• Journal of Sasang Constitutional Medicine
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• v.24 no.2
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• pp.47-53
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• 2012

1. Objectives : The aim of the present study was to describe the Korea Constitutional Multicenter Bank (KCMB), which was various clinical data bank for scientific advancement of constitutional diagnosis and treatment. 2. Methods and Results : The KCMB is based on the 28 multi-institute cooperative clinical research networks including domestic and international institute. Since the KCMB was founded in 2006, data have been accumulated from 10,412 subjects. The KCMB consists of three parts: The clinical constitutional data, the measurement data, and the biological data. The method of data entry is via web based electronic Case Report From (eCRF). The eCRF has been developed and programed to ensure the efficient entry of data. We also developed coding manual, ongoing quality control assessment to obtain high-quality data. 3. Conclusions : The KCMB with various data contribute to providing the scientification of Sasang Constitutional Medicine.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.153-170
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• 2020

The Educational Restitution Rate is an important parameter that determines the quality of university education. This paper analyzed data from 148 private universities over the 10 years from 2009 to 2018 using data mining techniques in Korea. A significant causal relationship is detected in the fixed effect model as a result of the panel estimation. And the scale of faculty expansion and fund management, which are the university evaluation indicators, and the size of basic funds, respectively, have a positive effect on the ERR, which is within the confidence interval. In the analysis, the more private universities improve the tuition dependence rate, the more decisively positive affecting ERR. As a result of nonparametric regression estimation, when the faculty expansion ratio is reinforced, the effect of economies of scale is detected in some sections, the improvement of the tuition dependence rate, and the result value is generated through the improvement that results are derived at a certain point in time. We hope that the university based on this study can be a basic Indicators for the diagnosis of basic competencies and policy of student-centered education.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.399-408
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• 2022

Because arrhythmia occurs irregularly, it should be examined for at least 24 hours for accurate diagnosis. For this reason, this paper developed firmware software for arrhythmia detection and prevented consumption of temporal and human resources and enabled continuous management and early diagnosis. Prior to the experiment, the interval between the R peaks of the QRS Complex was calculated using the Pan-Tompkins algorithm. The developed firmware software designed and implemented an algorithm to detect arrhythmia such as tachycardia, bradycardia, ventricular tachycardia, persistent tachycardia, and non-persistent tachycardia, and a data transmission format to monitor the collected data based on BLE. As a result of the experiment, arrhythmia was found in real time according to the change in BPM as designed in this paper. And the data quality for BLE communication was verified by comparing the sensor's serial communication value with the Android application reception value. In the future, wearable devices for real-time arrhythmia detection will be lightweight and developed firmware software will be applied.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.598-604
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• 2022

The academic information system of a university is the core system of the university, and since it has to manage all the various activities in the university, such as student academic records, it becomes complicated every year and the data increases indiscriminately. As a result, the reliability of the data of the academic information system is lowered, which causes communication problems with users and may cause a major failure in the system. Therefore, in this paper, column attribute analysis, allowable value list analysis, string pattern analysis, date type analysis, and unique value analysis methods were designed for the academic information system using the data profiling technique of data quality management. In the implementation stage, the script was implemented using the above five analysis methods, and by executing the script, errors by type of the academic information system were found, the cause of the error was found and corrected inside the system, and the probability of internal system failure was lowered.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.551-557
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• 2019

Diagnosis of abnormal faults is essential for producing high quality products. The role of real-time diagnosis is quite increasing in the batch processes of producing high value-added products such as semiconductors, pharmaceuticals, and so forth. In this study, we evaluate the effect of variable selection and future-value estimation techniques on the performance of the diagnosis system, which is based on nonlinear classification and measurement data. The diagnostic performance can be improved by selecting only the variables that are important and have high contribution for diagnosis. Thus, the diagnostic performance of several variable selection techniques is compared and evaluated. In addition, missing data of a new batch, called future observations, should be estimated because the full data of a new batch is not available before the end of the cycle. In this work the use of different estimation techniques is analyzed. A case study on the polyvinyl chloride batch process was carried out so that optimal variable selection and estimation methods were obtained: maximum 21.9% and 13.3% improvement by variable selection and maximum 25.8% and 15.2% improvement by estimation methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• Quality Improvement in Health Care
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• v.15 no.1
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• pp.123-133
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• 2009

Background : The principal diagnosis has been used in many different fields such as hospital statistics, medical research, insurance claim, national health statistics and so on. Some principal diagnoses have a relatively low level of reliability in the medium-sized hospitals. The purpose of this study is to identify the reliability level of principal diagnoses and to suggest ways to improve reliability of the principal diagnosis. Method : Data were collected from a medium-sized hospital located in Pusan. The discharge summaries on 323 patients who were discharged in January, 2008 and the outpatient summaries on 251 patients who visited the hospital on March 28, 2008 were collected, and descriptive analysis was performed using SPSS version 12.0K. Result : The findings are the followings: (1) the diagnostic consistency rate between medical records and doctors' was 92.0%; (2) the diagnostic consistency rate between medical records and insurance claims was 86.1%; (3) the diagnostic consistency rate between doctors' diagnoses and insurance claims was 80.2%. The evidence seems to indicate that some principal diagnoses have reliability problems in the medium-sized hospitals. Conclusion : The results of this study suggest the followings: (1) employees should be trained and supervision of hospital activities are needed; (2) network systems should be constructed for each department; (3) professions need to be fostered (4) doctors' awareness of medical records should be changed.

• Asian Oncology Nursing
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• v.1 no.1
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• pp.18-31
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• 2001

This Research was designed to develop an instrument that can be used for measuring and analysing the degree of the quality of life of the Allogenic bone marrow transplantation survivors and to provide basic data to help them attain a better quality of life. The subjects of this study were a total of 101 people who were undergone Allogenic bone marrow transplantation and were over 100 days after transplantation. Data were collected during the period from September 3 to December 2. 2000. In Developing this instrument, the researcher established a conceptual framework based on the result of previous research, interview of patients and medical staff and researcher's experience. The scale for this instrument consisted of 51 items. Responses were obtained from the respondents through a self reporting method and each item had a possible score of 5. The collected data were analyzed using the SPSS program. The reliability of the scale was tested by Cronbach‘s alpha. For the examination of the component factors of the measuring instruments, factor analysis method was used. Examination of the difference in the quality of life as related to demographic variables was done using t-test, analysis of variance(ANOVA). For the examination of the major variables influencing the quality of life, Pearson's Correlations was used. The results were as follows: (1) The reliability of the instrument was 0.90 (Cronbach's alpha) (2) The validity of the instrument was tested by factor analysis. The result of the factor analysis of the 51 items is making up the instruments were classified into the following factor; emotional state, Interpersonal problem, physical problem, spiritual state, social problem, decrease of physical energy, physical problem-eye, physical problem-skin and mucosa, health awareness, elimination problem, worry about health, financial problem, sexual problem. (3) Demographic variables related to quality of life is the time after transplantation. GVHD experience, lose of job. Age at the transplantation, diagnosis, type of the transplantation, marital status, monthly income, educational background, sex, religion are not related to the quality of life.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.65-77
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• 2017

The purpose of this paper is to develop a model of level evaluation for data governance that can diagnose and verify level of insufficient part of operating data governance. We expanded the previous study related on attribute indices of data governance and developed a level model of evaluation and items. The model of level evaluation for data governance is the level of evaluation and has items of 400 components. We used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a level evaluation model for data governance at the early phase. This paper will be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.61-77
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• 2022

The purpose of this study is to explain intention to use untact medical diagnosis and consultation services. We carried out the analysis of the survey data using Smart PLS 3.0 to test the hypotheses how the expected benefit variables and perceived risk variables of untact medical diagnosis and consultation services affect intention to use. According to the empirical analysis results, this study confirmed that quality of telemedicine service had a significant effects on perceived usefulness, Perceived Easy of Use. And accessibility had a significant effects on perceived easy of use, cost saving and expected benefits had a significant effects on use Intention of untact medical diagnosis and consultation services. Performance risk and service risk had a significant effect on medical risk. And medical risk had a significant negative(-) effects on use Intention of untact medical diagnosis and consultation services. This study has its meaning because it found out that it deals structurally and expansively with use intention of untact medical diagnosis and consultation services through positive and negative factors.