• Nuclear Engineering and Technology
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• 제54권7호
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• pp.2418-2426
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• 2022

The grouping analysis is a method guided by the Korea Radioactive Waste Agency for efficient analysis of radioactive waste for disposal. In this study, experiments to verify the adequacy of grouping analysis were conducted with radioactive soil, concrete, and dry active waste in similar environments. First, analysis results of the major radionuclide concentrations in individual waste samples were reviewed to evaluate whether wastes from similar environments correspond to a single waste stream. As a result, the soil and concrete waste were identified as a single waste stream because the distribution range of radionuclide concentrations was "within a factor of 10", the range that meet the criterion of the U.S. Nuclear Regulatory Commission for a single waste stream. On the other hand, the dry active waste was judged to correspond to distinct waste streams. Second, after analyzing the composite samples prepared by grouping the individual samples, the population means of the values of "composite sample analysis results/individual sample analysis results" were estimated at a 95% confidence level. The results showed that all evaluation values for soil and concrete waste were within the set reference values (0.1-10) when five-package and ten-package grouping analyses were conducted, verifying the adequacy of the grouping analysis.

• Nuclear Engineering and Technology
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• 제54권9호
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• pp.3336-3346
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• 2022

In general, a number of severe accident scenarios derived from Level 2 probabilistic safety assessment (PSA) are typically grouped into several categories to efficiently evaluate their potential impacts on the public with the assumption that scenarios within the same group have similar source term characteristics. To date, however, grouping by similar source terms has been completely reliant on qualitative methods such as logical trees or expert judgements. Recently, an exhaustive simulation approach has been developed to provide quantitative information on the source terms of a large number of severe accident scenarios. With this motivation, this paper proposes a machine learning-based categorization method based on exhaustive simulation for grouping scenarios with similar accident consequences. The proposed method employs clustering with an autoencoder for grouping unlabeled scenarios after dimensionality reductions and feature extractions from the source term data. To validate the suggested method, source term data for 658 severe accident scenarios were used. Results confirmed that the proposed method successfully characterized the severe accident scenarios with similar behavior more precisely than the conventional grouping method.

• Agricultural and Biosystems Engineering
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• 제6권1호
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• pp.15-21
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• 2005

This study was conducted to develop a nondestructive grouping system for soil organic matter using visible (VIS) and near infrared (NIR) spectroscopic method. The artificial light was irradiated on the cut soil surface at 15 to 20 cm depths to reduce the errors of light at open field. The reflectance energy from the cut soil surface was measured to group the soil organic matter using VIS/NIR light sensor with narrow band pass filter. From reflectance spectra of soil samples, the sensitive wavelengths for measuring the soil organic matter were selected and compared to previous research results. The grouping system for soil organic matter consisted of light sensor with band pass filter measuring the reflectance energy of the cut soil surface, global positing system (GPS), analog-to-digital (AD) converter, computer and operating software. The regression models to predict the soil organic matter were developed and evaluated. From field test, the accuracies of the developed light sensor system were 81.3% for five-stage grouping of the soil organic matters and 91.0% for three-stages grouping of the soil organic matters, respectively. It could be possible to support the decision making for variable rate applications with the developed grouping system for soil organic matter in precision agriculture.

• International Journal of Contents
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• 제1권1호
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• pp.1-5
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• 2005

This paper presents the development and application of electrical resistance imaging techniques for the visualization of two-phase flow fields. Two algorithms, the so-called the mesh grouping and the boundary estimation, are described for potential applications of electrical resistance tomography (ERT) and results from extensive numerical simulations are also presented. In the electrical resistance imaging for two-phase flows, numerical meshes fairly belonging to each phase can be grouped to improve the reconstruction performance. In many cases, the detection of phase boundary is a key subject and a mathematical model to estimate phase boundary can be formulated in a different manner. Our results indicated that the mesh grouping algorithm is effective to enhance computational performance and image quality, and boundary estimation algorithm to determine the phase boundary directly.

• Agricultural and Biosystems Engineering
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• 제6권1호
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• pp.8-14
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• 2005

This study was carried out to develop a real-time grouping system of chlorophyll contents of rice crop canopy for precision agriculture. The system measured reflected light energy of a rice canopy on a paddy field from visual to near-infrared range and analyzed the collected information of chlorophyll contents of rice crop canopy with given position data. The four filters, 560 nm $({\pm}10nm)$, 650 nm $({\pm}25nm)$, 700 nm $({\pm}12nm)$, and 850 nm $({\pm}40nm)$, were used for a multiple regression to estimate the chlorophyll contents of rice crop canopy. Every $0.2m^2$ area of the open field was inspected at a distance of 1 m above the rice canopy. According to the results of verification test, the chlorophyll content grouping by a commerical chlorophyll meter (SPAD) and by the developed system showed 58.7% match for five-stage chlorophyll contents of rice crop canopy grouping and 93.5% for the $five{\pm}1-stage$ grouping. In addition, the results showed 63.0% match for three-stage grouping and 100.0% for the $three{\pm}1-stage$ grouping.

• 한국통신학회논문지
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• 제31권2B호
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• pp.107-116
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• 2006

본 논문에서는 무선 센서 네트워크에서 센싱 정밀도에 기반 한 그룹화 통신 프로토콜 (SRG)을 제안한다. SRG 는 센서 노드가 밀집해 있는 네트워크에서 응용계층이 요구하는 센싱 정밀도를 만족시키는 방법을 제공하는데, 그룹 헤더 노드를 매 round 마다 라운드-로빈 방식으로 교체하여 전반적인 센싱 정밀도를 높이고 각 노드가 소모하는 에너지를 비슷하게 되도록 만든다. 또한 라우팅 시에 소모되는 에너지를 줄이기 위해 그룹의 크기와 에너지 소모를 고려한 중계 노드를 선택 방법 제안하여 에너지 효율적인 통신이 이뤄지도록 한다. 성능평가를 위한 모의실험 결과 제안한 SRG 프로토콜은 센서노드들의 에너지 소비량을 줄이고 네트워크의 생존시간을 늘리는 것을 알 수 있다.

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2019년도 춘계학술논문요약집
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• pp.239-240
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• 2019

• Nuclear Engineering and Technology
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• 제27권5호
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• pp.743-752
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• 1995

본 논문은 배관파단에 대한 원자로 내부구조물의 해석시 사용되는 원자로 내부구조물과 노심의 커플(couple)된 모델에서 핵연료집합체의 grouping수에 따른 동적 응답의 영향을 조사한 것이다. 177개의 핵연료집합체를 1, 3, 5 그리고 7개의 그룹으로 나누어 모델링 하였고 그 각각에 대한 응답을 구하였다. 해석결과 원자로 내부구조물과 핵연료집합체의 배관파단에 대한 응답은 핵연료집합체의 grouping수에 거의 영향을 받지 않음을 알 수 있었다. 또한 핵연료집합체의 해석시 사용되는 상세모델에서 2개 이상의 이웃하는 핵 연료다발을 하나의 등가모델로 나타내는 방법을 연구한 결과 집합체의 1차모드 주파수와 일치하는 등가스프링을 사용하고 각 핵연료다발사이의 간격을 그대로 유지했을 때의 모델이 원래의 응답과 가장 잘 일치함을 보였다.

• 한국정보통신학회논문지
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• 제14권12호
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• pp.2836-2842
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• 2010

본 논문에서는 다양한 3D 게임 진행에서 NPC들을 속성에 따라 그룹핑하는 방법을 제시한다. 움직임이 없는 NPC는 가버필터링 결과에서 특이한 방향성 특성을 띄는 경향이 있지만 사람이나 동물과 같은 NPC는 그렇지 않다. 그룹핑을 위해 우선 NPC 객체 내부의 방향성과 주파수 영역의 특징을 분석하고 각각을 24개의 가버 필터뱅크로 구성하며 필터의 스케일과 방향에 따른 24차원 특징 벡터를 산출한다. 추출된 벡터는 특정 방향에 따른 에너지를 나타낸다. 이러한 에너지는 NPC 내부에 있는 객체 질감의 특정 방향에 대한 크기를 나타내고 있기 때문에 NPC들을 그룹핑 속성으로 이용하였다. 제안한 방법은 게임진행에서 유사한 속성을 가진 NPC들이 자동으로 그룹핑되어 전략적이고 속도감 있게 플레이 할 수 있는 기능을 제공한다.

• 설비공학논문집
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• 제21권10호
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• pp.553-558
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• 2009

Energy demand characteristics of hotel, hospital, and office building are compared to provide guidelines for combining building in community energy system design. The annual, monthly, and daily energy demand patterns for electricity, heating, hot water and cooling are qualitatively compared and important features are delineated based on the energy demand models. Key statistical values such as the mean, the maximum are also provided. Important features of the hourly demand patterns are summarized for weekdays and weekends. Substantial variations in both magnitudes and patterns are observed among the 3 building types and smart grouping or combination of building type and size is essential for a successive energy supply.