• Asian Journal of Business Environment
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• v.3 no.1
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• pp.23-27
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• 2013

Purpose - This study will focus on motivation of temporary workers working in distributors as well as generic companies, especially MPS (motivating potential score) proposed by job characteristics model. We think that temporary workers required intrinsic motivation in order to commit with their organization because they are difficult switch-regular workers due to glass ceiling. Research design, data, methodology - This study operates a survey targeting temporary workers, specifically, we used 144 copies except uncollected copies and dishonesty response of total 165 copies on analysis. We used multiple regression and 3 step regression to investigate the proposed model. Results - The high level of perceived distributional justice and procedural justice was increased the level of organizational commitment, respectively. And, MPS was increased the level of organizational commitment, too. Finally, this study showed that both justice and Job characteristics were very important to increase organizational commitment. Conclusions - In order to inspire temporary workers, the company provides placing enough considering job characteristics as well as fairness of the procedure and distribution. Also, to more fully understand the underlying processes between HRM (Human Resource Management) concepts, new fundamental methods may be required such as switch full-time opportunities.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.5
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• pp.70-82
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• 2001

This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation suggested by the first report of this project. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the Generalized extreme value distribution among applied distributions. Regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the legions and consecutive durations were derived by the regional frequency analysis.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.513-528
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• 2017

Statistics are often used to test two samples if they have been drawn from the same underlying distribution. In this paper, we introduce several well-known distribution-free tests to compare distributions and conduct an extensive Monte-Carlo simulation to specify their behaviors. We consider various circumstances of when two distributions vary in (1) location, (2) scale, (3) symmetry, (4) kurtosis, (5) tail weight. A practical guideline for two-sample goodness-of-fit test is presented based on the simulation result.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1616-1625
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• 2019

Measuring occurrence times of random events, aimed to determine the statistical properties of the governing stochastic process, is a basic topic in science and engineering, and has been the subject of numerous mathematical modeling approaches. Often, true statistical properties deviate from measured properties due to the so called dead time phenomenon, where for a certain time period following detection, the detection system is not operational. Understanding the dead time effect is especially important in radiation measurements, often characterized by high count rates and a non-reducible detector dead time (originating in the physics of particle detection). The effect of dead time can be interpreted as a suitable rarefied sequence of the original time sequence. This paper provides a limit theorem for a high rate (diffusion-scale) counter with extendable (Type II) dead time, where the underlying counting process is a renewal process with finite second moment for the inter-event distribution. The results are very general, in the sense that they refer to a general inter arrival time and a random dead time with general distribution. Following the theoretical results, we will demonstrate the applicability of the results in three applications: serially connected components, multiplicity counting and measurements of aerosol spatial distribution.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.411-422
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• 2016

Rainfall-runoff modeling in conjunction with rainfall frequency analysis has been widely used for estimating design floods in South Korea. However, uncertainties associated with underlying distribution and sampling error have not been properly addressed. This study applied a Bayesian method to quantify the uncertainties in the rainfall frequency analysis along with Gumbel distribution. For a purpose of comparison, a probability weighted moment (PWM) was employed to estimate confidence interval. The uncertainties associated with design rainfalls were quantitatively assessed using both Bayesian and PWM methods. The results showed that the uncertainty ranges with PWM are larger than those with Bayesian approach. In addition, the Bayesian approach was able to effectively represent asymmetric feature of underlying distribution; whereas the PWM resulted in symmetric confidence interval due to the normal approximation. The use of long period data provided better results leading to the reduction of uncertainty in both methods, and the Bayesian approach showed better performance in terms of the reduction of the uncertainty.

• Korean Management Science Review
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• v.11 no.2
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• pp.1-27
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• 1994

A reliability data processing MPRDP (Multi-Purpose Reliability Data Processor) has been developed in FORTRAN language since Jan. 1992 at KAERI (Korean Atomic Energy Research Institute). The purpose of the research is to construct a reliability database(plant-specific as well as generic) by processing various kinds of reliability data in most objective and systematic fashion. To account for generic estimates in various compendia as well as generic plants' operating experience, we developed a 'three-stage' Bayesian procedure[1] by logically combining the 'two-stage' procedure[2] and the idea for processing generic estimates[3]. The first stage manipulates generic plant data to determine a set of estimates for generic parameters,e.g. the mean and the error factor, which accordingly defines a generic failure rate distribution. Then the second stage combines these estimates with the other ones proposed by various generic compendia (we call these generic book type data). This stage adopts another Bayesian procedure to determine the final generic failure rate distribution which is to be used as a priori distribution in the third stage. Then the third stage updates the generic distribution by plant-specific data resulting in a posterior failure rate distribution. Both running failure and demand failure data can be handled in this code. In accordance with the growing needs for a consistent and well-structured reliability database, we constructed a generic reliability database by the MPRDP code[4]. About 30 generic data sources were reviewed and available data were collected and screened from them. We processed reliability data for about 100 safety related components frequently modeled in PSA. The underlying distribution for the failure rate was assumed to be lognormal or gamma, according to the PSA convention. The dependencies among the generic sources were not considered at this time. This problem will be approached in further study.

• Journal of Periodontal and Implant Science
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• v.46 no.3
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• pp.207-217
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• 2016

Purpose: The aim of this study is to analyze and visualize the distribution of patients visiting the periodontology department at a dental college hospital, using a geographic information system (GIS) to utilize these data in patient care and treatment planning, which may help to assess the risk and prevent periodontal diseases. Methods: Basic patient information data were obtained from Dankook University Dental Hospital, including the unit number, gender, date of birth, and address, down to the dong (neighborhood) administrative district unit, of 306,656 patients who visited the hospital between 2007 and 2014. The data of only 26,457 patients who visited the periodontology department were included in this analysis. The patient distribution was visualized using GIS. Statistical analyses including multiple regression, logistic regression, and geographically weighted regression were performed using SAS 9.3 and ArcGIS 10.1. Five factors, namely proximity, accessibility, age, gender, and socioeconomic status, were investigated as the explanatory variables of the patient distribution. Results: The visualized patient data showed a nationwide scale of the patient distribution. The mean distance from each patient's regional center to the hospital was $30.94{\pm}29.62km$ and was inversely proportional to the number of patients from the respective regions. The distance from a regional center to the adjacent toll gate had various effects depending on the local distance from the hospital. The average age of the patients was $52.41{\pm}12.97years$. Further, a majority of regions showed a male dominance. Personal income had inconsistent results between analyses. Conclusions: The distribution of patients is significantly affected by the proximity, accessibility, age, gender and socioeconomic status of patients, and the patients visiting the periodontology department travelled farther distances than those visiting the other departments. The underlying reason for this needs to be analyzed further.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.3
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• pp.386-392
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• 1996

A numerical method based on genetic algorithms was introduced to characterize the grain-size distribution more effectively. This technique was proved significant particularly for multimodal size distributions, as was verified for samples from Korea Strait continental shelf. Sediment samples collected from the Korea Strait continental shelf revealed that $96\%$ of the grain-size distributions were multimodal. Therefore, the use of grain-size parameters was not the ideal method. As an alternative method, the decomposition of sue curves into elementary normal component curves was used. Means and standard deviations of 593 decomposed normal components were calculated by a numerical method from 268 size curves of Korea Strait sediments. The mean values of decomposed normal components showed peaks at $1\~3\phi\;and\;7\~9\phi$ size classes. The plot of mean and standard deviation values of the coarse fraction normal components on the map showed a characteristic areal distribution. The characteristic distribution was found to derive from underlying Pleistocene sediment on the basis of sea bottom geologic distribution of the area. The method of decomposition into normal components was found to be more effective than the analysis using traditional grain-size parameters in investigation of multimodal size distribution of Korea Strait shelf sediment.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.1-17
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• 2020

This study evaluated a debris landform distribution potential area map in the southwest region of the Korean peninsula. A GIS spatial integration technique and logistic regression method were used to produce a distribution potential area map. Seven topographic and environmental factors were considered for analysis and 28 different data set were combined and used to get most effective results. Moreover, in an accuracy assessment, the extracted results of the Distribution Potential area were evaluated by conducting a cross-validation module. Block stream showed the highest accuracy in the combination No. 6, and that DEM (digital elevation model) and TWI (topographic wetness index) have relatively high influences on the production of the Block stream Distribution Potential area map. Talus showed the highest accuracy in the combination No. 13. We also found that slope, TWI and geology have relatively high influences on the production of the Talus Distribution Potential area map. In addition, fieldwork confirmed the accuracy of the input data that were used in this study, and the slope and geology were also similar. It was also determined that these input data were relatively accurate. In the case of angularity, the block stream was composed of sub-rounded and sub-angular systems and Talus showed differences according to the terrain formation. Although the results of the rebound strain measurement using a Schmidt's hammer did not shown any difference in topographic conditions, it is determined that the rebound strain results reflected the underlying geological setting.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1039-1055
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• 2014

The distribution of a test statistic under a null hypothesis depends on the unknown distribution of the data and thus is unknown as well. Conditional tests replace the unknown null distribution by the conditional null distribution, that is, the distribution of the test statistic given the observed data. This approach is known as permutation tests and was developed by Fisher (Fisher, 1935). Theoretical framework for permutation tests was given by Strasser and Weber(1999). The coin package developed by Hothon et al. (2006, 2008) implements a unified approach for conditional inference via the generic independence test. Because convenient functions for the most prominent problems are available, users will not have to use the extremely flexible procedure. In this article we briefly review the underlying theory from Strasser and Weber (1999) and explain how to transform the data to perform the generic function independence test. Finally it was illustrated with a few real data sets.