• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.225-239
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• 2020

Analysis approaches for single compositional data are well established; however, effective analysis strategies for paired compositional data remain to be investigated. The current project was motivated by studies of age-related hearing loss (presbyacusis), where subjects are classified into four audiometric phenotypes that need to be ranked within these phenotypes based on their paired compositional data. We address this challenge by formulating this problem as a classification problem and integrating a penalized multinomial logistic regression model with compositional data analysis approaches. We utilize Elastic Net for a penalty function, while considering average, absolute difference, and perturbation operators for compositional data. We applied the proposed approach to the presbyacusis study of 532 subjects with probabilities that each ear of a subject belongs to each of four presbyacusis subtypes. We further investigated the ranking of presbyacusis subjects using the proposed approach based on previous literature. The data analysis results indicate that the proposed approach is effective for ranking subjects based on paired compositional data.

• The Journal of Industrial Distribution & Business
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• v.11 no.7
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• pp.41-49
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• 2020

Purpose: The purpose of this study is to recognize the role and necessity of public data visualization through prior research, investigation, and data verification processes. In addition, this study intends to check what factors should be considered in order to visualize data on the mobile web. Through this process, by identifying the cognitive load affecting information visualization by type, as a result, I would like to propose an effective information visualization method to effectively deliver public data related to government policies. Research design, data and methodology: In this study, we analyzed the case of information visualization according to infographics, which has been widely used in the public field among various visualization methods. For this study, a questionnaire survey was conducted for young people in their 20s and 30s with the highest mobile usage rate. Results: Based on the results, IPA (Importance Performance Analysis) was performed to conduct cognitive load test tools for information visualization of public data and confirmed the implications for each type of infographics. Conclusions: As a result of research, in order to efficiently deliver public data on the mobile web, first, it is necessary to construct a visual screen that can be easily identified through clear data. Appropriate graphic elements can be used according to the type to make it easier for users to acquire and understand information. Second, it is necessary to provide useful content in visualizing information. Third, in order to efficiently transmit information and increase understanding of data, it is necessary to visualize information that can induce interest in data and form metaphors. Fourth, it is necessary to visualize information to reduce cognitive load in terms of physical and mental aspects in order to accommodate users' comfortable information. Fifth, in order to effectively deliver public data, it is necessary to compose contents and information that are easy for users to understand. This study examines effective information visualization methods to increase the communication effect of public data in response to changes in the data-based intelligent information society and suggests implications for each type considering cognitive loads to help future public institutions to communicate and accept information.

• Journal of Korea Planning Association
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• v.54 no.3
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• pp.49-62
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• 2019

In order to balance with supply policy, public housing management and operation policies have been implemented in terms of housing welfare, but citizens have not yet achieved the results that the citizens are experiencing. The purpose of this study is to analysis the residential satisfaction of the including the housing performance through the characteristics of the public housing residents in Seoul. The data used in this study is based on the survey data of public housing panel survey in Seoul (2016). The study method used ordered logistic regression analysis based on the fact that dependent variables appeared as ordered responses. Major research results are as follows. Firstly, housing performance and residential satisfaction may not match. Even though the satisfaction of housing area, type, and management fee is high, satisfaction with residential environment is low if commuting distance, the number of small libraries, and hospitals are small. Secondly, it showed different characteristics of residential environment factors among types of public housing. Rather than focusing on supply, customized supply is needed considering characteristics of public housing types. Thirdly, the policy for public housing needs to be realized by a fair policy on the residential environment. It is necessary to contribute to better housing stability as a customized policy considering the local residential environment.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.91-116
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• 2015

This study aims to provide public sectors with eco-efficiency information. To implement the purposes of the study, environmental and economic variables of Eco-Efficiency were identified through decision tree model, then the relative Eco-Efficiencies of 243 public sectors were evaluated through input-oriented DEA (Data Envelopment Analysis) model. Specifically, the amount of public purchasing per a staff and the amount of energy use per a staff were considered as input factors. Sales per a staff was considered as output factor. The result shows that most of the public sectors (94.2%) were evaluated as "inefficient" taking into consideration of average value, 0.501 from market-based public corporations, 0.288 from local public corporations, 0.28 from quasi-market-based public corporations, 0.269 from fund-management-based quasi-governmental institutions, 0.09 from non-classified public institutions, and 0.078 from commissioned-service-based quasi-governmental institutions. Furthermore, it is possible to establish a plan for internal Eco-Efficiency improvement based on information of the reference set. In order to improve the Eco-Efficiency in the public sectors in the long term, environmental impacts of the overall public sectors' operations (e.g., energy saving, water saving, waste reduction, and purchasing of green products) needs to be properly proposed in consideration of BSC (Balanced Scorecard) indicators of public sectors.

• Journal of Korean Library and Information Science Society
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• v.39 no.1
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• pp.99-117
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• 2008

The purpose of this study is to identify the main subjects of the reading programs which are provided by the public libraries during september, "the reading month," in 7 metropolitan cities, Seoul, Pusan, Daegu, Incheon, Daejeon, Gwangju, and Ulsan. To achieve this purpose, the data are collected from 622 programs of the sixty-two libraries. The content analysis method was used to analyze data and find results from it. The results are summarized as follows: 1. Reading and culture are identified as the main subjects of the programs. 2. The preferred subjects among the public libraries in 7 metropolitan cities are identified as different.

• Asian Journal for Public Opinion Research
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• v.8 no.3
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• pp.393-406
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• 2020

The discourse on the lockdown in Indonesia is getting stronger due to the increasing number of positive cases of the coronavirus and the death rate. As of August 12, 2020, the confirmed number of COVID-19 cases in Indonesia reached 130,718. There were 85,798 victims who have recovered and 5,903 who have died. Data show a significant increase in cases of COVID-19 every day. For this reason, there needs to be an evaluation of the government policy of the Republic of Indonesia in dealing with the COVID-19 pandemic in Indonesia. An evaluation of policies for handling the pandemic must include public opinion to determine any weaknesses of this policy. The development of public opinion about the lockdown policy can be understood through social media. During the COVID-19 pandemic, measuring public opinion through traditional methods (surveys) was difficult. For this reason, we utilized big data on social media as research data. The main purpose of this study is to understand public opinion on the lockdown policy in overcoming the COVID-19 pandemic in Indonesia. The things observed included: volume of Twitter users, top influencers, top tweets, and communication networks between Twitter users. For the methodological development of future public opinion research, the researchers outline the obstacles faced in researching public opinion based on big data from Twitter. The research results show that the lockdown policy is an interesting issue, as evidenced by the number of active users (79,502) forming 133,209 networks. Posts about the lockdown on Twitter continued to increase after the implementation of the lockdown policy on April 10, 2020. The lockdown policy has caused various reactions, seen from the word analysis showing 14.8% positive sentiment, 17.5% negative, and 67.67% non-categorized words. Sources of information who have played the roles of top influencers regarding the lockdown policy include: Jokowi (the president of the Republic of Indonesia), online media, television media, government departments, and governors. Based on the analysis of the network structure, it shows that Jokowi has a central role in controlling the lockdown policy. Several challenges were found in this study: 1) choosing keywords for downloading data, 2) categorizing words containing public opinion sentiment, and 3) determining the sample size.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1085-1089
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• 2015

Text-mining technique in the past had difficulty in realizing the analysis algorithm due to text complexity and degree of freedom that variables in the text have. Although the algorithm demanded lots of effort to get meaningful result, mechanical text analysis took more time than human text analysis. However, along with the development of hardware and analysis algorithm, big data technology has appeared. Thanks to big data technology, all the previously mentioned problems have been solved while analysis through text-mining is recognized to be valuable as well. However, applying text-mining to Korean text is still at the initial stage due to the linguistic domain characteristics that the Korean language has. If not only the data searching but also the analysis through text-mining is possible, saving the cost of human and material resources required for text analysis will lead efficient resource utilization in numerous public work fields. Thus, in this paper, we compare and evaluate the public document classification by handwork to public document classification where word frequency(TF-IDF) in a text-mining-based text and Cosine similarity between each document have been utilized in big data environment.

• Journal of Preventive Medicine and Public Health
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• v.22 no.2 s.26
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• pp.236-241
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• 1989

The purpose of this study was to introduce the methodology of intervention analysis with time series data and to investigate the influence of the patient referral system on medical care utilization in Kangwha county. The data were obtained at the Kangwha Medical Inurance Society and we analysed the material based on the outpatient care fee. The results were as fellows: 1. The average outpatient care utilization in the hospital decreased by 41.7% due to the patient referral system. 2. The utilization of the health instituation increased by 278.8 persons per month due to the patient referral system. 3. The patient referral system did not influence the total outpatient are utilization. The methodology of intervention analysis, which detected the effect of intervention, will be helpful to the study of public health area.

• The Korean Journal of Health Service Management
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• v.10 no.2
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• pp.15-23
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• 2016

Objectives : The purpose of this study was to evaluate the productivity changes of 18 public health centers in Gangwon-do from 2006 to 2013 using the Malmquist Productivity Index(MPI). Methods : Data were collected from Statistics Korea from 2006 to 2013. The input variables were the numbers of medical, nursing and administrative personnels. The output variables were the performances of health promotion programs. Along with the traditional input-oriented DEA analysis, the MPI was calculated. Results : First, among the 18 public health centers, the productivity index of 14 public health centers was increased. Second, the annual productivity showed a 6% increase. Third, the productivity improvements were mainly caused by Scale Efficiency Change. Conclusions : Improving the productivity of public health centers requires the support and external policies of the national and local government. Internally, public health centers need to maintain scale optimization of the center. Additionally, efforts should be made to effectively use limited resources.

• Health Policy and Management
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• v.25 no.2
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• pp.118-128
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• 2015

Background: We measured productivity changes of regional public hospitals using both global Malmquist productivity index-based on global production possibility set over all the periods-and the traditional Malmquist productivity index and analyzed the factors of productivity change. Methods: The data used in this study is two annual inputs and two annual outputs of 32 regional public hospitals in Korea from 2005 to 2009 and the results such as distances and Malmquist productivity index and global Malmquist productivity index are obtained by an R program written for this study. Results: The results can be summarized as follows. Firstly, technical efficiencies of regional public hospitals are affected largely by scale efficiency than pure technical efficiency. Second, productivity progressed and technological change has more significant influence on productivity advance over the period between 2005 and 2009. Third, the circularity problem of the traditional Malmquist index is confirmed, and so the global Malmquist index without this problem are valid for the analysis. Conclusion: Though this study also has some limitations with the data of regional public hospitals with a short time span, it is the first study of hospitals using global Malmquist productivity index and later it can be expanded to private hospitals and longer time periods.