• 제목/요약/키워드: Data Analysis and Search

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빅데이터를 활용한 음식관광관련 의미연결망 분석의 탐색적 적용 (An Exploratory Study on the Semantic Network Analysis of Food Tourism through the Big Data)

  • 김학선
    • 한국조리학회지
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    • 제23권4호
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    • pp.22-32
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    • 2017
  • The purpose of this study was to explore awareness of food tourism using big data analysis. For this, this study collected data containing 'food tourism' keywords from google web search, google news, and google scholar during one year from January 1 to December 31, 2016. Data were collected by using SCTM (Smart Crawling & Text Mining), a data collecting and processing program. From those data, degree centrality and eigenvector centrality were analyzed by utilizing packaged NetDraw along with UCINET 6. The result showed that the web visibility of 'core service' and 'social marketing' was high. In addition, the web visibility was also high for destination, such as rural, place, ireland and heritage; 'socioeconomic circumstance' related words, such as economy, region, public, policy, and industry. Convergence of iterated correlations showed 4 clustered named 'core service', 'social marketing', 'destinations' and 'social environment'. It is expected that this diagnosis on food tourism according to changes in international business environment by using these web information will be a foundation of baseline data useful for establishing food tourism marketing strategies.

사회 네트워크 분석을 이용한 충성고객과 이탈고객의 구매 특성 비교 연구 (Social Network Analysis to Analyze the Purchase Behavior Of Churning Customers and Loyal Customers)

  • 김재경;최일영;김혜경;김남희
    • 경영과학
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    • 제26권1호
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    • pp.183-196
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    • 2009
  • Customer retention has been a pressing issue for companies to get and maintain the loyal customers in the competing environment. Lots of researchers make effort to seek the characteristics of the churning customers and the loyal customers using the data mining techniques such as decision tree. However, such existing researches don't consider relationships among customers. Social network analysis has been used to search relationships among social entities such as genetics network, traffic network, organization network and so on. In this study, a customer network is proposed to investigate the differences of network characteristics of churning customers and loyal customers. The customer networks are constructed by analyzing the real purchase data collected from a Korean cosmetic provider. We investigated whether the churning customers and the loyal customers have different degree centralities and densities of the customer networks. In addition, we compared products purchased by the churning customers and those by the loyal customers. Our data analysis results indicate that degree centrality and density of the churning customer network are higher than those of the loyal customer network, and the various products are purchased by churning customers rather than by the loyal customers. We expect that the suggested social network analysis is used to as a complementary analysis methodology with existing statistical analysis and data mining analysis.

평판 구조물의 손상규명 (Identification of Damages within a Plate Structure)

  • 김남인;이우식
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2000년도 추계학술대회논문집A
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    • pp.671-675
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    • 2000
  • In this study, an FRF-based structural damage identification method (SDIM) is proposed for plate structures. The present SDIM is derived from the partial differential equation of motion of the damaged plate, in which damage is characterized by damage distribution function. Various factors that might affect the accuracy of the damage identification are investigated. They include the number of modal data used in the analysis and the damage-induced modal coupling. In the present SDIM, an efficient iterative damage self-search method is introduced. The iterative damage search method efficiently reduces the size of problem by searching out and then by removing all damage-free zones at each iteration of damage identification analysis. The feasibility of the present SDIM is studied by some numerically simulated tests.

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청소년 건강관련 공개자료 접근 및 활용에 관한 고찰 (Access to and Utilization of the Open Source Data-related to Adolescent Health)

  • 이재은;성정혜;이원재;문인옥
    • 한국학교ㆍ지역보건교육학회지
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    • 제11권1호
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    • pp.67-78
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    • 2010
  • Background & Objectives: Current trend is that funding agencies require investigators to share their data with others. However, there is limited guidance how to access and utilize the shared data. We sought to determine what common data sharing practices in U.S.A. are, what data-related to adolescent health are freely available, and how we deal with the large dataset adopting the complex study design. Methods: The study included only research data-related to adolescent health which was collected in USA and unlimitedly accessible through the internet. Only the raw data, not aggregated, was considered for the study. Major keywords for web search were "adolescent", "children", "health", and "school". Results: Current approaches for public health data sharing lacked of common standards and varied largely due to the data's complex nature, large size, local expertise and internal procedures. Some common data sharing practices are unlimited access, formal screened access, restricted access, and informal exclusive access. The Inter-University Consortium for Political and Social Research and the Center for Disease Control and Prevention were the best data depository. "Data on the net" was search engine for the website providing data freely available. Six datasets related to adolescent health freely available were identified. The importance and methods of incorporating complex research design into analysis was discussed. Conclusion: There have been various attempts to standardize process for open access and open data using the information technology concept. However, it may not be easy for researchers to adapt themselves to this high technology. Therefore, guidance provided by this study may help researchers enhance the accessibility to and the utilization of the open source data.

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ARC(Heat-wait-search method)와 Isothermal 조건을 이용한 압축형 복합화약의 열적 특성 및 노화 예측 연구 (Study on the Thermal Property and Aging Prediction for Pressable Plastic Bonded Explosives through ARC(Heat-wait-search method) & Isothermal Conditions)

  • 이소정;김승희;권국태;전영진
    • 한국추진공학회지
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    • 제22권4호
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    • pp.55-60
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    • 2018
  • 열적 특성은 에너지 물질 분야에서 중요한 특성 중 하나로, 분해열을 방출하기 때문에, 열적 특성 분석에 DSC(Differential Scanning Calorimetry)가 자주 사용된다. 그러나 DSC 측정의 경우, 용융과 같은 열역학적 변화가 kinetics 분석에 방해를 끼친다. 이번 연구에서는 이 문제점을 해결하는 방안으로, 등온 조건으로 한 DSC 기초 데이터와 g 단위로 측정하는 ARC(Accelerating Rate Calorimetry)의 데이터를 이용하여 AKTS(Advanced Kinetics and Technology Solutions) thermokinetic 프로그램을 이용하여 열적 노화 특성을 예측, 비교한다.

ISO 최소영역법에 기준한 캠 디스크의 형상 오차 해석 (Form Error Analysis of a Cam Disk Profile Based on ISO Minimum Zone Criterion)

  • 강재관;김원일
    • 한국기계가공학회지
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    • 제5권3호
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    • pp.80-85
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    • 2006
  • In an effort to reduce the evaluation time of the precision of manufactured disk cams, an effective measuring method with an exclusively built profile-measuring machine and subsequent data analysis procedure is proposed. The design and measuring data are interpolated by cubic spline curves to compute the precision error which is defined by the maximum and minimum distances between two curves. The minimum zone criterion of ISO is employed to evaluate the form error, and genetic algorithm is used to search the orientation and location of design data for the measured data which minimizes the form error. The proposed system was applied to marine engine cams, and it shows that the form error is reduced to 30% down compared with the method which minimizes the form error with the assumption that the centers of measured data design cam curve are identical.

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빅데이터 처리를 위한 보안관제 시각화 구현과 평가 (Design and Evaluation Security Control Iconology for Big Data Processing)

  • 전상준;윤성열;김정호
    • Journal of Platform Technology
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    • 제8권4호
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    • pp.38-46
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    • 2020
  • 본 연구에서는 민간기업들이 전체적인 보안관제 인프라를 구축 할 수 있도록 오픈소스 빅데이터 솔루션을 이용하여 보안관제 체계를 구축하는 방법을 기술한다. 특히, 보안관제 시스템을 구축할 때 비용·개발시간을 단축 할 수 있는 하나의 방법으로 무료 오픈소스 빅데이터 분석 솔루션 중 하나인 Elastic Stack을 활용하여 인프라를 구축했으며, 산업에 많이 도입되는 제품인 Splunk와 비교실험을 진행했다. 또한 두 솔루션을 기능, 사용의 용이성, 서비스지원, 기술지원 등을 비교해석 한 결과, Elastic Stack이 사용자간 커뮤니티, 오픈 솔루션면에서 빅데이터의 보안관제가 유리함을 알 수 있었다. Elastic Stack을 활용해 보안 로그를 단계별로 수집-분석-시각화 하여 대시보드를 만들고 대용량 로그를 입력 후 보안관제 검색 속도를 측정하였다. 이를 통해 Elastic Stack이 Splunk를 대체할 수 있는 빅데이터 분석 솔루션으로 기업들이 접근 가능성을 얻을 수 있다.

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Reinterpretation of the protein identification process for proteomics data

  • Kwon, Kyung-Hoon;Lee, Sang-Kwang;Cho, Kun;Park, Gun-Wook;Kang, Byeong-Soo;Park, Young-Mok
    • Interdisciplinary Bio Central
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    • 제1권3호
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    • pp.9.1-9.6
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    • 2009
  • Introduction: In the mass spectrometry-based proteomics, biological samples are analyzed to identify proteins by mass spectrometer and database search. Database search is the process to select the best matches to the experimental mass spectra among the amino acid sequence database and we identify the protein as the matched sequence. The match score is defined to find the matches from the database and declare the highest scored hit as the most probable protein. According to the score definition, search result varies. In this study, the difference among search results of different search engines or different databases was investigated, in order to suggest a better way to identify more proteins with higher reliability. Materials and Methods: The protein extract of human mesenchymal stem cell was separated by several bands by one-dimensional electrophorysis. One-dimensional gel was excised one by one, digested by trypsin and analyzed by a mass spectrometer, FT LTQ. The tandem mass (MS/MS) spectra of peptide ions were applied to the database search of X!Tandem, Mascot and Sequest search engines with IPI human database and SwissProt database. The search result was filtered by several threshold probability values of the Trans-Proteomic Pipeline (TPP) of the Institute for Systems Biology. The analysis of the output which was generated from TPP was performed. Results and Discussion: For each MS/MS spectrum, the peptide sequences which were identified from different conditions such as search engines, threshold probability, and sequence database were compared. The main difference of peptide identification at high threshold probability was caused by not the difference of sequence database but the difference of the score. As the threshold probability decreases, the missed peptides appeared. Conversely, in the extremely high threshold level, we missed many true assignments. Conclusion and Prospects: The different identification result of the search engines was mainly caused by the different scoring algorithms. Usually in proteomics high-scored peptides are selected and low-scored peptides are discarded. Many of them are true negatives. By integrating the search results from different parameter and different search engines, the protein identification process can be improved.

Development of an Analysis Program of Type I Polyketide Synthase Gene Clusters Using Homology Search and Profile Hidden Markov Model

  • Tae, Hong-Seok;Sohng, Jae-Kyung;Park, Kie-Jung
    • Journal of Microbiology and Biotechnology
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    • 제19권2호
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    • pp.140-146
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    • 2009
  • MAPSI(Management and Analysis for Polyketide Synthase Type I) has been developed to offer computational analysis methods to detect type I PKS(polyketide synthase) gene clusters in genome sequences. MAPSI provides a genome analysis component, which detects PKS gene clusters by identifying domains in proteins of a genome. MAPSI also contains databases on polyketides and genome annotation data, as well as analytic components such as new PKS assembly and domain analysis. The polyketide data and analysis component are accessible through Web interfaces and are displayed with diverse information. MAPSI, which was developed to aid researchers studying type I polyketides, provides diverse components to access and analyze polyketide information and should become a very powerful computational tool for polyketide research. The system can be extended through further studies of factors related to the biological activities of polyketides.

자료포락분석을 이용한 간호조직 성과관리: 문헌 분석과 활용 전략 (Performance Management for Nursing Organization Using Data Envelopment Analysis: Literature Reviews and Usage Strategies)

  • 임지영;고국진;이현희;박연홍;양인자;최윤정
    • 가정∙방문간호학회지
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    • 제22권1호
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    • pp.59-68
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    • 2015
  • Purpose: The purpose of this study was to analyze nursing research using data envelopment analysis and suggest directions for future research. Methods: We established -criteria literature search. e reviewed 45 from RISS, KISS, National assembly library and NDSL DB. Data were collected on December 17, 2013. developed analytic framework of literature reviews using Yun's study. This framework had 8 items related to approach of data envelopment analysis. Results: literature established -criteria. Average numbers of input and output variables were 2.4 and 4.2, respectively. All selected research conducted efficiency analysis, analysis, and inefficiency analysis. However only 3 research. Conclusion: he results of studysuggest that data envelopment are needed to enhance efficiencies of nursing organization as follows individual nurse's profiling to develop customized performance management plans; patient centered nursing interventions; and financial performance financial reports.