• Journal of Digital Convergence
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• v.12 no.8
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• pp.377-387
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• 2014

The purpose of this study is to suggest improvement ways of outpatient process via a simulation model and to improve operational efficiency. Three experimentation scenarios were implemented into the simulation model to determine which proposed scenario provides better improvement in terms of the following performance measures: LOS(Length of Stay), patient waiting time, patient travel time, and staff utilization. The hospital medical data collection and statistical tools used to analyze the process mining tools. And the PIOS simulation tool was used and the validity of the model was verified by using t-test. The simulation results demonstrated that oupatient process of center type is most efficient. Simulation approach is a powerful technique that supports efficient decision-making compared to traditional healthcare management approach based on past experience, feelings, and intuition. Therefore, the proposed experimentation model has wide applicability in healthcare systems.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.905-912
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• 2012

We are dealing with the Bayes' rule education tool with Excel Macro and its usage example. When an event occurs, we are interested in whether it does under certain conditions or not. In this case, we use the Bayes' rule to calculate the probability. Bayes' rule is very useful in making decision based on newly obtained statistical information. We introduce an efficient self-teaching educational tool developed to help the learners understand the Bayes' rule through intermediate steps and descriptions. The concept and examples of intermediate steps such as conditional probability, multiplication rule, law of total probability, prior probability and posterior probability could be acquired through step-by-step learning. All the processes leading to result are given with diagrams and detailed descriptions. By just clicking the execution button, users could get the results in one screen.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.125-133
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• 2014

This paper develops a bankruptcy prediction model on an Artificial Neural Network for hotel management. A bankruptcy prediction model has a specific feature to predict a bankruptcy of the whole hotel business after evaluate bankruptcy possibility on the basis of business performance data of each branch. here are many traditional statistical models for bankruptcy prediction such as Multivariate Discriminant Analysis or Logit Analysis. However, we chose Artificial Neural Network because the method has accuracy rates of prediction better than those of other methods. We first selected 100 good enterprises and 100 bankrupt enterprises as experimental data and set up a bankruptcy prediction model by use of a tool for Artificial Neural Network, NeuroShell. The model and its experiments, which demonstrated high efficiency, can certainly provide great help in decision making in the field of hotel management and in deciding on the bankruptcy or financial solidity of each branch of serviced residence hotel.

• Journal of Environmental Health Sciences
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• v.42 no.5
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• pp.302-313
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• 2016

Objectives: This study was conducted to assess environmental health status on a local scale using environmental health-related indicators. It demonstrated the possibility of using a structural equation model, a methodological approach to provide synthesized information. Methods: Eighteen indicators were selected from official statistical data published by local governments. Each environmental health-related indicator was classified according to the PSR (pressure-state-response) model. Aggregation methods were performed using principal component analysis and fuzzy sets. Results: The five principal components were classified through principal component analysis (PCA) and obtained eigenvalues >1.0 from the initial 18 indicators. The aggregated index was obtained by condensing the original information into two broad and simple categories through fuzzy sets. Conclusion: This could be useful in that the aggregation procedure may provide a basis for establishing environmental health policies and a decision-making process. However, the availability and quality of indicators, assessment of aggregation method bias, choice of weighted scores for indicators, and other factors should be examined in future studies.

• Economic and Environmental Geology
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• v.37 no.1
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• pp.49-59
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• 2004

The concectration and distribution of contaminants obtained from a contaminated land investigation or an environmental geochemistry survey constitutes the basis of a decision-making process on environmental policies or of scientific researches. As the quality of data determines the reliability of the result, the investigation plan should be adjusted according to the purpose of the investigation. In general, the effort to improve the data quality had been focused mainly on the QA/QC procedures in laboratories. The rapid progress of analytical instrument has also contributed toward improving the analytical precision to a sacrificable degree. Nevertheless, in many cases, it is not the analytical precision that needs improvement for the better precision of overall measurement process: it is rather during the sampling process in the field that is responsible for the poor precision. To assess the data quality on a measured value, ISO recommends to provide information on "measurement uncertainty" along with the measured value. The measurement uncertainty in an environmental measurement context can be explained as the statistical number that expresses the degree of the uncertainty stemming from the sampling and analytical procedures. There is a cost involved in order to improve the precision of sampling and analytical methods so as to decrease the degree of measurement uncertainty. The economical point of compromise in an investigation planning can be achieved when the allowable degree of uncertainty has been set before-hand. The investigation can then be planned accordingly not to exceed the uncertainty limit. Furthermore, if the measurement uncertainty estimated from the preliminary investigation can be separated into sampling and analytical uncertainties, it can be used as a criterion where the resources for the investigation should be allotted cost-effectively to reinforce the weakest link of the whole investigation process. This paper aims to present a method of estimating the level of measurement uncertainty of a measured contamination concentration at a site used as an example and to show how the estimated uncertainty can be applied to serve the particular purpose of an investigation.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.5 s.164
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• pp.765-776
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• 2007

Customer expectations and requirements for products play an important role in product planning for companies and decision making process for the consumer. These expectations are expressed by product qualities that consumers consider important when they purchase. Therefore, to identify quality elements that reflect consumer requirements would be a useful guide for companies. The purposes of this study are to find out quality factors of apparel product, to identify apparel product quality elements using Kano's theory, to find attributes of product which improvement are required. Women over 20 years-old from metropolitan areas in South Korea participated in the study and a quota sampling method was used. A questionnaire was arranged with four separate subject sections, importance of quality, Kano's questionnaires, and demographics. Data from 525 questionnaires were used for the statistical analysis. The results were as follows: Six dimensions of product quality(i.e., usefulness, performance, aesthetic, symbol, individuality and appearance) were identified. According to Kano's quality elements, performance was categorized into must-be quality which could lead to product dissatisfaction. Usefulness and appearance were categorized into one-dimensional quality which lead to both satisfaction and dissatisfaction. Aesthetic, symbol, and individuality was categorized into attractive quality which could lead to satisfaction. Findings of this study provide both industry and academic researchers with a guide to increase customer satisfaction in the product development process.

• Journal of Trauma and Injury
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• v.28 no.3
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• pp.144-148
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• 2015

Purpose: Immediate identification of vascular injury requiring embolization in patients with pelvic bone fracture isn't an easy task. There have been many trials finding indicators of embolization for patients with pelvic bone fracture. Although Young and Burgess classification is useful in decision making of treatment, it is reported to have little value as indicator of embolization in major trauma patients. The aim of this study is to find out Young and burgess classification on predicting vessel injury by analzyng pelvic radiograph taken from major trauma patients with pelvic bone fracture. Methods: Among major trauma patients with injury severity scores (ISS) higher than 15 who visited our emergency room from January 2011 to June 2014, 200 patients were found with pelvic bone fracture in trauma series and thus pelvic CT angiography was taken. Setting aside patients with exclusion criteria, 153 patients were enrolled in this study for analysis of Young and Burgess classification. Results: The most common mechanism of injury was lateral compression in both groups. There was no statistical significant difference in Young and Burgess classification (p=0.397). The obturator artery was the most commonly injured artery in both groups. Six patients had more than one site of bleeding. Conclusion: Prediction of transcatheter angiographic embolization using Young and Burgess classification in severe trauma patients is difficult and requires additional studies.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.81-101
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• 2003

The financial statements purpose to provide useful information to decision-making process of business managers. The value-relevant information, however, embedded in the financial statement has been often overlooked in Korea. In fact, the financial statements in Korea have been utilized for nothing but account reports to Security Supervision Boards (SSB). The objective of this study is to develop earnings forecasting models through financial statement analysis using artificial intelligence (AI). AI methods are employed in forecasting earnings: artificial neural networks (ANN) for manufacturing industry and case~based reasoning (CBR) for banking industry. The experimental results using such AI methods are as follows. Using ANN for manufacturing industry records 63.2% of hit ratio for out-of-sample, which outperforms the logistic regression by around 4%. The experiment through CBR for banking industry shows 65.0% of hit ratio that beats the statistical method by 13.2% in holdout sample. Finally, the prediction results for manufacturing industry are validated through monitoring the shift in cumulative returns of portfolios based on the earning prediction. The portfolio with the firms whose earnings are predicted to increase is designated as best portfolio and the portfolio with the earnings-decreasing firms as worst portfolio. The difference between two portfolios is about 3% of cumulative abnormal return on average. Consequently, this result showed that the financial statements in Korea contain the value-relevant information that is not reflected in stock prices.

• Journal of Korean Elementary Science Education
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• v.25 no.spc5
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• pp.485-494
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• 2007

The aims of this study were to investigate the differences of the proportion of misconceptions and the reasons for selecting responses related to questions about small living things between talented and average students. The study subjects were made up of three groups. They were a class of 37 talented elementary students in science attending J National University of Education, a class of 37 talented students in science attending J City Office of Education, and a class of 33 average students attending J City. A questionnaire was composed of 20 test questions for examination of concepts related to small living things. The data obtained in this study was analyzed using a statistical program. The major results were as follows: In general, the level of the scientific concepts possessed by the talented students was much higher than that of the average students, especially in question 14. The reasons for the misconceptions which were revealed through this study were classified into vagueness of the language used, hasty decision and deduction making, using the wrong analogical inference, mass communications (TV or internet) and experimental differences between individuals. In terms of the reasons for the selection of a given response, the talented students had also a higher frequency in the 'science books for children' category than the average students, indicating that various kinds of science books for children have an influence on the formation of concepts on small living things. The misconception proportion of male students was 5.4% higher than that of female students in mean frequencies of all questions, although the difference was not statistically significant except for question 4. Data from this study may help teachers involved in education for gifted students to reconsider their conceptions on small living things.

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.77-82
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• 2017

Thus, chemicals are managed under 9 related central government department and 16 relevant laws with program such as Process Safety Management and Offsite Consequence Analysis in korea. Guidelines for set the endpoint concentration for chemcals based on the ERPG-2 (Emergency Response Planning Guidelines-2) and AEGL-2 (Acute Exposure Guidelines Level-2). but ERPG and AEGL do not describe exposure for less than 10 minutes. because of this, each guidelines define criteria differently for short time less than 10 minutes exposure. This indefinite exposure criteria would give rise to a confusion in the chemical plants, and potentially lead to a critical decision making error when accidents happen. In an effort to apply guidelines with evenly-distributed initial time frame, AEGL concentrations within 10 minute exposure time were evaluated by examining statistical regression curves. The results were in good agreement with those from the Probit Function based on each AEGL grade to explain 3 different threshold levels of exposure effects. Resultant re-enforced guidelines for endpoint chemical concentrations are, therefore, to provide powerful tool to assess and manage the risk associated with any potential chemical accidents at an early stage.