• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.607-610
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• 2008

국내외 연구자들은 각자의 분야에서 다양하고 중요한 연구를 수행하면서 그 연구결과물을 생산하고 있다. 연구결과물의 형태는 학회지 및 학술대회 논문, 연구보고서, 특허, 연구노트, 세미나 발표자료, 학교교재, 신문 및 잡지의 기사 등 매우 다양하다. 이런 다양한 연구결과물을 같은 학문 분야, 같은 주제의 연구자들끼리 서로 공유하고 교환하기 위해서는 정보의 자유로운 이용에 근거한 커뮤니티 환경이 필요하다. 이에, 국가 과학기술정보 유통기관인 한국과학기술정보연구원(KISTI)에서 보유하고 있는 문헌 콘텐트와 사실 콘텐트를 주제별로 분류하고 재가공하여 특정 주제분야 전문 연구자들을 위한 오픈 아카이빙, 오픈 액세스 개념을 적용한 커뮤니티 모델을 개발하여 제공하고자 한다. 본 커뮤니티 모델은 요즘들어 가장 많은 연구가 진행되고 있는 생명과학 분야의 연구결과물을 중심으로 개발하였다. 커뮤니티 모델을 개발하기 위하여 1) KISTI가 보유하고 있는 콘텐트 현황을 조사하고, 2) 그 중에서 생명과학분야 콘텐트의 형태와 특성을 분석하고, 3) 연구자들이 연구결과물을 자유롭게 업로드/다운로드할 수 있는 웹 환경의 플랫폼을 설계하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.563-567
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• 2015

우리나라 하천관리의 패러다임은 1990년대 이후 기존의 치수 및 이수능력을 고려함과 동시에 하천환경의 보전 및 복원을 새로운 목표로 설정한 자연친화적 방식으로 변화되었다. 하천법령 및 제도적 측면에서도 수자원 장기종합계획 및 유역 종합 치수계획은 하천의 환경보전 및 다목적 이용계획을 포함하도록 규정하고 있으며, 국내 하천법에 따르면 하천기본계획 수립 또한 자연친화적 하천조성 및 이와 관련된 보전지구 지정 등을 포함하도록 규정하고 있다. 하천설계기준, 자연 친화적 하천관리에 관한 통합지침, 또는 수자원 장기종합계획에서 적용하고 있는 하천환경조사 및 평가지표는 서로 다를 뿐만 아니라 과학적인 근거가 명확하지 않는 등 국가차원의 표준화가 이루어지지 못한 상태라 할 수 있다. 1990년대 이후 미국, 독일, 영국, 호주 등 선진국들은 하천환경 복원사업의 추진과정에서 복원사업의 타당성 제고 및 성공적인 사업수행을 위하여 그들 국가의 하천특성에 적합한 하천환경 평가 체계를 구축한 바 있으며, 이들 평가체계는 새로운 과학적 지식과 기술의 축적에 힘입어 지속적으로 발전되고 있다. Fujita의 유형화(Segment 분류)법에 의하면, 하천구간(Segment)은 하상경사, 하상재료, 식생, 생태 등이 통계적으로 동질인 하천 구간으로서, 하도 특성과 하천생태계 공간을 구분하는 단위이다. 자연하천에서 동일한 경사를 갖는 하천구간은 하상재료, 소류력, 저수로 폭, 수심 등이 대체로 동일한 값을 나타내고 있으며, 하도 특성을 지배하는 주요 인자로 각 하천의 평균 연최대유량, 하상재료의 대표입경, 하상경사 등을 설정하고 있다. 본 연구에서는 하천구간을 유형화하는 기준을 하상경사로 적용하여 평가단위를 분류하였으며, 평가체계는 미국의 USEPA를 한국형 하천환경에 맞도록 수정보완 하였다. 특히 미국의 USEPA의 지표 중 하안영역의 식생피복, 하반림 등은 생물분야 식생영역과 상충되어 제외하고 우리나라 특성에 적합한 하천횡단형상, 하천횡단 구조물 등의 평가기준을 재정립하여 내성천에 평가적용 분석하였다. 하천환경의 수리 및 하도 특성 평가기준 개발에 따라 평가체계의 개념적 틀을 토대로 통합적이고 표준화된 한국형 하천평가기준 개발을 위한 방법론을 정립하고, 나아가 하천환경의 지속가능성을 전제로 한 하천복원사업의 장 단기적 성공 여부를 평가할 수 있는 실무지침의 과학적 근거를 제시하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.106-107
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• 2022

The ship type identification of the surrounding ship is important information for navigators and VTS officers since they can estimate the maneuverability and near-future route of the ships. However, it is more than frequent that the information is not provided due to transmission trouble and seafarers' unfamiliarity with AIS. Thus, this study suggests predicting ship types through the Random Forest classifier after preparing a training and test dataset that contains ship features and types. The AIS data for Ulsan coast in 2018 was used for this study. The method may provide the effect that many navigators and VTS officers discuss and share the experience of predicting ship types.

• Journal of the Society of Disaster Information
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• v.13 no.3
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• pp.322-331
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• 2017

This study proposed subway construction information classification system based on civil engineering information classification system proposed by Korea Institute of Construction Technology. Also, Based on this criterion, This study established data modeling for NAS operating system Composed of construction information classification system - network - operation and presented an relational database integrated model. The data modeling method proposed in this study can be applied to other civil engineering facilities, so it can be operated as scientific NAS.

• Journal of Information Management
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• v.32 no.2
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• pp.40-53
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• 2001

The purpose of this study is to explore the current situation and problems in standardizing knowledge information and information technology in the KISTI, and collect the basic data necessary for establishing the national information infrastructure. Through a survey and interviews with nine departments of the Information Services Sector of the KISTI, data were collected regarding the management and exchange of information and the operation of communication networks. According to the analysis of fifty KISTI databases and their operation, tasks to be first standardized include Classification of ST resources, Metadata, Date modeling, Data format, DBMS, ST terminology, and Retrieval protocol.

• Journal of Information Management
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• v.41 no.3
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• pp.27-44
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• 2010

Most research about patent data analyzes the trend of technologies using a Patent Map(PM), and suggests the frequencies and trend of patents in a certain topic using tables or graphs in Excel. However, more advanced analysis tools are recently needed to compare the trends among national and international industries. This research discussed why statistical analysis is needed to improve the reliability in PM analysis, and the research compares the trends of patents in Korea between 1990 and 2004 by years, International Patent Classification(IPC) sections, and countries using the frequencies and Poisson regression model. The statistical analysis is also suggested and applied to R&D studies.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.3
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• pp.219-232
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• 2009

This paper is intended to comparatively analyzed the KDC/NDC/DDC classification system for the field of civil engineering, the research field classification system of National Research Foundation of Korea, and the science and technology research field classification system of Korea Science and Engineering Foundation. And based on the analysis, it tried to propose the ways of improving the KDC classification system for the civil engineering field. As a result of the analysis, this paper has found that the KDC 5th-edition for the civil engineering field needed some corrections. That is, the classification items that reflect the trend of academic development should be added, the classification terminology of the basic theories of civil engineering should be properly developed, segmented topics should be added, any errors in classification codes and Korean/English descriptions should be corrected, and the omission of the KDC relative index of classification items should be solved. This paper proposed the ways of improving those problems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.316-318
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• 2019

Recently, healthy life has become an issue in an aging society, and the number of people who have been interested in continuous health care for better life is increasing. In this paper, we implemented a personalized recommendation systm to provide convenient healthcare management for user. The PHR (Personal Health Record) of user could be stored in the server along with health related information such as lifestyle, disease, and physical condition. The users could be classified into similar clusters according to the PHR profile in order to provide healthcare contents to the users who had similar PHR profile. K-Means clustering was applied to generate clusters based on PHR profile and ACDT(Ant Colony Decision Tree) algorithm was used to provide personalised recommendation of health information stored in knowledge base. The app system developed in this paper is useful for users to perform healthcare themselves by providing information on serious diseases and lifestyle habits to be improved according to the clusters classified by PHR profile.

• Journal of KIBIM
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• v.9 no.4
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• pp.31-40
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• 2019

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.3
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• pp.248-262
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• 2021

Marine planktonic ciliates include two major groups, loricated tintinnids and naked oligotrichs. The study of marine ciliate plankton in Korea began with taxonomic efforts on tintinnids based on the morphology of lorica, a vase-shaped shell. Despite polymorphism in the lorica, it is utilized as a key characteristic in identification of tintinnid species. However, oligotrichs have been studied only recently in Korea due to challenges associated with the observation of ciliary arrangements and the technical development for cell staining. Species diversity and phylogenetic classification of the ciliates have been informed by recent advances in morphological and molecular analyses. Illustrations of the planktonic ciliate in Korea have been published on the basis of taxonomic data of tintinnids and oligotrichs. Planktonic ciliates acting as the major consumers of pico- and nanoplankton as well as the prey of mesozooplankton, has been monitored by spatial and temporal investigations in Korean coastal waters. A practical approach addressing the limitations and potential of marine ciliate studies in Korea is proposed here to improve the data quality of planktonic ciliates, providing an enhanced basis for quality control of ciliate monitoring.