• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.328-333
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• 2007

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for tm based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM In this paper, a Markov state model much can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2146-2156
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• 2017

When a failure occurs in active distribution system, it will be isolated through the action of circuit breakers and sectionalizing switches. As a result, the network might be divided into several connected components, in which distributed generations could supply power for customers. Aimed at decreasing customer interruption cost, this paper proposes a theoretically optimal island partition model for such connected components, and a simplified but more practical model is also derived. The model aims to calculate a dynamic island partition schedule during the failure recovery time period, instead of a static islanding status. Fluctuation and stochastic characteristics of the renewable distributed generations and loads are considered, and the interruption cost functions of the loads are fitted. To solve the optimization model, a heuristic search algorithm based on the hill climbing method is proposed. The effectiveness of the proposed model and algorithm is evaluated by comparing with an existing static island partitioning model and intelligent algorithms, respectively.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.4
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• pp.113-128
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• 2016

This paper proposes a Bi-level Genetic Algorithm for the Fixed Charge Transportation Problem with Non-linear Unit Cost. The problem has the property of mixed integer program with non-linear objective function and linear constraints. The bi-level procedure consists of the upper-GA and the lower-GA. While the upper-GA optimize the connectivity between each supply and demand pair, the lower-GA optimize the amount of transportation between the pairs set to be connected by the upper-GA. In the upper-GA, the feasibility of the connectivity are verified, and if a connectivity is not feasible, it is modified so as to be feasible. In the lower-GA, a simple method is used to obtain a pivot feasible solution under the restriction of the connectivity determined by the upper-GA. The obtained pivot feasible solution is utilized to generate the initial generation of chromosomes. The computational experiment is performed on the selected problems with several non-linear objective functions. The performance of the proposed procedure is analyzed with the result of experiment.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.2
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• pp.73-90
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• 2018

Various navigation systems are integrated with the Global Navigation Satellite System (GNSS) to improve navigation performance so that continuous navigation information can be obtained even when navigation performance is degraded or navigation is not available due to the outage of GNSS. Time and cost can be reduced by evaluating performance of the integrated navigation system through Modeling and Simulation (M&S) software prior to the deployment of the integrated navigation system. The measurements of the navigation system should be generated to evaluate performance through of the navigation system M&S software. This paper proposes a method of designing a navigation environment generation module in M&S software of the integrated navigation system. To show applicability of the proposed method to M&S software design of the integrated navigation system, functions are verified through MATLAB. And then visual C++ based M&S software for the integrated navigation system is implemented to check the operation of the navigation environment generation module. The reference trajectory is generated and true measurements of Global Positioning System (GPS), Korea Positioning System (KPS), and enhanced Long range navigation (eLoran) are generated from the reference trajectory. The navigation results obtained from the true measurements are compared with the reference trajectories. The results show that the measurements generated using the design generation module by the proposed method are valid and the navigation environment generation module can be applied to M&S software of the integrated navigation system.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.167-174
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• 2007

This study proposes a practical and realistic method to establish an optimal lifetime maintenance strategy for deteriorating bridges by considering the life-cycle performance as well as the life-cycle cost. The proposed method offers a set of optimal tradeoff maintenance scenarios among other conflicting objectives, such as minimizing cost and maximizing performance. A genetic algorithm is used to generate a set of maintenance scenarios that is a multi-objective combinatorial optimization problem related to the and the life-cycle cost and performance as separate objective functions. A computer program, which generates optimal maintenance scenarios, was developed based on the proposed method. The subordinate relation between bridge members has been considered to decide optimal maintenance sequence. The developed program has been used to present a procedure for finding an optimal maintenance scenario for steel-girder bridges on the Korean National Road. Through this bridge maintenance scenario analysis, it is expected that the developed method and program can be effectively used to allow bridge managers an optimal maintenance strategy satisfying various constraints and requirements.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.51-58
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• 2015

Since SBA is regarded as mandatory for DM&S, many M&S frameworks and solutions were developed and applied to military simulation systems. Simulation systems developed based on such framework or solution are consist of simulation control part, scenario generation part and modeling part in common. Although the functions of these parts are similar between another simulation systems, these are developed separately by different implementation, so it causes increase of development cost. In order to solve these problems, we developed a simulation scenario framework which can be reusable regardless of simulation purpose. In this paper, we propose an architecture of simulation scenario framework and its functions.

• Smart Media Journal
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• v.1 no.3
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• pp.15-21
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• 2012

Depth information is necessary for various three dimensional contents generation. Depth acquisition techniques can be categorized broadly into two approaches: active, passive depth sensors depending on how to obtain depth information. In this paper, we take a look at several ways of depth acquirement. We present not only depth acquisition methods using discussed ways, but also hybrid methods which combine both approaches to compensate for drawbacks of each approach. Furthermore, we introduce several matching cost functions and post-processing techniques to enhance the temporal consistency and reduce flickering artifacts and discomforts of users caused by inaccurate depth estimation in 3D video.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.51-61
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• 2019

In this paper, we have implemented soil simulation using fluid simulation technology. A widely used NVIDIA FleX was used to represent the soil generated by excavation work. FleX is a particle-based physics simulation library that combines SPH (Smoothed-particle hydrodynamics) and Position Based Dynamics techniques. However, since the soil has not only fluid properties but also non-fluid properties, it is difficult to simulate with the functions provided by conventional FleX. In this study, we added a technique to simulate non-fluid behavior using existing Flex. This can lead to effective results improvement at low cost.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.1
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• pp.51-61
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• 2019

There are strict evaluation processes before using new processors to satellites. Engineers evaluate processors from various viewpoints including specification, development environment, and cost. From a viewpoint of computation power, manufacturers provide benchmark results with processors, and engineers decide which processors are adequate to their satellites by comparing the benchmark results with requirements of their satellites. However, the benchmark results depends on a test environment of manufacturers, and it is quite difficult to achieve similar performance in a target environment. Therefore, it is necessary to evaluate the processors in the target environment. This paper compares performance of a processor, AT697F/LEON2, in software testbed (STB) with three development boards of XC2V/LEON3, GR712RC/LEON3, and GR740/LEON4. Seven benchmark functions of Dhrystone, Stanford, Coremark, Whetstone, Flops, NBench, and MiBench are selected. Results are analyzed with hardware and software properties: hardware properties of core architecture, number of cores, cache, and memory; and software properties of build options and compilers. Based on the analysis, this paper describes a guideline for choosing processors for next generation satellites.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.57-59
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• 2001

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model has been studied, proposed, and applied. Among those models, power pool is more popular than others. This paper assumes the power pool market structure having competitive generation sector and a new method is presented to build bidding strategy in that market. The utilities participating in the market have the perfect information on their cost and price functions, but they don't know the strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price function into discrete step function. An utility knows only his own strategy, so he estimates the other's strategy using stochastic methods. For considering these conditions, we introduce the Bayesian rules and noncooperative game theory concepts. Also additional assumptions are included for simplification of solving process. Each utility builds the strategy to maximize his own expected profit function using noncooperative Bayesian game. A numerical example is given in case study to show essential features of this approach.