⁺, Cu²⁺ and Hg²⁺ in water and some foodstuff samples.     

A Simple Approach for Multi‐fidelity Experimentation Applied to Financial Engineering

In practical applications, information about the accuracy or ‘fidelity’ of alternative surrogate systems may be ambiguous and difficult to determine. To address this problem, we propose to treat surrogate system fidelity level as a categorical factor in optimal response surface design. To design the associated experiments, we apply the Expected Integrated Mean Squared Error optimal design criterion, which takes into account both variance and bias errors. The performance of the proposed design was compared using three test cases to four types of alternatives using the Empirical Integrated Squared Error. Because of its ability to foster relatively accurate predictions, the proposed design is recommended in fidelity experimental design, particularly when the experimenters lack sufficient information about the fidelity levels of surrogate systems. The method was applied to the case of intraday trading optimization in which data were collected from the Taiwan Futures Exchange. We also calculated the implied volatility from the Merton's Jump‐diffusion model via the fast Fourier transform algorithm with three different models of varying fidelity levels. Copyright © 2014 John Wiley & Sons, Ltd.     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

Carrier Frequency Offset estimation for interleaved OFDMA uplink based on subspace processing

This paper investigates Carrier Frequency Offset （CFO）, estimation in the uplink of the Orthogonal Frequency-Division Multiple Access （OFDMA） systems with the interleaved subcarrier assignment. CFOs between the transmitters and the uplink receiver will destroy orthogonality among different subcarriers, hence resulting in inter-carrier interference and multiuser interference. A two-stage frequency offset estimation algorithm based on subspace processing is proposed. The main advantage of the proposed method is that it can obtain the CFOs of all users simultaneously using only one OFDMA block. Compared with the previously known methods, it not only has a relatively low implementation complexity but is also suitable for random subchannel assignment.     

基于Mean Shift算法的嵌入式实时彩色目标跟踪

为满足Mean Shift算法的实时运行要求,提出了核函数量化以及相关计算权值整数化的方法,将复杂的浮点运算转化为整数运算,减小算法的运算量.设计了以高性能DSP芯片TMS320C6418结合大规模门阵列的嵌入式目标跟踪平台,并与一个具有两自由度伺服系统构成闭环跟踪网络.目标的脱靶量(目标偏离视场中心的距离)作为反馈信号控制伺服系统带动摄像机运动,使目标处于视场的中心附近.实验结果表明系统具有良好的稳定性.     

方形自聚焦透镜的研制

经过方形玻璃丝的加工、离子交换及成品的精密加工等过程,成功制出了方形自聚焦透镜.并采用聚焦成像和雅明干涉等方法对其光学特性进行测试,得出了方形自聚焦透镜本身所具有的一些特性：中心部分畸变较小,成像性能好;四个棱角内的球差较大,像质较差;折射率分布不具有旋转对称性,而是与方向和半径有关.     

Finite element modelling of natural-convection-controlled change of phase

The problem of phase change in the presence of natural convection has been investigated. A model has been proposed based on the treatment of the release/absorption of latent heat as a heat source/sink in combination with the standard Galerkin finite element method with a primitive variable formulation on a fixed grid. To demonstrate the capabilities of the model, three cases of phase change of an aluminium alloy in the presence of natural convection arc considered, i.e. solidification, melting and combined solidification and melting. The solidification of water in a square cavity is modelled as another example, taking into account the density extremum, and the results are compared with a previously published work.     

概率神经网络和FTIR光谱用于食道癌的辅助分析

利用正常与相应癌化食道组织的主要FTIR特征峰aυs,CH3、sυ,CH2、σCH2、aυs,po4-、υc-o、sυ,po2-及sυ,磷酸化蛋白作为概率神经网络的输入向量,对网络的主要参数(网络径向基函数分布spread(0~5))、输入向量和网络表现(m ean accurate rate of recogn ition)之间的关系进行了研究。主要结论如下:i)无论输入向量是哪种特征频率的组合,其平均识别正确率都高于71.40%;ii)当输入向量为特征频率sυ,po2、sυ,磷酸化蛋白或υc-0、sυ,po2、sυ,磷酸化蛋白时,网络表现较佳,平均识别正确率较好。当spread介于1.4~2.3时,两者均达到网络具有的最高平均识别正确率(85.71%);iii)大多数情况下,网络的平均识别正确率与spread之间呈现二个高峰的特征,即spread介于0.1~0.3和1.5~5.0之间时,网络均具有较高的平均识别正确率。研究表明,以傅里叶变换红外光谱的主要特征峰为概率神经网络的输入向量,用于食道组织样品的癌化识别分析是完全可能的,其平均识别正确率可达85.71%。     

Improved MLV filter to remove multiplicative noise

More methods can be used to remove the additive noise, such as the Mean of Least Variance （MLV） filter. When the signal is noised by the multiplicative noise, it is difficult to remove. The paper presents an improved filter to remove multiplicative noise by changing the multiplicative noise to the additive noise, and then using the MLV-like to remove the additive noise. The simulation results show that the performance is better than Minimum Coefficient of Variation （MCV） filter and MLV filter. Both one-dimension and image experiments demonstrate its theoretical performance.     

A novel indoor geo-location method using MIMO array

In a Multiple-Input Multiple-Output （MIMO） Orthogonal Frequency Division Multiplexing （OFDM） based Wireless Local Area Network （WLAN） system, both Access Points （APs） and Mobile Terminals （MTs） are configured with multiple antennas, to make novel indoor geo-location method possible. In this paper, we presented a novel Least Square Support Vector Machine （LS-SVM） based data fusion algorithm to fuse signal strength measurements for indoor geo-location using only a single AP with MIMO arrays. We evaluate our proposed algorithms under indoor environments by MATLAB simulations. Simulation results show that our MIMO-based algorithm is superior to conventional least square algorithm.