• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.1533-1549
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• 2017

정부 R&D성과의 질적 수준을 제고하고 중장기 국가 재정사업의 효율성을 높이기 위한 각 연구 기관의 시도들이 있어 왔다. 연구사업의 발굴, 기획 및 수행에 있어 효과적인 정부 R&D 예산의 배분, 우선순위를 도출, 기술개발 전략 수립을 하는 것이 매우 중요해지고 있다. 정부 재정사업인 국가 R&D사업은 국가 기간산업을 활성화하고 경제발전을 수반할 수 있는 중요한 모멘텀으로서의 역할을 하고 있다. 또한, 국가 R&D사업의 한 축인 거대과학은 최첨단 기술의 개발과 미래성장동력의 발굴이라는 대명제로 그 중요성이 강조되고 있다. 거대과학 연구는 그 분야의 특수성으로 인해 대학의 과학자, 공공 연구기관의 연구원, 기업의 엔지니어가 함께 참여하여야 하고 대규모 국가 예산을 동원하는 과학 연구 사업이다. 이는 대규모 예산을 기반으로 하고 있기에 집중적 투자가 수반된다면 단기적으로 기초과학의 발전을 이뤄낼 수 있다. 이것은 산업발전에 밑거름이 되어 그 분야 자체로 하나의 산업생태계를 구성하고 요소 기술들의 응용으로 파생기술이 전파된다면 새로운 신산업 창출 등 국가산업에 많은 혜택을 줄 수 있다. 하지만 많은 인력과 대규모 투자 그리고 중장기 프로젝트라는 특성으로 인해 실패 가능성도 높아 전략적 선택 및 추진이 필요하다. 따라서 본 논문에서는 거대과학의 기술개발전략의 수립을 위하여 중이온 입자가속기 핵심부품 국산화 전략수립 사례를 중심으로 효율적인 R&D추진 방안을 도출해보고자 한다. 또한, 논문, 특허를 기반으로 한 3P분석을 통하여 중이온 가속기 핵심부품의 국산화 전략을 제안하고, 추진 우선순위 및 전략을 제시하고자 한다.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.3
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• pp.64-74
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• 2002

A special purposed program for ship hull strength analysis considering whipping phenomena is developed. In this program, the non-linear hydrodynamic impact force is considered using the momentum slamming theory and the hull girder is modeled as elastic body on the base of Timoshenko's beam theory. The numerical verifications are conducted in the view points that the effect of slamming impact force, the effect of hydro-elastic formulation, and the effect of various design parameters such as ship speed, wave amplitude, wave length and others. By the application of a real ship design process, the availability of the program is proved. This program has a GUI function for many I/O data process as well as the function to show the 2-D ship motion in the graphic window, and has other available functions for the whipping analysis.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.1.2-24
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• 2000

The field of neural networks has been a recent surge in activity as a result of progress in developments of efficient training algorithms. For this reason, and coupled with the widespread availability of powerful personal computer hardware for running simulations of networks, there is increasing focus on the potential benefits this field can offer. The neural network may be viewed as an advanced pattern recognition technique and can be applied in many areas such as financial time series forecasting, medical diagnostic expert system and etc.. The intention of this study is to build and implement one simple artificial neural networks hereinafter called ANN. For this purpose, some literature survey was undertaken to understand the structures and algorithms of ANN theoretically. Based on the review of theories about ANN, the system adopted 3-layer back propagation algorithms as its learning algorithm to simulate one case of medical diagnostic model. The adopted ANN algorithm was performed in PC by using turbo PASCAL and many input parameters such as the numbers of layers, the numbers of nodes, the number of cycles for learning, learning rate and momentum term. The system output more or less successful results which nearly agree with goals we assumed. However, the system has some limitations such as the simplicity of the programming structure and the range of parameters it can dealing with. But, this study is useful for understanding general algorithms and applications of ANN system and can be expanded for further refinement for more complex ANN algorithms.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.05a
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• pp.72-75
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• 2003

In this research, we focused on the effects of the orifice internal flow such as cavitation and hydraulic flip. The breakup characteristics such as the breakup length and trajectory were measured by changing the orifice diameter (d), the orifice length/orifice diameter (L/d), the injection pressure and the shapes (sharp and round) of orifice entrance to provide a lot of conditions of the orifice internal flow. It is found that cavitation bubbles that occur inside the sharp-edged orifice make the liquid jet ejecting from the orifice turbulent. In the orifices (L/d = 5), the hydraulic flip phenomenon is shown when the injection pressure is high. In case cavitation occurs it breaks up more earlier than that in case of non-cavitation. In case hydraulic flip occurs, since the area of the liquid jet becomes small, the breakup length is also small as that in case of cavitation. But the liquid column trajectories have a similar tendency irrespective of cavitation.

• Transactions of the KSME C: Technology and Education
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• v.3 no.1
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• pp.1-13
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• 2015

In this study, a new dynamic VRF-type heat pump simulation model is proposed which incorporates frosting and defrosting models. Toward this end, a simple frosting model based on the perfect analogy, and lumped system based defrost model, are proposed. Then, frosting and defrosting models are incorporated into a dynamic heat pump model which adopts segment-by-segment local heat exchanger model and map-based variable speed compressor model. Thus, the model can naturally represent locally uneven frosting and defrosting on the heat exchanger surface. Developed simulation model is validated against available experimental data to show good agreement within 10% error for capacity and COP. Finally, developed dynamic heat pump model is applied to annual heating season simulation to show that seasonal COP of heat pump is degraded by 7% due to frosting and defrosting.

• Journal of the Society of Naval Architects of Korea
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• v.36 no.4
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• pp.21-27
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• 1999

A low order panel method based on the perturbation potential is applied for prediction of performance of blown-flap rudders. In order to improve the solution behavior at the large angle of attacks, the geometry of the trailing wake sheet is computed by aligning freely with the local flow. The effect of the wake sheet roll-up is also included with use of a high order panel method. The flow in the gap between the main component and the flap of the rudder is modeled as Couette flow. The effects of the gap and the flow jet are included in application of a kinematic and a dynamic boundary condition on the inlet and the outlet of the gap as well as on the flap and the wake. The results with the present method are compared with existing experimental data. The method is shown to be capable of determining accurately the flow characteristics even for large flap angles.

• Journal of the Korean Geotechnical Society
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• v.18 no.5
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• pp.123-132
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• 2002

The purpose of this study is to predict the shear behavior of the weathered mudstone soil using dynamic neural network which mimics the biological system of human brain. SNN and RNN, which are kinds of the dynamic neural network realizing continuously a pattern recognition as time goes by, are used to predict a nonlinear behavior of soil. After analysis, parameters which have an effect on learning and predicting of neural network, the teaming rate, momentum constant and the optimum neural network model are decided to be 0.5, 0.7, 8$\times$18$\times$2 in SU model and 0.3, 0.9, 8$\times$24$\times$2 in R model. The results of appling both networks showed that both networks predicted the shear behavior of soil in normally consolidated state well, but RNN model which is effective fir input data of irregular patterns predicted more efficiently than SNN model in case of the prediction in overconsolidated state.

• The KSFM Journal of Fluid Machinery
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• v.18 no.2
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• pp.14-21
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• 2015

Design lifetime of a wind turbine is required to be at least 20 years. The most important step to ensure the deign is to evaluate the loads on the wind turbine as accurately as possible. In this study, extreme design load of a offshore wind turbine using Garrad Hassan (GH) Bladed and National Renewable Energy Laboratory (NREL) FAST codes are calculated considering structural dynamic loads. These wind turbine aeroelastic analysis codes are high efficiency for the rapid numerical analysis scheme. But, these codes are mainly based on the mathematical and semi-empirical theories such as unsteady blade element momentum (UBEM) theory, generalized dynamic wake (GDW), dynamic inflow model, dynamic stall model, and tower influence model. Thus, advanced CFD-dynamic coupling method is also applied to conduct cross verification with FAST and GH Bladed codes. If the unsteady characteristics of wind condition are strong, such as extreme design wind condition, it is possible to occur the error in analysis results. The NREL 5 MW offshore wind turbine model as a benchmark case is practically considered for the comparison of calculated designed loads. Computational analyses for typical design load conditions such as normal turbulence model (NTM), normal wind profile (NWP), extreme operation gust (EOG), and extreme direction change (EDC) have been conducted and those results are quantitatively compared with each other. It is importantly shown that there are somewhat differences as maximum amount of 18% among numerical tools depending on the design load cases.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.819-829
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• 2017

The aim of this study is to analyze intraday price momentum. When price trends are formed, price momentum is the phenomenon that future prices tend to follow the trend. When the market opened and closed, a U-shaped trading volume pattern in which the trading volume was concentrated was observed. In this paper, we defined price momentum as the 10 minute trend after market opening is maintained until the end of market. The strategy is to determine buying and selling in accordance with the price change in the initial 10 minutes and liquidating at closing price. In this study, the strategy was empirically analyzed by using minute data, and it showed effectiveness, indicating the presence of an intraday price momentum. A pattern in which returns are increasing at an early stage is called a J-shaped pattern. If the J-shaped pattern occurs, we have found that the price momentum phenomenon tends to be stronger than otherwise. The DTW algorithm, which is well known in the field of pattern recognition, was used for J-shaped pattern recognition and the algorithm was effective in predicting intraday price movements. This study showed that intraday price momentum exists in the KOSPI200 futures market.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1759-1769
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• 1997

The Error BackPropagation (EBP) algorithm for multi-layered neural networks is widely used in various areas such as associative memory, speech recognition, pattern recognition and robotics, etc. Nevertheless, many researchers have continuously published papers about improvements over the original EBP algorithm. The main reason for this research activity is that EBP is exceeding slow when the number of neurons and the size of training set is large. In this study, we developed new learning speed acceleration methods using variable learning rate, variable momentum rate and variable slope for the sigmoid function. During the learning process, these parameters should be adjusted continuously according to the total error of network, and it has been shown that these methods significantly reduced learning time over the original EBP. In order to show the efficiency of the proposed methods, first we have used binary data which are made by random number generator and showed the vast improvements in terms of epoch. Also, we have applied our methods to the binary-valued Monk's data, 4, 5, 6, 7-bit parity checker and real-valued Iris data which are famous benchmark training sets for machine learning.