PDDRA: A new pre-fetching based dynamic data replication algorithm in data grids

In recent years, grid technology has had such a fast growth that it has been used in many scientific experiments and research centers. A large number of storage elements and computational resources are combined to generate a grid which gives us shared access to extra computing power. In particular, data grid deals with data intensive applications and provides intensive resources across widely distributed communities. Data replication is an efficient way for distributing replicas among the data grids, making it possible to access similar data in different locations of the data grid. Replication reduces data access time and improves the performance of the system. In this paper, we propose a new dynamic data replication algorithm named PDDRA that optimizes the traditional algorithms. Our proposed algorithm is based on an assumption: members in a VO (Virtual Organization) have similar interests in files. Based on this assumption and also file access history, PDDRA predicts future needs of grid sites and pre-fetches a sequence of files to the requester grid site, so the next time that this site needs a file, it will be locally available. This will considerably reduce access latency, response time and bandwidth consumption. PDDRA consists of three phases: storing file access patterns, requesting a file and performing replication and pre-fetching and replacement. The algorithm was tested using a grid simulator, OptorSim developed by European Data Grid projects. The simulation results show that our proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, effective network usage, total number of replications, hit ratio and percentage of storage filled.     

Genetic application in a facility location problem with random demand within queuing framework

In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idle-time percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed methodology.     

Inhibition effect of a synthesized N, N＇-bis（2-hydroxybenzaldehyde）- 1, 3-propandiimine on corrosion of mild steel in HC1

The corrosion inhibition of mild steel in 1 mol/L HCl by N, N′-bis (2-hydroxybenzaldehyde)-1, 3-propandiimine (2-HBP) has been investigated by using potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and chronoamperometry measurements. The experimental results suggest that this compound is an excellent corrosion inhibitor for mild steel and the inhibition efficiency increases with the increase in inhibitor concentration. Polarization curves reveal that this organic compound is a mixed type inhibitor. The effect of temperature on the corrosion behavior of mild steel with the addition of the Schiff base was studied in the temperature range from 25℃ to 65℃. The experimentally obtained adsorption isotherms follow the Langmuir equation. Activation and thermodynamic adsorption parameters such as E a , ΔH, ΔS, K ads and ΔG ads were calculated by the corrosion currents at different temperatures and using the adsorption isotherm. The morphology of mild steel surface in the absence and presence of 2-HBP was examined by atomic force microscope (AFM) images.     

Classification of non-alcoholic beer based on aftertaste sensory evaluation by chemometric tools

Sensory evaluation is the application of knowledge and skills derived from several different scientific and technical disciplines, physiology, chemistry, mathematics and statistics, human behavior, and knowledge about product preparation practices. This research was aimed to evaluate aftertaste sensory attributes of commercial non-alcoholic beer brands (P1, P2, P3, P4, P5, P6, P7) by several chemometric tools. These attributes were bitter, sour, sweet, fruity, liquorice, artificial, body, intensity and duration. The results showed that the data are in a good consistency. Therefore, the brands were statistically classified in several categories. Linear techniques as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were performed over the data that revealed all types of beer are well separated except a partial overlapping between zones corresponding to P4, P6 and P7. In this research, for the confirmation of the groups observed in PCA and in order to calculate the errors in calibration and in validation, PLS-DA technique was used. Based on the quantitative data of PLS-DA, the classification accuracy values were ranked within 49-86%. Moreover, it was found that the classification accuracy of LDA was much better than PCA. It shows that this trained sensory panel can discriminate among the samples except an overlapping between two types of beer. Also, two types of artificial networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Back Propagation (BP) learning method. The highest classification success rate (correct predicted number over total number of measurements) of about 97% was obtained for RBF followed by 94% for BP. The results obtained in this study could be used as a reference for electronic nose and electronic tongue in beer quality control.     

A Study of the Effect of Aluminium on the Mechanochemical Reduction of Hematite by Graphite

The effect of addition of small amounts of aluminium on mechano‐chemical reduction of hematite by graphite was studied. Various amounts of aluminium (0 to 10%) were added to a hematite‐graphite mixture, in which C/O ratio was 1:1. The hematite‐graphite‐aluminium mixtures were then subjected to ball milling followed by heating up reduction. The heating up reduction was carried out in Ar atmosphere, using TG‐DTA device. In TG‐DTA experiments, samples were heated by a constant heating rate of 10 °C/min from room temperature up to 1100 °C and maintained for 30 minutes at this temperature. To clarify the reactions which took place during milling and heating up reduction, the samples were subjected to XRD examinations. It was found that the heat generated during exothermic reaction of aluminothermic reduction of hematite promoted the endothermic reaction of carbothermic reduction. In the course of heating up reduction, the carbothermic reaction occurred just after aluminothermic reaction. Increasing of aluminum content from 0 to 10% in 2 hours ball milled samples decreased the temperature of carbothermic reaction from 1020 °C to about 860 °C. The further ball milling of the samples up to 5 and 10 hours, for the samples containing 10 and 5% aluminium respectively, caused the decrease of the temperature of aluminothermic and carbothermic reactions to around the melting point of aluminium.     

Design, manufacture and evaluation of a new and simple mechanism for transmission of power between intersecting shafts up to 135 degrees (Persian Joint)

This paper introduces a new mechanism which is designed for the transmission of power between two intersecting shafts. The mechanism consists of one drive shaft and one driven shaft, six guide arms, and three connecting arms. The intersecting angle between the input shaft and the output shaft can be varied up to 135° while the velocity ratio between the two shafts remains constant. The research also includes a kinematic analysis and a simulation using Visual NASTRAN, Autodesk Inventor Dynamic and COSMOS Motion. The softwares showed that this mechanism can transmit constant velocity ratios at all angles between two shafts. By comparing the graphs of analytical analysis and simulation analysis, validity of equations was proved. Finally, by fabrication and evaluation of the mechanism it was shown that this mechanism can transmit constant velocity practically.     

Integrated Fuzzy DEA-ANFIS to Measure the Success Effect of Human Resource Spirituality

Workplace spirituality has gained attention as it is proven to be a contributor to organizational performance improvement. This paper aims to assess the impact of human resource spirituality on the success of organizational strategic change projects. The success of the projects is measured by the well-known criterion of deviation from the planned budget cost. Data collection is based on a questionnaire survey of 252 personnel in 36 large and medium-scale organizational change projects in power industry. The paper proposes an integrated algorithm of fuzzy data envelopment analysis (FDEA) and adaptive network-based fuzzy inference system (ANFIS) for measuring the pure effect of human resource spirituality on the success of organizational change projects in the power industry. It also achieves a verified tool capable of addressing complexity, nonlinearity, ambiguity, and fuzziness for measuring spirituality of human resources in the projects. Results show that spirituality of the project team has a significant effect on project success.     

Effect of Iron sulfate as electrolyte additive on plasma electrolytic oxidation of aluminum alloy

This study has been carried out to investigate the incorporation of Iron(II) sulfate as an additive of electrolyte on formed AA1010 aluminum alloy, using plasma electrolytic oxidation method in silicate-based electrolytes containing Iron(II) sulfate. In order to fabricate nanocomposite coating, silicon nitride nanopowder was added to electrolyte. The effects of iron(II) sulfate additive on the voltage-time trend, microstructure, compositions, wear, and corrosion resistances of PEO coatings were investigated. In addition, current density and concentration of additive were studied as parameters that were effective on coating. Results showed that although FeSO₄ enters to the coating structure, but it does not develop a new phase. The corrosion and wear behavior of coated samples with FeSO₄ indicate an improvement as compared to those without additive.