• Title/Summary/Keyword: 의사결정체계

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Development of prediction model identifying high-risk older persons in need of long-term care (장기요양 필요 발생의 고위험 대상자 발굴을 위한 예측모형 개발)

  • Song, Mi Kyung;Park, Yeongwoo;Han, Eun-Jeong
    • The Korean Journal of Applied Statistics
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    • v.35 no.4
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    • pp.457-468
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    • 2022
  • In aged society, it is important to prevent older people from being disability needing long-term care. The purpose of this study is to develop a prediction model to discover high-risk groups who are likely to be beneficiaries of Long-Term Care Insurance. This study is a retrospective study using database of National Health Insurance Service (NHIS) collected in the past of the study subjects. The study subjects are 7,724,101, the population over 65 years of age registered for medical insurance. To develop the prediction model, we used logistic regression, decision tree, random forest, and multi-layer perceptron neural network. Finally, random forest was selected as the prediction model based on the performances of models obtained through internal and external validation. Random forest could predict about 90% of the older people in need of long-term care using DB without any information from the assessment of eligibility for long-term care. The findings might be useful in evidencebased health management for prevention services and can contribute to preemptively discovering those who need preventive services in older people.

A research on the Construction and Sharing of Authority Record-focusing on the Case of Social Networks and Archival Context Project (전거레코드 구축 및 공유에 관한 연구 SNAC 프로젝트 사례를 중심으로)

  • Lee, Eun Yeong
    • The Korean Journal of Archival Studies
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    • no.71
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    • pp.49-89
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    • 2022
  • This study suggests the necessity and domestic application plan a national authority database that promotes an integrated access, richer search, and understanding of historical information sources and archival resources distributed among cultural heritage institutions through the "Social Networks and Archive Context" project case. As the SNAC project was transformed into an international cooperative organization led by NARA, it was possible to secure a sustainable operating system and realize cooperative authority control. In addition, SNAC authority records have the characteristics of providing richer contextual information about life and history and social and intellectual network information compared to libraries. Through case analysis, First, like SNAC, a cooperative body led by the National Archives and having joint ownership of the National Library of Korea should lead the development and expand the scope of participating institutions. Second, in the cooperative method, take a structure in which divisions are made for each field with special strengths, but the main decision-making is made through the administrative team in which the two organizations participate. Third, development of scalable open source software that can collect technical information in various formats when constructing authority data, designing with the structure and elements of archival authority records, designing functions to control the quality of authority records, and building user-friendly interfaces and the need for a platform design reflecting content elements.

Trend Forecasting and Analysis of Quantum Computer Technology (양자 컴퓨터 기술 트렌드 예측과 분석)

  • Cha, Eunju;Chang, Byeong-Yun
    • Journal of the Korea Society for Simulation
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    • v.31 no.3
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    • pp.35-44
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    • 2022
  • In this study, we analyze and forecast quantum computer technology trends. Previous research has been mainly focused on application fields centered on technology for quantum computer technology trends analysis. Therefore, this paper analyzes important quantum computer technologies and performs future signal detection and prediction, for a more market driven technical analysis and prediction. As analyzing words used in news articles to identify rapidly changing market changes and public interest. This paper extends conference presentation of Cha & Chang (2022). The research is conducted by collecting domestic news articles from 2019 to 2021. First, we organize the main keywords through text mining. Next, we explore future quantum computer technologies through analysis of Term Frequency - Inverse Document Frequency(TF-IDF), Key Issue Map(KIM), and Key Emergence Map (KEM). Finally, the relationship between future technologies and supply and demand is identified through random forests, decision trees, and correlation analysis. As results of the study, the interest in artificial intelligence was the highest in frequency analysis, keyword diffusion and visibility analysis. In terms of cyber-security, the rate of mention in news articles is getting overwhelmingly higher than that of other technologies. Quantum communication, resistant cryptography, and augmented reality also showed a high rate of increase in interest. These results show that the expectation is high for applying trend technology in the market. The results of this study can be applied to identifying areas of interest in the quantum computer market and establishing a response system related to technology investment.

A Study on Family Support Service for Adoptive Families in terms of Necessity and Role of the Family Center (가족센터(구 건강가정지원센터)의 입양가족 대상 서비스 제공의 필요성과 역할 정립에 관한 연구)

  • Lee, Sunhyung;Bae, Jiyeon
    • Journal of Family Resource Management and Policy Review
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    • v.26 no.2
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    • pp.1-17
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    • 2022
  • This study provides a critical analysis of the Family Center's programs for adoptive families by interviewing employees at these centers and at Adoption Agencies who have experiences with adoption programs. For this study, nine such workers from three separate Family Centers and three such workers from two separate Adoption Agencies have (voluntarily) engaged in in-depth interviews. Major findings from the interviews are that the Family Centers were initially motivated to carry out adoption family programs for three principal reasons: they located many families (in need of adoption family program); potential adoptees were interested in the program; adoption families participated in the pre-existing programs such as Self-help Group and Co-parenting Space. Workers in the study also reported that they approach to an adoption family and their contemplation on ways to provide better services to the adoption families. They don't have any official and formal manual or guidelines from the Government Ministries and offices such as Korean Institute for Healthy Family; as a result, the workers at Family Centers have endeavored to gain connection with Adoption Agencies in hopes of cooperation with them and to improve the services at Family Centers. For benefits of Family Centers as a delivery system, they mentioned nationwide infrastructure, family professional, and arrangement of integrated program for family. For improvements, they listed awareness education based on a thorough consideration of adoptee's varied characteristics, close cooperation with adoption institutions, provision of basic operational manual from Korean Institute for Healthy Family, and governmental efforts to enlarge the consideration pool for families.

Predicting the amount of water shortage during dry seasons using deep neural network with data from RCP scenarios (RCP 시나리오와 다층신경망 모형을 활용한 가뭄시 물부족량 예측)

  • Jang, Ock Jae;Moon, Young Il
    • Journal of Korea Water Resources Association
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    • v.55 no.2
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    • pp.121-133
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    • 2022
  • The drought resulting from insufficient rainfall compared to the amount in an ordinary year can significantly impact a broad area at the same time. Another feature of this disaster is hard to recognize its onset and disappearance. Therefore, a reliable and fast way of predicting both the suffering area and the amount of water shortage from the upcoming drought is a key issue to develop a countermeasure of the disaster. However, the available drought scenarios are about 50 events that have been observed in the past. Due to the limited number of events, it is difficult to predict the water shortage in a case where the pattern of a natural disaster is different from the one in the past. To overcome the limitation, in this study, we applied the four RCP climate change scenarios to the water balance model and the annual amount of water shortage from 360 drought events was estimated. In the following chapter, the deep neural network model was trained with the SPEI values from the RCP scenarios and the amount of water shortage as the input and output, respectively. The trained model in each sub-basin enables us to easily and reliably predict the water shortage with the SPEI values in the past and the predicted meteorological conditions in the upcoming season. It can be helpful for decision-makers to respond to future droughts before their onset.

Improvement of ISMS Certification Components for Virtual Asset Services: Focusing on CCSS Certification Comparison (안전한 가상자산 서비스를 위한 ISMS 인증항목 개선에 관한 연구: CCSS 인증제도 비교를 중심으로)

  • Kim, Eun Ji;Koo, Ja Hwan;Kim, Ung Mo
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.8
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    • pp.249-258
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    • 2022
  • Since the advent of Bitcoin, various virtual assets have been actively traded through virtual asset services of virtual asset exchanges. Recently, security accidents have frequently occurred in virtual asset exchanges, so the government is obligated to obtain information security management system (ISMS) certification to strengthen information protection of virtual asset exchanges, and 56 additional specialized items have been established. In this paper, we compared the domain importance of ISMS and CryptoCurrency Security Standard (CCSS) which is a set of requirements for all information systems that make use of cryptocurrencies, and analyzed the results after mapping them to gain insight into the characteristics of each certification system. Improvements for 4 items of High Level were derived by classifying the priorities for improvement items into 3 stages: High, Medium, and Low. These results can provide priority for virtual asset and information system security, support method and systematic decision-making on improvement of certified items, and contribute to vitalization of virtual asset transactions by enhancing the reliability and safety of virtual asset services.

A Spatial Analysis of Seismic Vulnerability of Buildings Using Statistical and Machine Learning Techniques Comparative Analysis (통계분석 기법과 머신러닝 기법의 비교분석을 통한 건물의 지진취약도 공간분석)

  • Seong H. Kim;Sang-Bin Kim;Dae-Hyeon Kim
    • Journal of Industrial Convergence
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    • v.21 no.1
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    • pp.159-165
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    • 2023
  • While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

A Study on Implementing BSC in the Public Enterprises : The Case of Korea Southern Power (공기업의 BSC 구축에 관한 연구: 한국남부발전(주) 사례를 중심으로)

  • Suh, Woo-Jong;Park, Jin-Bae;Hong, Jin-Won
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.4
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    • pp.163-182
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    • 2009
  • The BSC(Balanced Scorecard), a strategic performance evaluation system, has drawn attention as an innovative tool for improving an organization's performance. Recently, the Korean government has recognized the advantages of the BSC and encouraged public enterprises to implement the BSC. However, it has been pointed out that many public enterprises have faced difficulties in constructing and operating the BSC due to lack of clear understanding, a complex environment of performance evaluation, and inherent features of organizational culture. Therefore, this study analyzed a project case of a public enterprise, Korea Southern Power (KSP), which has ever been assessed as an excellent organization in implementing BSC and managing performance. This paper provides procedures, activities, resources (manpower and time), and decision-making issues and criteria required for implementing BSC, along with real project outcomes of the company. Such project details are expected to be used as helpful guidelines for public or non-profit organizations's BSC implementation. Furthermore, the KSP's efforts to cope with its problems and implications derived from the efforts are also expected to help other organizations construct and operate the BSC effectively.

A Basic Study on 'Ruralism' Perception through Expert Group: Focusing on Delphi and AHP Analysis (전문가집단을 통해 본 '농촌다움' 인식에 관한 기초연구: 델파이와 AHP분석을 중심으로)

  • Jee Yoon Do;Ki Chun Seo;Myeong Cheol Jeong;Jin Ah Choi
    • Journal of Environmental Impact Assessment
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    • v.32 no.4
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    • pp.251-259
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    • 2023
  • This study was conducted for the purpose of the basic direction for the new regulations and categories of Ruralism changing in the new era. To this end, the results of Delphi analysis and AHP analysis by dividing it into the definition, criteria, scope and component items of Ruralism based on systematic literature review are as follows. First, through studies representing most rural areas, it was found that Ruralism was the most problematic keyword and most of the studies did not cover it as they were studying various ranges of rural areas. Second, the Delphi survey was able to derive keywords that can be used as evidence for item classification and clear concept establishment for the regulation and category setting of Ruralism. Third, through the hierarchical decision-making method, it was found that landscape factors are the most important thing in forming Ruralism as well as deriving priorities that can be a baseline for each item. This study is meaningful in providing a minimum baseline as basic data for establishing the concept of Ruralism, and it is believed that future-oriented Ruralism can be established if reviews are added from various perspectives to overcome limitations dependent on expert groups.

A study on the Construction of a Big Data-based Urban Information and Public Transportation Accessibility Analysis Platforms- Focused on Gwangju Metropolitan City - (빅데이터 기반의 도시정보·접대중교통근성 분석 플랫폼 구축 방안에 관한 연구 -광주광역시를 중심으로-)

  • Sangkeun Lee;Seungmin Yu;Jun Lee;Daeill Kim
    • Smart Media Journal
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    • v.11 no.11
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    • pp.49-62
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    • 2022
  • Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.