Scheduling with an outsourcing option on both manufacturer and subcontractors

This paper addresses a single-stage scheduling problem with outsourcing allowed where each job can be either scheduled for in-house production or outsourced to one of the outside subcontractors available. The manufacturer has an unrelated parallel machine system, and each subcontractor has its own single machine. Subcontractors are capable to process all the jobs. Unlike most of past research, our study considers the joint scheduling of both in-house and outsourced jobs simultaneously. The objective is to minimize sum of the total weighted completion time and total outsourcing cost. An integer programming formulation is presented and then improved through an optimality property on job orders. A heuristic algorithm is also introduced to decompose the problem into smaller and easier subproblems and solve them to optimality.     

Terahertz fluorescence quantum beats in a dye solution

Time-resolved fluorescence of a dye molecule in liquid solution at room temperature, monitored with femtosecond resolution, reveals small-amplitude quantum beats with subpicosecond periods and picosecond damping. Specifically, the observation of damped ripples on the electronic fluorescence of a large dye molecule oxazine 1 (MW=324) in different liquid solvents (methanol, water) manifesting terahertz vibrational quantum beats is reported     

Estimating botnet virulence within mathematical models of botnet propagation dynamics

Mathematical models of botnet propagation dynamics are increasingly deemed to have potential for significant contribution to botnet mitigation. Botnet virulence, which comprises network vulnerability rate and network infection rate, is a key factor in those models. In this paper we discuss a practical approach that draws on epidemiological models in biology to estimate the botnet virulence in a network. Our research provides mathematical models of botnet propagation dynamics with concrete measures of botnet virulence, which make those models practical and hence employable in mitigation of real world botnets in a timely fashion. The approach is based on random sampling and follows a novel application of statistical learning and inference in a botnet-versus-network setting. We have implemented this research in the Matlab programming language. In this paper, we discuss an experimental evaluation of the effectiveness of this research with respect to botnet propagation dynamics realistically simulated in a GTNetS network simulation platform.     

Moisture and heat transfer in hybrid weft knitted fabric with artificial intelligence

One of the most important properties of clothes is their ability to help the body's thermal system to keep the body temperature in its natural range, even if the environmental conditions or physical activities are outside the body's ideal range. Perspiring is one of the most important effects of physical activities in warm weather for shedding the body's excessive heat. Therefore, the basic requirement of a fabric worn next to the skin is to transfer this moisture to the atmosphere to reach comfort through the avoidance of a feeling of wetness and clamminess and also through the generation of a situation for the best surface evaporation of moisture. The main goal of this study was to achieve a kind of fabric that guarantees comfort for the body by good heat and moisture transport. To achieve this goal, a group of double‐surface fabrics containing hydrophilic and hydrophobe fibers were knitted, and their simultaneous heat and moisture transport was evaluated with the help of a perspiration‐simulation machine; the results were analyzed as transfer process plots. Also, the transmission of heat and moisture was evaluated for all of the samples by differential modeling as an artificial neural network. Effective parameters on heat and moisture transfer were taken into consideration with modeling and statistical methods. The results were analyzed to find a suitable fabric with optimum comfort. The final results showed that a fabric made of micropolyester filaments and cotton yarns on the bottom and top surfaces, respectively, had the best heat and moisture transfer. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

[Hmim][HSO4], a Green and Recyclable Acidic Ionic Liqiud Medium for the One‐Pot Nitration of TADB to HNIW

An efficient and mild procedure for the one‐pot preparation of CL‐20 from TADB in the presence of the Brønsted acidic ionic liquid 1‐methylimidazolium hydrogen sulfate [Hmim][HSO₄] as catalyst was developed. The ionic liquid was stable during the reaction process and could also be reused several times with steady activity. In order to optimize the process parameters to obtain higher yield and purity, a study was carried out with variation of the ionic liquids and some parameters like temperature, mole ratio of [Hmim][HSO₄] and nitric acid. This procedure may be a practical alternative to the existing procedures to meet the nees of academics as well as industry.     

Statistical optimization of process conditions for photocatalytic degradation of phenol with immobilization of nano TiO<Subscript>2</Subscript> on perlite granules

Response surface methodology (RSM) using D-optimal design was applied to optimization of photocatalytic degradation of phenol by new composite nano-catalyst (TiO₂/Perlite). Effects of seven factors (initial pH, initial phenol concentration, reaction temperature, UV irradiation time, UV light intensity, catalyst calcination temperature, and dosage of TiO₂/perlite) on phenol conversion efficiency were studied and optimized by using the statistical software MODDE 8.02. On statistical analysis of the results from the experimental studies, the optimum process conditions were as follows: initial pH, 10.7; initial phenol concentration, 0.5 mM; reaction temperature, 27 °C; UV irradiation time, 6.5 h; UV light intensity, 250 W; catalyst calcination temperature, 600 °C; and TiO₂/perlite dosage, 6 g/L. Analysis of variance (ANOVA) showed a high coefficient of determination (R²) of 91.8%.     

Chemical vapor deposition of poly(3‐alkylthiophene) nanoparticles on fabric: Chemical and electrochemical characterization

Chemical vapor deposition of poly(3‐methylthiophene) and poly (3‐hexylthiophene) as conductive polymers on the surface of polyester fabrics was successfully obtained. Fourier transform infrared spectroscopy confirmed the formation of polymers on surface of fabrics (the fingerprint of polythiophenes, υ 600–1500 cm^?1). The uniformity of deposition and nanoparticles (average size of 60 nm) were proved with scanning electron microscopy. Electrochemical impedance spectroscopy showed that P3HT‐coated samples offer higher conductivity in compared to P3MT‐coated samples. The impedance modulus of P3HT‐coated samples was lowered nine times to that of row materials and reached to c8000 Ω. The samples have also shown electrochromic properties under electrical current, changing its color from yellowish green at 0 V to dark green at +12 V for poly (3‐hexylthiophene) samples and from brown at 0 V to red at +12 V for poly(3‐methylthiophene)‐coated fabrics (V = 0 V, λ = 450 nm; V = 12 V, λ = 650 nm). © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40673.