• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.77-82
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• 2006

Automatic vessel collision-avoidance systems have been studied in the fields of artificial intelligence and navigation for decades. And to facilitate automatic collision-avoidance decision-making in two-vessel-encounter situation, several expert and fuzzy expert systems have been developed. However, none of them can negotiate with each other as seafarers usually do when they intend to make a more economic overall plan of collision avoidance in the COLREGS-COST-HIGH situations where collision avoidance following the International Regulations for Preventing Collisions at Sea(COLREGS) costs too much. Automatic Identification System(AIS) makes data communication between two vessels possible, and negotiation methods can be used to optimize vessel collision avoidance. In this paper, a negotiation framework is put forward to enable vessels to negotiate to optimize collision avoidance in the COLREGS-COST-HIGH situations at open sea. A vessel vector space is defined and therewith a cost model is put forward to evaluate the cost of collision-avoidance actions. Negotiations between a give-way vessel and a stand-on vessel and between two give-way vessels are considered respectively to reach overall low cost agreements. With the framework proposed in this paper, two vessels involved in a COLREGS-COST-HIGH situation can negotiate with each other to get a more economic overall plan of collision avoidance than that suggested by the traditional collision-avoidance expert systems.

• Industrial Engineering and Management Systems
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• 제9권2호
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• pp.70-79
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• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제13권4호
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• pp.261-267
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• 2006

A local convergence analysis of Newton's method for perturbed generalized equations is provided in a Banach space setting. Using center Lipschitzian conditions which are actually needed instead of Lipschitzian hypotheses on the $Fr\'{e}chet$-derivative of the operator involved and more precise estimates under less computational cost we provide a finer convergence analysis of Newton's method than before [5]-[7].

• East Asian mathematical journal
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• 제24권2호
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• pp.161-168
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• 2008

We revisit the study of finding solutions of equations containing a differentiable and a continuous term on a Banach space setting [1]-[5], [9]-[11]. Using more precise majorizing sequences than before [9]-[11], we provide a semilocal convergence analysis for the generalized Newton's method as well the generalized modified Newton's method. It turns out that under the same or even weaker hypotheses: finer error estimates on the distances involved, and an at least as precise information on the location of the solution can be obtained. The above benefits are obtained under the same computational cost.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제14권4호
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• pp.279-282
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• 2007

Using the center instead of the Lipschitz condition we show how to provide weaker sufficient convergence conditions of the modified Newton Kantorovich method for the solution of nonlinear singular integral equations with Curleman shift (NLSIES). Finer error bounds on the distances involved and a more precise information on the location of the solution are also obtained and under the same computational cost than in [1].

• East Asian mathematical journal
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• 제23권2호
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• pp.257-260
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• 2007

Using the center instead of the Lipschitz condition we show how to provide weaker sufficient convergence conditions of the modified Newton Kantorovich method for the solution of nonlinear singular integral equations with Curleman shift (NLSIES). Finer error bounds on the distances involved and a more precise information on the location of the solution are also obtained and under the same computational cost than in [1].

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1076-1079
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• 2000

In this paper, a simplified visualization method is proposed for an urban space in consideration of weather and sun moving. In the proposed method, buildings and roads with shadows are visualized by the ray tracing algorithm. Also sky, snow, and rain are visualized by textures. Some textures such as snow and rain are generated in advance by the ray casting algorithm. Then we can obtain images with weather condition and shadows of sunlight by buildings along the road in relatively low computational cost

• East Asian mathematical journal
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• 제25권4호
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• pp.425-431
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• 2009

We provide a local convergence analysis for Newton-like methods for the solution of generalized equations in a Banach space setting. Using some ideas of ours introduced in [2] for nonlinear equations we show that under weaker hypotheses and computational cost than in [7] a larger convergence radius and finer error bounds on the distances involved can be obtained.

• 천문학회보
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• 제35권1호
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• pp.62.1-62.1
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• 2010

GMTO(Giant Magellan Telescope Organization) 이사회(Board Meeting)는 GMT의 1세대관측기기 1차 선정을 하였다. 의향서(Letter of Intent)를 제출한 12개 기기 중 9개 기기에 대해 제안서를 받아 과학자문위원회(Science Advisory Committee)에서 과학적 측면(Science), 기술적 측면(Technical), 비용 및 작업범위측면(Cost, scope & management)에서 심사한 결과 6개를 추천하였고 이사회에서 이를 승인하였다. 한국이 참여하는 GMTNIRS를 포함하여 G-CLEF, GMACS, GMTIFS, NIRMOS, TIGER가 선정되었다. 이 기기들은 2010년 4월부터 14개월 동안의 Conceptual Design Study를 거쳐 2011년 하반기에 이중에서 다시 3~4개가 GMT 1세대 관측기기로 최종 선정되어 제작될 예정이다.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1223-1230
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• 2020

Recently, extensive studies have been conducted to apply deep learning to reinforcement learning to solve the state-space problem. If the state-space problem was solved, reinforcement learning would become applicable in various fields. For example, users can utilize dance-tutorial systems to learn how to dance by watching and imitating a virtual instructor. The instructor can perform the optimal dance to the music, to which reinforcement learning is applied. In this study, we propose a method of reinforcement learning in which the action space is dynamically adjusted. Because actions that are not performed or are unlikely to be optimal are not learned, and the state space is not allocated, the learning time can be shortened, and the state space can be reduced. In an experiment, the proposed method shows results similar to those of traditional Q-learning even when the state space of the proposed method is reduced to approximately 0.33% of that of Q-learning. Consequently, the proposed method reduces the cost and time required for learning. Traditional Q-learning requires 6 million state spaces for learning 100,000 times. In contrast, the proposed method requires only 20,000 state spaces. A higher winning rate can be achieved in a shorter period of time by retrieving 20,000 state spaces instead of 6 million.