Design of Gravity Dam by Genetic Algorithms

The design of a gravity dam is performed through an interactive process involving a preliminary layout of the structure followed by a stability and stress analysis. This study presents a method to define the optimal top width of gravity dam with genetic algorithm. To solve the optimization task (minimize the cost of the dam), an optimization routine based on genetic algorithms (GAs) was implemented into an Excel spreadsheet. It was found to perform well and GA parameters were optimized in a parametric study. Using the parameters found in the parametric study, the top width of gravity dam optimization was performed and compared to a gradient-based optimization method (classic method). The accuracy of the results was within close proximity. In optimum dam cross section, the ratio of is dam base to dam height is almost equal to 0.85, and ratio of dam top width to dam height is almost equal to 0.13. The computerized methodology may provide the help for computation of the optimal top width for a wide range of height of a gravity dam.

Esterification of Free Fatty Acids in Crude Palm Oil Using Alumina-Doped Sulfated Tin Oxide as a Catalyst

The conventional production of biodiesel from crude palm oil which contains large amounts of free fatty acids in the presence of a homogeneous base catalyst confronts the problems of soap formation and very low yield of biodiesel. To overcome these problems, free fatty acids must be esterified to their esters in the presence of an acid catalyst prior to alkaline-catalyzed transesterification. Sulfated metal oxides are a promising group of catalysts due to their very high acidity. In this research, aluminadoped sulfated tin oxide (SO4 2-/Al2O3-SnO2) catalysts were prepared and used for esterification of free fatty acids in crude palm oil in a batch reactor. The SO4 2-/Al2O3-SnO2 catalysts were prepared from different Al precursors. The results showed that different Al precursors gave different activities of the SO4 2-/Al2O3-SnO2 catalysts. The esterification of free fatty acids in crude palm oil with methanol in the presence of SO4 2-/Al2O3-SnO2 catalysts followed first-order kinetics.

Identification of Industrial Health Using ANN

The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.

Regionalism and Regionalization in Central Asia

This article is dedicated to the question of regionalism and regionalization in contemporary international relations, with a specific focus on Central Asia. The article addresses the question of whether or not Central Asia can be referred to as a true geopolitical region. In addressing this question, the authors examine particular factors that are essential for the formation of a region, including those tied to the economy, energy, culture, and labor migration.

Quality Assurance and Effectiveness in Kurdistan Higher Education: The Reform Process

Implementing quality assurance in higher education establishments is the main focus of the reform process currently undertaken by the Ministry of Higher Education and Scientific Research in the Kurdistan Region of Iraq. The reform agenda has involved attempts to improve academic quality and management processes in universities, technical institutions and colleges. The central challenge for the reform process is to produce change in higher education in a region where administration is described as centralized and bureaucratic. To make these changes, there should be a well-designed plans and follow up processes in order to monitor progress and develop responses to obstacles. Lack of skills, resources, political dilemmas, poor motivation, and readiness to face the consequences of change are factors which will determine the success of the reform process.

Weighted k-Nearest-Neighbor Techniques for High Throughput Screening Data

The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.

Deposition Rate and Energy Enhancements of TiN Thin-Film in a Magnetized Sheet Plasma Source

Titanium nitride (TiN) has been synthesized using the sheet plasma negative ion source (SPNIS). The parameters used for its effective synthesis has been determined from previous experiments and studies. In this study, further enhancement of the deposition rate of TiN synthesis and advancement of the SPNIS operation is presented. This is primarily achieved by the addition of Sm-Co permanent magnets and a modification of the configuration in the TiN deposition process. The magnetic enhancement is aimed at optimizing the sputtering rate and the sputtering yield of the process. The Sm-Co permanent magnets are placed below the Ti target for better sputtering by argon. The Ti target is biased from –250V to – 350V and is sputtered by Ar plasma produced at discharge current of 2.5–4A and discharge potential of 60–90V. Steel substrates of dimensions 20x20x0.5mm3 were prepared with N2:Ar volumetric ratios of 1:3, 1:5 and 1:10. Ocular inspection of samples exhibit bright gold color associated with TiN. XRD characterization confirmed the effective TiN synthesis as all samples exhibit the (200) and (311) peaks of TiN and the non-stoichiometric Ti2N (220) facet. Cross-sectional SEM results showed increase in the TiN deposition rate of up to 0.35μm/min. This doubles what was previously obtained [1]. Scanning electron micrograph results give a comparative morphological picture of the samples. Vickers hardness results gave the largest hardness value of 21.094GPa.

Grid-HPA: Predicting Resource Requirements of a Job in the Grid Computing Environment

For complete support of Quality of Service, it is better that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History" using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68% to predict CPU usage of jobs and 91.29% of memory usage and 89.80% of the band width usage.

Control of Aspergillus flavus Growth in Tomato Paste by Cinnamomum zeylanicum and Origanum vulgare L. Essential Oils

This study was conducted to evaluate the antifungal activities of Cinnamomum zeylanicum and Origanum vulgare L. essential oil against Aspergillus flavus in culture media and tomato paste. 200 ppm of cinnamon and 500 ppm of oregano completely inhibited A. flavus growth in culture media, while in tomato paste 300 ppm of cinnamon and 200 ppm of oregano had the same effect. Test panel evaluations revealed that samples with 100 and 200 ppm cinnamon were acceptable. The results may suggest the potential use of Cinnamomum zeylanicum essential oil as natural preservative in tomato paste.

Triple-input Single-output Voltage-mode Multifunction Filter Using Only Two Current Conveyors

A new voltage-mode triple-input single-output multifunction filter using only two current conveyors is presented. The proposed filter which possesses three inputs and single-output can generate all biquadratic filtering functions at the output terminal by selecting different input signal combinations. The validity of the proposed filter is verified through PSPICE simulations.

Determinants of Brand Equity: Offering a Model to Chocolate Industry

This study examined the underlying dimensions of brand equity in the chocolate industry. For this purpose, researchers developed a model to identify which factors are influential in building brand equity. The second purpose was to assess brand loyalty and brand images mediating effect between brand attitude, brand personality, brand association with brand equity. The study employed structural equation modeling to investigate the causal relationships between the dimensions of brand equity and brand equity itself. It specifically measured the way in which consumers’ perceptions of the dimensions of brand equity affected the overall brand equity evaluations. Data were collected from a sample of consumers of chocolate industry in Iran. The results of this empirical study indicate that brand loyalty and brand image are important components of brand equity in this industry. Moreover, the role of brand loyalty and brand image as mediating factors in the intention of brand equity are supported. The principal contribution of the present research is that it provides empirical evidence of the multidimensionality of consumer based brand equity, supporting Aaker´s and Keller´s conceptualization of brand equity. The present research also enriched brand equity building by incorporating the brand personality and brand image, as recommended by previous researchers. Moreover, creating the brand equity index in chocolate industry of Iran particularly is novel.

Household Demand for Solid Waste Disposal Options in Malaysia

This paper estimates the economic values of household preference for enhanced solid waste disposal services in Malaysia. The contingent valuation (CV) method estimates an average additional monthly willingness-to-pay (WTP) in solid waste management charges of Ôé¼0.77 to 0.80 for improved waste disposal services quality. The finding of a slightly higher WTP from the generic CV question than that of label-specific, further reveals a higher WTP for sanitary landfill, at Ôé¼0.90, than incineration, at Ôé¼0.63. This suggests that sanitary landfill is a more preferred alternative. The logistic regression estimation procedure reveals that household-s concern of where their rubbish is disposed, age, ownership of house, household income and format of CV question are significant factors in influencing WTP.

The Effect of Ageing on Impact Toughness and Microstructure of 2024 Al-Cu-Mg Alloy

The present study aims at determining the effect of ageing on the impact toughness and microstructure of 2024 Al-Cu - Mg alloy. Following the 2 h solutionizing treatment at 450°C and water quench, the specimens were aged at 200°C for various periods (1 to 18 h). The precipitation stages during ageing were monitored by hardness measurements. For each specimen group, Charpy impact and hardness tests were carried out. During ageing the impact toughness of the alloy first increased, and then, following a maxima decreased due to the precipitation of intermediate phases, finally it reached its minimum at the peak hardness. Correlations between hardness and impact toughness were investigated.

Restriction Specificity of Some Soybean Genotypes to Bradyrhizobium japonicum Serogrous

Competitive relationships among Bradyrhizobium japonicum USDA serogroup 123, 122 and 138 were screened versus the standard commercial soybean variety Williams and two introductions P1 377578 "671" in a field trial. Displacement of strain 123 by an effective strain should improved N2 fixation. Root nodules were collected and strain occupancy percentage was determined using strain specific fluorescent antibodies technique. As anticipated the strain USDA 123 dominated 92% of nodules due to the high affinity between the host and the symbiont. This dominance was consistent and not changed materially either by inoculation practice or by introducing new strainan. The interrelationship between the genotype Williams and serogroup 122 & 138 was found very weak although the cell density of the strain in the rhizosphere area was equal. On the other hand, the nodule occupancy of genotypes 671 and 166 with rhizobia serogroup 123 was almost diminished to zero. . The data further exhibited that the genotypes P1 671 and P1 166 have high affinity to colonize with strains 122 and 138 whereas Williams was highly promiscuous to strain 123.

Aircraft Gas Turbine Engines Technical Condition Identification System

In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Validation of Reverse Engineered Web Application Models

Web applications have become complex and crucial for many firms, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering). The scientific community has focused attention to Web application design, development, analysis, testing, by studying and proposing methodologies and tools. Static and dynamic techniques may be used to analyze existing Web applications. The use of traditional static source code analysis may be very difficult, for the presence of dynamically generated code, and for the multi-language nature of the Web. Dynamic analysis may be useful, but it has an intrinsic limitation, the low number of program executions used to extract information. Our reverse engineering analysis, used into our WAAT (Web Applications Analysis and Testing) project, applies mutational techniques in order to exploit server side execution engines to accomplish part of the dynamic analysis. This paper studies the effects of mutation source code analysis applied to Web software to build application models. Mutation-based generated models may contain more information then necessary, so we need a pruning mechanism.

A Critics Study of Neural Networks Applied to ion-Exchange Process

This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ionexchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box", and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.

Optimal Conditions for Carotenoid Production and Antioxidation Characteristics by Rhodotorula rubra

This study aims to screen out and to optimize the major nutrients for maximum carotenoid production and antioxidation characteristics by Rhodotorula rubra. It was found that supplementary of 10 g/l glucose as carbon source, 1 g/l ammonium sulfate as nitrogen source and 1 g/l yeast extract as growth factor in the medium provided the better yield of carotenoid content of 30.39 μg/g cell dry weight the amount of antioxidation of Rhodotorula rubra by DPPH, ABTS and MDA method were 1.463%, 34.21% and 34.09 μmol/l, respectively.

Impact of Loading Conditions on the Emission- Economic Dispatch

Environmental awareness and the recent environmental policies have forced many electric utilities to restructure their operational practices to account for their emission impacts. One way to accomplish this is by reformulating the traditional economic dispatch problem such that emission effects are included in the mathematical model. This paper presents a Particle Swarm Optimization (PSO) algorithm to solve the Economic- Emission Dispatch problem (EED) which gained recent attention due to the deregulation of the power industry and strict environmental regulations. The problem is formulated as a multi-objective one with two competing functions, namely economic cost and emission functions, subject to different constraints. The inequality constraints considered are the generating unit capacity limits while the equality constraint is generation-demand balance. A novel equality constraint handling mechanism is proposed in this paper. PSO algorithm is tested on a 30-bus standard test system. Results obtained show that PSO algorithm has a great potential in handling multi-objective optimization problems and is capable of capturing Pareto optimal solution set under different loading conditions.