An e-Learning tool considering similarity measures for manufacturing cell formation

Manufacturing cell formation is the first step in the design of cellular manufacturing system. The primary objective of this step is to cluster machines into machine cells and parts into part families so that the minimum of intercell trips will be achieved. This paper will be focused on the configuration of machine cells considering three types of initial machine-part matrix: binary (zero-one) matrix, production volume matrix, and operation time matrix. The similarity measure uses only information from these types of matrix. A pure combinatorial programming formulation will be developed to maximize the sum of similarity coefficients between machine/part pairs. An e-Learning tool/application to help industrial students and engineers for enhancing their cell formation capability is proposed. This tool is designed to include a novel similarity coefficient-based heuristic algorithm for solving the cell formation problem. To determine the performance of the proposed tool, comparison is made with a well-known tool along a case study.     

Ion‐exchange resins. II. Acrylamide crosslinked copolymers as precursors for some ion exchangers

Crosslinked copolymers of acrylamide (AA) and ethylacrylate and some ion exchangers derived from them containing either primary amine groups, obtained by the Hofmann degradation of the amide groups, or carboxylic groups, obtained by the alkaline hydrolysis of the ester groups, were studied. Divinylbenzene and N,N′‐methylenebisacrylamide were used as crosslinkers. The starting copolymers and the corresponding ion exchangers were characterized by IR spectroscopy, swelling behavior, and thermogravimetric analysis. The ion‐exchanger properties were correlated with the crosslinker nature and the chemical reactions performed on the AA copolymers. The average molecular weight between two crosslinks, determined from the swelling data in water, was compared with that calculated on the basis of the copolymerization stoichiometry only for the carboxylic cation exchangers. In this way, the preservation of the crosslink density after the hydrolysis was revealed. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2701–2707, 2003     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

Electrochemical study of the chromium electrode behaviour in borate buffer solution

The electrochemical behaviour of the chromium electrode in borate buffer solution (pH 9.3) was studied by cyclic voltammetry and electrochemical impedance spectroscopy. Chromium passivity was observed over a broad potential region, from –1.0 to 0.5 V vs SCE. The passivation process took place in two steps: formation of a chromium oxide monolayer and transition of chromium to a higher valence state. The anodic film exhibited the properties of a p-type semiconductor. Transpassive dissolution of chromium occurred at 0.5 V vs SCE, with two reaction intermediates present, Cr_Cr ^III and Cr_ad ⁴⁺.     

Polyesterification and isomerization of maleic anhydride and 1,6-hexane diol as studied by 1H and 13C n.m.r.

The polyesterification and isomerization reaction of 1,6-hexane diol and maleic anydride in a melt without catalyst was studied by ¹³C and ¹H n.m.r. spectroscopy. The structure and concentration of oligoester species during the polyesterification and isomerization were determined depending on the reaction temperature and time. According to the number and configuration of repeating units determined from ¹H n.m.r. spectra kinetics of both reactions were also considered. The degree of isomerization is continuously increasing in the investigated reaction range.     

Vapour liquid equilibrium with association in both phases: A model with the concentration-dependent liquid phase association constant applied to acetic acid—benzene, -toluene, -p- and -o-xylene

A model employing the correction factors of Marek and Standart, but using a concentration-dependent liquid phase association factor of Jenkins—Robinson, has been used to model vapour—liquid equilibrium data for mixtures of acetic acid with benzene, toluene, o-xylene and p-xylene. With the aim to use systems of acetic acid—benzene and acetic acid—toluene as the test mixtures for distillation columns, the examination of the systems of acetic acid—aromatic hydrocarbons was undertaken. The model promises to be useful in modelling isobaric and isothermal data of acetic acid—benzine, acetic acid—toluene, acetic acid-p-xylene and acetic acid-o-xylene systems. Deviation plots show that the isothermal and isobaric data are represented well.     

Effect of low‐temperature plasma and chitosan treatment on wool dyeing with Acid Red 27

This study examines in detail the influence of low‐temperature plasma and biopolymer chitosan treatments on wool dyeability. Wool knitted fabrics were treated and characterized by whiteness and shrink‐resistance measurements. Surface modification was assessed by contact‐angle measurements of human hair fibers, which were used as a model to study the wetting properties of the treated wool knitted fabrics. The dyeing behavior was assessed from the diffusion mechanism point of view. The dyeing kinetics were measured at two different pHs (4.2 and 6.5) and three different temperatures (60, 85, and 100°C) to gain information about the contribution of the surface modification treatment to the dyeing mechanism. The exhaustion and reflectance data were compared, and the apparent diffusion coefficients were calculated. On the basis of the obtained results, a model for the dyeing mechanism of the chitosan treated wool was proposed. When treated with chitosan, the polymer sheath spread on the surface of the fibers acted as a predominant dyeing site in very short dyeing times, thus interacting with the dye and in later stages imparting the dye to the wool fiber. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 2204–2214, 2005     

meSAT: multiple encodings of CSP to SAT

One approach for solving Constraint Satisfaction Problems (CSP) (and related Constraint Optimization Problems (COP)) involving integer and Boolean variables is reduction to propositional satisfiability problem (SAT). A number of encodings (e.g., direct, log, support, order) for this purpose exist as well as specific encodings for some constraints that are often encountered (e.g., cardinality constraints, global constraints). However, there is no single encoding that performs well on all classes of problems and there is a need for a system that supports multiple encodings. We present a system that translates specifications of finite linear CSP problems into SAT instances using several well-known encodings, and their combinations. We also present a methodology for selecting a suitable encoding based on simple syntactic features of the input CSP instance. Thorough evaluation has been performed on large publicly available corpora and our encoding selection method improves upon the efficiency of existing encodings and state-of-the-art tools used in comparison.     

Ensemble-based noise detection: noise ranking and visual performance evaluation

Noise filtering is most frequently used in data preprocessing to improve the accuracy of induced classifiers. The focus of this work is different: we aim at detecting noisy instances for improved data understanding, data cleaning and outlier identification. The paper is composed of three parts. The first part presents an ensemble-based noise ranking methodology for explicit noise and outlier identification, named Noise- Rank, which was successfully applied to a real-life medical problem as proven in domain expert evaluation. The second part is concerned with quantitative performance evaluation of noise detection algorithms on data with randomly injected noise. A methodology for visual performance evaluation of noise detection algorithms in the precision-recall space, named Viper, is presented and compared to standard evaluation practice. The third part presents the implementation of the NoiseRank and Viper methodologies in a web-based platform for composition and execution of data mining workflows. This implementation allows public accessibility of the developed approaches, repeatability and sharing of the presented experiments as well as the inclusion of web services enabling to incorporate new noise detection algorithms into the proposed noise detection and performance evaluation workflows.