• Korea journal of population studies
• /
• v.16 no.2
• /
• pp.65-83
• /
• 1993

The purpose of this study is estimate limits of Korean life expectancy at birth by 'Gompertz growth curse Model', 'Cause-Elimination Model' and Multidimensional models of Senescencee and Mortality'. Data used in Gompertz curve were obtained from all life tables published from 1905 to 1990 in Korea, and life expectancies at birth of eighteen groups were selected at five-year interval in consideration of time-series changes. Data used in Cause-Elimination Model are 'Cause of Death statistics in 1991' published in 1992 by National Bureau of Statistics of Korea and 'life table of 1989' published in 1990 by National Bureau of Statistics, Economic Planning Board of Korea. The materials are all classifiable death data, 119, 253 cases of male and 82, 420 cases of female, which is from 1991 Causes of Death statistics. The cases of death analyzed belong to one of 8 categories; i.e., Infectious and Parasitic Diseases(001-139; with notation of Infectious Diseases), Malignant Neoplasms(140-208), Hypertensive Diseases(401-405), Ischemic Heart Dieases and Diseases of Pulmonary Circulation and Other Forms of Heart Diseases(410-429;with notation of Heart Disease), Cerebrovascular Diseases(430-438), Chronic Liver Diseases and Cirrhosis(571; with notation of Liver Diseases), Injury and Poisoning(800-999) and all other disease. Data used in 'Multidimensional models of senescence and mortality' were life table of 1989 published by National Bureau of statistics, Economic Planning Board of Korea and life table of 1970, 1978-79, 1983, 1985 and 1987. The major findings may be summarised as follows: 1. Estimate equations of Gompertz growth curve using life expectancy at birth during the 1905-1990 period are as the following. Male : y = 88.047697 $\times$ $0.199690^{0.903381x}$ Female : y = 95.632828 $\times$ $0.199690^{0.903381x}$ Limits of life expectancy at birth, which were estimated by Gompertz growth curve, are 88.05 for male and 95.63 for female. 2. The effect on life expectancy at birth eliminationg all causes death is 14.04 years(for male) and 10.86 years(for female). Astonishingly, eliminating the malignant neoplasms increase life expectancy at birth by 2.85 years for male 2.03 years for female in 1991. In table 8 we show the effect on life expectancy at birth of separately eliminating each of the 8 categorical causes of death. The theoretical limit to life expectancy by Cause-Elimination Model is 80.96 for male and 85.82 for female. 3. If the same rate of delay [0.376 year(male), 0.435 year(femable) per calendar year] continued, then life expectancy at birth would reach 74.82(male) years and 84, 10(female) years in 2010. With 14.04-years(male) and 10.86-years(female) effect attributable in 2010 would be 88.86 years(male) and 94.96(femable) years. 4. 'Multidimensional models of senescence and death' permits calculations of the value of the attribution coefficient (B), percent of loss per year of physiologic function. The results of Ro and B during the 1970-1989 period are listed in table 9. Estimate of limit to Korean life expectancy at birth by 'Multidimensional models of senescence and death' is 99.47 years for male and 104.74 years for female in 1989.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.2
• /
• pp.368-377
• /
• 2019

The purpose of this study is to examine the present operation process and to suggest the points of improvement so that vocational education and training institutions can be activated more effectively. The subjects of this study were 250 college students who completed or attended the vocational education and training course in Seoul and Gyeonggi-do, and collected 230 data, excluding inappropriate responses. Data analysis was performed by using the statistical package program SPSS Statistics (Ver. 24: IBM, USA). In this study, frequency analysis was conducted to examine the characteristics of data, and crossover analysis was conducted mainly to investigate the correlation between categorical data. The results of this study are as follows: First, it provides information about vocational education and training course to all general high school students at the beginning of the first year of high school, and then, from the first semester of the second grade, do. Second, it is to open four major courses in beauty education at the same time. This makes it possible to acquire qualifications according to four beauty courses during the training period at the training institute rather than the private education institute where private education expenses are incurred. By training all major courses in skin, hair, make-up, and nail art, you will be given the opportunity to carefully determine the major course that fits your aptitude. Based on the results of this research, we propose a plan to improve the vocational education system for vocational high school students who are majoring in cosmetology.

• Archives of design research
• /
• v.16 no.1
• /
• pp.35-44
• /
• 2003

In the past era, acquisition and utilization of useful information was the main origin of competition. Nowadays, unlike that era, is the era of knowledge information(management) in which we should create a new knowledge on the basis of information and apply it to the field of practice. And more acquisition of information is no more the competitive power of any person, any company and any nation because in such the era of knowledge management, anyone can access and get the information he needs, utilizing internet-based searching system. Such demands of the times of knowledge management change rapidly in each field through knowledge management system and researches about knowledge management are actively processed in various academic branches. However, in our field of design, researches about those demands(knowledge management) still remain on the level of one-dimensional searching service for general data about design. Therefore, in this study, we developed building database of researches on form, color, aesthetical elements, preference image word, satisfaction etc. about CI/BI of home electronics goods, living goods, apparels, and food goods companies, also suggesting searching system through which you can obtain useful data and information helpful for designers to process CI/BI works of new product by using that database. Especially, in case of developing specific CI/BI, various search results through help of suggested system will supply a useful design concept. And more, cross table which is the result of analysis two-dimensional categorical data about existing design factors(such as form, color, aesthetical elements, preference image word, and satisfaction) will make contribution for designers to create a new design knowledge.

• Journal of Korean Society of Forest Science
• /
• v.100 no.3
• /
• pp.455-465
• /
• 2011

In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.391-404
• /
• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of The Korean Society of Integrative Medicine
• /
• v.12 no.2
• /
• pp.89-100
• /
• 2024

Purpose : The objective of this study was to determine the major factors influencing the onset of diabetes and prediabetes and for collection of the basic data required to reduce the prevalence of diabetes and plan for administration of an effective health care system. By classifying the level of blood sugar management according to three categories: normal, prediabetes, and diabetes diagnosis, and determining the causes of diabetes in consideration of various variables, we will conduct an analysis of the main factors to be addressed for effective management of blood sugar and for preparation of basic data for use in early management. Methods : In this study, an analysis of raw data from the 8th National Health and Nutrition Examination Survey collected over a period of three years from 2019 to 2021, including 8,110 subjects in 2019, 7,359 subjects in 2020, and 7,090 subjects in 2021 was performed. A total of 22,559 subjects were aged 19 years or older, and 15,821 subjects were classified as subjects for inclusion in the final analysis. In the analysis, categorical variables were tested for difference, analysis of continuous variables using regression was performed, and analysis of influencing factors was performed using multinomial logistic analysis. Result : Significant factors related to the onset of diabetes and prediabetes included age (p<.001), marital status (p<.001), occupation (p<.001), hypertension (p<.001), dyslipidemia (p<.001), cardiovascular disease (p=.008), alcohol (p=.030) smoking (p=.005), systolic blood pressure (p<.001), diastolic blood pressure (p<.001), body mass index (p<.001) and waist circumference (p=.037), blood triglycerides (p<.001), and blood cholesterol (p<.001). Conclusion : Diabetes, a complex disease affected by a variety of diseases, requires active management from the prediabetes stage, and providing an appropriate level of medical information and services to elderly individuals without family support is considered a long-term health care system requirement in Korean society where the demographic structure is changing. In particular, determining the causes of prediabetes and development of a preventive approach to administering the health care system will be important for efficient management of diabetic patients.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.67-84
• /
• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Science of Emotion and Sensibility
• /
• v.20 no.3
• /
• pp.97-108
• /
• 2017

The purpose of this study was to propose a product planning and design direction for smart fitness wear that will improve the impact of personal training based on researching the requirements of smart fitness wear and its acceptance level, as well as the functional demand. The study conducted in-depth interviews with professional fitness trainers and derived five categories and thirteen keywords by analyzing the categorical data analysis using the interview data. In addition, we surveyed general consumers to measure the acceptance level of smart fitness wear and the functional demand for product development. The results revealed that the difference in the acceptance level of smart fitness wear generally depended on the characteristics related to exercise involvement and exercise-related culture rather than on the demographic characteristics. With regard to the difference in the functional demand of smart fitness wear, the results showed that professional trainers focused on the scientific improvement of the effect of exercise while general consumers focused on the function that considers the sustainability of exercise. Based on the results, we proposed product planning and design directions such as 'mounting of heart rate sensing, muscle activity sensing, motion angle or posture sensing, and motion sensing', 'development of concepts and contents for expert line, ordinary line', 'compression wear design', and 'differentiation of product development according to exercise areas'.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.5
• /
• pp.1699-1705
• /
• 2015

Background: Medication errors in oncology may cause severe clinical problems due to low therapeutic indices and high toxicity of chemotherapeutic agents. We aimed to investigate unintentional medication errors and underlying factors during chemotherapy preparation and administration based on a systematic survey conducted to reflect oncology nurses experience. Materials and Methods: This study was conducted in 18 adult chemotherapy units with volunteer participation of 206 nurses. A survey developed by primary investigators and medication errors (MAEs) defined preventable errors during prescription of medication, ordering, preparation or administration. The survey consisted of 4 parts: demographic features of nurses; workload of chemotherapy units; errors and their estimated monthly number during chemotherapy preparation and administration; and evaluation of the possible factors responsible from ME. The survey was conducted by face to face interview and data analyses were performed with descriptive statistics. Chi-square or Fisher exact tests were used for a comparative analysis of categorical data. Results: Some 83.4% of the 210 nurses reported one or more than one error during chemotherapy preparation and administration. Prescribing or ordering wrong doses by physicians (65.7%) and noncompliance with administration sequences during chemotherapy administration (50.5%) were the most common errors. The most common estimated average monthly error was not following the administration sequence of the chemotherapeutic agents (4.1 times/month, range 1-20). The most important underlying reasons for medication errors were heavy workload (49.7%) and insufficient number of staff (36.5%). Conclusions: Our findings suggest that the probability of medication error is very high during chemotherapy preparation and administration, the most common involving prescribing and ordering errors. Further studies must address the strategies to minimize medication error in chemotherapy receiving patients, determine sufficient protective measures and establishing multistep control mechanisms.

• Journal of the Korean Data and Information Science Society
• /
• v.11 no.1
• /
• pp.83-90
• /
• 2000

The chi-squared test statistic is usually employed for testing independence of two categorical variables in a two-way contingency table. It is well known that, under independence, the test statistic has an asymptotic chi-squared distribution under multinomial or product-multinomial models. For the case where both margins fixed, the sampling model of the contingency table is a multiple hypergeometric distribution and the chi-squared test statistic follows the same limiting distribution. In this paper, we study the difference between the small sample and large sample distributions of the chi-squared test statistic for the case with fixed margins. For a few small sample cases, the exact small sample distribution of the test statistic is directly computed. For a few large sample sizes, the small sample distribution of the statistic is generated via a Monte Carlo algorithm, and then is compared with the large sample distribution via chi-squared probability plots and Kolmogorov-Smirnov tests.