• 한국의류학회지
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• 제23권2호
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• pp.262-271
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• 1999

This paper presents a conceptual mode of the clothing complaining behavior process following dissatisfaction in a retail environment and influence of relevant variables. The data were collected 250 male and 358 female consumers by questionnaire employing critical incident technique. Given dissatisfaction with clothing the complaining behavior undertaken will be largely dependent on product importance the likelihood of success one's attitude toward complaining and demorgraphic variables. Through empirical research the clothing complaining behavior was dependent on the likelihood of success sex, dimension of complaining cost and product importance, Brand satisfaction was affected by only perceived justice. And repurchasing behavior was dependent upon brand satisfaction education product importance and income.

• 대한수학회지
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• 제16권2호
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• pp.107-111
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• 1980

• 한국시뮬레이션학회논문지
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• 제7권2호
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• pp.137-152
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• 1998

One of the components that constitute the simulation models is the state variables whose values are determined by the time related simulation process. Embedding rule-based expert systems into the simulation models should provide a systematic way of handling these time-dependent variables without distracting the essential problem solving capabilities of the expert systems which are well suited for expressing the decision making function of complex cases. The expert system, however, is inefficient in dealing with the time elapsing characteristics of target system compare to the simulation models. To solve the problem, this paper provides an interruptible inference engine whose inferencing process can be interrupted when the variables' value, which are used as the parameters of the rules, are not yet determined due to the time dependent nature of the state variables. The process is resumed when the variables are ready. The elapse of time is calculated by time-advance function of the simulation model to which the expert system has been embedded. The example modeling shown exploits the embedded interruptible inferencing capability for the controlling and monitoring of metal grating process.

• 보건교육건강증진학회지
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• 제6권2호
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• pp.4-22
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• 1989

This study aims to explore the relationship between housewives' health KAP level and the physical health of families. The data used in this study are obtained from the Last Evaluation Program of the National Note for Health surveyed in July, 1989. The respondents for this study are 770 housewives residing in Chunan and Buan. The reason why this study focus on KAP level of housewives is to find out whether a housewife as a emotional supporter contributes to the physical health of her families. A housewife gives her families emotional satisfaction insteade of economic satisfaction. So she has the most interest in family health among the members of her family. Therefore, housewife's KAP level will influence her family health. The independent variables chosen for the analysis are the general characteristic variables and KAP level. And the dependent variable is the physical health of families which excluded psychosocial one. This level of family health includes weight for family health and seriouseness of disease. The result of this study was summarized as follows. (1) KAP level was significantly correlated with variables which have mainly the socioeconomic characteristics. The variables were: area of residence, education level occupation, self assessment on wealth, and exposure to mass communication. (2) In the analysis of relationship between the general characteristic variables and family health, family health was significantly correlated with almost all variables. The variables were: Presence of the aged, Health status, Experience in disease, Self assessment on health, No. of families, Occupation, Education level, Self assessment on wealth, Concern on health, and Exposure to mass communication. (3) In the analysis of relationship between family health and KAP level, family health was not significantly correlated with KAP level but. (4) Also in the stepwise regression analysis, the general variables account for about 32.1 percent of the variance in the dependent variable, family health. The variable with the greatest explanatory power was presence of the aged. On the contrary, KAP level explain about 0.4 percent of the variance in the dependent variable. In sum, the study shows that housewives' health KAP level has relatively weak relationship with the physical health of families

• Communications for Statistical Applications and Methods
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• 제26권3호
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• pp.261-272
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• 2019

In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.

• 한국조경학회지
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• 제29권1호
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• pp.92-99
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• 2001

This study analyzed the effects of illumination on psychological accessibility from a view of satisfaction of night use at urban neighborhood park for actual night users. For this, we have classified the effects of illumination as five sampled independent variables from 12 effects of illumination, and tested the relationship with satisfaction of night use of a dependent variable by multiple regression analysis. The results of this study are as follows; 1) The effects of illumination for night use at urban neighborhood park were divided into five factors; (1) direct effect, (2) effect of promoting use, (3) effect of ensuring security, (4) effect of preparing landscape in the night time, and (5) psychological effect. Among independent variables indicating characteristics of effects of each illumination, uneasiness at night use was high. 2) In a multiple regression model, when other conditions were not changed, the value of security of night use (X\ulcorner) had maximumly an affect on the value of dependent. And, the value of danger to meet the depraved(X\ulcorner) had minimally an affect on the value of dependent variable. 3) For the contribution of security of nigh use(X\ulcorner) and brightness of present using space(X$_4$) to satisfaction of night use(Y) of dependent variable, they had a nearly equal effect on that, and showed about 2 times importance compared to familiarity with park(X\ulcorner) and the beauty of park(X\ulcorner). Also, they showed about 7 times contribution to satisfaction of night use compared to danger to meet the depraved(X\ulcorner), which had minimally an affect on the value of dependent variable, as the most important variables. 4) For the effects of illumination on satisfaction of night use, the effect of ensuring security - pursues security of park for the general rather than security for the specific class or subject - and direct effect to offer proper brightness in using space relatively affected on it much compared to psychological effect, effect of preparing landscape in night time, and effect of promoting use. A research on the psychological effects among the variables related to illumination as well as physical circumstances such as the height, location, direction of illumination should be studied.

• 한국안전학회지
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• 제30권1호
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• pp.8-13
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• 2015

The experimental design methodology was applied in the drop tube furnace (DTF) to predict the various combustion properties according to the operating conditions and to assess the coal plant safety. Response surface method (RSM) was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of DTF. The dependent variables such as burnout ratios (BOR) of coal and $CO/CO_2$ ratios were mathematically described as a function of three independent variables (coal particle size, carrier gas flow rate, wall temperature) being modeled by the use of the central composite design (CCD), and evaluated using a second-order polynomial multiple regression model. The prediction of BOR showed a high coefficient of determination (R2) value, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the simulation data. However, $CO/CO_2$ ratio had a big difference between calculated values and predicted values using conventional RSM, which might be mainly due to the dependent variable increses or decrease very steeply, and hence the second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, $CO/CO_2$ ratio was taken as common logarithms and worked again with RSM. The application of logarithms in the transformation of dependent variables showed that the accuracy was highly enhanced and predicted the simulation data well.

• 한국안전학회지
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• 제27권2호
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• pp.105-110
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• 2012

This study deals with the accident models of rotary. The objectives is to develop the models by day and nighttime. In pursuing the above, this study gives particular attentions to collecting the data of geometric structure and accidents of 20 rotaries and developing the Poisson and negative binomial regression models using NLOGIT 4.0. The main results are as follows. First, the numbers of accident of nighttime (1.03 per 1,000 entering vehicles) were analyzed to be very higher than those of day (0.47 per 1,000 entering vehicles). Second, 4 Poisson models which were all statistically significant were developed, in which the dependent variable were both the number of accident and EPDO (equivalent property damage only). Finally, the number of entry/exit ($X_1$) and the number of entering lane ($X_5$) in the models of the number of accident, and $X_1$ in the EPDO models were adopted as the common variables. The variables were analyzed to be all positive to the dependent variables.

• 수산경영론집
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• 제37권2호
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• pp.1-18
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• 2006

This study analyzes the effect of exchange rate and exchange risk on the import of Korea's fisheries. The estimation models consist of the following contents. The first model consists of one dependent variable-import quantity of fisheries$(IMQ_t^{Total})$ and three independent $variables-RP_t^{Total}$, $EX_t\;and\;EXV_t$. The second one-one dependent variable-import quantity of fisheries from China$(IMQ_t^{CN})$ and three independent $variables-RP_t^{CN},\;EX_t\;and\;EXV_t$. And the last one is made up of one dependent variable - import quantity of fisheries from $Japan(IMQ_t^{JP})$ and three independent $variables-RP_t^{CN},\;EX_t\;and\;EXV_t$. The estimation results show that all of the independent variables are statistically significant. Especially, the effect of Chinese $RP_t^{CN}$ is grater than Japanese $RP/P_t^{JP}$. However, the effect of Japanese $EX_t$ is grater than Chinese $EX_t$.

• Communications for Statistical Applications and Methods
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• 제23권5호
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• pp.385-397
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• 2016

The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability ${\theta}$ = P(X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating ${\theta}$ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of ${\theta}$ = P(X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS), via the bias and mean square error (MSE). We demonstrate that the suggested estimators based on BVRSS are more efficient than those based on BVSRS. A simulation study is conducted to gain insight into the performance of the proposed estimators. A real data example is provided to illustrate the process.