• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.08a
• /
• pp.187-192
• /
• 2008

최근 자신의 건강에 대한 관심이 고조되고 있는 반면, 현재 대부분 On-line에서 제공되는 진단 서비스 시스템은 질병 명을 이용하여 질병에 대한 처방이나 민간요법 등을 제시하고 있다. 이에 질병에 대해 전문지식이 부족한 일반인들이 이용하기에는 어려움이 있다. 따라서 본 논문에서는 On-line에서 퍼지 ART 알고리즘을 이용하여 사용자가 제시한 증상을 바탕으로 이미 학습되어진 질병의 증상과 비교하여 신경망을 통해 유사도가 높은 상위 3개의 질병을 도출한다. 도출된 질병에 대해 질병의 전체적인 증상과 동의보감에서 제시한 민간요법을 결과로 출력한다. 질병 데이터베이스는 서울대학교에서 교육용으로 출판한 가정의학(家庭醫學)을 기초로 동의보감과 한방의학백과서적을 통해 한의학 전문의의 검증을 거쳐 생성하였다. 그리고 본 시스템은 전문의의 상담시스템을 지원한다. 전문의의 상담시스템을 이용하여 자택 및 직장에서 편리하게 전문의의 진료와 소견을 받을 수 있도록 하였다. 전문의 상담 시스템은 전문의가 서버에 접속한 상태에서 사용자의 진로 신청으로 연결되며, 텍스트 데이터 및 기존의 진료기록이 있다면 이를 기반으로 전문의의 진단을 유도하도록 한다. 제안된 한방 자가 진단 시스템을 한의학 전문의가 분석한 결과 기존의 질병 진단 시스템 보다 일반성이 개선된 것을 확인하였다.

• Journal of the Economic Geographical Society of Korea
• /
• v.23 no.1
• /
• pp.1-17
• /
• 2020

The study aims to identify economic interdependencies between regions and define functional economic areas of Korea by analyzing inter-firm transaction networks. Previous research has relied on pre-given administrative boundaries or cultural homogeneity and used data such as commuting, population movement, and cargo flows which could not fully explain economic activities. To overcome the limitations, this study applies a community detection method to inter-firm transaction networks derived from the CRETOP+ database of Korean corporate data. The novel dataset and the network analysis enables us to identify Korea's functional economic areas based on actual inter-firm linkages. The result shows that there are six to seven economic blocs in the networks as of 2018. In particular, one huge economic bloc is formed integrating the Seoul metropolitan area, Chungcheong, and Gangwon provinces. Meanwhile, North Jeolla and South Jeolla provinces form two economic blocs separately rather than being tied up in one bloc due to the low frequency of transactions between each other. The two big economic blocs of Daegu-Gyeongbuk and Busan-Gyeongnam exist, and interestingly, Ulsan, Gyeongju, and Pohang form a separate middle-sized bloc across the administrative boundaries. The results reveal that the future balanced national development policies should be implemented based on functional economic areas derived from empirical data.

• Journal of Intelligence and Information Systems
• /
• v.14 no.2
• /
• pp.193-206
• /
• 2008

Medical diagnosis can be considered a classification task which classifies disease types from patient's condition data represented by a set of pre-defined attributes. This study proposes a hybrid genetic algorithm based classification method to develop classifiers for multidimensional pattern classification problems related with medical decision making. The classification problem can be solved by identifying separation boundaries which distinguish the various classes in the data pattern. The proposed method fits a finite number of regional agents to the data pattern by combining genetic algorithms and local adaptive operations. The local adaptive operations of an agent include expansion, avoidance and relocation, one of which is performed according to the agent's fitness value. The classifier system has been tested with well-known medical data sets from the UCI machine learning database, showing superior performance to other methods such as the nearest neighbor, decision tree, and neural networks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.431-435
• /
• 2005

Mobile Ad-Hoc network is the network(MANET) of mobile nodes which has no fixed infrastructure, and mobile node in MANET can move and communicate freely each other. Recently, many researches for mobility management of mobile nodes are actively carried out by using the location information of mobile nodes. The location management is an important issue in MANET because location information of mobile node is frequently changed in MANET. In this paper, an adaptive mobility management scheme using fuzzy-logic based GQS by considering the mobile locality is proposed in order to manage location information of mobile nodes in MANET efficiently. The proposed scheme selects mobility databases adaptively from GQS by considering the locality of mobile node. The performance of the mobility management scheme proposed in this paper is evaluated by an analytic model and compared with that of existing UQS based mobility management scheme.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2000.11a
• /
• pp.575-585
• /
• 2000

본 사업은 1994년부터 1996년까지 3년 간 시범사업으로 추진된 지역정보화 사업의 과제인 창원/마산 지역정보 유통망 구축사업을 확대 발전시키고 시스템 운영의 효율화를 도모하고자 DB를 통합하여 확대 재 구축함으로써 전자상거래 기반의 인터넷을 통한 웹 정보 이용 활성화 차원에서 추진되었다. 기 구축되었던 $\ulcorner$창원/마산 지역정보유통망 구축사업$\lrcorner$은 정보화를 통한 지역경제 발전에 일익을 담당하고자 관. 산. 연이 참여한 지역정보화 사업이다. 이러한 창원/마산지역 산업체에 대한 지원효과를 이번에 확대하여 그 동안 Multimedia, Graphics, Web 등 정보화 환경이 크게 변화, 발전됨에 따라 현실적이며 현장적용형 패키지의 개발 지원이 대두된 $\ulcorner$경남지역 정보화확산사업$\lrcorner$은 연구개발정보센터와 창원시, 진해시, 한국기계연구원이 매칭 펀드에 의한 대응자금으로 구축한 시스템이다. 정보수집대상은 경남지역에 소재하고 있는 20개 산업단지 3,700여 입주기업을 정보수집요원이 직접 방문하여 현장에서 필요로 하는 요구정보를 반영하였다. 신규로 구축한 정보는 산업기반 기업체기본정보 DB 및 기업 기술개발 현장적용형 기술정보 패키지정보를 중심으로 구축하였으며, 인터넷 활용교육을 통한 동종 업종간 정보교류체제 구축하였다. 특히 Cyber Market을 구현하기 위해 1,200여건의 기업체정보 및 제조상품 DB를 응용한 제품 Mall 데이터베이스를 구축하였다. 본 사업을 통하여 경남지역 산업단지에 입주한 기업체의 정보 활용을 극대화하여 지역경제 발전에 기여함과 동시에 국내 지역정보화 시범모델로서 위상을 확립하고자 한다.을 기업의 타인자본비용과 자기자본비용의 조합인 기회자본비용으로 할인함으로써 현재의 기업가치를 구할 수 있기 때문이다. 이처럼 기업이 영업활동이나 투자활동을 통해 현금을 창출하고 소비하는 경향은 해당 비즈니스 모델의 성격을 규정하는 자료도로 이용될 수 있다. 또한 최근 인터넷기업들의 부도가 발생하고 있는데, 기업의 부실원인이 어떤 것이든 사회전체의 생산력의 감소, 실업의 증가, 채권자 및 주주의 부의 감소, 심리적 불안으로 인한 경제활동의 위축, 기업 노하우의 소멸, 대외적 신용도의 하락 등과 같은 사회적·경제적 파급효과는 대단히 크다. 이상과 같은 기업부실의 효과를 고려할 때 부실기업을 미리 예측하는 일종의 조기경보장치를 갖는다는 것은 중요한 일이다. 현금흐름정보를 이용하여 기업의 부실을 예측하면 기업의 부실징후를 파악하는데 그치지 않고 부실의 원인을 파악하고 이에 대한 대응 전략을 수립하며 그 결과를 측정하는데 활용될 수도 있다. 따라서 본 연구에서는 기업의 부도예측 정보 중 현금흐름정보를 통하여 '인터넷기업의 미래 현금흐름측정, 부도예측신호효과, 부실원인파악, 비즈니스 모델의 성격규정 등을 할 수 있는가'를 검증하려고 한다. 협력체계 확립, ${\circled}3$ 전문인력 확보 및 인력구성 조정, 그리고 ${\circled}4$ 방문보건사업의 강화 등이다., 대사(代謝)와 관계(關係)있음을 시사(示唆)해 주고 있다.ble nutrient (TDN) was highest in booting stage (59.7%); however no significant difference was found among other stages. The concentrations of Ca and P were not different

• International Journal of Highway Engineering
• /
• v.3 no.2 s.8
• /
• pp.141-147
• /
• 2001

Maintenance cost for managing the whole network of Expressway system in Korea increases rapidly with the increase of the total length of the system. Implementation of the Pavement Management System(PMS) is essential for efficient management of the Expressway with a limited budget. The purpose of this study is to develop the main algorithm of PMS for Korea Expressway System and to associate the algorithm with database and the Highway Geographic Information System(HGIS) recently developed. Emphasis is laid on developing the algorithm as easy as possible, so that the users can use the PMS without practical difficulty. PMS is not the decision maker, but just a supporting system for the user. The algorithm is designed in such a way that the users can modify the decision criteria if necessary. The user is the one who makes the final decision of the priority and the maintenance alternatives. The users can also inquire the current condition of the whole Expressway network in detail by association of the database and the algorithm with HGIS.

• Journal of Digital Convergence
• /
• v.12 no.6
• /
• pp.637-643
• /
• 2014

The purpose of this study was twofold: 1) to analyze the impact factor of clothing and textile-related journals by utilizing the average number of cross-citation that evaluates the relative importance of an academic journal and 2) to provide a list of journals with higher impact factor by analyzing closeness and betweenness among individual journals through graph networks. To fulfill this, a total of 10 clothing and textile-related journals, which are accredited by National Research Foundation of Korea, were analyzed. For analysis of the average number of cross-citation, the targeted research papers were limited to those published between 2008 and 2011 and they were derived from the Korea Citation Index. The software used for network analysis was R ver. 2.15. The results of the study were as follow: First, 'The Korean Society of Knit Design' was indicated as the highest rate of self-citation, followed by 'Journal of the Korean Fashion & Costume Design Association.' Secondly, the average impact power of clothing & textile-related journals was relatively lower (0.681) compared to that (1.00) of 23 journals under the human ecology discipline. 'Korean Journal of Human Ecology' was found to have impact factor of 1.24, which was higher than the average impact factor of human ecology-related journals. Lastly, together with 'Journal of the Korean Society of Clothing and Textiles.'

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.12
• /
• pp.444-455
• /
• 2019

The purpose of this research was to analyze technological trends of 「Military Small Giant Venture Tech-Fi Net」 from Defense Technology Information Service via social network analysis. 「Military Small Giant Venture Tech-Fi Net」, which was constituted for their fine technology for application to the military field, registered 847 technologies of 388 companies. In this research, we analyzed 847 technologies for the relations between "Military System" and "Military Technology Category" via centrality measurement, one of the social network analysis methods. The results indicate that the major technologies of domestic military small giant venture companies were "Sensor" and "ICT" for "C4I System" and "Surveillance and Reconnaissance System" and "Platform/Structure" for "Land System", "Aeronautical System" and "Naval Sea System". In contrast, we recognized inadequate technologies, such as "Propellant" and "Material" for "Missile and Ammunition system" and "Sensor" and "ICT" for "Defense System", We hope that our results and method will be conducive to the technological development of Small Giant Venture companies.

• The Journal of Society for e-Business Studies
• /
• v.23 no.3
• /
• pp.207-224
• /
• 2018

In this article, an empirical study was conducted by using public dataset from Lending Club Corporation, the largest online peer-to-peer (P2P) lending in the world. We explore significant predictor variables related to P2P lending default that housing situation, length of employment, average current balance, debt-to-income ratio, loan amount, loan purpose, interest rate, public records, number of finance trades, total credit/credit limit, number of delinquent accounts, number of mortgage accounts, and number of bank card accounts are significant factors to loan funded successful on Lending Club platform. We developed online P2P lending default prediction models using discriminant analysis, logistic regression, neural networks, and decision trees (i.e., CART and C5.0) in order to predict P2P loan default. To verify the feasibility and effectiveness of P2P lending default prediction models, borrower loan data and credit data used in this study. Empirical results indicated that neural networks outperforms other classifiers such as discriminant analysis, logistic regression, CART, and C5.0. Neural networks always outperforms other classifiers in P2P loan default prediction.

• Journal of Korean Society of Transportation
• /
• v.29 no.5
• /
• pp.121-138
• /
• 2011

More affordable and available cutting-edge technologies (e.g., wireless vehicle communication) are regarded as a possible alternative to the fixed infrastructure-based traffic information system requiring the expensive infrastructure investments and mostly implemented in the uninterrupted freeway network with limited spatial system expansion. This paper develops an advanced decentralized traveler information System (ATIS) using vehicle-to-vehicle (V2V) communication system whose performance (drivers' travel time savings) are enhanced by three complementary functions (autonomous automatic incident detection algorithm, reliable sample size function, and driver behavior model) and evaluates it in the typical $6{\times}6$ urban grid network with non-recurrent traffic state (traffic incident) with the varying key parameters (traffic flow, communication radio range, and penetration ratio), employing the off-the-shelf microscopic simulation model (VISSIM) under the ideal vehicle communication environment. Simulation outputs indicate that as the three key parameters are increased more participating vehicles are involved for traffic data propagation in the less communication groups at the faster data dissemination speed. Also, participating vehicles saved their travel time by dynamically updating the up-to-date traffic states and searching for the new route. Focusing on the travel time difference of (instant) re-routing vehicles, lower traffic flow cases saved more time than higher traffic flow ones. This is because a relatively small number of vehicles in 300vph case re-route during the most system-efficient time period (the early time of the traffic incident) but more vehicles in 514vph case re-route during less system-efficient time period, even after the incident is resolved. Also, normally re-routings on the network-entering links saved more travel time than any other places inside the network except the case where the direct effect of traffic incident triggers vehicle re-routings during the effective incident time period and the location and direction of the incident link determines the spatial distribution of re-routing vehicles.