• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.6
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• pp.21-26
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• 2002

The propose of this study is to suggest objective data to be utilized for a plan and the improvement of open space through the analysis of people's behaviour and satisfaction after the introduction of an opened-fence around offices followed by a plan for wall-afforestation of public institution's. The sites examined are four offices; two of them have opened-walls and the others have traditional enclosure. Analysis of frequency is conducted to understand the actual use according to people's individual peculiarities. Pearson's correlation analysis, t-test, multiple regression analysis are carried out to find out relations of fluents. In the end, the satisfaction is high in public institution satisfaction, entrance, space perception. stability, Landscaped office with opened-fence rather than fence, and the increase in usage of fluent of public institution satisfaction, entrance, space perception. stability, confusion brings about rising of use-satisfaction. Satisfaction with the exterior of building is the most important variable that influences the whole urban open space. Furthermore the influences of the approach and stability having connection with open or not-open fence is major variable affecting satisfaction of use of open space. Whether open or not is important factor on satisfaction of open space of office building. Through this study, we can find that opened fence determines use satisfaction of resting space of outdoor-office. So factors affecting satisfaction must be regarded as important requisite on planning, design, development and management in plan for afforestation of fence at public institution.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.95-100
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• 2016

Background: Survival time of lymphoma patients can be estimated with the help of microarray technology. In this study, with the use of iterative Bayesian Model Averaging (BMA) method, survival time of Mantle Cell Lymphoma patients (MCL) was estimated and in reference to the findings, patients were divided into two high-risk and low-risk groups. Materials and Methods: In this study, gene expression data of MCL patients were used in order to select a subset of genes for survival analysis with microarray data, using the iterative BMA method. To evaluate the performance of the method, patients were divided into high-risk and low-risk based on their scores. Performance prediction was investigated using the log-rank test. The bioconductor package "iterativeBMAsurv" was applied with R statistical software for classification and survival analysis. Results: In this study, 25 genes associated with survival for MCL patients were identified across 132 selected models. The maximum likelihood estimate coefficients of the selected genes and the posterior probabilities of the selected models were obtained from training data. Using this method, patients could be separated into high-risk and low-risk groups with high significance (p<0.001). Conclusions: The iterative BMA algorithm has high precision and ability for survival analysis. This method is capable of identifying a few predictive variables associated with survival, among many variables in a set of microarray data. Therefore, it can be used as a low-cost diagnostic tool in clinical research.

• Journal of health informatics and statistics
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• v.43 no.4
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• pp.300-306
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• 2018

Objectives: The purpose of this study is to demonstrate empirically through a specialist AHP analysis what factors should be more important in the development of the public health care system. In addition, we will use Analytic Hierarchy Process (AHP) method for experts to achieve research purpose. Methods: The data analysis method of this study is as follows. First, we set up three metrics in order to measure the relative importance between the factors to be improved for the development of the public health care system and each of the sub-factors. A total of nine measurements (items) were set by combining the three measurement criteria for each measurement index. Second, the relative importance and priority analysis use the AHP analysis. Third, the subjects of this study were 15 experts in the field of public health care. The statistical processing was performed using the Expert Choice 2000 statistical program. Results: In order to development of the public health care system, experts ranked the most important as improvement in the systematic aspect of public health care (56%) as the first priority. Next, the relative importance analysis of the measurement items considering the multiple-weights of the sub-factors is as follows. The strengthen institutional improvement (revitalization of secondary public function hospital) was the number one, strengthen cooperation between agencies was the second, and Re-establishing the role of local public health care system was the third place. Conclusions: Considering the relative importance, factors that are considered to be important in the first place may not be improved as the best policy alternative due to limitations in spatial, temporal, financial, and institutional aspects. In this case, we suggest that we should choose the best policy alternative by using prioritization considering relative weights.

• Korea Journal of Hospital Management
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• v.24 no.2
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• pp.67-83
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• 2019

The aim of this study is to analyze the differences in the publicness indices depending on the environmental factors of regional public hospitals to derive the policy implications for improving management for regional public hospitals. The data of the 34 regional public hospitals from 2016 was used for the analysis. Major results of this study are as follows. First, the analysis of the differences in the scores of the medical safety net function showed significantly higher scores for regional public hospitals with a larger location, a larger number of hospitals in a unit area, a larger number of nurses per 100 beds, and the lower management fee ratio. Second, the analysis of the differences in the scores of the unmet healthcare needs showed significantly higher scores for regional public hospitals with a larger number of hospitals in a unit area, and a larger number of beds. Third, the analysis of the differences in the scores of the hospital-specialized services showed significantly higher scores for regional public hospitals with a larger location, a higher financial independence of the local government, a larger number of hospitals in a unit area, a larger number of beds, and a larger number of nurses per 100 beds. Major conclusions of this study are as follows. Consideration should be given to the appropriate number of nurses for each regional public hospital to maximize publicness by providing the appropriate amount of medical services, but not to incur unnecessary labor costs. In addition, efforts should be made to enhance profitability, which can be a means of strengthening publicness, by identifying the minimum administrative expenses required for efficient operation and reducing unnecessary administrative expenses. Finally, it is necessary to identify the appropriate number of beds to meet the needs of the customers and to create maximum profits.

• The Journal of Industrial Distribution & Business
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• v.11 no.10
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• pp.27-38
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• 2020

Purpose: The public sectors including government and public organizations have put an efforts to improve the quality of people's lives by providing enhanced services. The purpose of this paper is to investigate the factors that affect job attitude, job satisfaction, and job performance in the public sector, that are rarely examined by previous studies. Research Design, data, and methodology: The following research questions have been proposed: i) how do payroll system, personnel management system, cooperative working environment, and self-efficacy affect job attitude?; and ii) how does job attitude affect job satisfaction and performance? This paper used a survey through an online platform and collected data randomly from five classified public institutions. This study applied regression analysis and ANOVA. Results: This study found that cooperative working environment and self-efficacy had significant impacts on job attitude, while payroll system and personnel management system did not affect job attitude. Overall job attitude affected both job satisfaction and performance. Conclusions: The results provide policy implications to the public sector which factors should be considered to improve job attitude, job satisfaction, and job performance. The results also provide managerial implications how such efforts ultimately improve service quality to the citizens.

• Journal of agricultural medicine and community health
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• v.43 no.2
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• pp.74-84
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• 2018

Objectives: The purpose of this study is to compare the perceptions of the rural healthcare service improvement project' performance and reorganization of public health centers between project staffs and local residents. Methods: Data collection from this study was performed in 141 project areas using structured questionnaires. Data analysis was used in SPSS 22.0 version. Results: The public health center staffs were more positive about the items for improving health facilities than the local residents. Residents in the Si area generally perceived performance as more positive than residents in the Gun area, while public health center staffs in the Gun area perceived performance as more positive than public health center staffs in the Si area. Local residents expressed negative opinions about the reduction in the number of branches of public health clinics and health medical clinics. Conclusions: In conclusion, careful improvement projects for rural health care and the establishment of health care systems will be necessary, reflecting the opinions of local residents, along with a variety of regional characteristics.

• Journal of Industrial Convergence
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• v.14 no.2
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• pp.25-31
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• 2016

As the importance of big data begins to be recognized, the government, local self-governing bodies, and corporations have taken interest in big data. However, unlike the past, there is various typical and atypical data, and some fields make use of big data planning and analytical technique, which is opening a way to capture new opportunities. The present study analyzes an improvement plan for bicycle roads by using the public data of Seoul and proposes its implications.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1347-1356
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• 2017

Artificial intelligence-based services are expanding into a new industrial revolution. There is artificial intelligence technology applied in real life due to the development of big data and deep learning related technology. And data analysis and intelligent assistant services that integrate information from various fields have also been commercialized. Chatbot with interactive artificial intelligence provide shopping, news or information. Chatbot service, which has begun to be adopted by some public institutions, is now just a first step in the steps. This study summarizes the services and technical analysis of chatbot. and the direction of public administration service chatbot was presented.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.13-25
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• 2017

Volume in data storage is growing more than ever before. This phenomenon is caused by the participation of governments and firms as well as general users. As for big data, governments and public agencies are likely to play important roles in applications since they can access and operate personal data for public purposes. In this study, the author examined the status and countermeasure of big data from different countries and drew some common grounds. The suggestions are as follows. First of all, securing manpower and technology have to take precedence. In addition, share and development between the government and the private sector are required. And organizations should come up with long-term strategies along with the development of data loading and analysis. In conclusion, the author propose the recognition of the importance of data management, privacy protection and the expansion of field application possibilities for political usage of big data.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.101-113
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• 2017

This study examines the mobility of the disadvantaged population groups in terms of public transportation using the 2014 smart card data in Seoul, Korea. Particularly, we focus on the disadvantaged population such as senior group, junior group, and low-income population group. Based on the spatial distributions of public transportation mobility levels and the disadvantaged population groups, we identify specific areas where public transportation service should be improved for the disadvantaged population. As a result, we identify 15 administrative-dongs where the ratio of the disadvantaged population is high while the mobility index of public transit is low. The main contributions of this study are as follows. First, we use the smart card data which contains the information of actual trip made by individuals and develop the evaluation process of urban mobility for the disadvantaged population groups. Second, we identify the specific areas where public transportation service should be improved for the different group of the disadvantaged population. Lastly, we discuss policy implications to improve the urban mobility of the disadvantaged population.