• Title/Summary/Keyword: research data

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Pseudo-standard and Its Implementation for the Maintenance Data of Ship and Offshore Structures (선박 및 해양 구조물에 있어서 유지보수용 데이터 교환을 위한 준표준 분석과 사례 구현)

  • Son, Gum-Jun;Lee, Jang-Hyun;Lee, Jeongyoul;Han, Eun-Jung
    • Korean Journal of Computational Design and Engineering
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    • v.18 no.4
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    • pp.267-274
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    • 2013
  • This study focuses on the data schema and data content, which includes maintenance data, data structures and illustration data relevant with the maintenance process of ship and offshore structures. Product lifecycle management (PLM) is expected to encompass all the product data generated for the operation and maintenance information as well as the design and production. This paper introduces a data exchange schema in PLM of ship and offshore, serving as the basis for the role of standards required by the middle-of-life PLM. Also this paper identifies a typology of standards relevant to PLM that addresses the schema of evolving standards and identifies a XML schema supporting the exchange of data related with maintenance operations. Technical document based on standards in accordance with S1000D and Shipdex is explained. A case study illustrating the use of standard data exchange and technical document is presented.

A Comparison of Data Extraction Techniques and an Implementation of Data Extraction Technique using Index DB -S Bank Case- (원천 시스템 환경을 고려한 데이터 추출 방식의 비교 및 Index DB를 이용한 추출 방식의 구현 -ㅅ 은행 사례를 중심으로-)

  • 김기운
    • Korean Management Science Review
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    • v.20 no.2
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    • pp.1-16
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    • 2003
  • Previous research on data extraction and integration for data warehousing has concentrated mainly on the relational DBMS or partly on the object-oriented DBMS. Mostly, it describes issues related with the change data (deltas) capture and the incremental update by using the triggering technique of active database systems. But, little attention has been paid to data extraction approaches from other types of source systems like hierarchical DBMS, etc. and from source systems without triggering capability. This paper argues, from the practical point of view, that we need to consider not only the types of information sources and capabilities of ETT tools but also other factors of source systems such as operational characteristics (i.e., whether they support DBMS log, user log or no log, timestamp), and DBMS characteristics (i.e., whether they have the triggering capability or not, etc), in order to find out appropriate data extraction techniques that could be applied to different source systems. Having applied several different data extraction techniques (e.g., DBMS log, user log, triggering, timestamp-based extraction, file comparison) to S bank's source systems (e.g., IMS, DB2, ORACLE, and SAM file), we discovered that data extraction techniques available in a commercial ETT tool do not completely support data extraction from the DBMS log of IMS system. For such IMS systems, a new date extraction technique is proposed which first creates Index database and then updates the data warehouse using the Index database. We illustrates this technique using an example application.

Development of Data Acquisition System to Obtain Vessel and Weather Information in Around Mokpo Harbor Bridge (목포대교 주변의 선박 항행 정보 및 기상 정보 획득 시스템 개발)

  • Yim, Jeong-Bin
    • Journal of Navigation and Port Research
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    • v.35 no.1
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    • pp.1-7
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    • 2011
  • This paper describes the development of Data Acquisition System (DAS) to obtain the vessel and weather information needing to evaluate collision risks levels between Mokpo harbor bridge and passing vessels. DAS consists of Signal Receiving and Processing Unit to obtain the data sets of passing vessels and weather status, Networking Unit to transmit and distribute the acquisition data sets and Data Management Unit. Through the field tests on the deck of shuttle car ferry between Mokpo Port Passenger Terminal and An-Jua island, Sinan-Gun, we found that the DAS can provide useful data sets for adequate the collision risk evaluation. In addition, the noise-like data sets appeared in the weather data can be suppressed fully using 5-th order Butterworth digital filter.

A Study on Data Classification of Raman OIM Hyperspectral Bone Data

  • Jung, Sung-Hwan
    • Journal of Korea Multimedia Society
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    • v.14 no.8
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    • pp.1010-1019
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    • 2011
  • This was a preliminary research for the goal of understanding between internal structure of Osteogenesis Imperfecta Murine (OIM) bone and its fragility. 54 hyperspectral bone data sets were captured by using JASCO 2000 Raman spectrometer at UMKC-CRISP (University of Missouri-Kansas City Center for Research on Interfacial Structure and Properties). Each data set consists of 1,091 data points from 9 OIM bones. The original captured hyperspectral data sets were noisy and base-lined ones. We removed the noise and corrected the base-lined data for the final efficient classification. High dimensional Raman hyperspectral data on OIM bones was reduced by Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA) and efficiently classified for the first time. We confirmed OIM bones could be classified such as strong, middle and weak one by using the coefficients of their PCA or LDA. Through experiment, we investigated the efficiency of classification on the reduced OIM bone data by the Bayesian classifier and K -Nearest Neighbor (K-NN) classifier. As the experimental result, the case of LDA reduction showed higher classification performance than that of PCA reduction in the two classifiers. K-NN classifier represented better classification rate, compared with Bayesian classifier. The classification performance of K-NN was about 92.6% in case of LDA.

Estimation of Material Requirement of Piping Materials in an Offshore Structure using Big Data Analysis (빅데이터 분석을 이용한 해양 구조물 배관 자재의 소요량 예측)

  • Oh, Min-Jae;Roh, Myung-Il;Park, Sung-Woo;Kim, Seong-Hoon
    • Journal of the Society of Naval Architects of Korea
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    • v.55 no.3
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    • pp.243-251
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    • 2018
  • In the shipyard, a lot of data is generated, stored, and managed during design, construction, and operation phases to build ships and offshore structures. However, it is difficult to handle such big data efficiently using existing data-handling technologies. As the big data technology is developed, the ship and offshore industries start to focus on the existing big data to find valuable information from it. In this paper, the material requirement estimation method of offshore structure piping materials using big data analysis is proposed. A big data platform for the data analysis in the shipyard is introduced and it is applied to the analysis of material requirement estimation to solve the problems in piping design by a designer. The regression model is developed from the big data of piping materials and verified using the existing data. This analysis can help a piping designer to estimate the exact amount of material requirement and schedule the purchase time.

Construction of Street Trees Information Management Program Using GIS and Database (GIS와 데이터베이스를 이용한 가로수정보 관리프로그램 구축)

  • Kim, Hee-Nyeon;Jung, Sung-Gwan;Park, Kyung-Hun;You, Ju-Han
    • Current Research on Agriculture and Life Sciences
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    • v.26
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    • pp.45-54
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    • 2008
  • The purpose of this research is to develope street trees management program for more an effective street trees management. The principal point of this program is to relate spatial data and attribute data that is the main concept in GIS(Geographic Information System). To do this function, MapObjects which is ESRI's mapping and GIS components was used to process spatial data and Access which had been developed by MS was used to manipulate attribute data in this program. Visual Basic also was used to design and develop user interfaces and procedures, relate two sort of data, and lastly complete Application. Relational data model was adopted to design tables and their relation, Antenucci's GIS development model was selected to design and complete this program. The configuration of this application is composed of management data and reference data. The management data includes the location of street tree, a growth condition, a surrounding environment, the characters of tree, an equipments, a management records and etc. The reference data include general information about tree, blight and insects.

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Classification of Domestic Freight Data and Application for Network Models in the Era of 'Government 3.0' ('정부 3.0' 시대를 맞이한 국내 화물 자료의 집계 수준에 따른 분류체계 구축 및 네트워크 모형 적용방안)

  • YOO, Han Sol;KIM, Nam Seok
    • Journal of Korean Society of Transportation
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    • v.33 no.4
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    • pp.379-392
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    • 2015
  • Freight flow data in Korea has been collected for a variety of purposes by various organizations. However, since the representation and format of the data varies, it has not been substantially used for freight analyses and furthermore for freight policies. In order to increase the applicability of those data sets, it is required to bring them in a table and compare for finding the differences. Then, it is shown that the raw data can be aggregated by a particular criterion such as mode, origin and destination, and type commodity. This study aims to examine the freight data issue in terms of three different points of view. First, we investigated various freight volume data sets which are released by several organizations. Second, we tried to develop formulations for freight volume data. Third, we discussed how to apply the formulations to network models in which particular OR (Operations Research) techniques are used. The results emphasized that some data might be useless for modeling once they are aggregated. As a result of examining the freight volume data, this study found that 14 organizations share their data sets at various aggregation levels. This study is not an ordinary research article, which normally includes data analysis, because it seems to be impossible to conduct extensive case studies. The reason is that the data dealt in this study are diverse. Nevertheless, this study might guide the research direction in the freight transport research society in terms of data issue. Especially, it can be concluded that this study is a timely research because the governmemt has emphasized the importance of sharing data to public throughout 'government 3.0' for research purpose.

Obtaining bootstrap data for the joint distribution of bivariate survival times

  • Kwon, Se-Hyug
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.5
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    • pp.933-939
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    • 2009
  • The bivariate data in clinical research fields often has two types of failure times, which are mark variable for the first failure time and the final failure time. This paper showed how to generate bootstrap data to get Bayesian estimation for the joint distribution of bivariate survival times. The observed data was generated by Frank's family and the fake date is simulated with the Gamma prior of survival time. The bootstrap data was obtained by combining the mimic data with the observed data and the simulated fake data from the observed data.

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Air Pollutant Emission Factors from Composite Wood Products Manufacturing in Korea

  • Lee, Eun-Jung;Jung, Dong-Il;Kim, Dai-Gon;Lee, Sue-Been;Kang, Kyoung-Hee;Hong, Ji-Hyung
    • Journal of Korean Society for Atmospheric Environment
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    • v.23 no.E2
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    • pp.57-65
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    • 2007
  • In Korea, there is a general lack of information available on air emissions from industry. The reasons for this include the lack of regulatory requirements for emission monitoring, limited information on specific industries, and difficulties in monitoring certain sources. This paper presents the first detailed air pollutant emission factors from composite wood product manufacturing in Korea. This study introduced emission factors for wood-based panels such as plywood, particle board (PB), and medium density fiberboard (MDF). The emission factors of particulate matters (PM) and hazardous air pollutants (HAPs) from MDF were higher than that from other wood products. The concentration of total volatile organic compounds (TVOCs) for hot press from wood-based panels was higher than drying or gluing processes. Emissions data from NPIP were compared to the data from the suggested emission factors in this study and the US EPA's. The data from our emission factors were closer to the observed results than the data using the US EPA's emission factor.

A study on building the platform and development of algorithm for collecting real-time traffic data (실시간 교통정보 수집을 위한 알고리즘 개발 및 플랫폼 구축에 관한 연구)

  • Kim, Dong-Min;Jeong, Young-Mu;Min, Soo-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.535-538
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    • 2012
  • Recently active research for ITS(Intelligent Transportation System) helps to build for next generation traffic information system at information society. Build the system for sensing a vehicle speed and traffic information on the road. Provide collected data to driver, flow of overall traffic impacts have a good influence. In this study, research for building the platform and development algorithm that provided from other source processing real-time traffic data provides a more reliable real-time traffic data.

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