• 한국의료질향상학회지
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• 제7권1호
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• pp.106-116
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• 2000

Background : Severance Hospital is an university hospital which has 1,580 beds. A LAN system was installed in the Medical Record Department in 1992 and discharge abstract data have been added to the discharge abstract database(DB) The previous work flow in the Medical Record Department had 5 levels: 1) chart collection from wards, 2) assembling, 3) abstracting data from medical record on worksheet by 2 RRAs, 4) checking deficiencies and coding diagnosis and procedures by 4 RRAs, 5) inputting the data into the discharge abstract data base by 1 RRA. The average processing time took 19.3 days from the patient discharge date. It had the production of monthly statistical report delayed. Besides, it caused the users in the hospital to complain. Methods : A CQI team was organized to find a way to shorten the processing time less than 10 days. The team identified the factors making the processing time long and integrated three levels from the 3rd level into one. Each of 7 RRAs performed the integrated level on her workstation instead of taking one of three separate levels. The comparison of processing time before and after the changes was made with 3'846 discharges of April, 1999 and 4,189 discharges of August, 1999. Results : The average processing time was shortened from 19.3 days to 8.7 days. Especially the integrated level took only 3.6 days, compared with 12.3 days before the change. The percentage of finishing up the whole processing within 10 days from discharge was increased up to 77.6%, which was 2.4% before the integration. The prevalence of error in data input was not increased in the new method. Conclusions : The integrated processing method has the following advantages: 1) the expedition of production of monthly statistical report, 2) the increase of utilizing rate of dischare abstract data by Billing Dept, Emergency Room, QI Dept., etc., 3) the improvement of intradepartmental work follow, 4) the enhancement of medical record quality by checking the deficiencies earlier than before.

• Journal of applied mathematics & informatics
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• 제40권3_4호
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• pp.563-575
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• 2022

Many organizations seek statistical modelling facilitated by data analytics technologies for determining the prediction models associated with M&A (Merger and Acquisition). By combining these data analytics tool alongside with data collection approaches aids organizations towards M&A decision making, followed by achieving profitable insights as well. It promotes for better visibility, overall improvements and effective negotiation strategies for post-M&A integration. This paper explores on the impact of pre and post integration of M&A in a standard organizational setting via devising a suitable statistical model via employing techniques such as Naïve Bayes, K-nearest neighbour (KNN), and Decision Tree & Support Vector Machine (SVM).

• Journal of the Korean Statistical Society
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• 제1권1호
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• pp.66-78
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• 1973

In Korea, the statistical system is very weak because it is not functional. Knowledge of statistical theory remains iosolated from applications: routine tasks of collection or processing of data are continued often without utilization, and programms are started in a superficial imitation of other without any purpose. It is essential, in Korea, to make statistics purposive. The only way is to give training statistics-fully developed technology of a multi-discipline character in applied statistics. The purpose of this study is primarily to survey the necessity of, or desire for, statistical tarining for the statistical personnel of the government agencies or bank offices in Seoul, Korea and discuss an adequate method of vacational training in statistics. This survey can be summarized as follows : (1) about 94 percent of the sampled people (478) do not consider their present statistical background adequately trained and 128 persons out of 478 request a graduate level training in respective fields. (2) The statistical fields on job in the sample are : Economic statistics : 138, Sampling survey : 228, management statistics : 50, other fields : 62. (3) Educational background are * College graduate : 369 (male 347, female 22) Economics 99, Business administration 99, Law 71, Mathematics and statistics 24, Others 76 * High school graduate : 109 (male 43, female 66)

• 한국조사연구학회지:조사연구
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• 제1권1호
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• pp.21-43
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• 2000

전화면접을 개별직접면접에 대한 매력적 대안이 될 수 있지만 두 가지 자료 수집방식에서 동일한 결과를 얻을 수 있는지에 대하여는 많은 의문이 제기되어 왔다. 이러한 의문에 대답하기 위해서는 i)전화면접에 대한 피면접자의 선호도, 면접의 속도, 개방질문에 대한 응답의 상세성, 미응답 항목의 비율 등 직접효과 ii) 통계적 추정량 iii) 면접자의 차이와 자료수집양식 등의 관점에서 경험적 문헌검토를 하였다. 이러한 차이는 전화면접에 대한 사회적 소망성 효과, 서베이 질문에 대한 인지능력 및 양식효과와 면접자 효과로 설명될 수 있다.

• Journal of the Korean Statistical Society
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• 제36권3호
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• pp.397-410
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• 2007

For the two groups data from multivariate binomial distribution, we consider a bootstrap approach to inferring the simultaneous confidence level and its standard error of a collection of the dependent confidence intervals for the difference of proportions with an experimentwise error rate at the a level are presented. The bootstrap method is used to estimate the simultaneous confidence probability for the difference of proportions.

• 복식문화연구
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• 제14권1호
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• pp.64-78
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• 2006

The purpose of this study is to set a characteristic design by analyzing formative properties for the hat and fashion image shown in fashion collections from the S/S season of 1998 to the F/W season of 2004 in recent seven years. For the study, the 96 stimuli which found frequently in fashion collection were selected. The examines for the image evaluation were women college students majoring fashion design related fields and living in Seoul, Gyeonggi-do, and Gyeongsangnam-do. Data collection was performed in August 2004. As statistical methods for data analysis, internal consistency method, Factor Analysis, MANOVA were used. Based on the analysis of 31 pairs of adjectives for elucidating the total 96 stimuli which were devised by altering the types of garment, the relation between a garment and a color of hat, the types of hat, the length of hair, and the material and design of garment, five factors or attractiveness, gracefulness, concentration, cuteness, and hardness and softness were deduced. And it showed much difference in the types of garment, the relations between a garment and a color of hat, the types of hat, the length of hair, and the material and design of a garment.

• 한국의상디자인학회지
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• 제13권4호
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• pp.93-110
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• 2011

This study investigates the analysis on the acceptance of Foreign Fashion trends in Korean Fashion Collection by collections, years, season, and designers. The purpose of this study is Korean collection's degree to adopt and receive foreign collections, by comparative analysis of design features between Seoul and foreign collections. For such purpose, from 2006 S/S to 2011 F/W, 5185 pictures were collected from designer's photos of Seoul, Paris, Milan, NY, and London collections. The content analysis and statistical analysis using SPSS will be conducted for data analysis. The results of the research are as follows. First, regarding the design features, square-form silhouette, achromatic colors, and none pattern were presented as well. Second, there were significant differences in the design characteristics of each year. Particularly, in 2008, X-form silhouette, Yellow and Green color, and flower pattern were emphasized. Third, the design features by season were significant differences. In S/S season, square-form and X-form silhouette, achromatic colors of white and gray color, none pattern were evident while in F/W season, square-form Silhouette, achromatic colors of black and gray, and none pattern were emphasized. Fourth, the design features by designer are as follows. In terms of form, Seoul collection was influenced by Paris collection. In terms of colors, it was influenced by NY and London collections.

• Communications for Statistical Applications and Methods
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• 제27권6호
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• pp.589-602
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• 2020

The development of smart grids has enabled the easy collection of a large amount of power data. There are some common patterns that make it useful to cluster power consumption patterns when analyzing s power big data. In this paper, clustering analysis is based on distance functions for time series and clustering algorithms to discover patterns for power consumption data. In clustering, we use 10 distance measures to find the clusters that consider the characteristics of time series data. A simulation study is done to compare the distance measures for clustering. Cluster validity measures are also calculated and compared such as error rate, similarity index, Dunn index and silhouette values. Real power consumption data are used for clustering, with five distance measures whose performances are better than others in the simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.667-669
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• 2003

Since the restructuring in electricity industry, single utility company, KEPCO, was being unbundled horizontanly and vertically, which resulted in 6 generation companies. Hence, electricity statistics system leaded by KEPCO is no longer efficiently sustainable. By introduction of electricity market, the importance of statistical information is getting higher and higher. From now on, the leading role played in statistical system in electricity field should be switched from KEPCO to government. This paper looks into change in statistical work driven by electricity and provides alternatives applicable to new electricity market. In addition, this paper provides new standard form for the collection of statistical data and construction of statistical system.

• 한국신뢰성학회지:신뢰성응용연구
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• 제10권1호
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• pp.39-56
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• 2010

Statistical process control (SPC) is a powerful technique for monitoring, managing, analysing and improving the process performance. However, its has limitations such as lack of engineering, statistical skill and training, and lesser importance of activity. To solve the problems, this study proposes an intelligent SPC system using specified agents which are derived through analysis and evaluation of the SPC activities. The activities investigated by the relevant researches are categorized as collection, process analysis, diagnosis, detection, cause analysis and rule generation. Also, the evaluation criteria are established as feasibility of automation, frequency, level and time. The requirements of the agent functions are derived by the evaluation, and the types of customized agents are as data collection, store, analysis, diagnosis, monitoring, alarm and reporting. A prototype SPC system represents that the functions of the proposed agents are successfully validated.