• Proceedings of the Korea Technology Innovation Society Conference
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• 2001.05a
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• pp.369-385
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• 2001

A R&D project evaluation method has been applied for the national nuclear R&D projects in a developing-country setting. In the methodology, Saaty's analytic hierarchy process model is used to evaluate and rank of the selected nuclear R&D project which have a wide range of objectives and characteristics. The criteria used for evaluation related specifically to the Korea's evaluation needs and culture, and they are weighted according to their relative importance as perceived by the evaluator of the R&D project. As a real-world case of evaluation, we elicited and reproduced the evaluation process of the nuclear R&D projects which is going under the research process. As the results of the paper suggests, the methodology can be applied to the evaluation of the R&D projects and has much potential.

• Genomics & Informatics
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• v.13 no.3
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• pp.86-89
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• 2015

Because there are clear molecular differences entailing different treatment effectiveness between Korean and non-Korean cancer patients, identifying distinct molecular characteristics of Korean cancers is profoundly important. Here, we report a web-based data repository, namely Korean Cancer Genome Database (KCGD), for searching gene signatures associated with Korean cancer patients. Currently, a total of 1,403 cancer genomics data were collected, processed and stored in our repository, an ever-growing database. We incorporated most widely used statistical survival analysis methods including the Cox proportional hazard model, log-rank test and Kaplan-Meier plot to provide instant significance estimation for searched molecules. As an initial repository with the aim of Korean-specific marker detection, KCGD would be a promising web application for users without bioinformatics expertise to identify significant factors associated with cancer in Korean.

• Transactions of the Korean hydrogen and new energy society
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• v.21 no.5
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• pp.442-451
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• 2010

This paper describes the calculation method to obtain the product composition of coal pyrolysis at high pressure and high temperature. The products of coal pyrolysis should be determined for the coal gasifier simulation, and this is the first step of the coal gasifier simulation. The pyrolysis product distribution greatly affects the coal gasifier efficiency such as carbon conversion, cold gas efficiency and the syngas composition at the outlet of the gasifier. The present calculation method is based on the coal ultimate/proximate analysis and several correlations among gasifier pressure, coal properties and pyrolysis products. The calculated products for 5 coals have been compared with those from the commercial pyrolysis model.

• 한국연소학회:학술대회논문집
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• 2013.06a
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• pp.87-90
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• 2013

In pulverized coal fired boilers, slagging and fouling may cause significant effect on the operational life of boiler. As increasing a consumption of low rank coal, slagging and fouling are main issues in pulverized coal combustion. This study predicts ash deposition propensity in a 0.7 MW pilot-scale furnace. Slagging model is employed as a User-Defined Function (UDF) of FLUENT and validated against measurement and prediction. The results show good agreement compared with experiment. There is need to development of a pulverized coal combustion and slagging analysis at low coal.

• Journal of Korea Technology Innovation Society
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• v.7 no.2
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• pp.397-412
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• 2004

The importance of maritime sector in Korea has been increasingly recognized in recent days. As the country enters the $\ulcorner$new ocean era$\lrcorner$ the oceans are often regarded as holding the keys to solve the problems of modem industry associated with changing environment as well as changing societies and national politics. This paper attempts to address the national maritime R＆D policies and their relative importances. In the methodology, Saaty's analytic hierarchy process model is used to evaluate and rank the selected maritime R＆D projects which have a wide range of characteristics and policy implications. The criteria used for policy evaluation relates specifically to the Korea's evaluation needs and culture, and those criteria are weighted according to their relative importance as perceived by the maritime R＆D specialists.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.411-420
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• 2008

This paper considers a feasible two-step estimator for seasonal cointegration as the extension of $Br{\ddot{u}}ggeman$ and $L{\ddot{u}}tkepohl$ (2005). It is shown that the reducedrank maximum likelihood(ML) estimator for seasonal cointegration can still produce occasional outliers as that for non-seasonal cointegration even though the sizes of them are not extreme as those in non-seasonal cointegration. The ML estimator(MLE) is compared with the two-step estimator in a small Monte Carlo simulation study and we find that the two-step estimator can be an attractive alternative to the MLE, especially, in a small sample.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2180-2197
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• 2019

With the proliferation of the Android malicious applications, malware becomes more capable of hiding or confusing its malicious intent through the use of code obfuscation, which has significantly weaken the effectiveness of the conventional defense mechanisms. Therefore, in order to effectively detect unknown malicious applications on the Android platform, we propose DroidVecDeep, an Android malware detection method using deep learning technique. First, we extract various features and rank them using Mean Decrease Impurity. Second, we transform the features into compact vectors based on word2vec. Finally, we train the classifier based on deep learning model. A comprehensive experimental study on a real sample collection was performed to compare various malware detection approaches. Experimental results demonstrate that the proposed method outperforms other Android malware detection techniques.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.754-757
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• 2010

질의 확장은 초기 검색결과에서 질의와 연관된 단어를 선택하여 질의를 확장함으로써 검색 성능을 향상시키는 기법이다. 페이지 랭크(PageRank) 알고리즘은 웹문서 사이의 링크구조를 이용하여 문서들의 상대적인 중요성을 측정하기 위해 제안되었다. 본 논문에서는 문서들 사이의 관계가 아니라 문서 안에서 단어 그래프(Word Graph)를 통해 단어들 사이의 상대적인 중요성을 계산하였다. 질의와 가까이 위치한 단어들 사이의 관계를 단어 그래프에 적용하여 중요도를 계산하고 확장단어를 선택한다. 본 논문의 유효성을 검증하기 위해 웹문서 집합인 TREC WT10g 에 대해 실험하였고, 적합모델(Relevance Model)보다 MAP(Mean Average Precision)가 4.1% 향상되었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.547-550
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• 2009

블로그는 누구나 쉽게 이용할 수 있는 도구이며, 블로그를 통한 콘텐츠의 생산과 소비는 빠른 속도로 증가하고 있다. 이런 블로그의 글은 단순히 정보를 전달하는 웹 페이지 이상의 사회적 관계를 포함하고 있다. 하지만 지금까지 웹 페이지 및 블로그에 대한 검색은 이러한 사회적 관계를 고려하지 않고 있다. 따라서 본 논문에서는 사용자 행동과 사회적 관계에 기반한 블로그 랭크 모델을 제안한다. 이를 기반으로 국내의 서로 다른 서비스에서 제공한 블로그 랭킹을 새롭게 제안한 블로그 모델과 비교하였고, 이를 통해 제안하는 블로그 모델의 타당성을 제시하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.834-837
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• 2009

There is a growing need for ad-hoc analysis of extremely large data sets, especially at e-Commerce companies which depend on recommender application. Nowadays, as the number of e-Commerce web pages grow to a tremendous proportion; vertical recommender services can help customers to find what they need. Recommender application is one of the reasons for e-Commerce success in today's world. Compared with general e-Commerce recommender application, obviously, general e-Commerce recommender application's processing scope is greatly narrowed down. MapReduce is emerging as an important programming model for large-scale data-parallel applications such as web indexing, data mining, and scientific simulation. The objective of this paper is to explore MapReduce framework for the e-Commerce recommender application on major general and dedicated link analysis for e-Commerce recommender application, and thus the responding time has been decreased and the recommender application's accuracy has been improved.