Search results for: Statistical Performance.

Authors: Filiz Ersoz, Taner Ersoz, Tugrul Bayraktar

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Renewable energy is referred to as "clean energy" and common popular support for the use of renewable energy (RE) is to provide electricity with zero carbon dioxide emissions. This study provides useful insight into the European Union (EU) RE, especially, into electricity generation obtained from renewables, and their targets. The objective of this study is to identify groups of European countries, using multivariate statistical analysis and selected indicators. The hierarchical clustering method is used to decide the number of clusters for EU countries. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method and squared Euclidean distances. Hierarchical cluster analysis identified eight distinct clusters of European countries. Then, non-hierarchical clustering (k-means) method was applied. Discriminant analysis was used to determine the validity of the results with data normalized by Z score transformation. To explore the relationship between the selected indicators, correlation coefficients were computed. The results of the study reveal the current situation of RE in European Union Member States.

Keywords: Share of electricity generation, CO2 emission, targets, multivariate methods, hierarchical clustering, K-means clustering, discriminant analyzed, correlation, EU member countries.

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Authors: Seyed Habib A. Rahmati, Arash Haji Karimi, Reza Saffari, Zeeya Rashvand

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An important official knowledge in each country is to have a comprehensive knowledge about markets of each group of products. Drink markets are one the most important markets of each country as a sub-group of nourishment markets. This paper is going to study these markets in Iran. To do so, first, two drink products are selected as pilot, including milk and concentrate. Then, for each product, two groups of information are estimated for the last five years, including 1) total consumption (demand) and 2) total production. Finally, the two groups of productions are compared statistically by means of two statistical tests called t test and Mann- Whitney test. The implemented Different related tables and figures are also illustrated to show the method more explicitly.

Keywords: Market evaluation, Drink, Estimation, Mann- Whitney test

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Authors: Supattra Kanchanopast

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The purpose of this paper was to study motivation factors affecting job performance effectiveness. This paper drew upon data collected from an Internal Audit Staffs of Internal Audit Line of Head Office of Krung Thai Public Company Limited. Statistics used included frequency, percentage, mean and standard deviation, t-test, and one-way ANOVA test. The finding revealed that the majority of the respondents were female of 46 years of age and over, married and live together, hold a bachelor degree, with an average monthly income over 70,001 Baht. The majority of respondents had over 15 years of work experience. They generally had high working motivation as well as high job performance effectiveness. The hypotheses testing disclosed that employees with different working status had different level of job performance effectiveness at a 0.01 level of significance. Working motivation factors had an effect on job performance in the same direction with high level. Individual working motivation included working completion, reorganization, working progression, working characteristic, opportunity, responsibility, management policy, supervision, relationship with their superior, relationship with co-worker, working position, working stability, safety, privacy, working conditions, and payment. All of these factors related to job performance effectiveness in the same direction with medium level.

Keywords: Internal Audit Staffs, Job Performance Effectiveness, Working Motivation.

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Authors: Jana Kaděrová, Miroslav Vořechovský

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The presented paper copes with an experimental evaluation of a model based on modified Weibull size effect theory. Classical statistical Weibull theory was modified by introducing a new parameter (correlation length lp) representing the spatial autocorrelation of a random mechanical properties of material. This size effect modification was observed on two different materials used in civil engineering: unreinforced (plain) concrete and multi-filament yarns made of alkaliresistant (AR) glass which are used for textile-reinforced concrete. The behavior under flexural, resp. tensile loading was investigated by laboratory experiments. A high number of specimens of different sizes was tested to obtain statistically significant data which were subsequently corrected and statistically processed. Due to a distortion of the measured displacements caused by the unstiff experiment device, only the maximal load values were statistically evaluated. Results of the experiments showed a decreasing strength with an increasing sample length. Size effect curves were obtained and the correlation length was fitted according to measured data. Results did not exclude the existence of the proposed new parameter lp.

Keywords: Statistical size effect, concrete, multi filaments yarns, experiment, autocorrelation length.

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Authors: Hyung Jong Ko, Kyoung Hoon Kim

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In this study thermodynamic performance analysis of a combined organic Rankine cycle and ejector refrigeration cycle is carried out for use of low-grade heat source in the form of sensible energy. Special attention is paid to the effects of system parameters including the turbine inlet temperature and turbine inlet pressure on the characteristics of the system such as ratios of mass flow rate, net work production, and refrigeration capacity as well as the coefficient of performance and exergy efficiency of the system. Results show that for a given source the coefficient of performance increases with increasing of the turbine inlet pressure. However, the exergy efficiency has an optimal condition with respect to the turbine inlet pressure.

Keywords: Coefficient of performance, ejector refrigeration cycle, exergy efficiency, low-grade energy, organic rankine cycle.

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Authors: Thomas Jin-Chee Liu, Yu-Shen Chen

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Using the numerical and experimental methods, this paper discusses some primary studies on the vibration and cooling performances of the piezoelectric cooling fan with the rectangular blade. When the fan works at its natural frequency, the vibrating displacement is largest and the cooling performance is best. Due to the vibration behavior, the cooling performance is affected by the geometry, material property, and working frequency of the piezoelectric cooling fan. 

Keywords: Piezoelectric cooling fan, finite element, vibration, natural frequency.

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Authors: Mohd. Hasan, Ajmal Kafeel, S. D. Pable

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Ultra-low-power (ULP) circuits have received widespread attention due to the rapid growth of biomedical applications and Battery-less Electronics. Subthreshold region of transistor operation is used in ULP circuits. Major research challenge in the subthreshold operating region is to extract the ULP benefits with minimal degradation in speed and robustness. Process, Voltage and Temperature (PVT) variations significantly affect the performance of subthreshold circuits. Designed performance parameters of ULP circuits may vary largely due to temperature variations. Hence, this paper investigates the effect of temperature variation on device and circuit performance parameters at different biasing voltages in the subthreshold region. Simulation results clearly demonstrate that in deep subthreshold and near threshold voltage regions, performance parameters are significantly affected whereas in moderate subthreshold region, subthreshold circuits are more immune to temperature variations. This establishes that moderate subthreshold region is ideal for temperature immune circuits.

Keywords: Subthreshold, temperature variations, ultralow power.

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Authors: Amiel Satvedi, Richard Pyne

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Injuries in professional sports occur on a regular basis. Some may be minor while others can cause huge impact on a player’s career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player’s number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: Injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer.

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Authors: A. Sharma, R. Tewari, S. K. Soni

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Biofuels production has come forth as a future technology to combat the problem of depleting fossil fuels. Bio-based ethanol production from enzymatic lignocellulosic biomass degradation serves an efficient method and catching the eye of scientific community. High cost of the enzyme is the major obstacle in preventing the commercialization of this process. Thus main objective of the present study was to optimize composition of medium components for enhancing cellulase production by newly isolated strain of Bacillus tequilensis. Nineteen factors were taken into account using statistical Plackett-Burman Design. The significant variables influencing the cellulose production were further employed in statistical Response Surface Methodology using Central Composite Design for maximizing cellulase production. The optimum medium composition for cellulase production was: peptone (4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L), Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride (0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at 37oC. Analysis of variance (ANOVA) revealed high coefficient of determination (R2) of 0.99. Maximum cellulase productivity of 11.5 IU/ml was observed against the model predicted value of 13 IU/ml. This was found to be optimally active at 60oC and pH 5.5.

Keywords: Bacillus tequilensis, CMCase, Submerged Fermentation, Optimization, Plackett-Burman Design, Response Surface Methodology.

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Authors: Micheli Anna Paola, Intrisano Carmelo, Calce Anna Maria

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This research focused on the capability of health tourism to improve the economic and financial performance of healthcare companies. It is assumed that health tourism companies have better profitability and financial efficiency because they can also count on cross-border demand differently from no health tourism companies. A three-level gap analysis was conducted: the first concerns health tourism companies located in Italy and in the other EU28 states; in the second Italian and EU28, no health tourism companies were compared; the third level is about the Italian system with a comparison between health tourism and no health tourism companies. Findings highlighted that Italian healthcare companies have better profitability performance if compared to European ones, but they present weaknesses in the financial position given the illiquidity and excessive leverage. Furthermore, studying the Italian system, we found that health tourism companies are more profitable than no health tourism companies.

Keywords: Financial performance, gap analysis, health tourism, profitability performance, value creation.

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Authors: Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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The aim of this study is to determine the impact of metacognition on top management team members and firm performance based on full team integration. A survey of 1500 small to medium enterprises (SMEs) was initiated and 140 firms were obtained in this study (with response rate of 9%). The result showed that different metacognitive abilities of managers [knowledge and experience] could enhance team decision-making and problem solving, resulting in greater firm performance. This is a significant finding for SMEs because these organisations have small teams with owner leadership and entrepreneurial orientation.

Keywords: Metacognition, behavioural integration, top management team, performance.

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Authors: T. Mathumathi, S. Ganesh, R. Gunabalan

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This work presents an approach for AC load flow based centralized model for congestion management in the forward markets. In this model, transaction maximizes its profit under the limits of transmission line capacities allocated by Independent System Operator (ISO). The voltage and reactive power impact of the system are also incorporated in this model. Genetic algorithm is used to solve centralized congestion management problem for multilateral transactions. Results obtained for centralized model using genetic algorithm is compared with Sequential Quadratic Programming (SQP) technique. The statistical performances of various algorithms such as best, worst, mean and standard deviations of social welfare are given. Simulation results clearly demonstrate the better performance of genetic algorithm over SQP.

Keywords: Congestion management, Genetic algorithm, Sequential quadratic programming.

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Authors: Seo Young Kim, Toshimitsu Hamasaki

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Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.

Keywords: Gene expression, clustering, data preprocessing.

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Authors: Anita S. Gangal, P. K. Kalra, D. S. Chauhan

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The backpropagation algorithm in general employs quadratic error function. In fact, most of the problems that involve minimization employ the Quadratic error function. With alternative error functions the performance of the optimization scheme can be improved. The new error functions help in suppressing the ill-effects of the outliers and have shown good performance to noise. In this paper we have tried to evaluate and compare the relative performance of complex valued neural network using different error functions. During first simulation for complex XOR gate it is observed that some error functions like Absolute error, Cauchy error function can replace Quadratic error function. In the second simulation it is observed that for some error functions the performance of the complex valued neural network depends on the architecture of the network whereas with few other error functions convergence speed of the network is independent of architecture of the neural network.

Keywords: Complex backpropagation algorithm, complex errorfunctions, complex valued neural network, split activation function.

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Authors: Sylvester A. Aye, Philippus S. Heyns

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The effect of the rotational speed and axial torque on the diagnostics of tapered rolling element bearing defects was investigated. The accelerometer was mounted on the bearing housing and connected to Sound and Vibration Analyzer (SVAN 958) and was used to measure the accelerations from the bearing housing. The data obtained from the bearing was processed to detect damage of the bearing using statistical tools and the results were subsequently analyzed to see if bearing damage had been captured. From this study it can be seen that damage is more evident when the bearing is loaded. Also, at the incipient stage of damage the crest factor and kurtosis values are high but as time progresses the crest factors and kurtosis values decrease whereas the peak and RMS values are low at the incipient stage but increase with damage.

Keywords: crest factor, damage detection, kurtosis, RMS, tapered roller bearing.

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Authors: Ntantos P.N, Karpouzos D.K

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In this paper, a benchmarking framework is presented for the performance assessment of irrigations systems. Firstly, a data envelopment analysis (DEA) is applied to measure the technical efficiency of irrigation systems. This method, based on linear programming, aims to determine a consistent efficiency ranking of irrigation systems in which known inputs, such as water volume supplied and total irrigated area, and a given output corresponding to the total value of irrigation production are taken into account simultaneously. Secondly, in order to examine the irrigation efficiency in more detail, a cross – system comparison is elaborated using a performance indicators set selected by IWMI. The above methodologies were applied in Thessaloniki plain, located in Northern Greece while the results of the application are presented and discussed. The conjunctive use of DEA and performance indicators seems to be a very useful tool for efficiency assessment and identification of best practices in irrigation systems management.

Keywords: Benchmarking, D.E.A, Performance Indicators, Irrigation systems.

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Authors: R. Rajeswari, N. Kamaraj

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In this paper, Wavelet based ANFIS for finding inter turn fault of generator is proposed. The detector uniquely responds to the winding inter turn fault with remarkably high sensitivity. Discrimination of different percentage of winding affected by inter turn fault is provided via ANFIS having an Eight dimensional input vector. This input vector is obtained from features extracted from DWT of inter turn faulty current leaving the generator phase winding. Training data for ANFIS are generated via a simulation of generator with inter turn fault using MATLAB. The proposed algorithm using ANFIS is giving satisfied performance than ANN with selected statistical data of decomposed levels of faulty current.

Keywords: Winding InterTurn fault, ANN, ANFIS, and DWT.

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Authors: Hsiu-Pi Lin, Wen-Chen Huang, Hui-Fang Chen, Yan-Pin Ke

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Corporate Social Responsibility (CSR) has become a new trend of business governance. Few research studies on CSR published in Taiwanese academia, especially for medical settings, we were interested in probing the relationship of CSR and financial performance in medical settings in Taiwan. The results illustrate that: (1) a time delay effect exists with a lag between CSR effort and its performance in the hospital foundation, (2) input into the internal domains of CSR will be helpful to improve employee productivity in the hospital foundation, and (3) input into the external domains of CSR will be helpful in improving financial performance in the hospital foundation. This study overviews CSR in the medical industry in Taiwan and the relationship of CSR and financial performance. Discussions of possible implications from the study results are applied to consult the CSR concept that will be transferred into a business strategy for the organization manager.

Keywords: Corporate Social Responsibility (CSR), financialperformance, hospital foundation,

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Authors: Yaowaluck Ruampol, Suthakorn Wasupokin

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The research on the development of speaking using folk tales based on performance activities aimed to (1) study the development of speaking skill for early- childhood students, and (2) evaluate the development of speaking skill before and after speaking activities. Ten students of Kindergarten level 2, who have enrolled in the subject of the research for speaking development of semester 2 in 2013 were purposively selected as the research cohort. The research tools were lesson plans for speaking activities and pre-post test for speaking development that were approved as content validity and reliability (IOC=.66-1.00,α=0.967). The research found that the development of speaking skill of the research samples before using performance activities on folk tales in developing speaking skill was in the normal high level. Additionally, the results appeared that the preschoolers after applying speaking skill on performance activities also imaginatively created their speaking skill.

Keywords: Speaking development, folk tales, performance activities, early-childhood students.

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Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby

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This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.

Keywords: Weed crop discrimination, macrosprayer, herbicide reduction, site-specific, sprayer-boom.

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Authors: Marwah Mohsin, Thomas Beach, Alan Kwan, Mahdi Ismail

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This paper describes the differences in views on sustainable development between the general public and experts in a developing country, Iraq. This paper will answer the question: How do the views of the public differ from the generally accepted view of experts in the context of sustainable urban development in Iraq? In order to answer this question, the views of both the public and the experts will be analysed. These results are taken from a public survey and a Delphi questionnaire. These will be analysed using statistical methods in order to identify the significant differences. This will enable investigation of the different perceptions between the public perceptions and the experts’ views towards urban sustainable development factors. This is important due to the fact that different viewpoints between policy-makers and the public will impact on the acceptance by the public of any future sustainable development work that is undertaken. The brief findings of the statistical analysis show that the views of both the public and the experts are considered different in most of the variables except six variables show no differences. Those variables are ‘The importance of establishing sustainable cities in Iraq’, ‘Mitigate traffic congestion’, ‘Waste recycling and separating’, ‘Use wastewater recycling’, ‘Parks and green spaces’, and ‘Promote investment’.

Keywords: Urban sustainable development, experts’ views, public views, statistical analysis.

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Authors: Doaa Hegazy, Joachim Denzler

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SoftBoost is a recently presented boosting algorithm, which trades off the size of achieved classification margin and generalization performance. This paper presents a performance evaluation of SoftBoost algorithm on the generic object recognition problem. An appearance-based generic object recognition model is used. The evaluation experiments are performed using a difficult object recognition benchmark. An assessment with respect to different degrees of label noise as well as a comparison to the well known AdaBoost algorithm is performed. The obtained results reveal that SoftBoost is encouraged to be used in cases when the training data is known to have a high degree of noise. Otherwise, using Adaboost can achieve better performance.

Keywords: SoftBoost algorithm, AdaBoost algorithm, Generic object recognition.

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Authors: Partha Banerjee, Aritra Acharyya, Arindam Biswas, A. K. Bhattacharjee, Amit Banerjee, Hiroshi Inokawa

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The effect of magnetic field on the noise performance of the magnetic field tunable avalanche transit time (MAGTATT) device based on Si, designed to operate at W-band (75 – 110 GHz), has been studied in this paper. A comprehensive two-dimensional (2D) model has been developed. The simulation results show that due to the presence of applied external transverse magnetic field, both the noise spectral density and noise measure of the MAGTATT device increase significantly. The noise performance of the device has been found to be further deteriorated if the magnetic field strength is further increased. Hence, in order to achieve the magnetic field tuning of the radio frequency (RF) properties of impact avalanche transit time (IMPATT) source, the noise performance of it has to be sacrificed in fair extent. Moreover, it clearly indicates that an IMPATT source must be covered with appropriate magnetic shielding material to avoid undesirable shift in operating frequency and output power and objectionable amount of deterioration in noise performance due to the presence of external magnetic field.

Keywords: 2-D model, IMPATT, MAGTATT, mm-wave, noise performance.

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Authors: S. Visetpotjanakit, N. Nakkaew

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Determination of ⁹⁰Sr in environmental samples has been widely developed with several radioanlytical methods and radiation measurement techniques since ⁹⁰Sr is one of the most hazardous radionuclides produced from nuclear reactors. Liquid extraction technique using di-(2-ethylhexyl) phosphoric acid (HDEHP) to separate and purify ⁹⁰Y and Cherenkov counting using liquid scintillation counter to determine ⁹⁰Y in secular equilibrium to ⁹⁰Sr was developed and performed at our institute, the Office of Atoms for Peace. The approach is inexpensive, non-laborious, and fast to analyse ⁹⁰Sr in environmental samples. To validate our analytical performance for the accurate and precise criteria, determination of ⁹⁰Sr using the IAEA-TEL-2016-04 ALMERA proficiency test samples were performed for statistical evaluation. The experiment used two spiked tap water samples and one naturally contaminated spruce needles sample from Austria collected shortly after the Chernobyl accident. Results showed that all three analyses were successfully passed in terms of both accuracy and precision criteria, obtaining “Accepted” statuses. The two water samples obtained the measured results of 15.54 Bq/kg and 19.76 Bq/kg, which had relative bias 5.68% and -3.63% for the Maximum Acceptable Relative Bias (MARB) 15% and 20%, respectively. And the spruce needles sample obtained the measured results of 21.04 Bq/kg, which had relative bias 23.78% for the MARB 30%. These results confirm our analytical performance of ⁹⁰Sr determination in water and spruce needles samples using the same developed method.

Keywords: ALMERA proficiency test, Cherenkov counting, determination of 90Sr, environmental samples.

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Authors: Ssu-Han Chen, Der-Baau Perng

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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded,defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: Molding surface, machine vision, statistical texture, discrete Fourier transformation.

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Authors: Roshayani Arshad, Suaini Othman, Rohana Othman

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This study examines the effect of Islamic Corporate Social Responsibility disclosure and on corporate reputation as well as performance. These relationships are examined based on content analysis of of annual reports of 17 Islamic banks in Malaysia for 2008, 2009 and 2010. Results of this study provide evidence that CSR activities communicated in corporate annual reports are significantly positively related with corporate reputation as well as firm performance. These results indicate that CSR activities and disclosure from Islamic perspectives are equally important business strategies in creating continuous superior performance for organisations. In addition, it also highlights that organisations need to develop a stakeholder orientation particularly in an environment of increasing pressure from jurisdictions dominated by Islamic stakeholders on organisations engaging in Islamic products to increase their social responsibilities from the Islamic perspectives.

Keywords: Islamic Corporate Social Responsibility, Corporate Reputation, Firm Performance, Islamic Banks

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Authors: Galal Elkobrosy, Amr M. Abdelrazek, Bassuny M. Elsouhily, Mohamed E. Khidr

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Crank shaft length, connecting rod length, crank angle, engine rpm, cylinder bore, mass of piston and compression ratio are the inputs that can control the performance of the slider crank mechanism and then its efficiency. Several combinations of these seven inputs are used and compared. The throughput engine torque predicted by the simulation is analyzed through two different regression models, with and without interaction terms, developed according to multi-linear regression using LU decomposition to solve system of algebraic equations. These models are validated. A regression model in seven inputs including their interaction terms lowered the polynomial degree from 3^rd degree to 1^st degree and suggested valid predictions and stable explanations.

Keywords: Design of experiments, regression analysis, SI Engine, statistical modeling.

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Authors: Cesar H. Ortega Jimenez, Ignacio Eguia Salinas, Pedro Garrido Vega, Jose A. Dominguez Machuca

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The aim of this study is to identify the conditions of implementation for reconfigurability in summarizing past flexible manufacturing systems (FMS) research by drawing overall conclusions from many separate High Performance Manufacturing (HPM) studies. Meta-analysis will be applied to links between HPM programs and their practices related to FMS and manufacturing performance with particular reference to responsiveness performance. More specifically, an application of meta-analysis will be made with reference to two of the main steps towards the development of an empirically-tested theory: testing the adequacy of the measurement of variables and testing the linkages between the variables.

Keywords: FMS (flexible manufacturing system), HPM (highperformance manufacturing), reconfigurability, RMS (reconfigurablemanufacturing system), responsiveness

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Authors: Kwangho Cha, Hyeyoung Cho, Sungho Kim

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As many scientific applications require large data processing, the importance of parallel I/O has been increasingly recognized. Collective I/O is one of the considerable features of parallel I/O and enables application programmers to easily handle their large data volume. In this paper we measured and analyzed the performance of original collective I/O and the subgroup method, the way of using collective I/O of MPI effectively. From the experimental results, we found that the subgroup method showed good performance with small data size.

Keywords: Collective I/O, MPI, parallel file system.

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Authors: Luminita Dumitriu, Cristina Segal, Marian Craciun, Adina Cocu, Lucian P. Georgescu

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There are several approaches in trying to solve the Quantitative 1Structure-Activity Relationship (QSAR) problem. These approaches are based either on statistical methods or on predictive data mining. Among the statistical methods, one should consider regression analysis, pattern recognition (such as cluster analysis, factor analysis and principal components analysis) or partial least squares. Predictive data mining techniques use either neural networks, or genetic programming, or neuro-fuzzy knowledge. These approaches have a low explanatory capability or non at all. This paper attempts to establish a new approach in solving QSAR problems using descriptive data mining. This way, the relationship between the chemical properties and the activity of a substance would be comprehensibly modeled.

Keywords: association rules, classification, data mining, Quantitative Structure - Activity Relationship.

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