• Journal of Digital Convergence
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• v.13 no.3
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• pp.155-165
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• 2015

Bankruptcy prediction has been one of the important research topics in finance since 1960s. In Korea, it has gotten attention from researchers since IMF crisis in 1998. This study aims at proposing a novel model for better bankruptcy prediction by converging three techniques - support vector machine(SVM), fuzzy theory, and genetic algorithm(GA). Our convergence model is basically based on SVM, a classification algorithm enables to predict accurately and to avoid overfitting. It also incorporates fuzzy theory to extend the dimensions of the input variables, and GA to optimize the controlling parameters and feature subset selection. To validate the usefulness of the proposed model, we applied it to H Bank's non-external auditing companies' data. We also experimented six comparative models to validate the superiority of the proposed model. As a result, our model was found to show the best prediction accuracy among the models. Our study is expected to contribute to the relevant literature and practitioners on bankruptcy prediction.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.145-170
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• 2011

The purpose of this paper is to suggest a pilot model of knowledge organizing system which reflects the knowledge structure of research papers, using a case analysis on the "Korean Research Memory" of the National Research Foundation of Korea. In this paper, knowledge structure of the research papers in humanities and social science is described and the function of the "Korean Research Memory" for scholarly sense-making is analysed. In order to suggest the pilot model of the knowledge organizing system, the study also analysed the relation between indexed keyword and knowledge structure of research papers in the Korean Research Memory. As a result, this paper suggests 24 axioms and 11 inference rules for an ontology based on semantic relation of the knowledge structure.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.4
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• pp.103-110
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• 2018

Services that enhance user convenience by using various IoT devices are increasing with the development of Internet of Things(IoT) technology. Also, since the price of IoT sensors has become cheaper, companies providing services by collecting and utilizing data from various sensors are increasing. The smart IoT home system is a representative use case that improves the user convenience by using IoT devices. To improve user convenience of Smart IoT home system, this paper proposes a method for the control of related devices based on data analysis. Internal environment measurement data collected from IoT sensors, device control data collected from device control actuators, and user judgment data are learned to predict the current home state and control devices. Especially, differently from previous approaches, it uses deep neural network to analyze the data to determine the inner state of the home and provide information for maintaining the optimal inner environment. In the experiment, we compared the results of the long-term measured data with the inferred data and analyzed the discrimination performance of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.143-143
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• 2023

최근 대청댐('17), 평림댐('19) 등 광역 취수원에서 망간의 먹는 물 수질기준(0.05mg/L 이하) 초과 사례가 발생되어, 다수의 민원이 제기되는 등 취수원의 망간 관리 중요성이 부각되고 있다. 특히, 동절기 전도(Turn-over)시기에 고농도 망간이 발생되는 경우가 많은데, 현재 정수장에서는 망간을 처리하기 위해 유입구간에 필터를 설치하고 주기적으로 교체하는 방식으로 처리하고 있다. 그러나 단기간에 고농도 망간 다량 유입 시 처리용량의 한계 등 정수장에서의 공정관리가 어려워지므로 사전 예측에 의한 대응 체계 고도화가 필요한 실정이다. 본 연구는 광역취수원인 주암댐을 대상으로 망간 예측의 정확도 향상 및 예측기간 확대를 위해 다양한 머신러닝 기법들을 적용하여 비교 분석하였으며, 독립변수 및 초매개변수 최적화를 진행하여 모형의 정확도를 개선하였다. 머신러닝 모형은 수심별 탁도, 저수위, pH, 수온, 전기전도도, DO, 클로로필-a, 기상, 수문 자료 등의 독립변수와 화순정수장에 유입된 망간 농도를 종속변수로 각 변수에 해당하는 실측치를 학습데이터로 사용하였다. 그리고 데이터기반 모형의 정확도를 개선하기 위해서 성층의 수준을 판별하는 지표로서 PEA(Potential Energy Anomaly)를 도입하여 데이터 분석에 활용하고자 하였다. 분석 결과, 망간 유입률은 계절 주기에 따라 농도가 달라지는 것을 확인하였고 동절기 전도시점과 하절기 장마기간 난류생성 시기에 저층의 고농도 망간이 유입이 되는 것을 분석하였다. 또한, 두 시기의 망간 농도의 변화 패턴이 상이하므로 예측 모델은 각 계절별로 구축해 학습을 진행함으로써 예측의 정확도를 향상할 수 있었다. 다양한 머신러닝 모델을 구축하여 성능 비교를 진행한 결과, 동절기에는 Gradient Boosting Machine, 하절기에는 eXtreme Gradient Boosting의 기법이 우수하여 추론 모델로 활용하고자 하였다. 선정 모델을 통한 단기 수질예측 결과, 전도현상 발생 시기에 대한 추종 및 예측력이 기존의 데이터 모형만 적용했을 경우대비 약 15% 이상 예측 효율이 향상된 것으로 나타났다. 본 연구는 머신러닝 모델을 활용한 망간 농도 예측으로 정수장의 신속한 대응 체계 마련을 지원하고, 수처리 공정의 효율성을 높이는 데 기여할 것으로 기대되며, 후속 연구로 과거 시계열 자료 활용 및 물리모형과의 연결 등을 통해 모델의 신뢰성을 제고 할 계획이다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.139-143
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• 2002

1990 년대 후반부터 다양한 디지털 통신망을 이용하여 멀티미디어 컨텐츠 서비스가 가능하게 되었다. 하지만, 멀티미디어 컨텐츠의 전달 및 이용을 위한 기반 구조들의 독자적 발전 및 다양한 통합적 관리 체계 시스템으로 인해, 멀티미디어 컨텐츠 표현 방식의 호환성 문제, 혼재하는 네트워크 전달 방식과 단말 방식의 호환성 문제 등의 잠재적인 문제점이 발생한다. 이런 문제의 대안으로 현재 존재하는 기술 및 기반 구조들 사이의 연동을 통한 큰 프레임워크인 MPEG-21이 진행 중이다. MPEG-21 의 목표는 표준화 목표를 구체화하는 것부터 진행하여, 최종적으로 “다양한 네트워크 환경과 단말기에 있어서, 투명하고 통합적으로 멀티미디어 자원의 이용을 가능하게 하는 것”이다. 본 논문에서는 현재 표준화 작업이 진행 중인 MPEG-21 을 기반으로 하는 Testbed를 제안한다. Testbed는 server, client, DIA(Digital Item Adaptation) 의 세 모듈로 구성된다. Server 의 역할은 멀티미디어 컨텐츠를 Digital Item(DI)으로 생성하고, client 가 DI를 요구할 경우 DIA 모듈을 통해서 변환된 DI를 client 에게 제공한다. DIA 모듈은 server 에서 동작되며 client로부터 요청된 DI를 분석하고 client로부터 전송된 환경 정보를 이용하여 client 환경에 적합하게 변환된 (adapted) DI를 생성하는 것이 주 기능이다. Client 는 server 에 저장되어 있는 DI를 선택하고 user preference, terminal capability 등의 필요한 정보를 server로 전송한다. Testbed 에서는 스포츠 경기의 동영상, 정지 영상, 경기 내용 역사를 기록한 파일 등의 DI를 이용한다. 표현 언어는 XML이며, HTTP 기반의 Web 환경에서 구동되도록 설계된다.스템 사이에 의미 있는 데이터 전송, 지식 획득을 위해 정보 기술 분야에서 활용해야 할 영역으로 XML Web Services, Multi-agent Systems, 전문가 컴뮤니티를 위한 그룹웨어 연구 개발에 관해 사례 중심으로 발표한다.다 신선한 공기를 넣어 주었을 때는 배의 발달이 많이 늦어져 배양 3주째에 다른 처리보다 배의 수가 훨씬 적었다. 체세포배가 발달하는 동안에는 산소를 많이 요구하지 않으나 성숙하는 동안에는 산소를 많이 요구하는 것으로 생각된다.적인 것으로 나타났다. 다만, 곡선형은 물론 직선형에서도 열교환 튜브의 배치밀도, 튜브 길이 및 두께 등의 변화에 따른 최적화 연구가 수반되어야 할 것으로 판단된다.에서 제공된 API는 객체기반 제작/편집 도구에 응용되어 다양한 멀티미디어 컨텐츠 제작에 사용되었다.x factorization (NMF), generative topographic mapping (GTM)의 구조와 학습 및 추론알고리즘을소개하고 이를 DNA칩 데이터 분석 평가 대회인 CAMDA-2000과 CAMDA-2001에서 사용된cancer diagnosis 문제와 gene-drug dependency analysis 문제에 적용한 결과를 살펴본다.0$\mu$M이 적당하며, 초기배발달을 유기할 때의 효과적인 cysteamine의 농도는 25~50$\mu$M인 것으로 판단된다.N)A(N)/N을 제시하였다(A(N)=N에 대한 A값). 위의 실험식을 사용하여 헝가리산 Zempleni 시료(15%$S_{XRD}$)의 기본입자분포로부터 %$S_{XRD}$를 계산한 결과, 16%$S_{XRD}$의 결과값을 얻을 수 있었다. 따라서, 본 연구에서 도출한 관계식들이 유효함을 확인할 수 있었다.계식들이 유효함을 확인할 수 있었다.할 때 약간의 증가

• Korean Journal of Heritage: History & Science
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• v.45 no.4
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• pp.92-103
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• 2012

The Cheomsungdae was built in the Silla dynasty during the reign of queen Seondeok. It has a round cylindrical structure with a flowing curved fa ade. The identity of the Cheomsungdae has not been revealed since there is not much historical evidence or documents about the building. This study is trying to investigate the building technique and method from the technical point of view of the past when it was constructed. There have been much work and studies done for the Cheomsungdae, but not much were focusing on the technical aspects of the building. In addition there are many questions and doubts about the hypothesis of the building technique of Cheomsungdae since there aren't any remaining documents or historical evidence supporting it. Among many questions, we think that the discussion on falsework technique is not considering traditional construction method of the Dujabee (a traditional construction technique using various tools and equipment for the stability of the building) technique. Therefore, it is hard to identify them as reliable historical facts. As the result of the study, we want to provide the basic data on the construction techniques of Korean traditional architecture and broaden the study scope of technical history by narrowing the errors. The study could be summarized into three points. 1. The historical architecture Cheomseongdae was constructed by using traditional crane techniques such as a Noklo (pulley ladder). Cheomseongdae was re-evaluated as a high level technology for the history of architecture. 2. The benchmark method on Cheomseongdae construction has been applied with a precise scientific method based on the geometrical principals using the central axis. 3. In terms of the history of Korean traditional architecture technology, as there aren't many studies done we proposed various basic data for the traditional crane techniques and criteria of Korean traditional architecture technology. We could expect various and active studies for the technical approach of the history of architecture.

• Journal of The Korean Association For Science Education
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• v.33 no.4
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• pp.840-862
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• 2013

This study undertook a methodological investigation on previous research that had proposed alternative methods for analyzing argumentative discourse in science classes in terms of collaborative construction and epistemic enactments of argumentation. The study also proposed a new way of analyzing argumentation discourse based on the achievements and limitations of previous research. The new method was applied to actual argumentation discourse episodes to examine its feasibility. For these purposes, we chose the studies employing Toulmin's argument layout, seeking for a method to analyze comprehensively the structure, content, and justification of arguments, or emphasizing evidence-based reasoning processes of argumentation discourse. In addition, we contrived an alternative method of analyzing argumentative discourse, Discourse Register on the Evidence-Explanation Continuum (DREEC), and applied DREEC to an argumentative discourse episode that occurred in an actual science classroom. The advanced methods of analyzing argumentative discourse used in previous research usually examined argument structure by the presence and absence of the elements of Toulmin's argument layout or its extension. Those methods, however, had some problems in describing and comparing the quality of argumentation based on the justification and epistemic enactments of the arguments, while they could analyze and compare argumentative discourse quantitatively. Also, those methods had limitations on showing participants' collaborative construction during the argumentative discourse. In contrast, DREEC could describe collaborative construction through the relationships between THEMEs and RHEMEs and the links of data, evidence, pattern, and explanation in the discourse, as well as the justification of arguments based on the flow of epistemic enactments of the argumentative discourse.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.81-86
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• 2002

In current CBR(Case-Based Reasoning) systems, the case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck similar to those found in traditional expert system design. In this thesis, 1 present a model for learning method of case adaptation knowledge using case base. The feature difference of each pair of cases are noted and become the antecedent part of an adaptation rule, the differences between the solutions in the compared cases become the consequent part of the rule. However, the number of rules that can possibly be discovered using a learning algorithm is enormous. The first method for finding cases to compare uses a syntactic measure of the distance between cases. The threshold fur identification of candidates for comparison is fixed th the maximum number of differences between the target and retrived case from all retrievals. The second method is to use similarity metric since the threshold method may not be an accurate measure. I suggest the elimination method of duplicate rules. In the elimination process, a confidence value is assigned to each rule based on its frequency. The learned adaptation rules is applied in riven target Problem. The basic. process involves search for all rules that handle at least one difference followed by a combination process in which complete solutions are built.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.81-101
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• 2003

The financial statements purpose to provide useful information to decision-making process of business managers. The value-relevant information, however, embedded in the financial statement has been often overlooked in Korea. In fact, the financial statements in Korea have been utilized for nothing but account reports to Security Supervision Boards (SSB). The objective of this study is to develop earnings forecasting models through financial statement analysis using artificial intelligence (AI). AI methods are employed in forecasting earnings: artificial neural networks (ANN) for manufacturing industry and case~based reasoning (CBR) for banking industry. The experimental results using such AI methods are as follows. Using ANN for manufacturing industry records 63.2% of hit ratio for out-of-sample, which outperforms the logistic regression by around 4%. The experiment through CBR for banking industry shows 65.0% of hit ratio that beats the statistical method by 13.2% in holdout sample. Finally, the prediction results for manufacturing industry are validated through monitoring the shift in cumulative returns of portfolios based on the earning prediction. The portfolio with the firms whose earnings are predicted to increase is designated as best portfolio and the portfolio with the earnings-decreasing firms as worst portfolio. The difference between two portfolios is about 3% of cumulative abnormal return on average. Consequently, this result showed that the financial statements in Korea contain the value-relevant information that is not reflected in stock prices.

• Journal of the Korean Society for information Management
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• v.15 no.3
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• pp.133-150
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• 1998

For the purpose of new‘organizational knowledge centric knowledge management’, this paper proposes the knowledge creating organizational memory which shows the knowledge creation in organization according to the dialectical circulation between the domain knowledge and the task knowledge, based on the Yin Yang theory. This paper defines two kinds of organizational knowledge such as the domain knowledge and task knowledge and designs them in the pursuit of its lifecycle. Knowledge creating organizational memory is designed to three knowledge components that circulate through the domain knowledge and the task knowledge according to the object-oriented methodology. Organizational knowledge is designed into the graphical structure of ( i ) knowledge ( ⅱ ) relation between knowledge objects and ( ⅲ ) degree of relation, which receive the legacy of organizational knowledge such as data schema, process model and knowledge base. This design of organizational knowledge can be applied to CBR(Case Based Reasoning), one of knowledge mining tools to create new organizational knowledge.