Neuro-fuzzy Model and Regression Model a Comparison Study of MRR in Electrical Discharge Machining of D2 Tool Steel

In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively

Use of Regression Analysis in Determining the Length of Plastic Hinge in Reinforced Concrete Columns

Basic objective of this study is to create a regression analysis method that can estimate the length of a plastic hinge which is an important design parameter, by making use of the outcomes of (lateral load-lateral displacement hysteretic curves) the experimental studies conducted for the reinforced square concrete columns. For this aim, 170 different square reinforced concrete column tests results have been collected from the existing literature. The parameters which are thought affecting the plastic hinge length such as crosssection properties, features of material used, axial loading level, confinement of the column, longitudinal reinforcement bars in the columns etc. have been obtained from these 170 different square reinforced concrete column tests. In the study, when determining the length of plastic hinge, using the experimental test results, a regression analysis have been separately tested and compared with each other. In addition, the outcome of mentioned methods on determination of plastic hinge length of the reinforced concrete columns has been compared to other methods available in the literature.

Forming of Institutional Mechanism of Region's Innovative Development

The regional innovative competitiveness is an integrating characteristic of the innovative sphere of the region. It depends on a big variety of different parameters connected with all kinds of economic entities- activities. But management parameters shouldn't be irregular, so in order to avoid it, an institutional system should be formed. This system should carry out strategic management of factors having the greatest influence on the region's innovative development. This article is devoted to different aspects of organization of the region's development institutional mechanism, which is based on management of regional innovative competitiveness parameters. The base of the analysis is innovatively-active Russian regions which were compared according to the level of the innovative competitiveness. After that the most important parameters of successful innovative development of the region were revealed with the help of the correlation-regression analysis. The results of the research could be used for investigation of the region's innovative policy.

Integration of Asian Stock Markets

This paper is to explore the relationship and the level of stock market integration of the Asian countries, primarily concentrating on Malaysia, Thailand, Indonesia, and South Korea, with the world from January 1997 to December 2009. The degree of short-run and long-run stock market integration of those Asian countries are analyzed in order to determine the significance of series of regional and world financial crises, liberalization policies and other financial reforms in influencing the level of stock market integration. To test for cointegration, this paper applies coefficient correlation, univariate regression analyses, cointegration tests, and vector autoregressive models (VAR) by using the four Asian stock markets main indices and the MSCI World index. The empirical findings from this work reveal that there is no long-run stock market integration for the four countries and the world market. However, there is short run integration.

A Comparison of the Nonparametric Regression Models using Smoothing Spline and Kernel Regression

This paper study about using of nonparametric models for Gross National Product data in Turkey and Stanford heart transplant data. It is discussed two nonparametric techniques called smoothing spline and kernel regression. The main goal is to compare the techniques used for prediction of the nonparametric regression models. According to the results of numerical studies, it is concluded that smoothing spline regression estimators are better than those of the kernel regression.

Space-Time Variation in Rainfall and Runoff: Upper Betwa Catchment

Among all geo-hydrological relationships, rainfallrunoff relationship is of utmost importance in any hydrological investigation and water resource planning. Spatial variation, lag time involved in obtaining areal estimates for the basin as a whole can affect the parameterization in design stage as well as in planning stage. In conventional hydrological processing of data, spatial aspect is either ignored or interpolated at sub-basin level. Temporal variation when analysed for different stages can provide clues for its spatial effectiveness. The interplay of space-time variation at pixel level can provide better understanding of basin parameters. Sustenance of design structures for different return periods and their spatial auto-correlations should be studied at different geographical scales for better management and planning of water resources. In order to understand the relative effect of spatio-temporal variation in hydrological data network, a detailed geo-hydrological analysis of Betwa river catchment falling in Lower Yamuna Basin is presented in this paper. Moreover, the exact estimates about the availability of water in the Betwa river catchment, especially in the wake of recent Betwa-Ken linkage project, need thorough scientific investigation for better planning. Therefore, an attempt in this direction is made here to analyse the existing hydrological and meteorological data with the help of SPSS, GIS and MS-EXCEL software. A comparison of spatial and temporal correlations at subcatchment level in case of upper Betwa reaches has been made to demonstrate the representativeness of rain gauges. First, flows at different locations are used to derive correlation and regression coefficients. Then, long-term normal water yield estimates based on pixel-wise regression coefficients of rainfall-runoff relationship have been mapped. The areal values obtained from these maps can definitely improve upon estimates based on point-based extrapolations or areal interpolations.

A New Composition Method of Admissible Support Vector Kernel Based on Reproducing Kernel

Kernel function, which allows the formulation of nonlinear variants of any algorithm that can be cast in terms of dot products, makes the Support Vector Machines (SVM) have been successfully applied in many fields, e.g. classification and regression. The importance of kernel has motivated many studies on its composition. It-s well-known that reproducing kernel (R.K) is a useful kernel function which possesses many properties, e.g. positive definiteness, reproducing property and composing complex R.K by simple operation. There are two popular ways to compute the R.K with explicit form. One is to construct and solve a specific differential equation with boundary value whose handicap is incapable of obtaining a unified form of R.K. The other is using a piecewise integral of the Green function associated with a differential operator L. The latter benefits the computation of a R.K with a unified explicit form and theoretical analysis, whereas there are relatively later studies and fewer practical computations. In this paper, a new algorithm for computing a R.K is presented. It can obtain the unified explicit form of R.K in general reproducing kernel Hilbert space. It avoids constructing and solving the complex differential equations manually and benefits an automatic, flexible and rigorous computation for more general RKHS. In order to validate that the R.K computed by the algorithm can be used in SVM well, some illustrative examples and a comparison between R.K and Gaussian kernel (RBF) in support vector regression are presented. The result shows that the performance of R.K is close or slightly superior to that of RBF.

Economic Factors Affecting Rice Export of Thailand

The purpose of this study was primarily assessing how important economic factors namely: The Thai export price of white rice, the exchange rate, and the world rice consumption affect the overall Thai white rice export, using historical data during the period 1989-2013 from the Thai Rice Exporters Association, and Food and Agricultural Organization of the United Nations. The co-integration method, regression analysis, and error correction model were applied to investigate the econometric model. The findings indicated that in the long-run, the world rice consumption, the exchange rate, and the Thai export price of white rice were the important factors affecting the export quantity of Thai white rice respectively, as indicated by their significant coefficients. Meanwhile, the rice export price was an important factor affecting the export quantity of Thai white rice in the short-run. This information is useful in the business, export opportunities, price competitiveness, and policymaker in Thailand.

Optimization of Enzymatic Hydrolysis of Manihot Esculenta Root Starch by Immobilizeda-Amylase Using Response Surface Methodology

Enzymatic hydrolysis of starch from natural sources finds potential application in commercial production of alcoholic beverage and bioethanol. In this study the effect of starch concentration, temperature, time and enzyme concentration were studied and optimized for hydrolysis of cassava (Manihot esculenta) starch powder (of mesh 80/120) into glucose syrup by immobilized (using Polyacrylamide gel) a-amylase using central composite design. The experimental result on enzymatic hydrolysis of cassava starch was subjected to multiple linear regression analysis using MINITAB 14 software. Positive linear effect of starch concentration, enzyme concentration and time was observed on hydrolysis of cassava starch by a-amylase. The statistical significance of the model was validated by F-test for analysis of variance (p < 0.01). The optimum value of starch concentration temperature, time and enzyme concentration were found to be 4.5% (w/v), 45oC, 150 min, and 1% (w/v) enzyme. The maximum glucose yield at optimum condition was 5.17 mg/mL.

Application of the Improved QFD Method Case Study: Kitchen Utensils Rack Design

This paper presents an application of the improved QFD method for determining the specifications of kitchen utensils rack. By using the improved method, the subjective nature in original QFD was reduced; particularly in defining the relationship between customer requirement and engineering characteristics. The regression analysis that was used for obtaining the relationship functions between customer requirement and engineering characteristics also accommodated the inaccurateness of the competitive assessment results. The improved method which is represented in the form of a mathematical model had become a formal guidance to allocate the resource for improving the specifications of kitchen utensils rack. The specifications obtained had led to the achievement of the highest feasible customer satisfaction.

Performance Evaluation Standards and Innovation: An Empirical Investigation

In this empirical research, how marketing managers evaluate their firms- performances and decide to make innovation is examined. They use some standards which are past performance of the firm, target performance of the firm, competitor performance, and average performance of the industry to compare and evaluate the firms- performances. It is hypothesized that marketing managers and owners of the firm compare the firms- current performance with these four standards at the same time to decide when to make innovation relating to any aspects of the firm, either management style or products. Relationship between the comparison of the firm-s performance with these standards and innovation are searched in the same regression model. The results of the regression analysis are discussed and some recommendations are made for future studies and applicants.

Designing Early Warning System: Prediction Accuracy of Currency Crisis by Using k-Nearest Neighbour Method

Developing a stable early warning system (EWS) model that is capable to give an accurate prediction is a challenging task. This paper introduces k-nearest neighbour (k-NN) method which never been applied in predicting currency crisis before with the aim of increasing the prediction accuracy. The proposed k-NN performance depends on the choice of a distance that is used where in our analysis; we take the Euclidean distance and the Manhattan as a consideration. For the comparison, we employ three other methods which are logistic regression analysis (logit), back-propagation neural network (NN) and sequential minimal optimization (SMO). The analysis using datasets from 8 countries and 13 macro-economic indicators for each country shows that the proposed k-NN method with k = 4 and Manhattan distance performs better than the other methods.

Sequence-based Prediction of Gamma-turn Types using a Physicochemical Property-based Decision Tree Method

The γ-turns play important roles in protein folding and molecular recognition. The prediction and analysis of γ-turn types are important for both protein structure predictions and better understanding the characteristics of different γ-turn types. This study proposed a physicochemical property-based decision tree (PPDT) method to interpretably predict γ-turn types. In addition to the good prediction performance of PPDT, three simple and human interpretable IF-THEN rules are extracted from the decision tree constructed by PPDT. The identified informative physicochemical properties and concise rules provide a simple way for discriminating and understanding γ-turn types.

Positive Analysis on Vulnerability, Information Security Incidents, and the Countermeasures of Japanese Internet Service Providers

This paper includes a positive analysis to quantitatively grasp the relationship among vulnerability, information security incidents, and the countermeasures by using data based on a 2007 questionnaire survey for Japanese ISPs (Internet Service Providers). To grasp the relationships, logistic regression analysis is used. The results clarify that there are relationships between information security incidents and the countermeasures. Concretely, there is a positive relationship between information security incidents and the number of information security systems introduced as well as a negative relationship between information security incidents and information security education. It is also pointed out that (especially, local) ISPs do not execute efficient information security countermeasures/ investment concerned with systems, and it is suggested that they should positively execute information security education. In addition, to further heighten the information security level of Japanese telecommunication infrastructure, the necessity and importance of the government to implement policy to support the countermeasures of ISPs is insisted.

Empirical Analysis of Private Listed Companies- Debt Financing and Business Performance in Jiangsu Province

According to the theory of capital structure, this paper uses principal component analysis and linear regression analysis to study the relationship between the debt characteristics of the private listed companies in Jiangsu Province and their business performance. The results show that the average debt ratio of the 29 private listed companies selected from the sample is lower. And it is found that for the sample whose debt ratio is lower than 80%, its debt ratio is negatively related to corporate performance, while for the sample whose debt ratio is beyond 80%, the relationship of debt financing and enterprise performance shows the different trends. The conclusions reflect the drawbacks may exist that the debt ratio is relatively low and having not take full advantage of debt governance effect of the private listed companies in Jiangsu Province.

Functional Decomposition Based Effort Estimation Model for Software-Intensive Systems

An effort estimation model is needed for softwareintensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.

The Relation of College Students- Process of Study and Creativity: The Mediating Effect of Creative Self-Efficacy

The purpose of this study was to investigate the relationships among students- process of study, creative self-efficacy and creativity while attending college. A total of 60 students enrolled in Hsiuping Institute of Technology in central Taiwan were selected as samples for the study. The instruments for this study included three questionnaires to explore the aforesaid aspects. This researchers tested creative self-efficacy and process of study, and creativity with Pearson correlation and hierarchical regression analyses. The major findings of this research are (1) the process of study had direct positive predictability on creativity, and (2) the relationship between process of study and creativity is partially mediated by creative self-efficacy.

A Study on Exclusive Breastfeeding using Over-dispersed Statistical Models

Breastfeeding is an important concept in the maternal life of a woman. In this paper, we focus on exclusive breastfeeding. Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. This type of breastfeeding is very important during the first six months because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in Mauritius, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we give an overview of exclusive breastfeeding in Mauritius and the factors influencing it. We further analyze the local practices of exclusive breastfeeding using the Generalized Poisson regression model and the negative-binomial model since the data are over-dispersed.

Zero Inflated Strict Arcsine Regression Model

Zero inflated strict arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, we extend zero inflated strict arcsine model to zero inflated strict arcsine regression model by taking into consideration the extra variability caused by extra zeros and covariates in count data. Maximum likelihood estimation method is used in estimating the parameters for this zero inflated strict arcsine regression model.

Service Quality vs. Customer Satisfaction: Perspectives of Visitors to a Public University Library

This study proposes a conceptual model and empirically tests the relationships between customers and librarians (i.e. tangibles, responsiveness, assurance, reliability and empathy) with a dependent variable (customer satisfaction) regarding library services. The SERVQUAL instrument was administered to 100 respondents which comprises of staff and students at a public higher learning institution in the Federal Territory of Labuan, Malaysia. They were public university library users. Results revealed that all service quality dimensions tested were significant and influenced customer satisfaction of visitors to a public university library. Assurance is the most important factor that influences customer satisfaction with the services rendered by the librarian. It is imperative for the library management to take note that the top five service attributes that gained greatest attention from library visitors- perspective includes employee willingness to help customers, availability of customer representatives online for response to queries, library staff actively and promptly provide services, signs in the building are clear and library staff are friendly and courteous. This study provides valuable results concerning the determinants of the service quality and customer satisfaction of public university library services from the users' perspective.