• 대한약학회:학술대회논문집
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• 대한약학회 2002년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.2
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• pp.324.1-324.1
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• 2002

Human 5-reductase type II(5AR2) is an important target for the treatment of benign prostatic hyperplasia. In this study we describe the establishment of cell line which stably expressed 3X FLAG tagged human 5AR2. We used this cell line as a cell based assay tool and source for 5AR2 enzyme. First a plasmid (3XFLAGpCMVl0-5AR2) for the expression of 5AR2 was constructed by the use of the vector 3XFLAGpCMV10 and transfected into the HEK 293. By selection with G418 sulfate. ten HEK 293 single cell clones were obtained of which three stably exhibited high 5AR2 activity. (omitted)

• 한국멀티미디어학회논문지
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• 제12권6호
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• pp.867-875
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• 2009

More and richer information sources and services are available on the web everyday. However, harmful information, such as adult content, is not appropriate for all users, notably children. Since internet is a worldwide open network, it has a limit to regulate users providing harmful contents through each countrie's national laws or systems. Additionally it is not a desirable way of developing a certain system-specific classification technology for harmful contents, because internet users can contact with them in diverse ways, for example, porn sites, harmful spams, or peer-to-peer networks, etc. Therefore, it is being emphasized to research and develop context-based core technologies for classifying harmful contents. In this paper, we propose an efficient text filter for blocking harmful texts of web documents using context-based technologies and examine which algorithms for feature selection, the process that select content terms, as features, can be useful for text categorization in all content term occurs in documents, are suitable for classifying harmful contents through implementation and experiment.

• The Journal of the Acoustical Society of Korea
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• 제20권4E호
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• pp.31-38
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• 2001

A large-scale synthesis database for a unit selection based synthesis method usually retains redundant synthesis unit instances, which are useless to the synthetic speech quality. In this paper, to eliminate those instances from the synthesis database, we proposed a new pruning method called weighted vector quantization (WVQ). The WVQ reflects relative importance of each synthesis unit instance when clustering the similar instances using vector quantization (VQ) technique. The proposed method was compared with two conventional pruning methods through the objective and subjective evaluations of the synthetic speech quality: one to simply limit maximum number of instance, and the other based on normal VQ-based clustering. The proposed method showed the best performance under 50% reduction rates. Over 50% of reduction rates, the synthetic speech quality is not seriously but perceptibly degraded. Using the proposed method, the synthesis database can be efficiently reduced without serious degradation of the synthetic speech quality.

• 정보관리연구
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• 제33권2호
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• pp.33-48
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• 2002

본 연구는 연속간행물 선정과 평가에 관한 방법을 살펴보고, 포항공과대학교 SCI 게재논문의 참고문헌 분석을 통하여 학술지 구독의 투자효용성을 평가함으로써, 이용도에 근거한 연속간행물 선정과 장서관리의 기준을 제공하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.5132-5148
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• 2017

Cyber attacks are evolving commensurate with recent developments in information security technology. Intrusion detection systems collect various types of data from computers and networks to detect security threats and analyze the attack information. The large amount of data examined make the large number of computations and low detection rates problematic. Feature selection is expected to improve the classification performance and provide faster and more cost-effective results. Despite the various feature selection studies conducted for intrusion detection systems, it is difficult to automate feature selection because it is based on the knowledge of security experts. This paper proposes a feature selection technique to overcome the performance problems of intrusion detection systems. Focusing on feature selection, the first phase of the proposed system aims at constructing a feature subset using a sequential forward floating search (SFFS) to downsize the dimension of the variables. The second phase constructs a classification model with the selected feature subset using a random forest classifier (RFC) and evaluates the classification accuracy. Experiments were conducted with the NSL-KDD dataset using SFFS-RF, and the results indicated that feature selection techniques are a necessary preprocessing step to improve the overall system performance in systems that handle large datasets. They also verified that SFFS-RF could be used for data classification. In conclusion, SFFS-RF could be the key to improving the classification model performance in machine learning.

• Educational Technology International
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• 제14권2호
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• pp.167-187
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• 2013

Team project learning is a type of Project-Based Learning, which is an effective learning method for developing collaborative competency and interpersonal communication skills, as well as for developing cognitive competency such as critical thinking, creative thinking, and analytical skills. This research, conducted to analyze learning activities, focuses on students' creative thinking and activities in TPBL(Team Project-Based Learning). A qualitative approach including a reflective journal based on the 6 stages of TPBL, was adopted for this purpose. In this study, 69 reflective journals on the three stages (developing a theme, researching, theme-making) of 23 undergraduate students were categorized on the basis of three criteria: divergent thinking factors, convergent thinking factors and affective factors. The results show that the participants' journals demonstrated twenty-eight activities from nine cognitive factors and nine activities from three affective factors were derived from reflect journal. This finding indicates that more appropriate instructional strategies are needed for students to enhance their creative thinking skills and activities

• 한국수학사학회지
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• 제30권2호
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• pp.121-133
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• 2017

In the present study, we investigate and compare the International Mathematical Olympiad participation histories of Korea, China, and Japan. Especially, the processes for the first participation of the IMO, trends in team rankings of the IMO, and national team selection systems and education systems are compared. And we investigate and compare the policies for the talented girls mathematics Olympians. Several proposals are suggested for development of Korean Mathematical Olympiad and participations to IMO.

• 디지털융복합연구
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• 제12권7호
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• pp.217-227
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• 2014

2010년도에 들어서면서 학령인구의 감소와 함께 고등학교 졸업생들의 대학진학률 하향추세로, 대학들은 학생 선발과 양질의 교육콘텐츠 제공이라는 2중의 어려움에 직면하고 있다. 이에 각 대학은 환경의 변화에 대한 신속한 대응과 동시에 다양하고 전문화된 대학교육서비스(팀기반 프로젝트학습, 사례연구, e-러닝, 액션러닝 등)를 도입하고 있다. 본 연구에서는 대학생을 대상으로 팀기반 프로젝트학습이 수업만족에 미치는 영향을 조사하고자 하였다. 이를 위한 측정항목으로 4개 요인(팀 응집력, 팀워크, 팀 성과 및 목표달성)을 설정하고, 설문조사(4개 과목, 34팀, 134명)를 통해서 자료를 수집하여, 구조방정식모형으로 분석했다. 연구모형검증 결과는 팀 응집력${\rightarrow}$팀워크${\rightarrow}$수업만족의 구조가 제시되었으며, 팀 성과와 목표달성은 수업만족에 미치는 영향이 유의하지 않은 것으로 나타났다. 팀기반 프로젝트학습의 경우 팀응집력이 높아야 수업만족정도가 높아지는 것으로 분석되었다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.91-95
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• 2005

In the multidimensional protein identification technology of high-throughput proteomics, we use one-dimensional gel electrophoresis and after the separation by two-dimensional liquid chromatography, the sample is analyzed by tandem mass spectrometry. In this study, we have analyzed the Pseudomonas Putida KT2440 protein. From the protein identification, the protein database was combined with its reversed sequence database. From the peptide selection whose error rate is less than 1%, the SEQUEST database search for the tandem mass spectral data identified 2,045 proteins. For each protein, we compared the molecular weight calibrated from 1D-gel band position with the theoretical molecular weight computed from the amino acid sequence, by defining a variable MW$_{corr}$ Since the bacterial proteome is simpler than human proteome considering the complexity and modifications, the proteome analysis result for the Pseudomonas Putida KT2440 could suggest a guideline to build the protocol to analyze human proteome data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.496-498
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• 2004

An action-selection-mechanism is proposed to deal with sequential behaviors, where associations between some of stimulus and behaviors will be learned by a shortest-path-finding-based reinforcement team ins technique. To be specific, we define behavioral motivation as a primitive node for action selection, and then sequentially construct a network with behavioral motivations. The vertical path of the network represents a behavioral sequence. Here, such a tree fur our proposed ASM can be newly generated and/or updated. whenever a new sequential behaviors is learned. To show the validity of our proposed ASM, some experimental results on a "pushing-box-into-a-goal task" of a mobile robot will be illustrated.