Cost optimal scheduling in IaaS for dependent workload with particle swarm optimization

Optimizing cloud provisioning for scientific workflow applications is a challenging problem, since the workflows generally contain dependency between tasks and require specific deadlines. Usually, cloud providers offer many options to the consumers. These options include the number of virtual machines, the type of each virtual machine and the purchasing method for each machine. Currently, cloud provisioning cost optimization is an active research topic. Most of this literature is concerned with task scheduling, cloud option selection, and cloud option selection for scientific workflow applications. However, research that attempts to find solutions which cover both cloud option selection and workflow task scheduling is very limited. In this paper, we focus on optimizing the cost of purchasing infrastructure-as-a-service cloud capabilities to achieve scientific work flow execution within the specific deadlines. The proposed system considers the number of purchased instances, instance types, purchasing options, and task scheduling as constraints in an optimization process. Particle swarm optimization augmented with a variable neighborhood search technique is used to find the optimal solution. Our approach finds the configurations of purchasing options with the optimum budget for a specified workflow application based on the required performance. The solutions from the proposed system show promising performance from the perspectives of the total cost and fitness convergence when compared with other state-of-the-art algorithms.     

Cost-effective disposable thiourea film modified copper electrode for capacitive immunosensor

Cost-effective disposable electrodes were fabricated from copper clad laminate, usually used for printed circuit board (PCB) in electronic industries, by using dry film photoresist. Electro-oxidation (anodisation) was employed to obtain a good formation of thiourea film on the electrode surface. The affinity binding pair of carcinoembryonic antigen (CEA) and anti-carcinoembryonic antigen (anti-CEA) was used as a model system. Anti-CEA was immobilized on thiourea film via covalent coupling. This modified electrode was incorporated with a capacitive system for CEA analysis. This capacitive immunosensor provided a linear range between 0.01 and 10 ng ml⁻¹ with a detection limit of 10 pg ml⁻¹. When applied to analyze CEA in serum samples, the results agreed well with the enzyme linked fluorescent assay (ELFA) technique (P > 0.05). The proposed strategy for the preparation of disposable modified copper electrode is very cost effective and simple. Moreover, it provides good reproducibility. This technique can easily be applied to immobilize other biological sensing elements for biosensors development.     

Hydrophobic Zeolite‐Filled Polymeric Films with High Ethylene Permselectivity for Fresh Produce Packaging Applications

Gas permselective plastic films have been in a great deal of attention in the area of modified atmosphere packaging of fresh produces. Such films must allow transport of the respiring gases, i.e. oxygen and carbon dioxide, in a controlled manner and, moreover, should efficiently remove ethylene gas. Therefore, the development of highly permeable films with high ethylene permselectivity, i.e. high in both permeability and selectivity, was carried out. The concept of ‘mixed matrix membrane’, by which enhanced gas permselectivity can be obtained by incorporation of zeolite particles into the polymeric film, was applied. Fine particles of hydrophobic zeolites, i.e. zeolite beta and ZSM‐5, and the surface‐modified zeolites were used in this study. The films with uniform distribution of zeolite particles (10% w/w) in 70LDPE/30SEBS (styrene‐b‐(ethylene‐ran‐butylene)‐b‐styrene block copolymer) matrix can be prepared by blow film extrusion. Significantly high ethylene permselectivity, i.e. ethylene permeability of 1.78–2.67 × 10³ cm³ ? mm/m² ? day ? atm and ethylene/O₂ selectivity of 4.67–8.26, was obtained from the films containing octyl‐modified and phenyl‐modified zeolites. Particular enhancement was observed on the films containing phenyl‐modified zeolites. Crystallinity of polyethylene, transition temperatures and decomposition temperature were, however, indifferent among the studied films. Nevertheless, elongation at break and toughness of the films containing surface‐modified zeolites were superior. Particle–polymer interface could thus be improved. Copyright © 2014 John Wiley & Sons, Ltd.     

Maximum weight matching and genetic algorithm for fixed-shape facility layout problem

To achieve efficient facility design, the problem of finding an initial slicing tree of a complete graph may influence the layout solutions in many ways. We introduce a maximum weight-matching algorithm to generate the slicing tree, which is used as an initial solution. This initial solution produces modifications to generate alternative layouts for further selection. The system employs a genetic algorithm (GA) as the search engine with a relationship weight function to obtain good solutions. The model is proposed to solve a fixed-shape layout problem. The research has made contributions to two areas. First, it defines a quality function for the clustering technique to generate an initial slicing tree. Second, it designs a process for generating layout alternatives that can take predetermined location constraints and weights based on relationships among facilities into consideration. We compare our initial slicing tree GA with other approaches in the literature. In addition, computational results to demonstrate the performance characteristics of our algorithm are also evaluated.     

English-Thai Translation: Initial Experiments with a Multiphase Translation System

A multiphase machine translation approach, Generate and Repair Machine Translation (GRMT), is proposed. GRMT is designed to generate accurate translations that focus primarily on retaining the linguistic meaning of the source language sentence. GRMT presently incorporates a limited multilingual translation capability. The central idea behind the GRMT approach is to generate a translationcandidate (TC) by quick and dirty machine translation (QDMT), then investigate the accuracy of that TC by translation candidate evaluation (TCE), and, if necessary, revise the translation in the repair and iterate (RI) phase. To demonstrate the GRMT approach, a translation system that translates from English to Thai has been developed. This paper presents the design characteristics and some experimental results of QDMT and also the initial design, some experiments, and proposed ideas behind TCE and RI.     

English–Thai Structure–Based Machine Translation

We propose an alternative method of machine–aided translation: Structure–Based Machine Translation (SBMT). SBMT uses language structure matching techniques to reduce complicated grammar rules and provide efficient and feasible translation results. SBMT comprises the following four features: (1) source language input sentence analysis; (2) source language sentence transformation into target language structure; (3) dictionary lookup; and (4) semantic disambiguation or word sense disambiguation (WSD) for correct output selection. SBMT has been designed and a prototype system has been implemented that generates satisfactory translations.     

Intelligent Thai text – Thai sign translation for language learning

We present the Intelligent Thai text – Thai sign translation for language learning (IT³STL). IT³STL is able to translate Thai text into Thai sign language simply and conveniently anytime, anywhere. Thai sign language is the language of the deaf in Thailand. In the translation process, the distinction between Thai text and Thai sign language in both grammar and vocabulary are concerned in each processing step to ensure the accuracy of translation. IT³STL was designed not only to be an automatic interpreter but also to be a language tutor assistant. It provides meaning of each word and describes the structure formation and word order of the translated sentence. With IT³STL, the deaf and hearing-impaired are able to enhance their communication ability and to improve their knowledge and learning skills. Moreover IT³STL has increased motivation and opportunity for them to access multimedia and e-learning.     

Job Shop Scheduling with the Best-so-far ABC

The Job Shop Scheduling Problem (JSSP) is known as one of the most difficult scheduling problems. It is an important practical problem in the fields of production management and combinatorial optimization. Since JSSP is NP-complete, meaning that the selection of the best scheduling solution is not polynomially bounded, heuristic approaches are often considered. Inspired by the decision making capability of bee swarms in the nature, this paper proposes an effective scheduling method based on Best-so-far Artificial Bee Colony (Best-so-far ABC) for solving the JSSP. In this method, we bias the solution direction toward the Best-so-far solution rather a neighboring solution as proposed in the original ABC method. We also use the set theory to describe the mapping of our proposed method to the problem in the combinatorial optimization domain. The performance of the proposed method is then empirically assessed using 62 benchmark problems taken from the Operations Research Library (OR-Library). The solution quality is measured based on “Best”, “Average”, “Standard Deviation (S.D.)”, and “Relative Percent Error (RPE)” of the objective value. The results demonstrate that the proposed method is able to produce higher quality solutions than the current state-of-the-art heuristic-based algorithms.