• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.468-473
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• 1999

This study was carried out to assess the use of RADARSAT data which is C-band with HH polarization for the rice growth monitoring in Korea. Nine time-series data were taken by shallow incidence angle (standard beam mode 5 or 6) during rice growing season. And then, backscatter coefficient ($\sigma$$^{\circ}$) were extracted by calibration process for comparing with rice growth parameters such as plant height leaf area index(LAI), and fresh and dry biomass. Field experimental data concerned with rice growth were collected 8 times for the ground truth at the study area, Tangjin, Chungnam, Korea. At the maximum vegetative stage of rice, backscatter coefficients were the highest at the flooded rice field ranging from -4.4dB~-3.1dB. The temporal variation of backscatter coefficient($\sigma$$^{\circ}$) in rice field was significant in this study Backscatter coefficient ($\sigma$$^{\circ}$) of rice field was a little bit lower again after heading stage. This results show RADARSTA data is promising for rice monitoring.

• 산업경영시스템학회지
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• 제32권3호
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• pp.127-134
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• 2009

RAM(Reliability, Availability, Maintainability) is important performance factor to keep combat readiness and optimize operational and maintenance cost of weapon systems. This paper discusses the method to establish RAM for combat readiness by using field failure data from similarity equipments. Operational availability is estimated from a binomial distribution function of user's operational conditions such as combat readiness preservation probability, operational rate, operational availability and total number of equipment. Reliability and maintainability is estimated from field failure data from similarity equipment to accomplish operational availability. The effectiveness of established RAM is verified through analysis of combat readiness preservation probability and mission reliability. A case study of weapon system illustrates the process of the proposed method.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2007년 가을학술발표회
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• pp.431-439
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• 2007

Data logger is generally needed for gathering field information automatically(or manually), using various sensors. However it, currently used in the county, is produced and developed by overseas. It is difficult to upgrade related program due to developed system and limited user in terms of environment it is used. On the other hand, several companies developed and sold unique data logger based their technique expertise in the country. But enhancement and practical use of related technology has much difficulties because feasibility, marketability and demand for technique are uncertain. In this study, it is the main purpose to offer basic information to select equipment suitable for field characteristic through analysis and comparison with features about method of information collection, operating program and process technique data logger which is used primarily in geotechnical engineering in both domestic and international.

• 한국신뢰성학회지:신뢰성응용연구
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• 제8권1호
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• pp.1-13
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• 2008

A methodology for collection and analysis of automotive field reliability data is presented. Automotive warranty system usually covers a pre-determined period of time and/or mileage accumulation. Therefore mileage information for the vehicles that have not experienced any failure or problems during the warranty period is not available. In this paper, a reliability analysis method using the estimated mileage distribution from an additional survey for vehicles that have not any record during the warranty period is proposed. Methods of reliability analysis using the warranty information collected under the EU and US warranty policies are also provided.

• 한국군사과학기술학회지
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• 제13권4호
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• pp.594-600
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• 2010

In this paper, we introduced non-parametric statisticals method that could analyse the field data and proposed application ways such as repair-part demand forcasting, MTBF estimation and trend analysis, identity comparison with two populations using the analytical results. In addition, we applied that to real field data which has been collected for about ten years from K series tracked vehicle. After that, we compared the results with those using traditional parametric statistical method, and verified the usability of them.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.176-183
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• 2003

This paper presents a neural network based approach to disseminating information relating to experimental and field observations in engineering. Although the methodology is generic and can be applied to many areas of engineering science, attention is focussed here solely on geotechnical engineering applications. Field data relating to the settlement of foundations presented by Burland and Burbidge (1985) which led to their well known equation for calculation of settlement, now included in most text books, is re-visited. A part of the data, chosen randomly, is used to train an Artificial Neural Network (ANN), which relates foundation settlement to various causes as identified by the authors. Predictions are made for situations for which data were not used in training. These indicate sufficient accuracy when compared to the original field data. Accuracy of predictions is further improved when all the data are included in the training set. The finally trained ANN is shown to represent these data more accurately than the Burland and Burbidge equation. Based on the above heuristic example, an ANN is presented as an alternative to developing equations and design rules in geotechnical engineering practice. Significant advantages are shown to arise by using this methodology. Ease of updating the ANN, as and when additional data becomes available, being the most important one. Loss of transparency, however, seems to be the main disadvantage.

• 대한지구과학교육학회지
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• 제15권2호
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• pp.171-191
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• 2022

이 연구의 목적은 광물과 암석을 주제로 초등학생들이 가상 야외지질답사 모듈 개발에 직접 참여함으로써 관찰되는 학생들의 학습 효과를 귀납적으로 탐색하는 것이다. 수도권 소재 'H' 초등학교에 재학 중인 10명의 학생들이 본 연구에 참여하였다. 학생들은 가상 야외지질답사 모듈 개발을 위해 사전에 실제로 야외지질답사를 실행하고 가상 야외지질답사 모듈을 개발하였다. 이 과정에서 학생들이 작성한 서면 자료와 비디오 녹화 영상, 음성 자료, 그리고 모든 연구가 종료된 이후 진행된 면담 자료를 수집하였다. 가상 야외지질학습의 구성 요소 중 네 가지 영역(인지, 심리, 지리, 기술)을 중심으로 연구 참여자들의 학습 효과를 분석하였다. 그 결과 가상 야외지질학습의 네 가지 요소, 인지, 지리, 심리, 기술 영역에서 긍정적인 학습 효과를 확인하였다. 이 연구는 연구 참여자들이 가상 야외지질학습에 단순 참여자가 아니라 가상 야외지질답사 모듈 수업 개발자로서 참탐구의 측면에서 지질학 학습에 유의미한 결과가 있음을 밝혔다.

• Wind and Structures
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• 제4권2호
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• pp.101-118
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• 2001

This paper reports the field measurements concerning pressure equalization of rainscreen facades carried out at the Technical University of Eindhoven (TUE) in the Netherlands. The field facility including the details of test panel, meteorological tower, instrumentation, data collection and analysis is presented. Results of investigations into cavity response for various leakage and venting configurations are discussed. Frequency domain techniques have been utilized to show the influence of wind as well as facade characteristics on the pressure equalization performance. Further, this paper presents an early attempt to synthesize the experimental results into existing building codes.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.698-701
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• 2004

In many literatures, data mining has been used as a utilization of data warehouse and data collection. The biggest utilizations of data mining are for marketing and researches. This is solely because of the data available for this field is usually in large amount. The usability of the data mining is expandable also to the production process. While the object of research of the data mining in marketing is the customers and products, data mining in the production field is object to the so called 4MlE, man, machine, materials, method (recipe) and environment. All of the elements are important to the production process which determines the quality of the product. Because the final aim of the data mining in production field is the quality of the production, this data mining is commonly recognized as quality data mining. As the variables researched in quality data mining can be hundreds or more, it could take a long time to reveal the information from the data warehouse. Feature selection methodology is proposed to help the research take the best performance in a relatively short time. The usage of available simple statistical tools in this method can help the speed of the mining.

• 한국문헌정보학회지
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• 제54권4호
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• pp.169-194
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• 2020

최근 많은 학문 분야에서 해당 분야에서 생산되는 데이터를 관리하기 위한 메타데이터를 개발하고 있다. 범용적인 분야를 넘어서 특정 학문 분야를 지원하기 위한 메타데이터는 해당 분야의 연구데이터를 검색, 관리, 공유 및 재사용을 위한 필수한 것으로 여겨지고 있다. 따라서 본 연구에서는 임산공학에서 생산되는 연구데이터를 관리하기 위한 메타데이터 항목을 도출하였다. 메타데이터 항목을 도출하기 위하여 FGDC-CSDGM, ISO 19115, NEFIS, INSPIRE, ANZLIC, DataCite 4.3 그리고 TTA,KO-10.0976 등 7개 메타데이터를 대상으로 매핑작업을 진행하였다. 연구 결과, 필수 6개, 권고 13개 그리고 선택 요소 9개가 도출되었다. 도출된 메타데이터는 임산공학 분야의 연구데이터를 체계적으로 관리하기 위한 항목으로 활용될 수 있을 것이다.