• Journal of computational fluids engineering
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• v.17 no.4
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• pp.56-68
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• 2012

Nowadays, Unmanned Combat Air Vehicle(UCAV) has become an important aircraft system for the national defense. For its efficiency and survivability, shape optimization of UCAV is an essential part of its design process. In this paper, shape optimization of UCAV was processed for aerodynamic performance improvement and Radar Cross Section(RCS) reduction using Multi Objective Genetic Algorithm(MOGA). Lift and induced drag, friction drag, RCS were calculated using panel method, boundary layer theory, Physical Optics(PO) approximation respectively. In particular, calculation applied Radar Absorbing Material(RAM) was performed for the additional RCS reduction. Results are indicated that shape optimization is performed well for improving aerodynamic performance, reducing RCS. Further study will be performed with higher fidelity tools and consider other design segments including structure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1551-1558
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• 2021

Beacon signals used in indoor positioning system are reflected and distorted, resulting in noise signals. KF(Kalman Filter) has been widely used to remove this noise. In order to apply the KF, optimization process considering the signal type, signal strength, and environmental elements of each product is required. In this paper, we propose a solution to the optimization problem of KF Parameters using GA(Genetic Algorithm) in BLE(Bluetooth Low Energy) Beacon-based indoor positioning system. After optimizing KF Parameters by applying the proposed technique with a certain distance between Beacon and receiver, we compared the estimated distance passed through KF with the unfiltered distance. The proposed technique is expected to reduce the time required and improve accuracy of KF Parameters optimization in an indoor positioning system based on RSSI (Received Signal Strength Indication).

• Journal of the Korean Solar Energy Society
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• v.34 no.4
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• pp.23-29
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• 2014

Recently, in power system studies, Multiple Energy Carriers (MECs) such as Energy Hub has been broadly utilized in power system planners and operators. Particularly, Energy Hub performs one of the most important role as the intermediate in implementing the MECs. However, it still needs to be put under examination in both modeling and operating concerns. For instance, a probabilistic optimization model is treated by a robust global optimization technique such as multi-agent genetic algorithm (MAGA) which can support the online economic dispatch of MECs. MAGA also reduces the inevitable uncertainty caused by the integration of selected input energy carriers. However, MAGA only considers current state of the integration of selected input energy carriers in conjunctive with the condition of smart grid environments for decision making in Energy Hub. Thus, in this paper, we propose an immune algorithm based Multiple Energy Carriers System which can adopt the learning process in order to make a self decision making in Energy Hub. In particular, the proposed immune algorithm considers the previous state, the current state, and the future state of the selected input energy carriers in order to predict the next decision making of Energy Hub based on the probabilistic optimization model. The below figure shows the proposed immune algorithm based Multiple Energy Carriers System. Finally, we will compare the online economic dispatch of MECs of two algorithms such as MAGA and immune algorithm based MECs by using Real Time Digital Simulator (RTDS).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Journal of Korean Society for Quality Management
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• v.15 no.2
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• pp.20-26
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• 1987

An algorithm for the minimum total process percent defective under marginal costs is presented. Initial process is single series system, which is constructed by k process units, and each process is considered priority. Minimum of total process percent defective for parallel-series system exists when additional process setup costs are larger than marginal costs.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.6
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• pp.24-30
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• 2018

Dental implants are currently widely used as artificial teeth due to their good chewing performance and long life cycle. A dental implant consists of an abutment as the upper part and a fixture as the lower part. When chewing forces are repeatedly applied to a dental implant, gap at the interface surface between the abutment and the fixture is often occurred, and results in some deteriorations such as loosening of fastening screw, dental retraction and fixture fracture. To cope with such problems, a sealing-type abutment having a number of grooves along the conical-surface circumference was previously developed, and shows better sealing performance than the conventional one. This study carries out optimization of the groove shape by genetic algorithm(GA) as well as structural analysis in consideration of external chewing force and pretension between the abutment and the fixture. The overall optimization system consists of two subsystems; the one is the genetic algorithm with MATLAB, and the other is the structural analysis with ANSYS. Two subsystems transmit and receive the relevant data with each other throughout the optimization processes. The optimization result is then compared with that of the conventional one with respect to the contact pressure and the maximum stress. The result shows that the optimized model gives better sealing performance than the conventional sealing abutment.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.26 no.2
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• pp.151-157
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• 2013

In this paper, properties of pattern using LBG (Linde-Buzo-Gray) Algorithm was explored including the exactness of K-means algorithm and process time of EM (Expectation Maximization) algorithm in order to develop analysis algorithm of partial discharge pattern in a cable using acoustic data analysis system. Partial discharge was measured by generating inner fault due to lamination of XLPE which is used for cable insulation material. Discharge pattern was analysed by changing the number of swarm article to 2, 4, and 6 in order to interpret swarm structure and properties.

• Smart Structures and Systems
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• v.26 no.4
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• pp.533-544
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• 2020

Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.311-316
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• 2017

High Efficiency Video Coding (HEVC) is the newest video coding standard for improvement in video data compression. This new standard provides a significant improvement in picture quality, especially for high-resolution videos. A quadtree-based structure is created for the encoding and decoding processes and the rate-distortion (RD) cost is calculated for all possible dimensions of coding units in the quadtree. To get the best combination of the block an optimization process is performed in the encoder, called rate distortion optimization (RDO). In this work we are proposing a novel approach to enhance the overall RDO process of HEVC encoder. The proposed algorithm is performed in two steps. In the first step, like HEVC, it performs general rate distortion optimization. The second step is an extra checking where a SSIM based cost is evaluated. Moreover, a fast SSIM (FSSIM) calculation technique is also proposed in this paper.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.822-830
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• 2009

The spectrum efficiency of mobile communication networks can be improved dramatically adopting multiple antennas technologies. In order to guarantee the licensed rights of primary user (PU), the cognitive radio system should perform in a relatively low interference manner when it gets access to the spectrum of licensed networks. In this paper, we explore a uniformly distributed circular antenna array to implement beamforming algorithm that is accomplished by optimization method at the base station of cognitive radio networks, and therefore we can suppress the interference to PU by steering quite low transmission power toward PU and constructing a narrow beam toward cognitive user (CU). By reducing the constraint number of the optimization problem, we also propose a null steering algorithm that steers rather low radiation power toward PU, while the other areas in the same cell are covered by radiation power except the local area around PU. It is pursued to reduce the computation load and enlarge the capacity of cognitive radio networks extremely. The simulation results demonstrate that the proposed algorithms process superior performance.