• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.24-30
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• 1978

This study was designed to analyse effects of Family Health Workers' activities on the performance of a child immunization program as part of the evaluative research in the community health demonstration project in Kang Wha. Frequent shortcomings of evaluative research are problems in setting evaluative indices, difficulties in interpreting influences of socioeconomic changes due to lack of control and failure of demonstrating association between activity input and program performance. Specific objectives of this study was to improve the frequent shortcoming of evaluative research by isolating the effects of Family Health Workers' activities on the performance of the program through controlling other variables which also influenced the program performance. The target population consisted of 1240 children who were born between Jan. 1971 and Dec. 1975 in Sunwon Myun, and Naega Myun in Kwang Wha Gun, Kyonggi Province. The data were collected in part through 20 Family Health Workers who interviewed the mothers of these children in their villages during Nov. 1977. Part of the data were obtained by summarizing Family Health Workers daily activity records. All data were grouped for each birth cohort according to the 20 villages. Dependent variable of the model is the measle immuinization rate of each village and the independent variables are characteristics of baby, mother, household, travel time to the health subcenter, to Kang Wha Town, and the mean member of visits to the household by Family Health Workers as well as their other related activities and the year of birth of children according to village. The model was analysed by stepwise multiple regression technique. The summarized results show that overall $R^2$ were 39.3% and mean number of Family Health Worker household visits, mean age of mother and mean economic status were significant variables in explaining the immunization rate. Therefore Family Health Workers' activities are one of the significant variables in influencing the increased immunization rate of children in villages of the project area.

• 한국벤처창업학회:학술대회논문집
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• 2021.04a
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• pp.33-42
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• 2021

Based on the findings of Lee et al.(2020) and Lee & Oh(2021), this paper aims to fill the gap in our knowledge regarding the relationship between strategic choices and corporate growth by utilizing a novel dataset of 'Unicorn' and 'Hyper-growing' companies. Two previous studies provide coherent findings that the relationship between firms' strategies and their performance should be explored under a more comprehensive framework with consideration of both internal and external factors. Therefore, in this study, we apply a single conceptual framework to two different datasets, which considers the strategy factors as independent variables, and the industry(market) and the firm age as moderating variables. For our dependent variables, valuations for unicorn companies and revenue CAGR for hyper-growing companies are used after categorizing them into three uniform groups. The strategy variables include 'Generic (Cost-leadership, Differentiation, focus) strategies', 'Growth(Organic, M&A) strategies', 'Leading(Pioneer, Fast-follower) strategies', 'Target market(B2B, B2C, B2G, C2C) strategies', 'Global(Global, Local) strategies', 'Digital(Online, Offline) strategies.' For industry(market) factors, it consists of historical growth rate for industries and economic, demographic, and regulatory aspects of states and countries. To overcome the differences in their units, they are also uniformly categorized into multiple groups. Before we conduct a regression analysis, we analyze the industry distribution of the 'Unicorn' and the 'Hyper-growing' companies with descriptive statistics at the integrated and individual levels. Next, we employ hierarchical regression models on Study A('Unicorn' companies in 2019) and Study B('Hyper-growing' companies in 2019) under the same comprehensive framework. We then analyze the relationship between the 'strategy' and the 'performance' factors with two different approaches: 1) an integrated regression model with both the sample of Study A and B and 2) respective regression models on Study A and B. This empirical study aims to provide a complete understanding and a reference to which strategy factors should be considered to promote firms' scale-up and growth.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.819-833
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• 2005

Code size reduction is ever becoming more important for compilers targeting embedded processors because these processors are often severely limited by storage constraints and thus the reduced code size can have a positively significant Impact on their performance. Various code size reduction techniques have different motivations and a variety of application contexts utilizing special hardware features of their target processors. In this work, we propose a novel technique that fully utilizes a set of hardware instructions, called the multiple load/store (MLS), that are specially featured for reducing code size by minimizing the number of memory operations in the code. To take advantage of this feature, many microprocessors support the MLS instructions, whereas no existing compilers fully exploit the potential benefit of these instructions but only use them for some limited cases. This is mainly because optimizing memory accesses with MLS instructions for general cases is an NP-hard problem that necessitates complex assignments of registers and memory off-sets for variables in a stack frame. Our technique uses a couple of heuristics to efficiently handle this problem in a polynomial time bound.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.219-225
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• 2019

There is a problem with the existing method of selecting the difficulty levels of Hanja characters. Some Hanja characters selected by the existing methods are different from Sino-Korean words used in real life and it is impossible to know how many times the Hanja characters are used. To solve this problem, we measure the difficulty of Hanja characters using the multiple regression analysis with the frequency as the features. Based on the elementary textbooks, FWS and FHU are counted. A questionnaire is written using the two frequencies and stroke together to answer the appropriate timing of learning the Hanja characters and use them as target variables for regression. Use stepwise regression to select the appropriate features and perform multiple linear regression. The R² score of the model was 0.1105 and the RMSE was 0.1105.

• Journal of Preventive Medicine and Public Health
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• v.54 no.4
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• pp.238-244
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• 2021

Objectives: Previous pandemics have demonstrated that several demographic, geographic, and socioeconomic factors may play a role in increased infection risk. During this current coronavirus disease 2019 (COVID-19) pandemic, our aim was to examine the association of timing of lockdown at the county level and aforementioned risk factors with daily case rate (DCR) in the United States. Methods: A cross-sectional study using publicly available data was performed including Americans with COVID-19 infection as of May 24, 2020. The United States counties with >100 000 population and >50 cases per 100 000 people were included. The independent variable was the days required from the declaration of lockdown to reach the target case rate (50/100 000 cases) while the dependent (outcome) variable was the DCR per 100 000 on the day of statistical calculation (May 24, 2020) after adjusting for multiple confounding socio-demographic, geographic, and health-related factors. Each independent factor was correlated with outcome variables and assessed for collinearity with each other. Subsequently, all factors with significant association to the outcome variable were included in multiple linear regression models using stepwise method. Models with best R² value from the multiple regression were chosen. Results: The timing of mandated lockdown order had the most significant association on the DCR per 100 000 after adjusting for multiple socio-demographic, geographic and health-related factors. Additional factors with significant association with increased DCR include rate of uninsured and unemployment. Conclusions: The timing of lockdown order was significantly associated with the spread of COVID-19 at the county level in the United States.

• Korea Journal of Hospital Management
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• v.12 no.1
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• pp.75-99
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• 2007

The purpose of this study was to provide basic materials needed to enhance quality of organizational life by identifying the improvements of labor union management in the perspective of general hospital organization management. The subjects of this study were 428 employees in 8 Hospitals in Metro Capital including Seoul. Materials were collected from administrators, nurses and medical technicians in target hospitals from November 10 to November 30, 2006 through survey questionnaires. The main results of this study were as follows: 1. The commitment level of the subjects according to their characteristics was higher in older employees than the younger ones, large family to support than small family to support and those who had higher positions in labor union. 2. The commitment level of the subjects according to the Job and role related variables were higher those who had higher satisfaction level to their job, role conflict in all hospitals. 3. The commitment level of the subjects according to union related variables, variables jointly controlled by union and employer was statistically significant positive correlation. 4. The results of multiple regression analysis shows that formal and informal socialization, satisfaction with the labor union's were all found as important antecedents of labor union commitment. 5. The results of AMOS shows that structure characteristics of hospital, Job and manager satisfaction, socialization were statistically significant labor union satisfaction. The satisfaction level of labor union was statistically significant labor union commitment To summarize study results, the level of commitment in labor union depends on job satisfaction, managers' attitudes, union satisfaction factors, their colleagues attitudes toward union. Therefore hospital managers should have democratic and flexible attitudes toward labor union. Additionally, as formal and informal socialization is important determinant in union commitment, hospital managers should have countermeasures to enhance the colleague attitude and job satisfaction level of hospital employees. Moreover, as managerial factors of the principal of hospital influence union commitment directly, the attitudes of hospital managers toward union and transparency of hospital management should be improved.

• Korean Journal of Community Nutrition
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• v.16 no.6
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• pp.683-696
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• 2011

This study compared levels of health beliefs and health behavior practices according to lifestyle pattern among adults in Seoul. A self-administered survey questionnaire was collected from a total of 1,004 Seoul residents aged 30-59 years. The levels of perceived benefit, perceived barrier, and self-efficacy from health belief model and health behavior practices were measured across multiple health behavior areas including dietary behavior, drinking, smoking, exercise, functional food consumption, and weight control behavior. Factor analysis and subsequent cluster analysis based on 28 lifestyle questions divided the subjects into four lifestyles of society-, economy-, trend-, and health-oriented lifestyle. Some general characteristics were significantly different by lifestyles. The society-oriented lifestyle was significantly higher in proportions of men and overweight. The trend-oriented lifestyle was significantly younger and spent more monthly allowance. Health-oriented lifestyle was older. The levels of health belief variables and health behavior practices significantly differed by lifestyles. Overall the health-oriented lifestyle showed more desirable levels of health belief variables and health behavior practice in various health behavior areas compared to the other lifestyles, whereas the society-oriented lifestyle was found the other way. Health belief model variables including perceived benefit, perceived barrier, and self-efficacy were generally significant in predicting the levels of various health behavior practice, with somewhat differences by lifestyle pattern and health behavior type. The study findings suggest it may be useful to segment target subjects according to lifestyle pattern in planning and administering health education programs.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• The Korean Journal of Health Service Management
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• v.2 no.1
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• pp.56-83
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• 2008

The purpose of this study was to provide basic materials needed to enhance quality of organizational life by identifying the improvements of labor union management in the perspective of general hospital organization management. The subject of this study were 686 employees in 12 General Hospitals in Metro Capital including Seoul. Materials were collected from administrators, nurses and medical technicians in target hospitals from March 20 to May 10, 2005 through survey questionnaires. The main results of this study were as follows: 1. the commitment level of the subjects according to their characteristics was higher in older employees than the younger ones, large family to support than small family to support and those who had higher positions in labor union. 2. The commitment level of the subjects according to the job and role related variables were higher those who had higher satisfaction level to their job and manager, role conflict in all hospitals. 3. The commitment level of the subjects according to union related variables, variables jointly controlled by union and employer was satistically significant positive correlation. In other words, the commitment level of the subjects according to the subjects' labor union involvement was higher in those who had higher satisfaction in labor union and perceived their colleagues' attitudes more positively in all hospitals. Regarding the atmosphere of the relationship between union and employer and the level of commitment in labor union, the better the atmosphere of the relationship between union and employer was, the higher the level of commitment in labor union was in all hospitals. 4. The results of multiple regression analysis shows that formal and informal socialization, union participation to the union management cooperation program, job satisfaction, satisfaction with the labor union's were all found as important antecedents of labor union commitment. 5. Job and role-related variables, union-related variables, variables jointly controlled by union and employer, and labor union commitment level were all found significantly different in accordance with the characteristics of unions concerned. To summarize study results, the level of commitment in labor union depends on job satisfaction, manager's attitudes, satisfaction to their jobs, union satisfaction, their colleagues attitudes toward union and the atmosphere of employer-employee relationship. Therefore hospital managers should have democratic and flexible attitudes toward labor union. Additionally, as formal and informal socialization, union participation to the union-management cooperation program is important determinant in union commitment, hospital managers should have countermeasures to enhance the colleague attitude and job satisfaction level of hospital employees. Since this study deals with psychological nature of workers not a few drawbacks and shortcomings may be detected in the finding. Nevertheless, the finding of this study, to become a momentum that will stimulate further research to detect all the cues of labor union commitment and to provide valuable reference in forming logical union commitment and labor union-management cooperation.

• Journal of Environmental Health Sciences
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• v.34 no.4
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• pp.316-326
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• 2008

The Earth's temperature has risen $0.76^{\circ}C$ (degree) during last 100 years which Implies a sudden rise, compare with the 4oC (degrees) rise through out the past 20,000 years. If the volume of GHG (Greenhouse Gas) emission continues at the current level, the average temperature of the Earth will rise by $1^{\circ}C$ (degree) by 2030 with the further implication that the temperature of Earth will rise by $2{\sim}5^{\circ}C$ (degrees) every 100 years. Therefore, as we are aware that the temperature of the glacial epoch was $8{\sim}9^{\circ}C$ (degrees) lower than the present time, we can easily predict that the above temperature rises can be potentially disastrous for human life. Every country in the world recognizes theseriousness of the current climate change and adopted a convention on climate change in June 1992 in Rio. The COP1 was held in March 1995 in Berlin and the COP3 in Dec. 1997 in Kyotowhere the target (2008-2012) was determined and the advanced nations' reduction target (5.2%, average)was also agreed at this conference. Korea participated in the GHG reduction plan which required the world's nations to ratify the Kyoto Protocol. Ratification of the Kyotoprotocol and the followup requirement to introduce an international emissions trading scheme will require severe reductions in GHGs and considerable economic consequences. USA are still refusing to fully ratify the treaty as the emission reductions could severely damage the economies of these countries. In order to estimate the exact $CO_2$ emission, this study statistically analyzed $CO_2$ emission of each country based on the following variables : level of economic power and scientific development, the industrial system, productivity and energy efficiency.