• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.43-50
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• 2001

In this paper, we propose the design procedure of advance Polynomial Neural Networks(PNN) architecture for optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling(GMDH). PNN is a flexible neural architecture whose structure is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated in a dynamic way. In this sense, PNN is a self-organizing network. With the aid of three representative numerical examples, compari-sons show that the proposed advanced PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

• Journal of the Korean institute of surface engineering
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• v.36 no.1
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• pp.69-73
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• 2003

The atmospheric pressure plasma is regarded as an effective method for surface treatments because it can reduce the period of process and doesn't need expensive vacuum apparatus. The performance of non-transferred plasma torches is significantly depended on jet flow characteristics out of the nozzle. In order to produce the high performance of a torch, the maximum discharge velocity near an annular gap in the torch should be maintained. Also, the compulsory swirl is being produced to gain the shape that can concentrate the plasma at the center of gas flow. In this work, the distribution of gas flow that goes out to atmosphere through a plenum chamber and nozzle is analyzed to evaluate the performance of atmospheric pressure plasma torch which can present the optimum design of the torch. Numerical analysis is carried out with various angles of an inlet flow velocity. Especially, three-dimensional model of the torch is investigated to estimate swirl effect. We also investigate the stabilization of plasma distribution. For analyzing the swirl in the plenum chamber and the flow distribution, FVM (finite volume method) and SIMPLE algorithm are used for solving the governing equations. The standard k-model is used for simulating the turbulence.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.1
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• pp.127-134
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• 2016

Most of reconstruction algorithms for the calculation of temperature distributions in CT (computed tomography)-TDLAS (tunable diode laser absorption spectroscopy) are based upon two-line thermometry method. This method gives unstable calculation convergence due to signal noise, bias error, and signal mis-matches. In this study, a new reconstruction algorithm based on cross-correlation for temperature calculation is proposed. The patterns of the optical signals at all wave lengths were used to reconstruct the temperature distribution. Numerical test has been made using phantom temperature distributions. Using these phantom temperature data, absorption spectra for all wave lengths were constructed, and these spectra were regarded as the signals that would be obtained in an actual experiments. Using these virtually generated experimental signals, temperature distribution was once again reconstructed, and was compared with those of the original phantom data. Calculation errors obtained by the newly proposed algorithm were slightly large at high temperatures with small errors at low temperature.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.5
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• pp.365-372
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• 2021

This paper deals with an optimal Weapon-Target Assignment (WTA) algorithm for Closed-In Weapon Systems (CIWS), considering variable burst time. In this study, the WTA problem for CIWS is formulated based on Mixed Integer Linear Programming (MILP). Unlike the previous study assuming that the burst time is fixed regardless of the engagement range, the proposed method utilizes the variable burst time based on the kill probability according to the engagement range. Thus, the proposed method can reflect a more realistic engagement situation and reduce the reaction time of CIWS against targets, compared to the existing method. In this paper, we first reformulate the existing MILP-based WTA problem to accommodate the variable burst Time. The proposed method is then validated through numerical simulations with the help of a commercial optimization tool.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.3
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• pp.318-327
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• 2016

In order to improve the performance of temperature field measurements by CT-TDLAS (Computer Tomography Tunable Diode Laser Absorption Spectroscopy), a new reconstruction algorithm, named two-ratios-of-three-peaks method is proposed in this paper. Further, two methods for selecting appropriate initial values of the iterative calculation of CT-TDLAS are proposed. One is MLOS (multiplicative line of sight) method and the other one is ALOS (additive line of sight) method. Two-ratios-of-three-peaks (2R3P) algorithm combined with MART (multiplicative algebraic reconstruction technique) is finally developed for the enhancements of reconstructive calculations. The results have been compared with those obtained by the conventional one-ratio-of-two-peaks (1R2P) algorithm. In order to evaluate the performance of this algorithm, numerical test has been performed using phantom Gaussian temperature distributions with $11{\times}11$ square mesh. The performance of the constructed algorithm has been demonstrated by comparing the results obtained in actual burner experiments with those obtained by thermocouples. It has been verified that 2R3P algorithm with MART and MLOS showed best performance than that of 1R2P algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.613-623
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• 2002

Ascent trajectory optimization and explicit guidance problems for a satellite launch vehicle with yaw maneuver in a 3-dimension are considered. The trajectory optimization problem with boundary conditions is formulated as a nonlinear programming problem by parameterizing the inertial pitch and yaw attitude control variables, and is solved by using the SQP algorithm. The flight constraints such as gravity-turn and range safety conditions are imposed. An explicit inertial guidance algorithm in the exoatmospheric phase is also presented. The guidance algorithm provides steering command and time-to-go value directly using the current states of the vehicle and the desired orbit insertion conditions. The liquid propelled Delta 2910 launch vehicle is used as a numerical model.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.74-81
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• 2008

In this paper, adaptive watermarking algorithm which based on fuzzy reasoning and hybrid scheme is presented. To enforce the time and space complexity, hybrid scheme which utilize a color information as well as visual characteristics is also addressed. Proposed approach have double-aim: in first to use the visual characteristics so as to enforce the robustness of watermarking, and in second to select the optimal sub-band which is to be embedded a watermark. One of the principal advantage is that this approach involved the fuzzy inference module which is designed to select an optimal sub-band from the DWT coefficient blocks. In order to demonstrate the effectiveness of proposed algorithm, some numerical experiments of robustness and imperceptibility are evaluated with respect to such attacks as JPEG compression, noise and cropping.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.121-129
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• 2014

The trend of an increasing demand for a high-quality user experience, coupled with a shortage of radio resources, has necessitated more advanced wireless techniques to cooperatively achieve the required quality-of-experience enhancement. In this study, we investigate the critical problem of rate splitting in heterogeneous cellular networks, where concurrent transmission, for instance, the coordinated multipoint transmission and reception of LTE-A systems, shows promise for improvement of network-wide capacity and the user experience. Unlike most current studies, which only deal with spectral efficiency enhancement, we implement an optimal rate splitting strategy to improve both spectral efficiency and energy efficiency by exploring and exploiting cooperation diversity. First, we introduce the motivation for our proposed algorithm, and then employ the typical cooperative bargaining game to formulate the problem. Next, we derive the best response function by analyzing the dual problem of the defined primal problem. The existence and uniqueness of the proposed cooperative bargaining equilibrium are proved, and more importantly, a distributed algorithm is designed to approach the optimal unique solution under mild conditions. Finally, numerical results show a performance improvement for our proposed distributed cooperative rate splitting algorithm.

• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.369-374
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• 2005

This study proposes a technique for the recognition of crack patterns, which includes horizontal, vertical, diagonal($-45^{\circ}$), diagonal($+45^{\circ}$), and random cracks, based on image processing technique and artificial neural network. A MATLAB code was developed for the proposed image processing algorithm and artificial neural network. Features were determined using total projection technique, and the structure(no. of layers and hidden neurons) and weight of artificial neural network were determined by learning from artificial crack images. In this process, we adopted Bayesian regularization technique as a generalization method to eliminate overfitting Problem. Numerical tests were performed on thirty-eight crack images to examine validity of the algorithm. Within the limited tests in the present study, the proposed algorithm was revealed as accurately recognizing the crack patterns when compared to those classified by a human expert.

• Atmosphere
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• v.31 no.5
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• pp.489-510
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• 2021

In this paper, we propose an algorithm for detecting convective initiation (CI) using GEO-KOMPSAT-2A/advanced meteorological imager data. The algorithm identifies clouds that are likely to grow into convective clouds with radar reflectivity greater than 35 dBZ within the next two hours. This algorithm is developed using statistical and qualitative analysis of cloud characteristics, such as atmospheric instability, cloud top height, and phase, for convective clouds that occurred on the Korean Peninsula from June to September 2019. The CI algorithm consists of four steps: 1) convective cloud mask, 2) cloud object clustering and tracking, 3) interest field tests, and 4) post-processing tests to remove non-convective objects. Validation, performed using 14 CI events that occurred in the summer of 2020 in Korean Peninsula, shows a total probability of detection of 0.89, false-alarm ratio of 0.46, and mean lead-time of 39 minutes. This algorithm can be useful warnings of rapidly developing convective clouds in future by providing information about CI that is otherwise difficult to predict from radar or a numerical prediction model. This CI information will be provided in short-term forecasts to help predict severe weather events such as localized torrential rainfall and hail.