• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.2
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• pp.1-22
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• 2007

This paper is targeting on developing pre-test Methodology for start-up as tuning successful business modelling with their implementation. Start-up is asked to a complete preparation and analysis for business to enhance the success possibility. In this stream, Start-up should test the validity of their business model before starting a business. This paper deliver alternatives to meet this requirement. Overall, this paper suggest two different approaches. First, by literature review, this paper prove the importance of BM in success factor analysis of high-tech start-up. Second, This paper prove BMO Model as the best practicing model to assess the validity of BM. Additionally, this paper, BMO will be utilized to bring significant implications to sort out enhancing strategies of BM validity.

• Journal of Science Education
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• v.33 no.1
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• pp.69-76
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• 2009

Probabilistic reasoning and combinational reasoning are essential to build a logical thinking and a process of thinking dealing with everyday life as well as scientific knowledge. This research aims at finding the optimal period to teach reasoning to the students who haven't developed probabilistic reasoning and combinational reasoning. The treatment program was performed for 20 students from each grade who couldn't develop two parts of reasoning. The treatment program using baduk stones and cards was performed repeatedly, focusing on the specific activities. After four weeks of treatment program, the test to check the development of probabilistic reasoning and combinational reasoning was performed again and the changes of reasoning development were identified. After giving treatment program for reasoning development, 15.0%, 25.0% and 40.0% of improvement in the 4th, the 5th, the 6th graders respectively were shown. With regard to the combinational reasoning, the results showed the improvement of 20.0% in the 4th grades, 25.0% in the 5th graders and 63.2% in the 6th graders. As a result of research in the above, students, who were not formed probabilistic reasoning and combinational reasoning, could be known to be enhanced through learning, but to fail to be formed the qualitative change like the cognitive development. It is expected that this research can contribute to the improvement of students' cognitive level and there would be more active researches in different fields to improve the cognitive level of the 6th graders who are in their optimal periods to learn two parts of reasoning.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.12a
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• pp.739-745
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• 1999

This paper forcuses on the measurement of increased work efficiency expected from the factory automation through random interactions of the organizational behavioral factors whose attributes can be changed with the implementation of the factory automations. Specifically the work reported here is concerned with modeling and analyzing the random interrelationships among the organizational behavioral factory which factory automation will have impact on throughout the time horizon of its implementation in terms of productivity. In addition, it is also concerned with developing a stochastic continuous simulation model to be used to assess the impact of factory automations.

• The Journal of the Acoustical Society of Korea
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• v.10 no.3
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• pp.31-36
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• 1991

We propose an efficient pre-classification algorithm extracting candidate words to reduce the recognition time in a large-vocabulary recognition system and also propose the use of spectral and temporal smoothing of the observation probability to improve its classification performance. The proposed algorithm computes the coarse likelihood score for each word in a lexicon using the observation probabilities of speech spectra and duration information of recognition units. With the proposed approach we could reduce the computational amount by 74% with slight degradation of recognition accuracy in 1160-word recognition system based on the phoneme-level HMM. Also, we observed that the proposed coarse likelihood score computation algorithm is a good estimator of the likelihood score computed by the Viterbi algorithm.

• Annual Conference on Human and Language Technology
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• 1999.10d
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• pp.117-122
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• 1999

본 연구는 형태소 분석에 필요한 언어 지식과 품사 태깅에 필요한 확률 정보를 별도의 언어 지식 추가 없이 학습 말뭉치를 통해서 얻어내는 방법을 제안한다. 먼저 품사 부착된 학습 말뭉치로부터 형태소 사전과 결합 정보를 추출한다. 그리고 자주 발생하는 어절 및 해석상 모호성이 많은 어절에 대해서는 학습 말뭉치에서 발견된 형태소 분석 결과를 저장하여 형태소 분석에 소요되는 시간과 형태소 분석의 정확률을 높인다. 또한 미등록어의 많은 부분을 차지하는 인명, 지명, 조직명에 대해서는 정보 추출 분야에서 사용하는 고유 명사 분류법으로 해결한다. 품사 태깅을 위해서는 품사열 정보와 품사열 정보로는 해결할 수 없는 경우를 위한 어휘 정보를 학습 말뭉치에서 추출한다. 품사열 정보와 어휘 정보는 정형화 과정을 거쳐 최대 엔트로피 모델의 자질로 사용되어 품사 태깅 시스템을 위한 확률 분포를 구성한다. 본 연구에서 제안하는 방법은 학습 말뭉치를 기반으로 한다는 특성에 의해 다양한 영역에 사용하기 쉽다. 또한 어휘 정보로 품사 문맥 정보를 보완하기 때문에 품사 분류 체계와 형태소 해석 규칙에 영향을 적게 받는다는 장점을 가진다. MATEC '99 데이터 실험 결과 형태소 단위로 94%의 재현률과 93%의 정확률을 얻을 수 있었다.

• Annual Conference on Human and Language Technology
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• 1999.10d
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• pp.145-150
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• 1999

본 논문에서는 한국어 자연어 정보처리 기술 표준화를 위한 형태소 분석기 및 품사 태거 평가 대회(MATEC99)에 참여한 고려대학교의 형태소 분석기, 품사 태거, 그리고 명사 추출기를 설명하고 평가 결과를 기술한다. 형태소 분석기는 입력된 어절을 우에서 좌로 분석하며 각 상태에 대한 예측 정보를 활용하여 불필요한 분석 후보에 대한 탐색을 수행하지 않도록 한다. 품사 태거로는 띄어쓰기를 고려한 형태소 품사 2-그램 확률과 띄어쓰기를 고려한 형태소 어휘-품사 3-그램 어휘 확률을 이용하는 결합 독립 모형을 사용한다. 고속 명사 추출기는 고속의 FST 사전과 한국어 특성을 반영한 휴리스틱을 이용한다.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.36-44
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• 2009

The sum of each work duration are entire period in construction project. Each work occurs to be late, the total period of construction project will delays. Therefore, the total period of construction project will not be delayed if probability of work progress makes higher. Finding each work constraints performs constraints analysis in process of construction for checking probability of work progress. Grasp work constraints through the constraints analysis and removes. This research will show preventing delay of construction project, through work condition analysis process.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.292-297
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• 2008

복잡한 시맨틱을 포함한 웹 문서를 정확히 범주화하고 이 과정을 자동화하기 위해서는 인간의 지식체계를 수용할 수 있는 표준화, 지능화, 자동화된 문서표현 및 분류기술이 필요하다. 이를 위해 키워드 빈도수, 문서내 키워드들의 관련성, 시소러스의 활용, 확률기법 적용 등에 사용자의도(intention) 정보를 활용한 범주화와 조정 프로세스를 도입하였다. 웹 문서 분류과정에서 시소러스 등을 사용하는 지식베이스 문서분류와 비 감독 학습을 하는 사전 지식체계(a priori)가 없는 유사성 문서분류 방법에 의도정보를 사용할 수 있도록 기반체계를 설계하였고 다시 이 두 방법의 차이는 Hybrid조정프로세스에서 조정하였다. 본 연구에서 설계된 HDCI(Hybrid Document Classification with Intention) 모델은 위의 웹 문서 분류과정과 이를 제어 및 보조하는 사용자 의도 분석과정으로 구성되어 있다. 의도분석과정에 키워드와 함께 제공된 사용자 의도는 도메인 지식(domain Knowledge)을 이용하여 의도간 계층트리(intention hierarchy tree)를 구성하고 이는 문서 분류시 제약(constraint) 또는 가이드의 역할로 사용자 의도 프로파일(profile) 또는 문서 특성 대표 키워드를 추출하게 된다. HDCI는 문서간 유사성에 근거한 상향식(bottom-up)의 확률적인 접근에서 통제 및 안내의 역할을 수행하고 지식베이스(시소러스) 접근 방식에서 다양성에 한계가 있는 키워들 간 관계설정의 정확도를 높인다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.12C
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• pp.1276-1281
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• 2002

Bellare and Rivest proposed the translucent cryptography which was a kind of key recovery system. Translucent cryptography is a system in which the third party can recover encrypted message with the probability p(0$\leq$p$\leq$1). The key recovery agency doesn't need to store the user's private key in advance. The balance between key recovery agency and user can be controlled by the value of p. For example, if p is set to be 0.4 then the key recovery agency can recover 40 out of 100 encrypted messages. In this paper, we show that user can easily deceive the key recovery agency in the translucent cryptography. Then we propose the solution of this problem.

• Journal of the Korean association of regional geographers
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• v.13 no.6
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• pp.712-723
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• 2007

The objective of this paper is to search the factors inducing the visitors to revisit in Bangeo Festival of Jeju region. To get this objective, this study analyzed the data with the Multinomial Logit Model applied dependent variable to intention of revisit. As a result, 'festival program' factor is the most important thing and if the factor increases by 1 unit, the probability of 'revisit' can be increased by 5.255 times than the probability of 'no revisit'. Secondly, the next significant factors are 'festival convenience' and 'festival recognition in advance'. So the providers of the festival will intend to prepare the festival focused on the important factor proposed by this results.