• Proceedings of the Korea Information Processing Society Conference
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.49-55
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• 2006

Two data mining techniques, analysis of variance (ANOVA) and self-organizing map (SOM), are applied to knowledge discovery in aerodynamic design space. These methods make it possible to identify the effect of each design variable on the objective functions. Furthermore, ANOVA shows the effect of interaction between design variables on the objective function and SOM visualizes the trade-off among objective functions. Present methods are applied to the result of the supersonic wing design which includes 72 design variables and 4 objective functions.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.126-131
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• 2010

국가과학기술지식정보서비스(NTIS)는 현재 15개 부처 청 16개 대표전문기관 및 8개 성과물전담기관으로 부터 데이터를 연계수집 및 통합하여 공동 활용하고 있다. NTIS가 상기와 같은 분산 환경에서 데이터를 통합한 후 서비스를 제공하고 있는 이유로 인해, 데이터를 제공하는 각 기관에서는 데이터 제공과 관련 하드웨어, 소프트웨어 및 제공대상 데이터에 대한 상세정보를 실시간으로 모니터링할 수 있는 기능을 요구하였다. 본 논문에서는 이러한 요구사항을 충족시키기 위해 개발한 정보연계모니터링(Real-time Monitoring: ReMon) 서비스를 소개한다. ReMon서비스를 활용함으로써 분산 환경에서의 데이터 통합을 실시간으로 모니터링할 수 있으며, 나아가 국가R&D정보의 수집 및 공동 활용체계를 개선시키는 데에 기여하였다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.44-51
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• 1999

This paper presents a massively parallel computational model for the efficient integration of speech and natural language understanding. The phoneme model is based on continuous Hidden Markov Model with context dependent phonemes, and the language model is based on a knowledge base approach. To construct the knowledge base, we adopt a hierarchically-structured semantic network and a memory-based parsing technique that employs parallel marker-passing as an inference mechanism. Our parallel speech recognition algorithm is implemented in a multi-Transputer system using distributed-memory MIMD multiprocessors. Experimental results show that the parallel speech recognition system performs better in recognition accuracy than a word network-based speech recognition system. The recognition accuracy is further improved by applying code-phoneme statistics. Besides, speedup experiments demonstrate the possibility of constructing a realtime parallel speech recognition system.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.182-189
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• 2007

To reform and improve the productivity of construction industry, 1) it should be encouraged to improve the construction production process and 2) it is required to enhance reliability of construction information based on the systematic thinking process. To promote the information reliability created during construction production process, Lean Construction Research Center(LRC2) is developing a supporting system to improve design/material supply/schedule management, functioning to efficiently manage the information created at construction production processes and developing a web based construction information system that provides result management/decision making support/knowledge based information services.

• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.5-17
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• 2008

The purpose of this paper is to identify the usefulness of Weblog genre analysis in knowledge creation within an organization where communications are occurred frequently among the employees with information and communication technologies (ICTs). Knowledge creation is essential to achieve competitive advantage in today's knowledge-oriented working environments. There has been huge investment on knowledge management systems to achieve such advantages. It is, however, widely recognized that distributed knowledge management systems often fail due to the different social contexts across the sub-organizations where the local information systems are deployed. It is important to coordinate such social gaps across the sub-organizations to achieve better advantages. Given that Weblogs users often feel a shared social norm. Weblogs playa positive role of narrowing the social gaps. This paper argues that the genre analysis of Web logs could provide important clues to narrow the social gaps existed across the sub-organizations within an organization. Hence, such taxonomical practice may be a solution for the high rate of failure in knowledge management system implementations in an organization. This paper uses the theory of organizational knowledge creation (Nonaka & Takeuchi. 1995) and social construction of technology (SCOT) approach (Bijker, 1995) to compare the socialized with the non-socialized integration of distributed information systems. The findings of this research provide a useful framework for better implementing knowledge management practices especially in distributed working environments.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.408-411
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• 2006

유비쿼터스 컴퓨팅 환경에서 서비스를 제공함에 있어 지능적인 수행 능력은 사용자의 만족도를 높여주는 핵심 요소이다. 시스템의 지능을 부여하기 위해서는 지식을 관리, 처리, 활용하는 기능이 필요한데, 이들 기능은 그 지식이 어떻게 표현되어 있는지에 큰 영향을 받는다. 일차 술어 논리 기반 지식 표현 방법은 폭넓은 표현 범위와 유연한 지식 정의, 추론 방법으로 선호되고 있지만, 복잡한 계산 비용을 갖고 있기 때문에, 전문적인 지식 처리 시스템이 아닌 경우, 불필요한 계산 비용이 소요된다. Description Logic은 Frame기반 지식 표현 방식으로 일차 술어 논리를 사용하는 것보다 지식을 표현할 수 있는 범위는 제한적이지만, 빠른 추론 결과를 보장해 준다. 유비쿼터스 컴퓨팅 환경에서는 분산된 다양한 오브젝트들이 협력과정을 통해 사용자에게 지능적인 서비스를 제공하게 되고, 이들 개별적인 오브젝트들은 저사양의 계산능력을 갖고 있다고 가정된다. 그러므로, 저사양의 컴퓨팅 오브젝트들을 조합하여 지능적인 서비스를 성공적으로 제공하기 위해서, 각각의 오브젝트들은 제한된 지식을 효과적으로 관리할 수 있는 방법이 필요하다. 이를 위해 본 논문에서는 Frame 기반의 Description Logic을 기반으로 SUNHI의 표현 범위를 가진 인식론적 온톨로지 표현 언어를 제안하고, SUNHI의 표현 범위의 효율성을 증명하고자 한다.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.3096-3101
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• 2013

The study is to develop a tool to measure knowledge, attitude and behavior towards irradiated food derived from three factors of 20 items in regard to the knowledge of irradiated food. The variances in explanatory power for the first, second and third factors were 43.1%, 12.0% and 9.9% respectively, which marked a total of 65.0%. As to the attitude towards irradiated food, one factor was derived from 4 items and this factor, the result of measurement scale analysis, was named "the attitude towards irradiated food". The variance in the explanatory power of this factor was 71.1%. In regard to the behavior towards irradiated food, one factor was derived from 5 items and the variance in its explanatory power was measured to 57.6%, that is total 57.6% was explained.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.268-270
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• 2004

네트워크가 보편화되면서 어떠한 정보의 교환도 시간과 장소에 상관없이 가능하게 되었다. 자체 실험실에서 실험한 값을 포함하여 분산된 다양한 소스로부터 많은 실험 값의 정보를 통합하는 즉, 멀티 소스 데이터에 대한 통합 규칙을 만들 수 있다면 다양하고 유용한 정보를 얻을 수 있을 것이다. 또한 통합된 규칙을 통해서 새로운 안목으로 실험을 진행할 수도 있으며, 미처 생각하지 못했던 관련 지식을 습득할 수도 있을 것이다. 본 논문에서는 이러한 분산된 데이터를 통합하여 멀티 소스 데이터들 간의 통합 규칙을 만들고 이의 분석 기반이 되도록 하는 방법에 대해 소개한다.