On a new class of analytic functions associated with conic domain

The aim of this paper is to generalize the conic domain defined by Kanas and Wisniowska, and define the class of functions which map the open unit disk E onto this generalized conic domain. A brief comparison between these conic domains is the main motivation of this paper. A correction is made in selecting the range interval of order of conic domain.     

A hybridisation of metaheuristics for flow shop scheduling

The present paper deals with the formation of an optimal sequence of flow shop scheduling (FSS) for efficient operation. The primary concern of FSS is to obtain the optimal sequence, which minimises the idle time, tardiness, makespan, etc. Among these, the criteria of minimising the makespan plays a vital part. Thus, in this paper, the sequencing of the FSS for minimising the makespan is addressed. An effective hybrid has been formed with the metaheuristics, namely an ant system and a genetic algorithm (GA). A number of illustrative examples with different combinations of machines and jobs have been solved using the proposed hybrid method.     

Chitosan/CNTs nanocomposite as green carrier material for pesticides controlled release

Chitosan-based nanocomposites containing gamma-treated carbon nanotubes (CNTs) were developed for controlled release of pesticide. The CNTs were irradiated under gamma irradiation in air at different doses. The transmission electron microscopic images of gamma-treated CNTs showed disentanglement of the tubes without distorting their tubular structure which effectively increased the dispersion properties of CNTs in nanocomposites. X-ray diffraction analysis of CNTs showed some structural changes, and an irradiation dose of 150 kGy is the most effective. Azinphos methyl (AZM) was selected as a model drug, and its release was studied using HPLC technique. Controlled release response of CNTs-based nanocomposites opens a new avenue for pesticides applications because it requires less quantity of pesticides. As a result, the side effects of pesticide in our environment are minimized.     

A Study on the FTIR Spectroscopy of Polylactide Doped with Nano-Aluminium Oxide and Nano-Cupric Oxide

Elucidation of the structure of naturally existing or synthesized substances is an important criterion in the study of materials to predict the application of the substance. In this study, polylactide was doped with nano-aluminium oxide and nano-cupric oxide with 1 and 3 mg of concentration variants. The interaction between the polymer matrix and the nanoparticles has been studied using Fourier transform infrared. Successful doping of the polymer has been observed. Attention has been drawn to check the intermolecular bonding in films having varying thicknesses, films prepared at higher sonication temperatures, and chemical homogeneity of the doped polymer films.     

An efficient numerical algorithm for multi-dimensional time dependent partial differential equations

An efficient and robust numerical scheme based on Haar wavelets and finite differences is suggested for the solution of two-dimensional time dependent linear and nonlinear partial differential equations (PDEs). Excellent feature of the scheme is the conversion of linear and non-linear PDEs to algebraic equations which are comparatively easy to handle. Convergence of the scheme, which guarantees small error norm as the resolution level increases, is also an important part of this work. Different error norms are computed to check efficiency of the technique. Computations verify accuracy, flexibility and low computational cost of the method.     

Heterogeneous Reactor Modeling of an Industrial Multitubular Packed‐Bed Ethylene Oxide Reactor

The one‐dimensional heterogeneous model of an industrial multitubular packed‐bed ethylene oxide (EO) reactor was developed using the equation‐oriented platform Aspen Custom Modeler. Reactor operation was optimized in terms of maximized EO production and selectivity and enhanced safety related to the presence of oxygen in the EO reactor. Good agreement was found between the model results during validation against the available information under identical operating conditions. The model predicts the behavior of the EO reaction and demonstrates the extent of catalyst utilization with product distribution, product yield, by‐product formation, temperature and concentration profiles, over time and along the length of the reactor or catalyst bed. The model sensitivity studies compute the optimum feed flow, oxygen concentration, feed pressure, etc. and suggest the best operational philosophy.     

Preparation and characterization of aluminum oxide–poly(ethylene-co-butyl acrylate) nanocomposites

This article describes the preparation and characterization of composites containing poly(ethylene-co-butyl acrylate) (EBA–13 and EBA–28 with 13 and 28 wt % butyl acrylate, respectively) and 2–12 wt % (0.5–3 vol %) of aluminum oxide nanoparticles (two types differing in specific surface area and hydroxyl-group concentration; uncoated and coated with, respectively, octyltriethoxysilane and aminopropyltriethoxysilane). A greater surface coverage was obtained with aminopropyltriethoxysilane than with octyltriethoxysilane. An overall good dispersion was obtained in the EBA-13 composites prepared by extrusion compounding. Composites with octyltriethoxysilane-coated nanoparticles showed the best dispersion. The addition of the nanoparticles to EBA–28 resulted in poor dispersion, probably due to insufficiently high shear forces acting during extrusion mixing which were unable to break down nanoparticle agglomerates. The nanoparticles had no effect on the crystallization kinetics in the EBA–13 composites, but in the EBA–28 composites the presence of the nanoparticles led to an increase in the crystallization peak temperature, suggesting that the nanoparticles had a nucleating effect in this particular polymer. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

New Synthetic Control Charts for Monitoring Process Mean and Process Dispersion

A statistical quality control chart is widely recognized as a potentially powerful tool that is frequently used in many manufacturing and service industries to monitor the quality of the product or manufacturing processes. In this paper, we propose new synthetic control charts for monitoring the process mean and the process dispersion. The proposed synthetic charts are based on ranked set sampling (RSS), median RSS (MRSS), and ordered RSS (ORSS) schemes, named synthetic‐RSS, synthetic‐MRSS, and synthetic‐ORSS charts, respectively. Average run lengths are used to evaluate the performances of the control charts. It is found that the synthetic‐RSS and synthetic‐MRSS mean charts perform uniformly better than the Shewhart mean chart based on simple random sampling (Shewhart‐SRS), synthetic‐SRS, double sampling‐SRS, Shewhart‐RSS, and Shewhart‐MRSS mean charts. The proposed synthetic charts generally outperform the exponentially weighted moving average (EWMA) chart based on SRS in the detection of large mean shifts. We also compare the performance of the synthetic‐ORSS dispersion chart with the existing powerful dispersion charts. It turns out that the synthetic‐ORSS chart also performs uniformly better than the Shewhart‐R, Shewhart‐S, synthetic‐R, synthetic‐S, synthetic‐D, cumulative sum (CUSUM) ln S², CUSUM‐R, CUSUM‐S, EWMA‐ln S², and change point CUSUM charts for detecting increases in the process dispersion. A similar trend is observed when the proposed synthetic charts are constructed under imperfect RSS schemes. Illustrative examples are used to demonstrate the implementation of the proposed synthetic charts. Copyright © 2014 John Wiley & Sons, Ltd.     

An Improved Maximum Exponentially Weighted Moving Average Control Chart for Monitoring Process Mean and Variability

Maximum exponentially weighted moving average (MaxEWMA) control charts have gained considerable attention for detecting changes in both process mean and process variability. In this paper, we propose an improved MaxEWMA control charts based on ordered ranked set sampling (ORSS) and ordered imperfect ranked set sampling (OIRSS) schemes for simultaneous detection of both increases and decreases in the process mean and/or variability, named MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts. These MaxEWMA control charts are based on the best linear unbiased estimators of location and scale parameters obtained under ORSS and OIRSS methods. Extensive Monte Carlo simulations have been used to estimate the average run length and standard deviation of run length of the proposed MaxEWMA control charts. These control charts are compared with their counterparts based on simple random sampling (SRS), that is, MaxEWMA‐SRS and MaxGWMA‐SRS control charts. The proposed MaxEWMA‐ORSS and MaxEWMA‐OIRSS control charts are able to perform better than the MaxEWMA‐SRS and MaxGWMA‐SRS control charts for detecting shifts in the process mean and dispersion. An application to real data is provided to illustrate the implementation of the proposed MaxEWMA control charts. Copyright © 2013 John Wiley & Sons, Ltd.