• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1103-1111
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• 1996

The design of distrbuted systems is difficult to achieve as the execution patterns of distrbuted systems are typically more complex than those of non- distributed systems. Thus, research toward the development of design methods for distributed systems is quitely needed. As object-oriented systems and distrbuted systems share similar properties, the combination of these two is somehow natural. In this work, a design of distributed systems is introduced. The goal of the method in this paper is to provide assistance to the process of specifying a formal object- oriented specification from graphical representation specification inputs such as data flow diagrams, state transition diagrams and Petri nets. It addresses the extraction of objects, operations and reationshipsfrom the problem domain with emphasis on the specification of the characteristics of distributed systems. This object identification method is supported by a knowledge base that provides for the automated analysis and reasoning about objects and their relationsships. The final object model is represented in a format which provides a formal mechanism for reprsenting the object information.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1082-1092
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• 1996

The design of distrbuted systems is difficult to achieve as the execution patterns of distrbuted systems are typically more complex than those of non- distributed systems. Thus, research toward the development of design methods for distributed systems is quitely needed. As object-oriented systems and distrbuted systems share similar properties, the combination of these two is somehow natural. In this work, a design of distributed systems is introduced. The goal of the method in this paper is to provide assistance to the process of specifying a formal object- oriented specification from graphical representation specification inputs such as data flow diagrams, state transition diagrams and Petri nets. It addresses the extraction of objects, operations and reationshipsfrom the problem domain with emphasis on the specification of the characteristics of distributed systems. This object identification method is supported by a knowledge base that provides for the automated analysis and reasoning about objects and their relationsships. The final object model is represented in a format which provides a formal mechanism for reprsenting the object information.

• The Journal of Korean Institute of Information Technology
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• v.17 no.7
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• pp.31-45
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• 2019

The core technologies for intelligent services today are deep learning, that is neural networks, and parallel and distributed processing technologies such as GPU parallel computing and big data. However, for intelligent services and knowledge sharing services through globally shared ontologies in the future, there is a technology that is better than the neural networks for representing and reasoning knowledge. It is a knowledge representation of IF-THEN in RIF or SWRL, which is the standard rule language of the Semantic Web, and can be inferred efficiently using the rete algorithm. However, when the number of rules processed by the rete algorithm running on a single computer is 100,000, its performance becomes very poor with several tens of minutes, and there is an obvious limitation. Therefore, in this paper, we analyze the past and current studies on parallel and distributed processing of rete algorithm, and examine what aspects should be considered to implement an efficient rete algorithm.

• The Journal of Society for e-Business Studies
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• v.6 no.3
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• pp.63-80
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• 2001

The construction of the students knowledge in e-Learning systems, namely the student modeling, is a core component used to develop e-Learning systems. However, existing e-Learning systems have many problems to share the knowledge in a heterogeneous student model and a distributed knowledge base. Because the methods of the knowledge representation are different in each e-Learning systems, the accumulated knowledge cannot be used or shared without a great deal of difficulty. In order to share this knowledge, existing systems must reconstruct the knowledge bases. Consequently, we propose a new a Case Markup Language based on XML in order to overcome these problems. A distributed e-Learning systems fan have the advantage of easily sharing and managing the heterogeneous knowledge base proposed by CaseML. Moreover students can generate and share a case knowledge to use the communication protocol of agents. In this paper, we have designed and developed a CaseML by using a knowledge markup language. Furthermore, in order to construct an intelligent e-Learning systems, we have done our research based on the design and development of the intelligent agent system by using CaseML.

• Annual Conference of KIPS
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• 2017.04a
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• pp.941-944
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• 2017

심층 학습에 기반을 둔 통계적 언어모형에서 가장 중요한 작업은 단어의 분산 표현(Distributed Representation)이다. 단어의 분산 표현은 단어 자체가 가지는 의미를 다차원 공간에서 벡터로 표현하는 것으로서, 워드 임베딩(word embedding)이라고도 한다. 워드 임베딩을 이용한 심층 학습 기반 통계적 언어모형은 전통적인 통계적 언어모형과 비교하여 성능이 우수한 것으로 알려져 있다. 그러나 워드 임베딩 역시 자료 부족분제에서 벗어날 수 없다. 특히 학습데이터에 나타나지 않은 단어(unknown word)를 처리하는 것이 중요하다. 본 논문에서는 고품질 한국어 워드 임베딩을 위하여 단어의 의미적 계층정보를 이용한 워드 임베딩 방법을 제안한다. 기존연구에서 제안한 워드 임베딩 방법을 그대로 활용하되, 학습 단계에서 목적함수가 입력 단어의 하위어, 동의어를 반영하여 계산될 수 있도록 수정함으로써 단어의 의미적 계층청보를 반영할 수 있다. 본 논문에서 제안한 워드 임베딩 방법을 통해 생성된 단어 벡터의 유추검사(analog reasoning) 결과, 기존 방법보다 5%가 증가한 47.90%를 달성할 수 있었다.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.86-92
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• 2014

This paper provides an integrated view on human and system interaction in advanced and automated systems, which adopting computerized multi-functional artifacts and complicated organizations, such as nuclear power plants, chemical plants, steel and semi-conduct manufacturing system. As current systems have advanced with various automated equipments but human operators from various organizations are involved in the systems, system safety still remains uncertain. Especially, a human operator plays an important role at the time of critical conditions that can lead to catastrophic accidents. The knowledge on human error helps a risk manager as well as a designer to create and control a more credible system. Several human error theories were reviewed and adopted for forming the integrated perspective: gulf of execution and evaluation; risk homeostasis; the ironies of automation; trust in automation; design affordance; distributed cognition; situation awareness; and plan delegation theory. The integrated perspective embraces human error theories within three levels of human-system interactions such as affordance level, psychological logic level and trust level. This paper argued that risk management process should dealt with human errors by providing (1) reasoning improvement; (2) support to situation awareness of operators; and (3) continuous monitoring on harmonization of human system interaction. This approach may help people to understand risk of human-system interaction failure characteristics and their countermeasures.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.13-20
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• 2003

As it increase electronic commerce user rapidly, it is necessary to study on Improvement of performance for electronic commerce system. This paper suggests electronic commerce system using functionally distributed structure based on multi-agent and evaluate it's performance using prototype. In the suggested system, we use multi-agent using combined reasoning to offer a proper commodity information and meet the customer's requirement. And we can reduce load of the electronic commerce system with distribute agents both main server system and local server system functionally. In experiment result, we can confirm suggested electronic commerce system can prevent customer's unexpected long waiting causes by network traffic and server load, and can improve efficiency.

• Journal of the Korea Institute of Building Construction
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• v.11 no.1
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• pp.91-99
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• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.91-93
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• 2012

최근 모바일 컴퓨팅 환경 지원을 실현하기 위한 연구가 전 세계적으로 활발히 진행되고 있으며, 나아가 그 중요성은 점점 더 증가하고 있다. 모바일 컴퓨팅 환경에서 지능형 서비스를 제공하기 위해서는 상황 데이터를 수집하고 적절한 가공을 통해 상황정보로 변환시켜 해석, 추론 및 학습 과정을 거쳐 사용자의 상황에 맞는 적절한 서비스를 제공할 수 있어야 한다. 본 논문은 모바일 환경에서 단일 상황추론의 한계를 개선하는 다중 상황추론과 완전히 형성되지 않은 상황정보를 기반으로 한 상황추론으로 불확실성을 지원하는 다중추론지원 분산형 상황인식 시스템을 제안한다.

• Annual Conference of KIPS
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• 2012.11a
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• pp.168-171
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• 2012

본 논문에서는 모바일 컴퓨팅 환경과 불확실성을 지원하는 다중추론지원 분산형 상황인식 시스템의 지식 베이스(KB: Knowledge Base)를 위한 모델로써 상황정보(OWL), 온톨로지 추론정보(OWL DL), 규칙 추론정보(SWRL), 베이지안 추론정보(PR-OWL)를 통합적으로 표현하는 UniOWL 통합상황모델을 제안한다. 제안한 통합상황모델은 상황정보와 다중 추론정보를 단일 구문, 즉 OWL 구문으로 표현하여 지식베이스 설계를 수월하게 하고 표현을 단순화하는 장점이 있다.