• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.219-228
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• 2006

Many biomedical research groups have been trying to share their outputs to increase the efficiency of research. As part of their efforts, a common ontology named Gene Ontology(GO), which comprises controlled vocabulary for the functions of genes, was built. However, data from many research groups are distributed and most systems don't support integrated semantic queries on them. Furthermore, the semantics of the associations between concepts from external classification systems and GO are still not clarified, which makes integrated semantic query infeasible. In this paper we present an ontology matching and integration system, called AutoGOA, which first resolves the semantics of the associations between concepts semi-automatically, and then constructs integrated ontology containing concepts from GO and external classification systems. Also we describe a web-based application, named GOGuide II, which allows the user to browse, query and visualize integrated data.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.89-98
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• 2002

As XML has become an emerging standard for information exchange on the World Wide Web it has gained attention in database communities to extract information from XML seen as a database model. Recently, many researchers have addressed the problem of storing XML data and processing XML queries using traditional database engines. Here, most of them have used relational database systems. In this paper, we show that OODBSs can be another solution. Our technique generates an OODB schema from DTDs and processes XML queries, Especially, we show that the semi-structural part of XML data can be represented by the 'inheritance' and that this can be used to improve query processing.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.2
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• pp.167-174
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• 2009

The AIRWARE System was developed from one of the EUREKA PROJECT E!3266-EUROENVIRON WEBAIR System. The AIRWARE can nowcast and forecast the air quality of Seoul and Gyeonggi-do regions. To nowcast and forecast concentration of pollutants, MM5, AERMOD/CAMx, and SMOKE Models were used for each meteorologic data, measured data, and emission data. All DB were constructed for 2001 year. The episode analysis and time series analysis were accomplished to analyze the AIRWARE reliability. The simulated results were very well agreed with measured result for measured pollutants and meteorological data. The developed AIRWARE system can analyze with real-time, support web-based air quality information. This information can used with policy data to manage the air quality and prepare reduction plan in air impact assessment or air environmental plan.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.235-242
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• 2014

Internet telephony is an Internet service which supports voice telephone using VoIP technology on the IP-based Internet. It has some advantages in that voice telephone services can be accompanied with multimedia services such as video communication and messaging services. In this paper we suggested an Asterisk-based Internet telephony system which can be easily scalable. Most current systems use text files to manage their configuration: SIP users, dialplans, IVR service and etc. But we designed the management system which introduces database tables for efficiency and scalability. It also supports web-based functions developed by using Asterisk, Apache, MySQL, jQuery, PHP and open source softwares.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2015.05a
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• pp.241-254
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• 2015

최근 연구개발(R&D) 관련 연구 주체 간 융복합 연구를 통한 신규 사업 발굴의 관심이 높아지고 있다. 이로 인해 융복합 신규 사업을 발굴하고 기획하는 것이 매우 중요해지고 있으며, 관련하여 이종 분야 간 융복합 분야 발굴을 위한 다양한 방법이 시도되고 있다. 본 논문은 논문 특허 정보 분석을 통해 기존 방법 대비 빠르게 공통 기술을 식별하고, 식별된 결과를 활용한 융복합 연구 전략 수립의 과정을 핵융합 가속기 공통 부품국산화 추진 전략 사례 연구를 통해 제시하고자 한다. 먼저 양 분야 간 어떤 기술들이 공통적으로 다루어지고 있는지를 논문 특허 분석으로 식별하기 위해 핵융합 가속기 분야를 중심으로 WoS(Web of Science) 논문 DB를 활용하여 두 분야 간 공통적으로 출현하는 색인(Index) 빈도수 분석 및 Thomson Innovation을 활용한 신규성(Novelty) 중심의 특허 분석을 수행하여 공통 기술을 식별하는 방법론을 제시하였다. 이렇게 도출된 공통기술 분야는 기술과 관련 산업체의 사상(寫像, mapping) 과정에 활용하여 국산화 추진 후보를 선별하였고, 기술경쟁력, 기술성숙도 등의 기술성 평가 수행으로 국산화 추진을 위한 최종 전략 분야를 선정하여 핵융합 가속기 공통기술 기반의 융복합 연구의 전략 수립 전 과정을 제시하였다.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.209-214
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• 2005

Immunoglobulins (IG) , T cell receptors (TR) and major histocompatibility complex (MHC) are major components of the immune system. Their experimentally determined three-dimensional (3D) structures are numerous and their retrieval and comparison is problematic. IMGT, the international ImMunoGeneTics information system$^{\circledR}$(http://imgt.cines.fr), has devised controlled vocabulary and annotation rules for the sequences and 3D structures of the IG TR and MHC. Annotated data from IMGT/3D sructure-DB, the IMGT 3D structure database, are used in this paper to compare 3D structure of the domains and receptor, and to characterize IG/antigen, peptide/MHC and TR/peptide/MHC interfaces. The analysis includes angle measures to assess receptor flexibility, structural superimposition and contact analysis. Up-to-date data and analysis results are available at the IMGT Web site, http://imgt.cines.fr.

• Genomics & Informatics
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• v.5 no.4
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• pp.188-193
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• 2007

The Functional Element SNPs Database (FESD) categorizes functional elements in human genic regions and provides a set of single nucleotide polymorphisms (SNPs) located within each area. Users may select a set of SNPs in specific functional elements with haplotype information and obtain flanking sequences for genotyping. Our previous version of FESD has been improved in several ways. We regenerated all the data in FESD II from recently updated source data such as HapMap, UCSC GoldenPath, dbSNP, OMIM, and $TRANSFAC^{(R)}$. Users can obtain information about tagSNPs and simulate LD blocks for each gene from four ethnicities in the HapMap project on the fly. FESD II employs a Java/JSP web interface for better platform portability and higher speed than PHP in the previous version. As a result, FESD II provides its users with more powerful information about functional element SNPs of human ethnicities.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.562-565
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• 2000

A data registry is a physical place to keep characteristics of classes of objects exist in the real world when they are chosen to record as data. It provides a centralized directory to describe the meaning, representation, and identification of data elements and their values. It assists to prevent redundancy and to preserve common understanding about the data described in a metadata set. In this paper, we investigate and classify various components of IBS(Intelligent Building Systems), specially HVAC in Building Automation Systems. We present IBSDR(Intelligent Building Systems Data Registry) model that specifies not only the detailed information on data elements but also the process of documenting data in IBS. It functions as the medium to create the data sharing environment to maintain exact meaning of data for every data elements so that database management designers or related users can create and exchange their DB without major modification. It also serves as a clearinghouse for information about IBS data. So all users can freely retrieve from and register data elements to IBSDR based on ISO/IEC 11179 through World Wide Web.

• Journal of the Korean Society for information Management
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• v.28 no.4
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• pp.183-200
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• 2011

This study surveyed editors of 309 gratis open access journals in Korea in order to examine the reason why they decided to open their journals to the public on the Web. Also this study examined their perceptions and attitudes toward open access publishing. The main reasons of open access publishing in Korea were expansion of free use, increasing citation, and international trends regarding open access in their scholarly fields. Also, 65% of all respondents were aware of the concepts of open access, and 75% supported open access. The reasons of supporting open access were sharing of research results with the public, increasing the availability of peer researchers, and enhancing journal reputations.