• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.676-683
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• 2011

In this paper, we propose a robust method which can detect and track a high-speed small approaching target in a cluttered environment for Korean Active Protection System. The proposed method uses a temporal and spatial filter, tracking filter to detect and track a single target in consecutive order. And it is comprised of a candidate target detection step, a prior target selection step and a target tracking. Field tests on real infrared image sequences show that the proposed method could stably track a high speed and small target in complex background and target occlusion.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.225-229
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• 2012

We examine spectrum sensing in a situation of uncertain channel model. In particular, we assume that, besides additive noise, the observed signal contains an interference term whose probability distribution is unknown, and only its range and maximum power are known. We discuss the evaluation of the detector performance and its design in this situation. Although this paper specifically deals with the design of spectrum sensors, its scope is wider, as the applicability of its results extends to a general class of problems that may arise in the design of receivers whenever there is uncertainty about how to model the environment in which one is expected to operate. The theory expounded here allows one to determine the performance of a receiver, by combining the available (objective) probabilistic information with (subjective) information describing the designer's attitude.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.288-291
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• 2011

Video stabilization is an important image enhancement widely used in surveillance system in order to improve recognition performance. Most previous methods calculate inter-frame homography to estimate global motion. These methods are relatively slow and suffer from significant depth variations or multiple moving object. In this paper, we propose a fast and practical approach for video stabilization that selects the most reliable key frame as a reference frame to a current frame. We use optical flow to estimate global motion within an adaptively selected region of interest in static camera environment. Optimal global motion is found by probabilistic voting in the space of optical flow. Experiments show that our method can perform real-time video stabilization validated by stabilized images and remarkable reduction of mean color difference between stabilized frames.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.159-162
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• 2001

In this Paper, a new multi-sensor single-target tracking method in cluttered environment is proposed. Unlike the established methods such as probabilistic data association filter (PDAF), the proposed method intends to reflect the information in detection phase into parameters in tracking so as to reduce uncertainty due to clutter. This is achieved by first modifying the Bayes risk in Bayesian detection criterion to incorporate the likelihood of measurements from multiple sensors. The final estimate is then computed by taking a linear combination of the likelihood and the estimate of measurements. We develop the procedure and discuss the results from representative simulations.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.139-148
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• 2009

In a real-life supply chain environment, demand forecasting is usually represented by probabilistic distributions due to the uncertainty inherent in customer demands. However, the customer demand used for an actual supply chain planning is a single deterministic value for each of periods. In this paper we study the choice of single demand value among of the given customer demand distribution for a period to be used in the supply chain planning. This paper considers distributed multi-echelon supply chain and the objective function of this paper is to minimize the total costs, that is the sum of holding and backorder costs over the distribution network under the service level constraint, by using demand selection scheme. Some useful findings are derived from various simulation-based experiments.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05b
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• pp.249-252
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• 2005

Chloride ingress is a common cause of deterioration of reinforced concrete structures. Modeling the chloride ingress is an important basis for designing reinforced concrete structures and for assessing the reliability of an existing structure. The modelling is also needed for predicting the deterioration of a reinforced structure. This paper presents an approach for the probabilistic modeling of the chloride-induced corrosion of reinforcement steel in concrete structures that takes into account the uncertainties in the physical models. The parameters of the models are modeled as random variables and the distribution of the corrosion time and probability of corrosion are determined by using Monte Carlo simulation. The predictions of the proposed model is very effective to do the decision-making about initiation time and deterioration degree.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.11
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• pp.668-674
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• 2003

The electric marketplace is in the midst of major changes designed to promote competition. No longer vertically integrated with guaranteed customers and suppliers, electric generators and distributors will have to compete to sell and buy electricity. Unit commitment (UC) in such a competitive environment is not the same as the traditional one anymore. The objective of UC is not to minimize production cost as before but to find the solution that produces a maximum profit for a generation firm. This paper presents a hi-level formulation that decomposes the UC game into a generation-decision game (first level game) and a state(on/off)-decision game (second level game). Derivation that the first-level game has a pure Cournot Nash equilibrium(NE) helps to solve the second-level game. In case of having a mixed NE in the second-level game, this paper chooses a pure strategy having maximum probability in the mixed strategy in order to obviate the probabilistic on/off state which may be infeasible. Simulation results shows that proposed method gives the adequate UC solutions corresponding to a NE.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.420-426
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• 1998

Evolutionary algorithms are probabilistic optimization algorithms based on the model of natural evolution. Recently the efforts to improve the performance of evolutionary algorithms have been made extensively. In this paper, we introduce the research for improving the convergence rate and search faculty of evolution algorithms by using reinforcement learning. After providing an introduction to evolution algorithms and reinforcement learning, we present adaptive genetic algorithms, reinforcement genetic programming, and reinforcement evolution strategies which are combined with reinforcement learning. Adaptive genetic algorithms generate mutation probabilities of each locus by interacting with the environment according to reinforcement learning. Reinforcement genetic programming executes crossover and mutation operations based on reinforcement and inhibition mechanism of reinforcement learning. Reinforcement evolution strategies use the variances of fitness occurred by mutation to make the reinforcement signals which estimate and control the step length.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.62-66
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• 2003

In recent, the importance and necessity of some studies on reliability evaluation of grid comes from the recent black-out accidents occurred in the world. The quantity evaluation of transmission system reliability is very important under competitive electricity environment. The reason is that the successful operation of electric power under the deregulated electricity market depends on transmission system reliability management. This paper introduces features and operation modes of the Transmission Reliability Evaluation for Large-Scale Systems(TRELSS) Version 5_1, a program made in EPRI, for assessing reliability indices of composite power system. The package accesses not only bulk but also buses indices for reliability evaluation of composite powers system. The characteristics of the TRELSS program are illustrated by the case studies using the IEEE 25buses system.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.67-70
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• 2003

In recent, the importance and necessity of some studies on reliability evaluation of grid come from the recent black-out accidents occurred in the world. The quantity evaluation of transmission system reliability is very important under competitive electricity environment. The reason is that the successful operation of electric power under the deregulated electricity market depends on transmission system reliability management. The various results of many case studies for the IEEE 25buses system using the Transmission Reliability Evaluation for Large-Scale Systems(TRELSS) Version 5_1, a program made in EPRI are introduced in this paper. Some sensitivity analysis has been included. This paper suggests that the some important input parameters of the TRELSS can be determined optimally from this sensitivity analysis for high reliability level operation of a system.