The MM-Estimator in Response Surface Methodology

In this article, a robust regression technique called MM-estimator is proposed to model the responses in response surface methodology (RSM). Model fitting based on the MM-estimator allows practitioners to find a better optimal setting in dual-response surface optimization and multiple-response optimization when the responses are considerably nonnormal and/or contain some outliers. The MM-estimator is one of the robust regression techniques that can dampen the effect of the outliers. An example from the Roman catapult experiment is used to illustrate our proposal.     

Optimization approach in variable-charge potential for metal/metal oxide systems

Earlier attempts on minimizing the total system energy of metal/metal oxide systems with given charge constraints appear to be indirect and unnecessarily complicated. The energy minimization problem is in fact a constrained optimization problem and hence can be solved by a constrained optimization method. We propose a new direct approach for finding charge distributions among ions in molecular dynamics simulations. The approach is based on an optimization algorithm, called the Generalized Reduced Gradient (GRG) Method. This efficient approach can be readily employed in molecular dynamic simulations for metal/metal oxide systems.     

Alternatives to the Multivariate Control Chart for Process Dispersion

In this article, we compare the performances of six new multivariate control chart schemes for process dispersion to the standard multivariate process dispersion control chart. The six new schemes are designed by transforming the standard multivariate control chart statistic for process dispersion into a standard scale so that runs rules can be incorporated into these schemes. This article discusses a simple extension for using runs rules in a multivariate control chart for process dispersion. The extension is deemed important since the use of runs rules is always confined to univariate control charts only. The performances of the six control chart schemes together with the standard control chart are based on the computed average run length (ARL) profiles. Five of the six schemes have shown better ARL performances than the standard multivariate process dispersion control chart.     

A simple and controllable nanostructure comprising non-conductive poly(vinylidene fluoride) and graphene nanosheets for supercapacitor

An effective method was used to produce stable and homogeneous colloidal suspensions of highly reduced graphene oxide (RGO) in N,N-dimethylformamide (DMF) without the assistance of dispersing agents.Ac...     

A New Database Intrusion Detection Approach Based on Hybrid Meta-Heuristics

A new secured database management system architecture using intrusion detection systems (IDS) is proposed in this paper for organizations with no previous role mapping for users. A simple representation of Structured Query Language queries is proposed to easily permit the use of the worked clustering algorithm. A new clustering algorithm that uses a tube search with adaptive memory is applied to database log files to create users’ profiles. Then, queries issued for each user are checked against the related user profile using a classifier to determine whether or not each query is malicious. The IDS will stop query execution or report the threat to the responsible person if the query is malicious. A simple classifier based on the Euclidean distance is used and the issued query is transformed to the proposed simple representation using a classifier, where the Euclidean distance between the centers and the profile’s issued query is calculated. A synthetic data set is used for our experimental evaluations. Normal user access behavior in relation to the database is modelled using the data set. The false negative (FN) and false positive (FP) rates are used to compare our proposed algorithm with other methods. The experimental results indicate that our proposed method results in very small FN and FP rates.     

A Modified S Chart for the Process Variance

Both the R and S charts are widely used in many manufacturing industries to monitor the process dispersion. The R chart is more popular among quality control practitioners especially when dealing with small sample sizes because of the simplicity of computing the range, R, from each sample. For larger sample sizes, the preferred choice is the S chart because it is slightly more effective than the R chart. The computation of the standard deviation, S, from each sample can now be made easily due to the availability of computers and scientific calculators. This article addresses the shortcomings of the conventional S chart and suggests a modified S chart to overcome these problems.     

A Modeling Approach to Maintenance Decisions Using Statistical Quality Control and Optimization

Maintenance concerns impact systems in every industry and effective maintenance policies are important tools. We present a methodology for maintenance decision making for deteriorating systems under conditions of uncertainty that integrates statistical quality control (SQC) and partially observable Markov decision processes (POMDPs). We use simulation to develop realistic maintenance policies for real‐world environments. Specifically, we use SQC techniques to sample and represent real‐world systems. These techniques help define the observation distributions and structure for a POMDP. We propose a simulation methodology for integrating SQC and POMDPs in order to develop and valuate optimal maintenance policies as a function of process characteristics, system operating and maintenance costs. A two‐state machine replacement problem is used as an example of how the method can be applied. A simulation program developed using Visual Basic for Excel yields results on the optimal probability threshold and on the accuracy of the decisions as a function of the initial belief about the condition of the machine. This work lays a foundation for future research that will help bring maintenance decision models into practice. Copyright © 2005 John Wiley & Sons, Ltd.     

应用蜜蜂繁殖进化型粒子群算法求解车辆路径问题

为了提高粒子群算法求解车辆路径问题时收敛速度和全局搜索能力,将蜜蜂繁殖进化机制与粒子群算法相结合,应用到CVRP问题的求解。该算法中,最优的个体作为蜂王与通过选择机制选择的雄蜂以随机概率进行交叉,增强了最优个体信息的应用能力;同时,随机产生一部分雄蜂种群,并将其与蜂王交叉增加了算法的多样性。实例分析表明该算法具有较好的全局搜索能力,验证了该算法的可行性。     

Bio-inspired Hybrid Feature Selection Model for Intrusion Detection

Intrusion detection is a serious and complex problem. Undoubtedly due to a large number of attacks around the world, the concept of intrusion detection has become very important. This research proposes a multilayer bio-inspired feature selection model for intrusion detection using an optimized genetic algorithm. Furthermore, the proposed multilayer model consists of two layers (layers 1 and 2). At layer 1, three algorithms are used for the feature selection. The algorithms used are Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Firefly Optimization Algorithm (FFA). At the end of layer 1, a priority value will be assigned for each feature set. At layer 2 of the proposed model, the Optimized Genetic Algorithm (GA) is used to select one feature set based on the priority value. Modifications are done on standard GA to perform optimization and to fit the proposed model. The Optimized GA is used in the training phase to assign a priority value for each feature set. Also, the priority values are categorized into three categories: high, medium, and low. Besides, the Optimized GA is used in the testing phase to select a feature set based on its priority. The feature set with a high priority will be given a high priority to be selected. At the end of phase 2, an update for feature set priority may occur based on the selected features priority and the calculated F-Measures. The proposed model can learn and modify feature sets priority, which will be reflected in selecting features. For evaluation purposes, two well-known datasets are used in these experiments. The first dataset is UNSW-NB15, the other dataset is the NSL-KDD. Several evaluation criteria are used, such as precision, recall, and F-Measure. The experiments in this research suggest that the proposed model has a powerful and promising mechanism for the intrusion detection system.     

Models for measuring and predicting shareholder value: A study of third party software service providers

In this study, we use the strategic profit model (SPM) and the economic value-added (EVA to measure shareholder value). SPM measures the return on net worth (RONW) which is defined as the return on assets (ROA) multiplied by the financial leverage. EVA is defined as the firm's net operating profit after taxes (NOPAT) minus the capital charge. Both, RONW and EVA provide an indication of how much shareholder value a firm creates for its shareholders, year on year. With the increasing focus on creation of shareholder value and core competencies, many companies are outsourcing their information technology (IT) related activities to third party software companies. Indian software companies have become leaders in providing these services. Companies from several other countries are also competing for the top slot. We use the SPM and EVA models to analyse the four listed players of the software industry using the publicly available published data. We compare the financial data obtained from the models, and use peer average data to provide customized recommendations for each company to improve their shareholder value. Assuming that the companies follow these rules, we also predict future RONW and EVA for the companies for the financial year 2005. Finally, we make several recommendations to software providers for effectively competing in the global arena.     

A decreasing inertia weight particle swarm optimizer

It has been over ten years since the pioneering work of particle swarm optimization (PSO) espoused by Kennedy and Eberhart. Since then, various modifications, well suited to particular application areas, have been reported widely in the literature. The evolutionary concept of PSO is clear-cut in nature, easy to implement in practice, and computationally efficient in comparison to other evolutionary algorithms. The above-mentioned merits are primarily the motivation of this article to investigate PSO when applied to continuous optimization problems. The performance of conventional PSO on the solution quality and convergence speed deteriorates when the function to be optimized is multimodal or with a large problem size. Toward that end, it is of great practical value to develop a modified particle swarm optimizer suitable for solving high-dimensional, multimodal optimization problems. In the first part of the article, the design of experiments (DOE) has been conducted comprehensively to examine the influences of each parameter in PSO. Based upon the DOE results, a modified PSO algorithm, termed Decreasing-Weight Particle Swarm Optimization (DW-PSO), is addressed. Two performance measures, the success rate and number of function evaluations, are used to evaluate the proposed method. The computational comparisons with the existing PSO algorithms show that DW-PSO exhibits a noticeable advantage, especially when it is performed to solve high-dimensional problems.     

一种研究圆柱度目标函数单谷性的新方法

提出了一种研究圆柱目标函数单谷性的新方法，圆柱度目标函数单谷性的问题目前研究得还少，而弄清楚圆柱度目标函数是否是单谷函数对于用优化原理正确地计算其极值是非常重要的。     

基于纹理特征的合成孔径声纳图像目标检测研究

随着成像声纳技术的发展,声纳图像的目标检测与识别逐渐成为数字图像处理领域的一个重要研究课题。合成孔径声纳图像含有丰富的纹理特征,而灰度共生矩阵具有丰富的特征参数,可以从不同的角度对纹理进行细致刻画。采用灰度共生矩阵可以描述合成孔径声纳图像纹理方面的特征,通过计算灰度共生矩阵在方位向和距离向的能量、相关性、对比度和熵值,并构造特征向量,可以对合成孔径声纳图像中的目标进行准确检测。从实验结果可以看出,基于纹理信息可以准确实现合成孔径声纳图像的目标检测。     

A New Method of Global Path Planning for AGV

Path planning is important in the research of a mobile robot （MR）. Methods for it have been used in different applications. An automated guided vehicle（ AGV） , which is a kind of MR, is used in a flexible manufacturing system （FMS）. Path planning for it is essential to improve the efficiency of FMS. A new method was proposed with known obstacle space FMS in this paper. FMS is described by the Augmented Pos Matrix of a Machine （ APMM ） and Relative Pos Matrix of Machines （ RPMM）, which is smaller. The optimum path can be obtained according to the probability of the path and the maximal probability path. The suggested algorithm of path planning was good performance through simulation result： simplicity, saving time and reliability.     

人力资源个体价值计量模型新探

人力资源个体价值的计量问题是人力资源会计能否实施的关键。针对这个问题,提出了人力资源当期实现价值系数法计量模型。应用层次分析法确定每个员工在企业新增价值中的权重,从而计算出人力资源个体价值,并通过实例验证了计量模型的实用性。     

一种自动提取IVUS图像血管包络的新方法

提取血管内超声(IVUS)图像的血管包络对冠状动脉疾病的诊断有一定的积极意义。本文综合考虑IVUS图像的灰度特征、序列时间特性、先验知识等三类信息,提出一种自动提取血管包络的方法。先由序列时间特性和先验知识减少噪声和伪像干扰,提取出第一帧图像的初始包络;然后用结合梯度、灰度方差、灰度均值信息的B样条GVFsnake对初始包络进行变形得到第一帧的最终包络;最后利用序列图像的时间特性提取后续帧的包络。通过实验表明:综合三类信息的包络自动提取方法在精度和鲁棒性等方面优于以往的方法。     

A New Optimized Algorithm with Nonlinear Filter for Ultra-Tightly Coupled Integrated Navigation System of Land Vehicle

The extended particle filter (EPF) assisted by the Takagi-Sugeno (T-S) fuzzy logic adaptive system (FLAS) is used to design the ultra-tightly coupled GPS/INS (inertial navigation system) integrated navigation, which can maneuver the vehicle environment and the GPS outages scenario. The traditional integrated navigation designs adopt a loosely or tightly coupled architecture, for which the GPS receiver may lose the lock due to the interference/jamming scenarios, high dynamic environments, and the periods of partial GPS shading. An ultra-tight GPS/INS architecture involves the integration of I (in-phase) and Q (quadrature) components from the correlator of a GPS receiver with the INS data. The EPF is a particle filter (PF) which uses the extended Kalman filter (EKF) to generate the proposal distribution. The PF depends mostly on the number of particles in order to achieve a better performance during the high dynamic environments and GPS outages. The T-S FLAS is one of these approaches that can prevent the divergence problem of the filter when the precise knowledge on the system models is not available. The results show that the proposed fuzzy adaptive EPF (FAEPF) can effectively improve the navigation estimation accuracy and reduce the computational load as compared with the EPF and the unscented Kalman filter (UKF).     

An examination of compaction meter value for asphalt pavement compaction evaluation

Abstract

The potential of using compaction meter value (CMV) for evaluating the compaction of asphalt pavements has been hindered by the fact that the value of CMV can be affected by many factors, which include not only roller operation parameters, but also the temperature of asphalt layer and the underlying support. However, the conventional data processing of CMV usually ignores these factors. The study proposed a new approach to thoroughly examine the relationships between CMV and other factors. Using a field project in Tennessee, USA, the intelligent compaction data were examined to establish the relationships between CMV and other operation parameters such as roller frequency and amplitude first, then the effects of asphalt temperature and underlying support were analysed further utilising the original Witczak model and Abaqus software. After eliminating the influence of other factors, the proposed method could improve the correlation between the asphalt mixture density and CMV.     

基于混合粒子群算法的群岛泊位分配问题研究

泊位分配是提高港口运营效率的关键。针对群岛泊位分配问题,以船舶总在港时间为优化目标,构建了群岛泊位分配问题模型,并提出了一种混合粒子群算法进行求解。该算法在更新粒子状态时加入模拟退火和免疫调节操作,增强了算法的全局搜索能力。实验结果表明,混合粒子群算法在求解群岛泊位分配问题时,具有较好的优化性能,验证了算法的有效性和可行性。     

Optimization of Polishing Parameters with Taguchi Method for LBO Crystal in CMP

Chemical mechanical polishing(CMP)was used to polish Lithium triborate(LiB3O5 or LBO)crystal.Taguchi method was applied for optimization of the polishing parameters.Material removal rate(MRR)and surface roughness are considered as criteria for the optimization.The polishing pressure,the abrasive concentration and the table velocity are important parameters which influence MRR and surface roughness in CMP of LBO crystal.Experiment results indicate that for MRR the polishing pressure is the most significant p...