• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.77-86
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• 2004

In this study, we applied the Bayesian Network for the case of the mode choice models using the Seoul metropolitan area's house trip survey Data. Sex and age were used lot the independent variables for the explanation or the mode choice, and the relationships between the mode choice and the travellers' social characteristics were identified by the Bayesian Network. Furthermore, trip and mode's characteristics such as time and fare were also used for independent variables and the mode choice models were developed. It was found that the Bayesian Network were useful tool to overcome the problems which were in the traditional mode choice models. In particular, the various transport policies could be evaluated in the very short time by the established relation-ships. It is expected that the Bayesian Network will be utilized as the important tools for the transport analysis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.11
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• pp.24-32
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• 2005

The object of this study is to design radar absorbing structures(RAS) with load-bearing ability in X-band. Glass/Epoxy plain-weave composites of excellent specific stiffness and strength, containing multi-walled carbon nanotubes(MWNT) added to induce dielectric loss were fabricated. The observation of microstructure and the permittivity of the composites confirmed that the materials are suitable to be used for radar absorbing material. Genetic algorithm and theory for reflection/transmission of electromagnetic waves in a multi-layered RAS were applied to conduct an optimal design of a RAS composed of the developed composites. We observed that the thickness per ply changes with the number of ply and MWNT contents. The fabrication process was proposed considering the problem and applied to fabricate a designed RAS and the theoretical and measured reflection loss of the RAS were also found in good agreement.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.125-131
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• 2008

It is very useful to predict orthologs for new genome annotation and research on genome evolution. We showed that the previous work can be extended to construct OCs(Ortholog Clusters) automatically from multiple complete-genomes. The proposed method also has the quality of production of InParanoid, which produces orthologs from just two genomes. On the other hand, in order to predict more exactly the function of a newly sequenced gene it can be an important issue to prevent unwanted inclusion of paralogs into the OCs. We have, here, investigated how well it is possible to construct a functionally purer OCs with score cut-offs. Our OCs were generated from the datasets of 20 procaryotes. The similarity with both COG(Clusters of Orthologous Group) and KO(Kegg Orthology) against our OCs has about 90% and inclines to increase with the growth of score cut-offs.

• Korean Journal of Cognitive Science
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• v.22 no.1
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• pp.39-55
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• 2011

People tend to overestimate their emotional reactions to events such as physical handicap and buying a new car in the future. Students overestimate their reactions to a future grade as compared to their reactions after receiving the grade. Impact bias refers to people's tendency to overestimate the intensity and the duration of emotional reactions to a future event. The present study explored whether impact bias occurs to risky objects such as nuclear energy, genetically engineered food, and mobile phone. Participants were asked to predict their emotional reactions at three time points, that is, at the present, a week after, and a year after. They predicted their reactions before and after two debiasing tasks. The present study demonstrated a different pattern of impact bias at three time points: A largest bias was observed a week after the present. A defocalism manipulation has eliminated the impact bias whereas an adaptation manipulation has not. Several points were discussed regarding the difference between the previous and the present work.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.2
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• pp.136-142
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• 2012

Various factors affecting on the bioassay were investigated. Experiments with a low mixture ratio (cell to toxicant solution) of 0.5 : 9.5 (v/v) produced observable bioluminescence intensity for assay. Both sodium lactate and potassium nitrate stimulate bioluminescence activity; 2.6~4.0 times of control. Distilled water and MSM, which gave non significant effects on the bioluminescence activity, were determined as proper diluent or extract solutions. A wide range of toxic responses of metals and organics were observed. In general, organics were much less sensitive than metals. Samples collected from eleven sites showed the bioluminescence activity ranging from 29 to 111% of the control. Significant correlation between toxicity and total metal contents was not observed, but the toxicity of two groups, sorted based on the contaminated arsenic concentration in soils, was 44% and 20%, showing considerable differences.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.104-106
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• 2005

In this work, a PWR reactor core dynamics is identified online by a recursive least squares method. Based on this identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to design an automatic controller for thermal power control in PWRs. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired one, and the variation of the control rod positions. Also, the objectives are subject to maximum and minimum control rod positions and maximum control rod speed. Therefore, the genetic algorithm that is appropriate to accomplish multiple objectives is used to optimize the model predictive controller. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the 5%/min ramp increase or decrease of a desired load and its 10% step increase or decrease which are design requirements, it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• KSBB Journal
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• v.19 no.1
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• pp.42-49
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• 2004

A gene coding for epoxide hydrolase (EH) of Aspergillus niger LK, a fungus possessing the enantioselective hydrolysis activity for racemic epoxides, was characterized by phylogenetic analysis. The deduced protein of A. niger LK epoxide hydrolase shares significant sequence similarity with several bacterial EHs and mammalian microsomal EHs (mEH) and belongs to the a/${\beta}$ hydrolase fold family. EH from A. niger LK had 90.6% identity with 3D crystal structure of lqo7 in Protein Data Bank. Sequence comparison with other source EHs suggested that Asp$\^$l92/, Asp$\^$374/ and His$\^$374/ constituted the catalytic triad. Based on the multiple sequence comparison of the functional and structural domain sequence, the phylogenetic tree between relevant epoxide hydrolases from various species were reconstructed by using Neighbor-Joining method. Genetic distances were so far as 1.841-2.682 but characteristic oxyanion hole and catalytic triad were highly conserved, which means they have diverged from a common ancestor.

• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.151-157
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• 2012

Recently, owing to the technology advances in computer science and image processing, age of face classification have become prevalent topics. It is difficult to estimate age of facial shape with statistical figures because facial shape of the person should change due to not only biological gene but also personal habits. In this paper, we proposed a robust age of face classification method by using Gabor feature and fuzzy support vector machine(SVM). Gabor wavelet function is used for extracting facial feature vector and in order to solve the intrinsic age ambiguity problem, a fuzzy support vector machine(FSVM) is introduced. By utilizing the FSVM age membership functions is defined. Some experiments have conducted to testify the proposed approach and experimental results showed that the proposed method can achieve better age of face classification precision.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.684-695
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• 2001

Recent recommender system uses a method of combining collaborative filtering system and content based filtering system in order to solve sparsity and first rater problem in collaborative filtering system. Collaborative filtering systems use a database about user preferences to predict additional topics. Content based filtering systems provide recommendations by matching user interests with topic attributes. In this paper, we describe a method for discovery of user preference through combining two techniques for recommendation that allows the application of machine learning algorithm. The proposed collaborative filtering method clusters user using genetic algorithm based on items categorized by Naive Bayes classifier and the content based filtering method builds user profile through extracting user interest using relevance feedback. We evaluate our method on a large database of user ratings for web document and it significantly outperforms previously proposed methods.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2006.02a
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• pp.57-61
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• 2006

Microarray란 유리, 실리콘, 플라스틱 등의 매체위에 생체분자를 집적하여 만든 플랫폼을 의미한다. 현재 이러한 플랫폼에 DNA, 화학물질, 유기물질 등 바이오소재를 집적하여 다양한 연구용 제품들이 출시되어 있으며, 수년간 Microarray를 이용한 연구가 진행되어 최근에는 질병진단/예후예측 등의 포괄적인 정보를 포함하는 임상용 microarray제품도 등장하고 있다. 디지탈지노믹스(주)는 2000년 이후로 6년의 기간동안 연구자에게 다양한 종류의microarray를 공급하여 왔으며, 현재 국내에서 가장 많은 종류의 microanay 분석 시스템을 확보하고 있다. 따라서 다양한 연구자들에게 가장 적합한 microarray를 소개할 수 있음은 물론, 그 결과분석 데이터를 제공함으로써 양질의 데이터와 서비스를 제공하고 있다. 특히 디지탈지노믹스(주)에서는 최근에 Combimatrix사의 microarray 시스템을 도입하여, 연구자가 원하는 맞춤형 microarray를 제작할 수 있는 새로운 형태의 차세대 플랫폼을 제공할 수 있게 되었다. 이 기술은 연구자의 목적에 맞게 microarray 제작이 가능하도록 가변적인 특성을 가지고 있으며 높은 민감도 및 재현성을 보여주는 우수한 기술력을 보여준다. Microarray 분야는 그 플랫폼과 분석기술이 나날이 발전하고 있으며, 그 응용범위도 날로 넓어 지고 있다. 그 활용범위의 예를 보면, 1) 유전체 수준에서 발현양상 분석, 2) 약물에 대한 반응성 분석, 3) 질환에 대한 원인 유전자 규명 및 진단제 개발, 4) 독성유전체에서의 약효 및 유효성 분석, 5) 대량의 SNP 분석, 6) 대량의 단백질 수준에서의 발현분석 등이 있으며, 일일이 다 언급하기 힘들 정도로 그 응용범위가 넓어지고 있다. 이러한 microarray기술은 관심 있는 대상에 대한 검색(screening)의 기능과 더불어 분석된 데이터를 기초로 제품화 플랫폼으로써 다시 활용될 수 있는 장점을 가지고 있다. 디지탈지노믹스(주)에서는 구축되어 있는 microarray 분석 시스템을 이용하여 질병 진단, 약물반응성 진단 및 플랫폼 개발에 대한 내부연구도 심도 있게 수행하고 있으며, microarray 기술을 응용하여 산업화, 제품화 할 수 있는 구체적인 사례와 모범답안을 만들기 위해 노력하고 있다.