• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.202-209
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• 2023

In the 21st century, the dualistic worldview of the Cold War era collapsed and we entered an era of new creation and fusion. The fusion of different designs between East and West, the design activities of traditional clothing from the past, the use of new materials that are continuously being developed, and the mixing of unique items are being conducted in various fields. However, research is being conducted by combining fusion characteristics with hair. In addition, the period is short and the amount of research is small. Therefore, this study analyzed hairstyles of fusion images shown in hair collection using data of Juno Hair collection from 2013 to 2022 as analysis data and examined types of fusion images shown in the work of folk images, mixed images, and future images. Oriented images were divided into three categories and analyzed. In this study, we added Results of such research can be used not only as data for predicting future fashion trends, but also as basic data for exploring new design developments. In future research, it is expected that convergent research will be conducted, such as analyzing fusion images from an integrated perspective.

• 한국입자에어로졸학회지
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• 제16권1호
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• pp.19-30
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• 2020

The organic carbon in the ambient particulate matter (PM) is divided into primary organic carbon (POC) and secondary organic carbon (SOC) by their formation way. To regulate PM effectively, the estimation of the amount of POC and SOC separately is one of important consideration. Since SOC cannot be measured directly, previous studies have evaluated determination of SOC by the EC tracer method. The EC tracer method is a method of estimating the SOC value from calculating the POC by determining (OC/EC)pri which is the ratio of the measured values of OC and EC from the primary combustion source. In this study, three different ways were applied to OC and EC concentrations in PM_2.5 measured at Seoul for determining (OC/EC)pri: 1) the minimum value of OC/EC ratio during the measurement period; 2) regression analysis of OC vs. EC to select the lower 5-20% OC/EC ratio; 3) determining the OC/EC ratio which has lowest correlation coefficient value (R²) between EC and SOC which is reported as minimum R squared method (MRS). Each (OC/EC)pri ratio of three ways are 0.35, 1.22, and 1.77, respectively from the 1 hourly data. We compared the (OC/EC)pri ratio from 1hourly data with 24 hourly data and revealed that (OC/EC)pri estimated from 24 hourly data had twice larger than 1hourly data due to the low time resolution of sampling. We finally confirmed that the most appropriate value of (OC/EC)pri is that calculated by a regression analysis of 1 hourly data and estimated SOC amounts at PM_2.5 of the Seoul atmosphere.

• 경영과학
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• 제11권2호
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• pp.1-27
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• 1994

A reliability data processing MPRDP (Multi-Purpose Reliability Data Processor) has been developed in FORTRAN language since Jan. 1992 at KAERI (Korean Atomic Energy Research Institute). The purpose of the research is to construct a reliability database(plant-specific as well as generic) by processing various kinds of reliability data in most objective and systematic fashion. To account for generic estimates in various compendia as well as generic plants' operating experience, we developed a 'three-stage' Bayesian procedure[1] by logically combining the 'two-stage' procedure[2] and the idea for processing generic estimates[3]. The first stage manipulates generic plant data to determine a set of estimates for generic parameters,e.g. the mean and the error factor, which accordingly defines a generic failure rate distribution. Then the second stage combines these estimates with the other ones proposed by various generic compendia (we call these generic book type data). This stage adopts another Bayesian procedure to determine the final generic failure rate distribution which is to be used as a priori distribution in the third stage. Then the third stage updates the generic distribution by plant-specific data resulting in a posterior failure rate distribution. Both running failure and demand failure data can be handled in this code. In accordance with the growing needs for a consistent and well-structured reliability database, we constructed a generic reliability database by the MPRDP code[4]. About 30 generic data sources were reviewed and available data were collected and screened from them. We processed reliability data for about 100 safety related components frequently modeled in PSA. The underlying distribution for the failure rate was assumed to be lognormal or gamma, according to the PSA convention. The dependencies among the generic sources were not considered at this time. This problem will be approached in further study.

• 한국도서관정보학회지
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• 제47권3호
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• pp.213-239
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• 2016

전 세계적으로 오픈 데이터가 강조되는 환경에서 데이터의 공유 및 재이용으로 인해 발생하는 문제점을 최소화하기 위한 정책적 논의도 함께 진행되고 있다. 본 연구에서는 연구데이터 레포지터리에서 데이터의 접근 및 이용을 통제하는 정책요소들을 조사하고 학문 분야별로 그러한 정책 요소들의 공통점과 차이점을 살펴보는 것을 목적으로 하였다. 이를 위해 해외 연구데이터 레포지터리 37곳을 대상으로 데이터 접근 및 이용 통제를 규정하고 있는 정책 요소를 분석하였다. 생명과학 및 보건과학분야 20개 레포지터리, 화학 지구환경과학 물리학 분야 10개 레포지터리, 사회과학 및 일반과학 분야 7개 레포지터리로 구분하여 분석을 실시한 결과 저작권 및 라이선스 규정, 데이터 인용, 면책조항 및 엠바고 적용 관련 규정이 공통적으로 제시되는 정책 요소인 것으로 나타났다. 그러나 분야별로 규정되고 있는 정책 요소의 다양성에는 차이가 있는 것으로 나타났으며 이는 분야별로 강조되는 데이터 접근 및 이용 통제 근거의 차이를 반영하는 것으로 볼 수 있다.

• 농촌계획
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• 제19권4호
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• pp.319-327
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• 2013

The objective of this research was to develop a relational database management system(RDBMS) to collect, manage and analyze data on agricultural non-point source(NPS) pollution. The system consists of the relational database for agricultural NPS data and data process modules. The data process modules were composed of four sub-modules for data input, management, analysis, and output. The data collected from the watershed of the upper Cheongmi stream and Geunsam-Ri were used in this study. The database was constructed using Apache Derby with meteorological, hydrological, water quality, and soil characteristics. Agricultural NPS-Data Management System(ANPS-DMS) was developed using Oracle Java. The system developed in this study can deal with a variety of agricultural NPS data and is expected to provide an appropriate data management tool for agricultural NPS studies.

• 서비스연구
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• 제5권2호
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• pp.119-132
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• 2015

낮은 품질의 데이터가 기업의 효율적인 운영과 신속한 의사결정을 저해한다는 이슈가 제기되고 있다. 이에, 본 연구는 경영층의 지원과 경쟁력이 심화되고 있는 경영환경이 데이터 활용 품질관리 활동의 영향요인이 될 수 있는지, 해당 활동이 업무처리 또는 의사결정을 위한 데이터 활용을 촉진시킴으로써 고객 지향성에 긍정적인 영향을 미치는지 살펴보았다. 연구결과 데이터 활용 품질관리는 데이터를 업무처리에 직접적 또는 의사결정에 활용하는데 긍정적인 영향요인이 될 수 있으며, 데이터 활용이 고객지향성에 간접적인 효과를 줄 수 있음을 확인하였다. 본 연구는 직접적인 매출 향상의 성과를 기대할 수 있을 것 같지 않다는 인식으로 데이터 품질관리의 중요성을 간과하는 기업의 경영자들에게 데이터 품질관리활동의 가치 및 경영층의 지원에 대한 실무적 함의를 제시하였다.

• 수산경영론집
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• 제36권3호
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• pp.89-117
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• 2005

Currently, the tax - exempted vessel fuel is provided for commercial fishing in order to increase the competitive power of fishery production thorough the National Federation of Fisheries Cooperatives. The National Federation of Fisheries Cooperatives should predict the exact amount of fuel consumption for fishing every year to request the fuel from the government. Unfortunately, there is no sophisticated model to predict the tax - exempted vessel fuel consumption. In 2003, the consumption of the tax- exempted vessel fuel was only $25.1\%$ of the estimation amount by the National Federation of Fisheries Cooperatives. This causes an inefficiency in the petroleum management. Moreover, we need some data such as the annual average fishing hours, fishing days and fishing behavior to adopt a new policy regarding fishing. Up to now, the data have been obtained by survey with response in the fishery field. In the most case, we have a small number of data because we spend so much time and money consuming for collecting fishing data. As a result, the level of confidence of the data is associated with the sample size and normally low. In order to achieve more accurate data, we need to develope an efficient method for collecting fishing data. In this research, we proposed a new method to predict the tax- exempted vessel fuel consumption more exactly. The prediction results from the proposed method has been compared with the results from the current method. According to the results in this research, the method proposed here produced much better accuracy than the current method. In addition, we also proposed in the paper for collecting fishing data of the annual average fishing hours using the tax - exempted vessel fuel consumption and the gasoline consumption of vessel engine. The fishing data obtained by using the method proposed in this research could be much more efficient and accurate because it doesn't need to estimate from survey sample data.

• 한국농림기상학회지
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• 제25권2호
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• pp.99-107
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• 2023

농업은 기상에 매우 민감한 산업으로, 따라서 농업분야의 기상을 이용한 연구는 더욱 중요해지고 있다. 연구자들은 기상청과 농촌진흥청에서 제공하는 기상정보서비스 웹사이트에 접속해 기상관측자료를 다운로드할 수 있다. 그러나 대량의 기상자료를 받아야 할 때는 여러 번의 조회작업이 필요한 단점이 있다. 본 데이터 논문은 기상청과 농촌진흥청에서 수집한 자료를 원격 저장소 서비스인 깃허브에 업로드하고 소프트웨어 프로그램인 파이썬을 이용해 기상자료에 쉽게 접근할 수 있는 패키지를 제작했다. 이를 통해 추가적인 인증 절차 없이 누구나 자료를 가져갈 수 있는 방식을 채택하여 농업 관계자들의 기상자료에 대한 접근성 및 활용성을 높이는 방법을 제안한다. 자료와 패키지는 분산 버전 관리 시스템인 깃에 업로드하여 수정 및 관리가 용이하게 하였다.

• International Journal of Air-Conditioning and Refrigeration
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• 제15권3호
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• pp.85-100
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• 2007

This study presents a short overview of the researches in connection to the fin-and-tube heat exchangers with and without the influence of dehumidification. Contents of this review article include the data reduction method, performance data, updated correlations, and the influence of hydrophilic coating for various enhanced fin patterns. This study emphasizes on the experimental researches. Performance of both sensible cooling and dehumidifying conditions are reported in this review article.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제18권1호
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• pp.75-87
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• 2014

It is central to use a scale to measure a person's level of a construct in mathematics education research. This article explains a practical process through which a researcher rapidly can develop an instrument to measure the construct. The process includes research questioning, reviewing the literature, framing a background theory, treating the data, and reviewing the instrument. The statistical treatment of data includes normality analysis, item-total correlation analysis, reliability analysis, and factor analysis. A virtual example is given for better understanding of the process.