• The Journal of Engineering Geology
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• v.20 no.3
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• pp.257-269
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• 2010

We analyzed patent trends regarding stabilization technology for steep slope hazards, focusing on patents applied for and registered in Korea, the USA, Japan, and Europe. The technology was classified into four groups at the second classification step: prediction techniques, instrumentation techniques, countermeasure/reinforcement/mitigation techniques, and laboratory tests. A total of 2,134 patents were selected for the final effective analysis. As a result of portfolio analysis using the correlation between the number of patents and the applicant for each patent, the Korean and USA situations were classified as belonging to the developing period, and the Japanese and European situations were classified as belonging to the ebbing period. In particular, patent activity in Korea has been enlivened by government-led research. As a result of technology analysis at the second classification step, prediction techniques arising from Japan are evaluated as a competitive power technique, and laboratory tests arising from the USA are evaluated as a competitive power technique. However, prediction techniques and laboratory tests arising from Korea are evaluated as a blank technique. According to the prediction results regarding future research and developments, a new finite element analysis method and a numerical model should be established as part of prediction techniques, as well as sensors, and hazard prediction should be developed by integrating information and equipment using IT technology as part of instrumentation techniques. In addition, improvements to existing structures for erosion control and the development of new slope-reinforcement methods are required as part of countermeasure/reinforcement/mitigation techniques, and new laboratory apparatus and methods with an optimizing structure should be developed as part of laboratory tests.

• Journal of Technology Innovation
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• v.25 no.3
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• pp.1-24
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• 2017

With the rise of internet of things (IoT), there have been several studies to analyze the technological trend and technological convergence. However, previous work have been relied on the qualitative work that investigate the IoT trend and implication for future business. In response, this study considers the patent information as the proxy measure of technology, and conducts a quantitative and analytic approach for analyzing technological convergence using patent co-classification analysis and text mining. First, this study investigate the characteristics of IoT business, and characterize IoT business into four dimensions: device, network, platform, and services. After this process, total 923 patent classes are classified into four types of IoT technology group. Since most of patent classes are classified into device technology, we developed a co-classification network for both device technology and all technologies. Patent keywords are also extracted and these keywords are also classified into four types: device, network, platform, and services. As a result, technologies for several IoT devices such as sensors, healthcare, and energy management are derived as a main convergence group for the device network. For the total IoT network, base network technology plays a key role to characterize technological convergence in the IoT network, mediating the technological convergence in each application area such as smart healthcare, smart home, and smart grid. This work is expected to effectively be utilized in the technology planning of IoT businesses.

• Journal of Korea Technology Innovation Society
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• v.18 no.4
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• pp.693-718
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• 2015

This paper examines the presence of network structures among convergence technologies focusing on national R&D projects performed by GRIs(Government-sponsored Research Institutes) in Korea. The dataset of convergence technology projects, which were conducted by 24 GRIs over 3 years (2011-2013), are analysed using the network analysis method. In this paper, a convergence technology project is defined as a project that consists of 2 or more then 2 technologies according to the intermediate classification of National Standard Classification of S&T. The research results confirm that convergence researches of government-sponsored research institutes are performed more actively than the entire convergence researches of national R&D projects. Furthermore, technological fields of GRIs' convergence projects are found to be much more varied. This paper also shows that in-house researches are more active than collaborative ones with external organizations. According to the network centrality analysis, it is identified that the network central characteristics of convergence technologies can be classified into internally oriented technologies and externally oriented technologies. Convergence technologies do not just mean simple mixture of different technologies. Therefore Korean government-sponsored research institutes should make more efforts to create convergence research areas which could generate new technologies and industries more effectively than simple multidisciplinary technology researches. From this perspective, some policy suggestions can be derived on the role of government-sponsored research institutes for activating convergence researches through the analysis of status of convergence researches and networks of institutions.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.105.2-105.2
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• 2010

석탄의 직접 연소 대신 고온/고압의 조건에서 불완전연소 및 가스화 반응을 통하여 일산화탄소(CO)와 수소($H_2$)가 주성분인 합성가스를 제조하여 이용하는 석탄 가스화 기술은 현실적인 에너지원의 확보를 위한 방법인 동시에 이산화탄소를 저감할 수 있는 기술이라 할 수 있다. 따라서, 본 연구에서는 non-slagging 방식의 pilot급 분류층 석탄가스화기를 대상으로 고압 미분탄공급장치, 합성가스 냉각장치, 고온 집진장치 등을 연계하여 상용급 석탄가스기와 유사한 $1,300^{\circ}C$, 20 kg/$cm^2$의 운전조건에서 미분탄의 안정적인 공급을 통한 양질의 합성가스 제조 및 제조된 합성가스의 분기 공급특성 시험을 진행하였다. 그리고, 고압 미분탄공급장치는 공급호퍼에 저장된 미분탄을 고온/고압 조건으로 운전되는 석탄가스화기에 공급하기 위한 설비로서, 이러한 고압 미분탄공급장치를 이용한 기류수송 방식의 미분탄 공급 기술은 가스화기 설계 및 운전제어 기술과 더불어 석탄가스화기 시스템의 안정적 연속운전을 위한 가장 핵심적인 기술 중 하나라고 할 수 있다. 따라서, 본 연구에서는 아역청탄인 인도네시아 ABK탄을 대상으로 향후 dense phase 고압 기류수송을 목적으로 하는 고압 미분탄공급장치의 성능특성을 시험을 진행하였는데, 시험 결과 73 kg/h 조건에서 20 kg/$cm^2$의 가스화기에 대한 안정적인 미분탄 공급특성을 확인할 수 있었으며, 이러한 미분탄 공급 조건에서 CO 40～45%, $H_2$ 16~20%, $CO_2$ 5~8% 조성의 양질의 합성가스를 평균적으로 $230{\sim}50Nm^3/h$ 안정적으로 제조할 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.31-39
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• 2008

Until now, there are many technologies to improve studying ability using e-learning system. In most of e-learning system, learners are studying through the lecture materials and studying problems. The studying ability and intention, however, can be improved through the shared materials and discussion. In this case, learning materials are shared by the learners' discussion and shared materials through the board Internet and MSN. Such data was not classified by learners; it was not easy for the learners to search related valuable information. Therefore, it was not helping to learning. The technologies of most text mining extract summary data from the collection of document or classify into similar document from the complex document. In this paper, we implemented e-learning system for learners to improve learning abilities and especially, applied text mining technology to classify learning material for helping learners.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.300-311
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• 2014

According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1323-1331
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• 2017

Despite the fact that the copyright has grown into a large-scale business, there are many constant problems especially in image copyright. In this study, we propose an automatic object extraction and classification system for the scanned educational book image by combining document image processing and intelligent information technology like deep learning. First, the proposed technology removes noise component and then performs a visual attention assessment-based region separation. Then we carry out grouping operation based on extracted block areas and categorize each block as a picture or a character area. Finally, the caption area is extracted by searching around the classified picture area. As a result of the performance evaluation, it can be seen an average accuracy of 83% in the extraction of the image and caption area. For only image region detection, up-to 97% of accuracy is verified.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.461-476
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• 2013

Knowledge maps for science and technology are used extensively in the research projects. However, they are not organized systematically and are not necessarily suitable to be used in the research projects. Therefore, this study aims to organize the knowledge maps in order to support scientific research projects. To this end, the existing knowledge maps for science and technology are classified as one of four types based on data representation methods; the frequency summary map, trend summary map, distribution-based knowledge map and network-based knowledge map. Additionally, by summarizing and classifying the knowledge maps through the principle of 'five w's and one h', the unexplored area are investigated. Finally, some examples of useful knowledge maps in terms of data analysis are provided with details such as definitions, components and utilization purposes. These findings may be a starting point for future research into a better understanding of knowledge maps for science and technology.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.434-434
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• 2018

에코톱은 가장 작고 균일하며 도면의 단위로 사용 가능한 토지, 일반적인 구성요소의 상태, 잠재자연식생, 잠재생태계 기능을 최소한의 단위로 균일하게 분류가 가능한 요소로서 천이단계 또는 토지이용이 서로 다른 패치들로 이루어진 무생물과 생물이 결합된 생태공간으로서 일반적으로 세가지 특성을 포함한다. (1) 가장 작은 동질성 가진 지도로 분류 가능한 단위, (2) 일반적인 기질조건, 잠재적 자연식생 및 잠재적 생태계 기능에 대한 동질성, 그리고 (3) 서로 다른 연속적인 토지 이용 단계에서의 패치로 구성 된다. 현재 네덜란드, 스페인을 포함한 유럽국가에서는 에코톱분류를 통한 하천을 관리하는 방안을 제시하고 있으며 이에 대한 많은 연구가 진행되고 있다. 본 연구에서는 만경강 중류 소양천 합류점의 터지네 구간을 대상으로 하천공간의 복원 이후 연중유황에 따른 에코톱의 변화를 예측하고 이에 따른 개선효과를 정량적으로 분석하는 것이 목적이다. 제방 후퇴, 제방후퇴/구하도 복원, 제방 후퇴/습지 조성 세가지 복원 시나리오를 현재지형과 비교하여 연중 유황별 흐름조건에 따라 에코톱을 도식화 하였으며, 이에 따른 에코톱 다양성 지수를 도출하여 비교분석하였다. 복원 대상지의 복원 시나리오 및 흐름조건에 따른 에코톱의 변화를 분석한 결과 '제방 후퇴/구하도 복원' 일 때 자연요소가 현재지형보다 가장 크게 증가되었으며 3가지 복원 유형 간 자연요소를 비교한 결과 '제방 후퇴/구하도 복원' 일 때 수역과 일년생 초본이 가장 많은 면적을 차지하였으며, '제방 후퇴/습지 조성' 일 때 습지와 다년생 초본이 가장 많은 면적을 차지하였다. 복원 유형 별 연중 유황 조건에 따른 에코톱 다양성 지수분석결과 제방후퇴/습지 조성시 에코톱 다양성 개선효과가 가장 큰 것으로 나타났다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.3
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• pp.237-245
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• 2004

In designing a tunnel, RMR has been widely used to classify rock mass and to decide the support pattern according to the class of rock mass. However, this RMS system can't help relying on the empirical judgment of engineers who use variables which can be obtained only through consideration of the site conditions. In actuality, it is impossible to consider all the rating factors of RMS when using RMR system at the stage of designing. Therefore, in order to confirm possibility of RMR by use of only the quantitative factors for designing, this paper has done discriminant analysis. Rock strength or RQD has high coefficient of correlation with RMR value, and in consideration of the existing standards for rock mass classification, rock intensity and RQD are important factors for classification of rock mass. Through rock mass classification by the existing RMR system and rock mass classification by the discriminant analysis which has considered two variables only, the discriminant analysis using the rock intensity as an independent variable has shown 74.8% accuracy while the discriminant analysis using RQD as an independent variable has shown 74.3% accuracy. In case of the discriminant analysis which has considered both rock intensity and RQD, it has shown 82.5% accuracy. The existing cases have shown 40.3% accuracy at the stage of designing in which all the RMR factors are considered. It means that at the stage of designing, RMR system can work only with the rock intensity and RQD.