• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.33-49
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• 2018

The importance of convergence activities among business is increasing due to the necessity of designing and developing new products to satisfy various customers' needs. In particular, decision makers such as CEOs are required to participate in networks between entrepreneurs for being connected with valuable convergence partners. Moreover, it is important for entrepreneurs not only to make a large number of network connections, but also to understand the networking relationship with entrepreneurs with similar topic information. However, there is a difficult limit in collecting the topic information that can show the lack of current status of business and the technology and characteristics of entrepreneur in industry sector. In this paper, we solve these problems through the topic extraction method and analyze the business network in three aspects. Specifically, there are C, S, T-Layer models, and each model analyzes amount of entrepreneurs relationship, network centrality, and topic similarity. As a result of experiments using real data, entrepreneur need to activate network by connecting high centrality entrepreneur when the corporate relationship is low. In addition, we confirmed through experiments that there is a need to activate the topic-based network when topic similarity is low between entrepreneurs.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.147-158
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• 2008

Fuzzy Cognitive Map (FCM) and Bayesian Belief Network (BBN) are two major frameworks for modeling, representing and reasoning about causal knowledge. Despite their extensive use in causal knowledge engineering, there is no reported work which compares their respective roles. This paper aims to fill the gap by providing a qualitative comparison of the two frameworks through a systematic analysis based on some inherent features of the frameworks. We proposed a set of comparison criteria which covers the entire process of causal knowledge engineering, including modeling, representation, and reasoning. These criteria are usability, expressiveness, reasoning capability, formality, and soundness. The results of comparison have revealed some important facts about the characteristics of FCM and BBN, which will help to determine how FCM and BBN should be used, with respect to each other, in causal knowledge engineering.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.127-136
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• 2022

As technological development continues, platforms with more diverse structures are emerging. Existing research predicts that a new structure based on technology and innovation will affect the two-sided market. This study evaluated the decentralized identifier (DID) platform, a new platform based on blockchain technology, of the importance of this platform from the perspective of the two-sided market. Using the Analytic Network Process, IT, platform, and blockchain experts conducted a dual comparison survey. Data with a consistency ratio value of 0.1 or less were selected and analyzed for 12 data. The research results showed the importance of service quality, policy support, openness, and uncertainty. This study is expected to be used to support the development of strategic decision-making for blockchain and DID platform-based business companies.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.469-469
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• 2017

기후 변화 및 환경오염으로 인하여 물부족 국가가 세계적으로 증가하고 있는 추세이며, 특히 집중형 강우의 형태가 많아짐에 따라 홍수피해 및 상수공급의 문제가 사회적으로 큰 이슈가 되고 있다. 최근 20여 년간의 급속한 경제성장과 도시화 과정에서 인도네시아는 인구와 산업의 과도한 도시집중으로 지난 1960-80년대 한국이 산업화 과정에서 겪었던 것보다 훨씬 심각한 환경문제에 직면하고 있으며, 자카르타와 반둥을 포함하는 광역 수도권 지역의 물 부족과 수질 오염, 환경문제가 이미 매우 위험한 수준에 도달하고 있는 실정이다. 특히, 찌따룸강 중상류에 위치한 인도네시아 3대 도시인 반둥시는 고질적인 용수부족 문제를 겪고 있다. 2010년 현재 약 일평균 15 CMS의 용수가 부족한 상황이며, 2030년에는 지속적인 인구증가로 약 23 CMS의 용수가 추가로 더 필요한 것으로 전망된다. 이러한 용수공급 문제 해결을 위해 반둥시 및 찌따룸강 유역관리청은 댐 및 지하수 개발, 유역 간 물이동 등의 구조적인 대책뿐만 아니라 비구조적인 대책으로써 기존 및 신규 저수지 연계운영을 통한 용수이용의 효율성을 높이는 방안을 모색하고 있다. 이에 따라 본 연구에서는 해당유역의 용수공급 부족 문제를 해소할 수 있는 비구조적인 대책의 일환으로써 다양한 댐 및 보, 소수력 발전, 취수장 등 유역 내 수리 시설물의 운영 최적화를 위한 지능형 물관리 시스템 적용 방안을 제시하고자 한다. 본 연구의 지능형 물관리 시스템은 센서 및 사물 인터넷(Internet of Things, IoT), 네트워크 기술을 바탕으로 시설물 및 운영자, 유관기관 간의 양방향 통신을 통해 유기적인 상호연계 체계를 제공 할 수 있다. 또한 유역의 수문상황과 시설물의 운영현황, 용수공급 및 수요 현황을 실시간으로 확인함으로써 수요에 따른 즉각적인 용수공급량의 조절이 가능하다. 또한, 빅데이터 분석 및 기계학습(Machine Learning)을 통해 개별 물관리 시설물에 대한 최적 운영룰을 업데이트할 수 있으며, 유역의 수문상황과 용수 수요 현황을 고려하여 최적의 용수공급 우선순위를 선정할 수 있다. 지능형 물관리 시스템 개발의 목적은 찌상쿠이 유역의 수문현황을 실시간으로 모니터링하고, 하천시설물의 운영을 분석하여 최적의 용수공급 및 배분을 통해 유역의 수자원 활용 효율성을 향상시키는 데 있다. 이를 위해 수문자료의 수집체계를 구축하고 기관간 정보공유체계를 수립함으로써 분석을 위한 기반 인프라를 구성하며, 이를 기반으로 유역 유출을 비롯한 저수지 운영, 물수지 분석을 수행하고, 분석 및 예측결과, 과거 운영 자료를 토대로 새로운 물관리 시설 운영룰 및 시설물 간 연계운영 방안, 용수공급 우선순위 의사결정 등을 지원하고자 한다. 본 연구의 지능형 물관리 시스템은 통합 DB를 기반으로 수리수문 현상의 모의 분석을 통해 하천 시설물 운영의 합리적 기준을 제시함으로써 다양한 관리주체들의 시설물운영에 대한 이견 및 분쟁을 해소하고, 한정된 수자원과 다양한 수요 간의 효율적이고 합리적인 분배 및 시설물 운영문제를 해결하기 위한 의사결정도구로써 활용할 수 있을 것으로 기대된다.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.107-116
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• 2014

The purpose of this study is to verify the applicability of concept mapping in the process of planning social welfare program based on community network. Concept mapping is a kind of decision-making method that structuralized complex ideas and presented visually. Already, concept mapping is widely utilized in counseling, nursing and public health area to plan and evaluation their program and service. For recent, effectiveness of concept mapping has been reported. Concept mapping is a effective decision-making method that they recognize outcome gap between service provider and client, reach the outcome's consensus in counseling and nursing, medical area. In this study, we conceptualized 3rd year outcomes of Community Impact Project that was supported from Busan Chest using concept mapping. This CI project intervenes children and youth who lives in Buk-gu, Busan. Concept mapping has six stages-preparation, collecting ideas, structuring statements, representing statement, interpreting the results of the analysis, applying the results. We followed these steps. The participants were working at social welfare organizations, total 11 persons. We obtained 60 statements and analyzed using multidimensional scaling. we collected 5 clusters, cluster 1 'awareness and attitude change of children and youth', cluster 2 'social system change of children and youth', cluster 3 'friendly community formation', cluster 4 'community people change', cluster 5 'service provider change'. As a result, among total 5 clusters formed, 'awareness and attitude change of children and youth' came to the strongest outcomes. When concept mapping was applied to the program planning, the consensus of the opinion came easily in the decision-making process, and the participants were empowered. In addition, clear conceptualization on each element of the program planning was made.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.143-152
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• 1999

South-eastern part of Kyungbuk Province is suffering from lack of suitable water development sources due to geographic condition and insufficient water sources condition. In order to find an appropriate solution, extensive studies are carried out such as investigation of new dam sites, regional water supply system, modification of existing water supply system, rehabilitation of old water resources structures and development of off-stream reservoirs. The network optimization model is applied for evaluation of the newly suggested water development alternatives. The results show that if water supply system is constructed until 2011, the reliability of water supply to Pohang and Kyungju region will be more than 95% and the network optimization model can be used to analyse the management of water resources system considering water rights or priority orders.

• Journal of Korea Port Economic Association
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• v.34 no.4
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• pp.17-38
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• 2018

The purpose of this study is to establish shipping companies' selection factors related to a classification society and to explore the relative importance of each factor using the analytical hierarchy process(AHP) technique. Insufficient research exists on the hierarchial structure of shipping companies' factors of selecting a classification society. The factors are identified and classified into two tiers of major and detailed factors, by referring to the related industrial linkages, prior research related to the determinants, and the process and service delivery of the classification society's activities. The empirical analysis of this study is based on the relative importance of determinants when selecting a classification society, and experts engaged with shipping companies were surveyed using questionnaires. The results of the AHP methodology on the main factors of shipping companies in selecting a classification society are as follows. The relative importance of the main factors was 0.373 for technical and survey services, 0.284 for recognized organizations(RO) functions, 0.177 for cost and 0.167 for market(related industry) expectations. The relative importance of the detailed factors is 0.144 for the ability to respond to a port state control(PSC) inspection, 0.143 for technical services, 0.090 for the requirements of financial institutions/ shippers/shipyards, 0.087 for class maintenance costs, 0.086 for the survey network, 0.085 for surveyor competency, 0.072 for cooperation with IMO and government authorities, 0.067 for recognition for RO, 0.058 for the business power of the classification society, 0.052 for the initial inspection costs, 0.040 for reputation and trustworthiness, 0.038 for the costs related to the class, and 0.037 for connections to related industries.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.373-384
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• 2014

Data mining is to clarify pattern or correlation of mass data of complicated structure and to predict the diverse outcomes. This technique is used in the fields of finance, telecommunication, circulation, medicine and so on. In this paper, we selected risk factors of respiratory diseases in the field of medicine. The data we used was divided into respiratory diseases group and health group from the Gyeongsangbuk-do database of Community Health Survey conducted in 2012. In order to select major risk factors, we applied data mining techniques such as neural network, logistic regression, Bayesian network, C5.0 and CART. We divided total data into training and testing data, and applied model which was designed by training data to testing data. By the comparison of prediction accuracy, CART was identified as best model. Depression, smoking and stress were proved as the major risk factors of respiratory disease.

• Knowledge Management Research
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• v.24 no.3
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• pp.195-215
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• 2023

In the telecommunications service industry, until now, it has been possible for Network Operators (NOs) to secure a competitive advantage to increase subscribers and profits through network investment. However, amid a big change to digital economy, network investment fails to lead to increase profits. These days platform companies without holing network infrastructure have a more competitive advantage and take more profits. This makes NOs gradually lose interest in network investment. The purpose of this paper is to find policy measures to promote network investment in digital economy. Specifically, we identify the factors influencing the network investment and promising policy measures energizing the investment, and then analyze their priorities and derive policy implications through Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). The results of this paper show that market competition is more preferred to public intervention in promoting network investment. However, in order to guarantee and expand the universal access to network, it is necessary to consider expanding the role of the public, focusing on non-economic areas.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.657-660
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• 2006

최근까지 데이터웨어하우스와 OLAP 에 관한 연구와 더불어 데이터 큐브(data cube)는 많은 다차원 데이터웨어하우스에서 데이터 분석과 의사 결정 지원을 위해 빠르게 OLAP 연산을 처리하기 위한 중요한 역할을 수행해 왔다. 최근에는 빠른 속도로 생성됨과 동시에 지속적으로 발생되는 연속적인 데이터로 구성된 데이터 스트림이 네트워크 트래픽 모니터링, 증권, 날씨, 콜 센터 등과 같은 많은 분야에서 생성된다. 데이터 스트림은 무한의 집합이기 때문에 기존의 데이터 큐브 방법은 처리시간과 저장공간의 문제 때문에 데이터 스트림에 적용하기 어렵다. 이에 본 논문에서는 기존의 데이터 큐브와 같은 데이터의 요약 정보를 데이터 스트림 환경에서 제한된 메모리를 이용하여 관리 할 수 있는 전원트리를 이용한 데이터 스트림 요약 기법을 제안하고, 실험을 통해 본 논문에서 제안한 방법이 데이터 스트림 환경에서 적응적으로 동작함을 증명한다.