• Title/Summary/Keyword: 바이오 데이터

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The authentication technology Research for using secure e-passports (안전한 전자여권 사용을 위한 인증 기술 연구)

  • Jun, Sang-Yeob;Park, Jung-Hyo;Jang, Seung-Jae;Jun, Moon-Seog
    • Proceedings of the KAIS Fall Conference
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    • 2010.05a
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    • pp.183-186
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    • 2010
  • 최근 전 세계적으로 전자여권을 도입하기 위한 연구가 미국을 중심으로 활발히 진행되고 있다. 또한 전자여권은 비접촉식 스마트카드 기능의 IC(Integrated Circuit) 칩에 사용자의 정보와 바이오정보 그리고 여러 보안 기능들을 포함함으로써 기존의 여권에서 발생하는 문제점들을 해결하고 있다. 그러나 기존의 RFID(Radio Frequency Identification) 기술에서 발생하는 데이터 위변조, 도청, 무단복제 및 바이오정보 노출 등의 문제점들을 아직 내재하고 있다. 따라서 본 논문에서는 현재 필수로 적용되는 BAC 메커니즘을 조금 더 안정적이고 효율적으로 개선한 EBAC 메커니즘을 제안한다.

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SMS : An SBML Document Manager (SMS : SBML 문서관리기)

  • 임정곤;김태경;정태성;조완섭
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.04b
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    • pp.334-336
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    • 2004
  • 최근 이슈가 되고 있는 시스템 생물학(Systems Biology)은 생물학적인 이론과 컴퓨터의 계산적인 모델링 그리고 실험의 상호 의존적인 통합으로써 특징 지워진다. 그 중 컴퓨터의 계산적인 모델링에 대한 연구가 무엇보다 중요한 비중을 차지하고 있다. 하지만 계산적인 모델링에서 여러 자원을 통합하기 위한 공통의 기반 구조나 표준에 대한 연구는 미흡한 실정이다. 이러한 문제점을 해결하기 위해 XML 기반의 형식을 갖춘 SBML(Systems Biology Markup Language)이 시스템 생물학의 표준으로 개발되어 연구 중에 있다. 현재 개발 중인 시뮬레이션과 데이터 분석을 위한 다양한 옹용 어플리케이션이 이미 SBML 문서를 지원하고 있다 본 연구에서는 시스템 생물학 분야에서 SBML 표준에 대한 중요성을 인식하여, 객체지향 바이오 데이터베이스로부터 질의의 결과를 SBML 문서로 변환하고, 반대로 SBML 문서를 객체지향 데이터베이스에 저장하는 변환기를 제안하고자 한다.

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Clustered Segment Indexing for Searching on the Secondary Structure of Protein (단백질 이차구조의 검색을 위한 클러스터링된 세그먼트 인덱싱)

  • 서민구;박상현
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.04b
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    • pp.298-300
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    • 2004
  • 바이오 인포메틱스에서의 데이터 검색은 DNA와 단백질 시퀀스에 대해서 주로 이루어지며, 지금까지의 연구는 주로 DNA와 단백질 1차 구조의 검색에 대해 이루어졌다. 단백질 2차구조는 1차구조 내 인접한 아미노산들의 공간적인 배열을 나타내며. 단백질의 기능을 예측하는데 중요한 3차구조의 지역적 아미노산의 특성을 나타낸다. 따라서 2차구조에 대한 검색은 단백질의 기능을 이해하는데 매우 중요한 역할을 한다[1]. 이 논문에서는 단백질 2차구조 및 질의 문자열을 세그먼트 단위로 나누고 검색하는 r41의 방법을 개선하여 세그먼트를 조합한 클러스터 구조 및 Look Ahead를 사용해 Exact Matching 및 Wildcard Matching 질의를 효율적으로 처리할 수 있는 기법을 제시한다.

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Mood and Color Distribution of Music genres (음악 장르에 따른 분위기와 색상 분포)

  • Moon, Chang-Bae;Kim, Hyun-Soo;Kim, Byeong-Man;Yi, Jong-Yeol;Suk, Jin-Weon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.04a
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    • pp.357-360
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    • 2011
  • 스트레스는 다양한 질병의 원인이 되며 스트레스의 해소는 질병 예방에 중요한 요인이라 할 수 있을 것이다. 스트레스를 해소시키는 방법 중 한 가지는 청각이나 시각을 이용하는 방법이다. 청각과 시각을 동시에 이용할 수 있다면 그 효과를 극대화 할 수 있을 것이다. 이러한 맥락에서 본 논문에서는 음원의 분위기와 분위기 단어의 색상을 수집한 후 수집한 데이터를 이용하여 음악 장르에 따른 분위기 분포와 분위기 단어에 따른 색상을 이용하여 음악 장르에 따른 색상 분포가 다르다는 것을 확인하기 위해 Minitab을 이용하여 $x^2$-test를 실시하였다. 분석결과, P<0.001로 음악 장르에 따라 분위기 색상이 다르게 분포되며 분위기에 따라 색상 및 명도, 채도의 분포도 다르게 나타남을 확인하였다.

Big data distributed processing system using RHadoop (RHadoop을 이용한 빅데이터 분산처리 시스템)

  • Shin, Ji Eun;Jung, Byung Ho;Lim, Dong Hoon
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.5
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    • pp.1155-1166
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    • 2015
  • It is almost impossible to store or analyze big data increasing exponentially with traditional technologies, so Hadoop is a new technology to make that possible. In recent R is using as an engine for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with various data sizes of actual data and simulated data. Experimental results showed our RHadoop system was faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and biglm packages available on bigmemory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Estimation of Fresh Weight and Leaf Area Index of Soybean (Glycine max) Using Multi-year Spectral Data (다년도 분광 데이터를 이용한 콩의 생체중, 엽면적 지수 추정)

  • Jang, Si-Hyeong;Ryu, Chan-Seok;Kang, Ye-Seong;Park, Jun-Woo;Kim, Tae-Yang;Kang, Kyung-Suk;Park, Min-Jun;Baek, Hyun-Chan;Park, Yu-hyeon;Kang, Dong-woo;Zou, Kunyan;Kim, Min-Cheol;Kwon, Yeon-Ju;Han, Seung-ah;Jun, Tae-Hwan
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.329-339
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    • 2021
  • Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R2=0.74, RMSE=246 g/m2, RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m2 and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m2 and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m2) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

A Study on MAC Protocol Design for Mobile Healthcare (모바일 헬스케어를 위한 MAC 프로토콜 설계에 관한 연구)

  • Jeong, Pil-Seong;Kim, Hyeon-Gyu;Cho, Yang-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.2
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    • pp.323-335
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    • 2015
  • Mobile healthcare is a fusion of information technology and biotechnology and is a new type of health management service to keep people's health at anytime and anywhere without regard to time and space. The WBAN(Wireless Body Area Network) technology that collects bio signals and the data analysis and monitoring technology using mobile devices are essential for serving mobile healthcare. WBAN consisting of users with mobile devices meet another WBAN during movement, WBANs transmit data to the other media. Because of WBAN conflict, several nodes transmit data in same time slot so a collision will occur, resulting in the data transmission being failed and need more energy for re-transmission. In this thesis, we proposed a MAC protocol for WBAN with mobility to solve these problems. First, we proposed a superframe structure for WBAN. The proposed superframe consists of a TDMA(Time Division Muliple Access) based contention access phase with which a node can transmit data in its own time slot and a contention phase using CSMA/CA algorithm. Second, we proposed a network merging algorithm for conflicting WBAN based on the proposed MAC protocol. When a WBAN with mobility conflicts with other WBAN, data frame collision is reduced through network reestablishment. Simulations are performed using a Castalia based on the OMNeT++ network simulation framework to estimate the performance of the proposed superframe and algorithms. We estimated the performance of WBAN based on the proposed MAC protocol by comparing the performance of the WBAN based on IEEE 802.15.6. Performance evaluation results show that the packet transmission success rate and energy efficiency are improved by reducing the probability of collision using the proposed MAC protocol.

The Analysis Framework for User Behavior Model using Massive Transaction Log Data (대규모 로그를 사용한 유저 행동모델 분석 방법론)

  • Lee, Jongseo;Kim, Songkuk
    • The Journal of Bigdata
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    • v.1 no.2
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    • pp.1-8
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    • 2016
  • User activity log includes lots of hidden information, however it is not structured and too massive to process data, so there are lots of parts uncovered yet. Especially, it includes time series data. We can reveal lots of parts using it. But we cannot use log data directly to analyze users' behaviors. In order to analyze user activity model, it needs transformation process through extra framework. Due to these things, we need to figure out user activity model analysis framework first and access to data. In this paper, we suggest a novel framework model in order to analyze user activity model effectively. This model includes MapReduce process for analyzing massive data quickly in the distributed environment and data architecture design for analyzing user activity model. Also we explained data model in detail based on real online service log design. Through this process, we describe which analysis model is fit for specific data model. It raises understanding of processing massive log and designing analysis model.

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The Cut Detection System using Sum of Square Difference of Color between frames of Video Image Data (동영상데이터의 프레임간 색상차의 자승합을 이용한 컷 검출시스템)

  • 김병철;정창렬;고진광
    • Journal of Internet Computing and Services
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    • v.3 no.5
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    • pp.51-62
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    • 2002
  • The development of computer technology and the advancement of the technology of information and communications spread the technology of multimedia and increased the use of multimedia data with large capacity, Users can grasp the overall video data and they are able to play wanted video back. To grasp the overall video data it is necessary to offer the list of summarized video data information, In order to search video efficiently on index process of video data is essential and it is also indispensable skill, Therefore, this thesis suggested the effective method about the cut detection of frames which will become a basis of an index based on contents of video image data. This suggested method was detected as the unchanging pixel color intelligence value, classified into diagonal direction. Pixel value of color detected in each frame of video data is stored as A(i, j) matrix-i is the number of frames. j is an image height of frame. By using the stored pixel value as the method of sum of squared difference of color two frames I calculated a specified value difference between frames and detected cut quickly and exactly in case it is bigger than threshold value set in advance, To carry out on experiment on the cut detection of frames comprehensively, I experimented on many kinds of video. analyzing and comparing efficiency of the cut detection system.

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A Case Study of U.S. Academic Libraries' Research Data Support Services (미국 대학도서관의 연구데이터 지원 서비스 사례 연구)

  • Shim, Wonsik
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.4
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    • pp.311-332
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    • 2016
  • Academic libraries have actively responded to social requirements and changes in scholarly communication system. In recent years, social and scholarly requirements for systematic management and sharing of research data have become apparent. Major countries including U.S., UK and Australia have begun national policies requiring management and sharing of research data from publicly funded R&D projects. This case study identified four academic libraries in the US with active research data support services and analyzed them in terms of how they established dedicated unit and the extent of services in the areas of instruction, consulting and system support. The analysis provides context for academic libraries in Korea in formulating their future research data strategies. The core of the recommendation is primarily concerned with developing instructional services and strengthening library's capabilities for research data management and sharing.