• International Journal of Aeronautical and Space Sciences
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• 제17권3호
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• pp.391-400
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• 2016

In satellite operations, stable maneuvering of a satellite's onboard antenna to prevent undesirable vibrations to the satellite body is required for high-quality high-resolution images. For this reason, the onboard antenna's angular rate is typically minimized while still satisfying the system requirement that limits the speed of the onboard antenna. In this study, a simple yet effective method, called the ground station searching method, is proposed to reduce the angular rate of a satellite's onboard antenna. The performance of the proposed method is tested using real flight data from the KOMPSAT-3 satellite. Approximately 83% of arbitrarily selected real flight scenarios from 66 test cases show reductions in the onboard antenna's azimuth angular rates. Additionally, reliable solutions were consistently obtained within a reasonably acceptable computation time while generating an onboard antenna tracking profile. The obtained results indicate that the proposed method can be used in real satellite operations and can reduce the operational loads on a ground operator. Although the current work only considers the KOMPSAT-3 satellite as a test case, the proposed method can be easily modified and applied to other satellites that have similar operational characteristics.

• 한국습지학회지
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• 제10권2호
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• pp.39-51
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• 2008

최근 하수처리, 홍수조절, 광산침출수, 농업유출수 등의 처리에 습지를 이용하려는 시도가 증가하고 있다. 하지만 장기모니터링의 어려움으로 인해 습지에 대한 장기간의 자료들이 부족하여 습지의 올바른 이용이 어려운 실정이다. 이에 본 연구에서는 장기간의 자료 생성을 목적으로 한 수문분석의 일환으로 장기유출 수문모형인 SWAT(Soil and Water Assessment Tool)모형을 이용하여 토평천 유역의 우포, 목포, 사지포, 쪽지벌에 대한 저류량을 모의하였다. 이를 바탕으로 토평천 유역에 천변저류지를 조성하는 가상 시나리오를 작성하여 조성된 천변저류지의 저류량 거동을 분석하였다. 천변저류지의 조성에 따른 우포늪의 저류량 변화를 분석한 결과 천변저류지 조성에 따라 우포늪도 일정 정도의 영향을 받을 수 있음이 파악되었다.

• 한국멀티미디어학회논문지
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• 제22권12호
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• pp.1447-1456
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• 2019

As artificial intelligence technology is actively used in image processing, it is possible to generate high-quality fake images based on deep learning. Fake images generated using GAN(Generative Adversarial Network), one of unsupervised learning algorithms, have reached levels that are hard to discriminate from the naked eye. Detecting these fake images is required as they can be abused for crimes such as illegal content production, identity fraud and defamation. In this paper, we develop a deep-learning model based on CNN(Convolutional Neural Network) for the detection of StyleGAN fake images. StyleGAN is one of GAN algorithms and has an excellent performance in generating face images. We experiment with 48 number of experimental scenarios developed by combining parameters of the proposed model. We train and test each scenario with 300,000 number of real and fake face images in order to present a model parameter that improves performance in the detection of fake faces.

• International Journal of Aeronautical and Space Sciences
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• 제18권4호
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• pp.709-718
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• 2017

This paper proposes the guidance laws for an agile turn of air-to-air missiles during the initial boost phase. Optimal solution for the agile turn is obtained based on the optimal control theory with a simplified missile dynamic model. Angle-of-attack command generating methods for completion of agile turn are then proposed from the optimal solution. Collision triangle condition for non-maneuvering target is reviewed and implemented for update of terminal condition for the agile turn. The performance of the proposed method is compared with an existing homing guidance law and the minimum-time optimal solution through simulations under various initial engagement scenarios. Simulation results verify that transition to homing phase after boost phase with the proposed method is more effective than direct usage of the homing guidance law.

• 자원ㆍ환경경제연구
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• 제9권5호
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• pp.853-876
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• 2000

The purpose of this paper is to come up with the measures for sustainable development of the agricultural sector in store for the strengthened U.N. Framework Convention on Climate Change. We analyze the spillover effects of Methane and Nitrous Oxides taxes (carbon tax) on the Korean agricultural sector. Unlike the other sectors, the agricultural sector has a unique characteristic generating greenhouse gas in the process of production itself even without consuming much fossil fuel. In order to estimate the impacts of those taxes, non-linear optimization method has been used with various assumed scenarios. The production effect, income and' price effect, and greenhouse gas emission reduction effect in the agricultural sector have been estimated through this method. The empirical results show that the paddy sector has a bigger tax effect than the livestock sector. In the paddy sector, the carbon tax has more impacts in the suburban areas than in the rural areas, while the swine farming section in the livestock sector has a conspicuous income effect in the midst of low greenhouse gas emission effect. These results allude us to apply graded tax rates to the crop, the livestock, and the region of different kind. Even if the agricultural sector has a less tax effect when compared with other industrial sectors, an environmental tax might be an effective measure to prevent global warming.

• 한국경영과학회지
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• 제20권2호
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• pp.39-60
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• 1995

In this paper, an integration of stochastic dynamic programming (SDP), integer goal programming (IGP) and analytic hierarchy process (AHP) is proposed to handle multiobjective-multicriteria sequential decision making problems under uncertainty inherent in R & D investment planning. SDP has its capability to handle problems which are sequential and stochastic. In the SDP model, the probabilities of the funding levels in any time period are generated using a subjective model which employs functional relationships among interrelated parameters, scenarios of future budget availability and subjective inputs elicited from a group of decision makers. The SDP model primarily yields an optimal investment planning policy considering the possibility that actual funding received may be less than anticipated one and thus the projects being selected under the anticipated budget would be interrupted. IGP is used to handle the multiobjective issues such as tradoff between economic benefit and technology accumulation level. Other managerial concerns related to the determination of the optimal project portifolio within each stage of the SDP model. including project selection, project scheduling and annual budget allocation are also determined by the IGP. AHP is proposed for generating scenario-based transformation probabilities under budgetary uncertainty and for quantifying the environmental risk to be considered.

• Advances in Energy Research
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• 제1권2호
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• pp.127-146
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• 2013

Torrefaction technologies convert assorted biomass feedstocks into energy-concentrated, carbon neutral fuel that is economically transported and easily ground for blending with fossil coals at numerous power plants around the world without needs to retrofit. Utilization of torrefied biomass in conventional electric generating units may be an increasingly attractive alternative for electricity generation as aging power plants in the world need to be upgraded or improved. This paper examines the economic feasibility of torrefaction in different scenarios by modeling torrefaction plants producing 136,078 t/year (150,000 ton/year) biocoal from wood and corn stover. The utilization of biocoal blends in existing coal-fired power plants is modeled to determine the demand for this fuel in the context of emerging policies regulating emissions from coal in the U.S. setting. Opportunities to co-locate torrefaction facilities adjacent to corn ethanol plants and coal-fired power plants are explored as means to improve economics for collaborating businesses. Life cycle analysis was conducted in parallel to this economic study and was used to determine environmental impacts of converting biomass to biocoal for blending in coal-fired power plants as well as the use of substantial flows of off-gasses produced in the torrefaction process. Sensitivity analysis of the financial rates of return of the different businesses has been performed to measure impacts of different factors, whether input prices, output prices, or policy measures that render costs or rewards for the businesses.

• 한국멀티미디어학회논문지
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• 제22권4호
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• pp.502-514
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• 2019

Existing user research methods are subject to a variety of research conditions such as the amount and variety of data collected and the expertise of the facilitator of a group research session. In this study, we propose a new user research methodology using an 'Issue-Network' system, which is developed based on the theory and methods of social network analysis. The Issue-Network is designed to define problem spaces from the issues raised by users in a group research session in a form of an interactive network graph. The system helps to break out of ordinary perspectives of looking into problem spaces by enabling an alternative and more creative way to connect issues in the network. In this study, we took a case study of generating the Issue-Network on behalf of the problems raised by users in various driving-related situations. We were able to draw three navigation usage scenarios that cover relatively important problem spaces: safety and being ready for the unexpected, smart navigation and notifications, making use of the spare time. In the future, the Issue-Network system is expected to be used as a tool to identify problems and derive solutions in group research sessions involving a large number of users.

• Structural Engineering and Mechanics
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• 제68권6호
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• pp.735-745
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• 2018

The Big Bang-Big Crunch (BB-BC) algorithm is an effective global optimization technique of swarm intelligence with drawbacks of being easily trapped in local optimal results and of converging slowly. To overcome these shortages, an improved BB-BC algorithm (IBB-BC) is proposed in this paper with taking some measures, such as altering the reduced form of exploding radius and generating multiple mass centers. The accuracy and efficiency of IBB-BC is examined by different types of benchmark test functions. The IBB-BC is utilized for damage detection of a simply supported beam and the European Space Agency structure with an objective function established by structural frequency and modal data. Two damage scenarios are considered: damage only existed in stiffness and damage existed in both stiffness and mass. IBB-BC is also validated by an existing experimental study. Results demonstrated that IBB-BC is not trapped into local optimal results and is able to detect structural damages precisely even under measurement noise.

• 대한임베디드공학회논문지
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• 제14권1호
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• pp.1-9
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• 2019

In this paper, we propose a method of generating a 2D gray image from LiDAR 3D reflection intensity. The proposed method uses the Fully Convolutional Network (FCN) to generate the gray image from 2D reflection intensity which is projected from LiDAR 3D intensity. Both encoder and decoder of FCN are configured with several convolution blocks in the symmetric fashion. Each convolution block consists of a convolution layer with $3{\times}3$ filter, batch normalization layer and activation function. The performance of the proposed method architecture is empirically evaluated by varying depths of convolution blocks. The well-known KITTI data set for various scenarios is used for training and performance evaluation. The simulation results show that the proposed method produces the improvements of 8.56 dB in peak signal-to-noise ratio and 0.33 in structural similarity index measure compared with conventional interpolation methods such as inverse distance weighted and nearest neighbor. The proposed method can be possibly used as an assistance tool in the night-time driving system for autonomous vehicles.