Mining fuzzy temporal association rules by item lifespans

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. In real-world applications, transactions may contain quantitative values and each item may have a lifespan from a temporal database. In this paper, we thus propose a data mining algorithm for deriving fuzzy temporal association rules. It first transforms each quantitative value into a fuzzy set using the given membership functions. Meanwhile, item lifespans are collected and recorded in a temporal information table through a transformation process. The algorithm then calculates the scalar cardinality of each linguistic term of each item. A mining process based on fuzzy counts and item lifespans is then performed to find fuzzy temporal association rules. Experiments are finally performed on two simulation datasets and the foodmart dataset to show the effectiveness and the efficiency of the proposed approach.     

Smooth trajectory planning for a parallel manipulator with joint friction and jerk constraints

In order to achieve better tracking accuracy effectively, a new smooth and near time-optimal trajectory planning approach is proposed for a parallel manipulator subject to kinematic and dynamic constraints. The complete dynamic model is constructed with consideration of all joint frictions. The presented planning problem can be solved efficiently by formulating a new limitation curve for dynamic constraints and a reduced form for jerk constraints. The motion trajectory is planned with quartic and quintic polynomial splines in Cartesian space and septuple polynomial splines in joint space. Experimental results show that smaller tracking error can be obtained. The developed method can be applied to any robots with analytical inverse kinematic and dynamic solutions.     

Objective evaluation of speech dysfluencies using wavelet packet transform with sample entropy

Dysfluency and stuttering are a break or interruption of normal speech such as repetition, prolongation, interjection of syllables, sounds, words or phrases and involuntary silent pauses or blocks in communication. Stuttering assessment through manual classification of speech dysfluencies is subjective, inconsistent, time consuming and prone to error. This paper proposes an objective evaluation of speech dysfluencies based on the wavelet packet transform with sample entropy features. Dysfluent speech signals are decomposed into six levels by using wavelet packet transform. Sample entropy (SampEn) features are extracted at every level of decomposition and they are used as features to characterize the speech dysfluencies (stuttered events). Three different classifiers such as k-nearest neighbor (kNN), linear discriminant analysis (LDA) based classifier and support vector machine (SVM) are used to investigate the performance of the sample entropy features for the classification of speech dysfluencies. 10-fold cross validation method is used for testing the reliability of the classifier results. The effect of different wavelet families on the classification performance is also performed. Experimental results demonstrate that the proposed features and classification algorithms give very promising classification accuracy of 96.67% with the standard deviation of 0.37 and also that the proposed method can be used to help speech language pathologist in classifying speech dysfluencies.     

Sensitivity analysis for biometric systems: A methodology based on orthogonal experiment designs

The purpose of this paper is to introduce an effective and structured methodology for carrying out a biometric system sensitivity analysis. The goal of sensitivity analysis is to provide the researcher/developer with insight and understanding of the key factors—algorithmic, subject-based, procedural, image quality, environmental, among others—that affect the matching performance of the biometric system under study. This proposed methodology consists of two steps: (1) the design and execution of orthogonal fractional factorial experiment designs which allow the scientist to efficiently investigate the effect of a large number of factors—and interactions—simultaneously, and (2) the use of a select set of statistical data analysis graphical procedures which are fine-tuned to unambiguously highlight important factors, important interactions, and locally-optimal settings. We illustrate this methodology by application to a study of VASIR (Video-based Automated System for Iris Recognition)—NIST iris-based biometric system. In particular, we investigated k = 8 algorithmic factors from the VASIR system by constructing a (2^6?1 × 3¹  × 4¹) orthogonal fractional factorial design, generating the corresponding performance data, and applying an appropriate set of analysis graphics to determine the relative importance of the eight factors, the relative importance of the 28 two-term interactions, and the local best settings of the eight algorithms. The results showed that VASIR’s performance was primarily driven by six factors out of the eight, along with four two-term interactions. A virtue of our two-step methodology is that it is systematic and general, and hence may be applied with equal rigor and effectiveness to other biometric systems, such as fingerprints, face, voice, and DNA.     

Improved concentration and separation of particles in a 3D dielectrophoretic chip integrating focusing, aligning and trapping

This article presents a dielectrophoresis (DEP)-based microfluidic device with the three-dimensional (3D) microelectrode configuration for concentrating and separating particles in a continuous throughflow. The 3D electrode structure, where microelectrode array are patterned on both the top and bottom surfaces of the microchannel, is composed of three units: focusing, aligning and trapping. As particles flowing through the microfluidic channel, they are firstly focused and aligned by the funnel-shaped and parallel electrode array, respectively, before being captured at the trapping unit due to negative DEP force. For a mixture of two particle populations of different sizes or dielectric properties, with a careful selection of suspending medium and applied field, the population exhibits stronger negative DEP manipulated by the microelectrode array and, therefore, separated from the other population which is easily carried away toward the outlet due to hydrodynamic force. The functionality of the proposed microdevice was verified by concentrating different-sized polystyrene (PS) microparticles and yeast cells dynamically flowing in the microchannel. Moreover, separation based on size and dielectric properties was achieved by sorting PS microparticles, and isolating 5 μm PS particles from yeast cells, respectively. The performance of the proposed micro-concentrator and separator was also studied, including the threshold voltage at which particles begin to be trapped, variation of cell-trapping efficiency with respect to the applied voltage and flow rate, and the efficiency of separation experiments. The proposed microdevice has various advantages, including multi-functionality, improved manipulation efficiency and throughput, easy fabrication and operation, etc., which shows a great potential for biological, chemical and medical applications.     

A novel method to construct 3D electrodes at the sidewall of microfluidic channel

We report a simple, low-cost and novel method for constructing three-dimensional (3D) microelectrodes in microfluidic system by utilizing low melting point metal alloy. Three-dimensional electrodes have unique properties in application of cell lysis, electro-osmosis, electroporation and dielectrophoresis. The fabrication process involves conventional photolithography and sputtering techniques to fabricate planar electrodes, positioning bismuth (Bi) alloy microspheres at the sidewall of PDMS channel, plasma bonding and low temperature annealing to improve electrical connection between metal microspheres and planar electrodes. Compared to other fabrication methods for 3D electrodes, the presented one does not require rigorous experimental conditions, cumbersome processes and expensive equipments. Numerical analysis on electric field distribution with different electrode configurations was presented to verify the unique field distribution of arc-shaped electrodes. The application of 3D electrode configuration with high-conductive alloy microspheres was confirmed by particle manipulation based on dielectrophoresis. The proposed technique offers alternatives to construct 3D electrodes from 2D electrodes. More importantly, the simplicity of the fabrication process provides easy ways to fabricate electrodes fast with arc-shaped geometry at the sidewall of microchannel.     

A Comparative study on multiobjective reliable and robust optimization for crashworthiness design of vehicle structure

Design optimization without considering uncertainties of system variables and parameters can be problematic in real life. In order to take into account the effect of uncertainties, reliable and robust design schemes have proven effective, but limited studies have been reported to compare their difference in a multiobjective framework. This paper takes a typical vehicle structure subject to offset frontal crashing scenario as an example to compare reliable and robust designs with their deterministic counterpart. The thicknesses of some key components of vehicle frontal structures were selected as design variables, the vehicle weight and energy absorption as the objectives, deceleration and firewall intrusion as the constraints. The deterministic multiobjective optimization problem was first solved by adopting Design of Experimental (DOE), metamodels and Non-dominated Sorting Genetic Algorithm II (NSGA-II). Take into account the uncertainties, a Monte Carlo Simulation (MCS) is adopted to generate random distributions of the objective and constraint functions for each design. For the reliability-based optimization the desired reliabilities of 90 %, 95 % and 99 % are considered, respectively. For the robustness-based optimization, two different formulation strategies are adopted. The optimization showed that the reliable and robust Pareto fronts are shifted away from their deterministic counterpart due to uncertainties. The different Pareto fronts yielded from the deterministic, reliable and robust designs are compared to provide some quantitative insights into how to apply these different design schemes for resolving uncertainty problems. It is shown that, compared with the baseline design, the optimizations enhance the crashworthiness of vehicle, though more conservative solutions could have been generated from the reliable and robust optimizations.     

四履带双摆臂机器人越障机理及越障能力

为发挥四履带双摆臂机器人的最佳越障性能,本文从运动学的角度,在固定双履带机器人越障机理的 基础上,分析了四履带双摆臂机器人克服台阶、斜坡、沟道等典型障碍的运动机理及其最大越障能力,重点研究了 四履带双摆臂机器人正向和反向两种攀越台阶方式的运动机理及其最大越障能力．以CUMT-II 型煤矿探测机器人 样机为例,绘制了机器人仰角、摆臂摆角与跨越台阶高度的3 维关系图,以及斜坡坡度与摆臂摆角关系曲线,并求 出了相应的最大越障能力的理论值,与实验室实测数据进行了对比分析．本文推导出机器人的最佳越障性能及对应 的质心和摆臂的位置,可为机器人越障时质心位置的控制提供理论依据．     

面向运动分割优化的变分光流计算方法研究

面向运动分割的需求,围绕变分光流计算中的运动边缘保留问题,对反应-扩散式光流计算模型中的扩散张量设计与改进方法进行系统深入研究。 在分析已有设计方法的基础上,提出了一种融合图像和流场信息驱动的扩散张量设计方法,并利用该扩散张量建立光流计算模型,然后在多尺度计算框架下给出了相应的偏微分方程数值计算方法。 理论分析与对比实验结果表明,这种设计方法能有效克服现有方法提取运动边缘不精确的缺点,更准确地刻画出运动边缘,提高光流的计算精度。     

基于MSP430的太阳光源跟踪控制系统设计

为了提高太阳能电池板的能量转换效率,提出了一种基于MSP430的太阳光源跟踪控制系统。系统设计原理采用光强比较法,硬件部分设计了光强信号采集电路、以MSP430为核心的主控制器、步进电机驱动电路等;软件部分采用模块化编程,加入数字滤波和控制算法。系统实现了刘信号采集与处理、电机驱动等模块的控制,能够快速准确跟踪太阳光源。运行实验结果表明,系统运行稳定,控制灵活,达到预期的设计目标。