• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.131-136
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• 2003

CF8M cast austenitic stainless steel is used for several components such as primary coolant piping, elbow, pump casing, and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. In this study, three kinds of the aged CF8M specimen were prepared using an artificially simulated aging method. The objective of this study is to summarize the method of estimating ferrite contents, Charpy impact energy and J-R curve, and to evaluate the thermal embrittlement of the CF8M cast austenitic stainless steel piping used in the domestic nuclear power plants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2350-2364
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• 2014

This paper addresses the problem of resource allocation in amplify-and-forward (AF) relayed OFDM based cognitive radio networks (CRNs). The purpose of resource allocation is to maximize the overall throughput, while satisfying the constraints on the individual power and the interference induced to the primary users (PUs). Additionally, different from the conventional resource allocation problem, the rate-guarantee constraints of the subcarriers are considered. We formulate the problem as a mixed integer programming task and adopt the dual decomposition technique to obtain an asymptotically optimal power allocation, subcarrier pairing and relay selection. Moreover, we further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Numerical simulation results confirm the optimality of the proposed algorithms and demonstrate the impact of the different constraints.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1174-1179
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• 2003

Cast austenitic stainless steel is used for several components, such as primary coolant piping, elbow, pump casing and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. This study shows that ferrite content can be predicted by use of the artificial neural network. The neural network has trained learning data of chemical components and ferrite contents using backpropagation learning process. The predicted results of the ferrite content using trained neural network are in good agreement with experimental ones.

• Journal of Microbiology
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• 제44권4호
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• pp.466-471
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• 2006

In this study, we attempted to characterize the biomolecular effects of an atmospheric-pressure cold plasma (APCP) system which utilizes helium/oxygen $(He/O_2)$. APCP using $He/O_2$ generates a low level of UV while generating reactive oxygen radicals which probably serve as the primary factor in sterilization; these reactive oxygen radicals have the advantage of being capable to access the interiors of the structures of microbial cells. The damaging effects of plasma exposure on polypeptides, DNA, and enzyme proteins in the cell were assessed using biochemical methods.

• 농촌계획
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• 제22권2호
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• pp.109-119
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• 2016

Most of countries are trying to increase the supply of renewable energy as the substitute of the fossil energy for reducing greenhouse gas emissions. However, renewable energy sources account for only about 3.86% of the total Korea primary energy supply. To increase the rate of renewable energy in Korea's energy consumption, various policies for expanding the use of renewable energy should be applied. Also these policies should be consider renewable energy resources distribution and regional inequality. In this study, the potentials of photovoltaic, wind power and bioenergy from rice straw, livestock waste and food waste are calculated and the distribution characteristic and regional inequalities are analyzed using Gini's coefficient and Gini decomposition method. As the results, technical potentials of photovoltaic and wind power of city region(Gu) has more potential rate than theoretical potentials. Livestock waste has the most unequal distribution (Gini's coefficient: 0.617) among renewable resources.

• 대한기계학회논문집A
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• 제28권4호
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• pp.460-466
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• 2004

Cast austenitic stainless steel is used for several components, such as primary coolant piping, elbow, pump casing and valve bodies in light water reactors. These components are subject to thermal aging at the reactor operating temperature. Thermal aging results in spinodal decomposition of the delta-ferrite leading to increased strength and decreased toughness. This study shows that ferrite content can be predicted by use of the artificial neural network. The neural network has trained teaming data of chemical components and ferrite contents using backpropagation learning process. The predicted results of the ferrite content using trained neural network are in good agreement with experimental ones.

• 대한원격탐사학회지
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• 제39권1호
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• pp.111-127
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• 2023

In visual slam and 3D data modeling, the Iterative Closest Point method is a primary fundamental algorithm, and many technical fields have used this method. However, it relies on search methods that take a high search time. This paper solves this problem by applying an effective point cloud refinement method. And this paper also accelerates the point cloud registration process with an indexing scheme using the spatial decomposition method. Through some experiments, the results of this paper show that the proposed point cloud refinement method helped to produce better performance.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.203-211
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• 2022

Multi-objective optimization problems (MOPs) arise in many real-world applications. MOPs involve two or more objectives with the aim to be optimized. With these problems improvement of one objective may led to deterioration of another. The primary goal of most multi-objective evolutionary algorithms (MOEA) is to generate a set of solutions for approximating the whole or part of the Pareto optimal front, which could provide decision makers a good insight to the problem. Over the last decades or so, several different and remarkable multi-objective evolutionary algorithms, have been developed with successful applications. However, MOEAs are still in their infancy. The objective of this research is to study how to use and apply machine learning (ML) to improve evolutionary multi-objective optimization (EMO). The EMO method is the multi-objective evolutionary algorithm based on decomposition (MOEA/D). The MOEA/D has become one of the most widely used algorithmic frameworks in the area of multi-objective evolutionary computation and won has won an international algorithm contest.

• 한국해양학회지:바다
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• 제2권2호
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• pp.78-86
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• 1997

시화 방조제 건설 후 급속도로 오염되고 있는 시화호 내의 식물플랑크톤 대증식 현상을 파악하기 위하여 1995년 10월부터 1996년 8월까지 시화호 내외에서 환경요인들과 식물플랑크톤 chlorophyll-a, 현존량, 우점종, 일차생산력 등을 4계절 조사하였다. 시화호는 부영양화된 기수호의 성격을 띄고 있으며 저층에는 밀도가 높은 잔류해수가 남아있다. 시화호의 표층에서 육상으로부터 유입된 오염된 하천수의 영향으로 chlorophyll-a 농도가 평균 168.0 ${\mu}g\;l^{-1}$에 이르는 식물플랑크톤 대증식 현상이 연중 지속적으로 일어났다. 식물플랑크톤의 대증식은 추계와 동계에는 돌말류 Cyclotella atomus 에 의해 주로 일어났고, 춘계와 하계에는 와편모류 Prorocentrum minimum 등과 황갈조류 등에 의해 일어났다. 시화호 바깥해역에서도 시화호수의 방류로 통계에서 하계에 걸쳐 돌말류 Thalassiosira nordenskioeldii, Skeletonema costatum, Chaetoceros sp. 등에 의해 대증식이 계속 일어났다. 시화호의 식물플랑크톤에 의한 일차생산력은 연평균 3,972 mgC $m^{-2}\;day^{-1}$로 높게 일어났다. 그러나 일차생산력의 대부분은 표층에서의 높은 광흡수로 수심 3 m 내로 국한되고, 추계와 동계에는 규산염이 제한요인으로 작용하여 더 이상 높게 나타나지 못하였다. 저층에서는 광제한 등으로 광합성 작용이 거의 없었고, 표층에서 떨어진 유기물이 분해되어 산소가 고갈되는 양상을 보였다.

• 한국물환경학회지
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• 제25권2호
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• pp.295-305
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• 2009

The purpose of this study was to understand of water quality characteristics of lake Paldang, especially at a certain representative site, right in front of Paldang dam ($P_2$ site) and to propose the directions of water quality management of lake Paldang. Water characteristics at $P_2$ site was investigated by principle components analysis and the Pearson correlation coefficient analysis. Also, seasonality was identified by the Kruskal-Wallis test and long term trend of nutrients and chlorophyll-a was analyzed by seasonal decomposition method at lake Paldang statistically. The primary factor affecting on water quality at $P_2$ site was identified as nutrients, while physical parameters, such as rainfall and inflow rate were also important factors. At the result of linear regression analysis particulate organic phosphorus (POP) vs total phosphorus (TP) showed very high correlation of 0.78. TP loading was increased annually from 1995 to 2006. Chlorophyll-a and nutrients show seasonality at $P_2$ site. Long term trend of Chlorophyll-a was increased by increase of TP at lake Paldang.