• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.489-497
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• 1996

Lower bounds for the full level probabilities are derived under order restrictions in weights. Discussions are made on typical isotonic cones such as linear order, simple tree order, and unimodal order cones. We also discuss applications of these results for constructing conditional likelihood ratio tests for ordered hypotheses in a contingency table. A real data set on torus mandibularis will be analyzed for illustrating the testing procedure.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.623-632
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• 2007

Some tests of the goodness of fit of the uniform distribution between 0 and 1 are presented. The powers of the tests under certain alternatives are examined. As a result, the statistic based on the difference between the order statistics and the modal value of them gives good powers. We also give modifications of the statistic without using the extensive tables of the critical points.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.445-455
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• 1999

We modify the Gompertz regression model for estimation of cure rates from pediatric clinical trials by assuming different hazard rates on the different periods. A treatment period may be divided by the stages of treatments under the different treatment arms. The piecewise Gompertz models provide an efficient method for estimation of the cure rates and a method for testing the difference of the treatment effects in the given interval.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.67
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• pp.83-92
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• 2001

This paper is to measure and evaluate the degree of customer satisfaction for internet search engines. The service quality scale is developed after testing validity and reliability through the result of inquiring into the literature and the interview of university students. The stepwise regression analysis using MINITAB is used to analyze the survey results.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.205-220
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• 1998

Dependence concepts for ordered two-way contingency tables have been of considerable interest. We consider a dependence concept which is less restrictive than likelihood ratio dependence and more restrictive than regression dependence. Maximum likelihood estimation of cell probability under this dependence restriction is studied. The likelihood ratio statistics for and against this dependence are proposed and their large sample distributions are derived. A real data is analyzed to illustrate the estimation and testing procedures.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.190-206
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• 1996

In case measurements are made on units of production in time order, it is reasonable to expect that the measurement errors will sometimes be first order autocorrelated, and a technique to test such autocorrelation is required to give good control of the productive process. Tool-wear process provide an example for which regression model can sometimes be useful in modeling and controlling the process. For the control of such process, we present a simple method for testing first order autocorrelation in regression errors. The method is based on Bayesian test method via Bayes factor and derived by observing that in general, a Bayes factor can be written as the product of a quantity called the Savage-Dickey density ratio and a correction factor ; both terms are easily estimated from Gibbs sampling technique. Performance of the method is examined by means of Monte Carlo simulation. It is noted that the test not only achieves satisfactory power but eliminates the inconvenience occurred in using the well-known Durbin-Watson test.

• Journal of the East Asian Society of Dietary Life
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• v.18 no.3
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• pp.294-301
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• 2008

The purpose of this study was to analyze the effects of food neophobia on food choice motives, such as health concern, weight control, ethical concern, and vegetable consumption. A total of 290 questionnaires were completed. Moderated regression analysis was used to measure the moderating effects of food neophobia. Results demonstrated Model 3 to be the best fit, compared to Model 1 and Model 2. In Model 3, the effects of health concern and food neophobia on vegetable consumption were statistically significant (p<0.01). However, the effects of weight control and ethical concern on vegetable consumption were not statistically significant (p>0.05). As expected, the combination of health concern and food neophobia had a significant effect on vegetable consumption (p<0.05). However, weight control and food neophobia, and ethical concern and food neophobia had no significant effects on vegetable consumption (p>0.05). Moreover, health concern related to vegetable consumption was statistically significant at all levels of food neophobia, except, when level of food neophobia was high (p<0.001). In developing and testing moderated regression models, which integrate relationship among food neophobia, health concern, weight control, ethical concern and vegetable consumption in the future, this study may provide a deeper understanding of the complex relationship among vegetable consumption behavior-related variables.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.107-112
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• 2008

The maintenance of legacy software systems is very important in the field of a software engineering. In the maintenance, a regression test confirms the behavior preserving of the software which has been changed but most of regression tests are done in a system level and rarely done in a unit test level because there is no test case. This paper proposes how to modify legacy software systems and make unit test cases as an asset. It uses a technique with a specific module of a real software development project and analyzes test coverage results. After this, if a study about automatic restructuring techniques and a test case generation proceeds continuously, we can expect the big advance of legacy software systems maintenance.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.5
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• pp.463-474
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• 2003

In this research, adult women＇s shoulder types were Classified through direct and indirect measurements to present a judging individual body size according to the type. Also, regression formula by shoulder types were calculated and presented the basic bodice pattern. The results were as follows: 1. The result of factor analysis indicated that 6 factors were extracted through factor analysis and those factors comprised 66.1 to of total variance. 2. By using factor scores, cluster analysis was carried out and subject were classified into 5 clusters. Type 1 was the inclined shoulders, wide shoulders and passive posture. Type 2 was the front type shoulders and active posture. Type 3 was the thick shoulders and back type shoulders. Type 4 was the narrow shoulders. Type f was the drooped shoulders, thin shoulder and sway posture. 3. The body types of individuals were judged by discriminant analysis. 4. After setting 4 items such as the bust girth, posterior waist length, neck base girth and waist girth as representative items and regression formulas were presented. the superiority of the final basic bodice patterns were demonstrated by high approval rate of the subjects who participated in testing.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.671-681
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• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.