• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.316-323
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• 1995

This paper presents an image processing technique to get traffic information such as vehicle volume, velocity, and occupancy for measuring the traffic congestion rate. To obtain these information, two horizontal lines are previously set on the screen. A moving vehicle is detected using the gray level difference on each line, and also template matching method at night. Threshold values are determined by sampling pavement grey level, and updated dynamically to cope with the change of ambient light conditions. These technique is successfully used to calculate vehicle volume, occupancy, and velocity. This study can be applied to traffic signal control system for minimizing traffic congestion in urban areas.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1963-1970
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• 2001

It is essential design process to analyze processing method and set out top level HW configuration using main parameters before implementation of the SAR processor. This paper identifies the impact of the I/O and algorithm structure upon the parallel processing to be assessed and suggests the practical mapping method fur parallel processing to the SAR data. Also, simulation is performed to the E-SAR processor to examine the usefulness of the method, and the results are analyzed and discussed.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.2
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• pp.109-123
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• 2008

The present paper presents the CFD result for a beam wave test case. An ONR tumblehome ship model with bilge keels is used. The beam wave test is for zero forward speed and roll and heave 2DOF with wave slope $a_k=0.156$ and wavelength ${\lambda}=1.12L_{PP}$, with $L_{PP}$ the ship length. The problems is solved numerically with an unsteady Reynolds averaged Navier-Stokes approach. The free surface flow is computed using a single-phase level-set method and the motions in each time step are integrated using a predictor-corrector iteration approach which uses dynamic overset grids moving with relative ship motion. The predicted CFD results for motions and forces are compared with experimental data, showing a reasonable agreement.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.627-638
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• 1998

For any hazardous operation or risky project to be carried out safely and economically, it is of the utmost importance to formulate proper risk management policies based on the rational assessment of the risk levels of various potential hazards. In this paper, a Fuzzy Multi-Criteria Decision Making(FMCDM) method for risk assessment is proposed. The method evaluates, on the basis of fuzzy set theory, the risk level of a risky situation by aggregating the assessed levels of risk factors and their subjective weights. The method also allows some flexibility for the future users in the sense that, first, the relative importance weights for the three risk factors can be adjusted according to the nature of projects or systems and, second, the users have the choice between the two types of risk assessment results, that is, the assessed risk levels or the ranks of the risk situations. A numerical example for the proposed FMCDM method is provided to illustrate the computational procedure. To see how the suggested FMCDM method describes well people's perceived risk level, we compared the risk values derived from the suggested method with the subjective risk evaluations for ten risky situations.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.155-157
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• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• Earthquakes and Structures
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• v.16 no.2
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• pp.165-175
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• 2019

Incremental dynamic analysis (IDA), as an accurate method to evaluate the parameters of structural performance levels, requires many non-linear time history analyses, using a set of ground motion records which are scaled to different intensity levels. Therefore, this method is very computationally demanding. In this study, a new method is presented to estimate the summarized (16%, 50%, and 84% fractiles) IDA curves of a first-mode dominated structure using discrete wavelet transform and bees optimization algorithm. This method reduces the number of required ground motion records for the prediction of the summarized IDA curves. At first, a subset of first list ground motion records is decomposed by means of discrete wavelet transform which have a low dispersion estimating the summarized IDA curves of equivalent SDOF system of the main structure. Then, the bees algorithm optimizes a series of factors for each level of detail coefficients in discrete wavelet transform. The applied factors change the frequency content of original ground motion records which the generated ground motions records can be utilized to reliably estimate the summarized IDA curves of the main structure. At the end, to evaluate the efficiency of the proposed method, the seismic behavior of a typical 3-story special steel moment frame, subjected to a set of twenty ground motion records is compared with this method.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.1
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• pp.29-41
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• 2008

The present paper provides a CFD analysis of diffraction problem for a ship with forward speed using an unsteady RANS simulation method, a WAVIS code. The WAVIS viscous solver adopting a finite volume method has second order accuracy in time and field discretizaions for the RANS equations. A two phase level-set method and a realizable ${\kappa}-{\varepsilon}$ turbulence model are adopted to compute the free surface and to meet the turbulence closure, respectively. To validate the capability of the present numerical methods for the simulation of an unsteady progressive regular wave, computations are performed for three grid sets with refinement ratio of ${\sqrt{2}}$. The main simulation is performed for a DTMB5512 model with a forward speed in a regular head sea condition. Validation of the present numerical method is carried out by comparing the present CFD results with available unsteady experimental data published in the 2005 Tokyo CFD Workshop: resistance, heave force, pitch moment, unsteady free surface elevations and velocity fields.

• Journal of Power Electronics
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• v.19 no.1
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• pp.168-178
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• 2019

Discrete space vector modulation (DSVM) is an effective method to improve the steady-state performance of the finite control set predictive control for permanent magnet synchronous motor drive systems. However, it requires complex computations due to the presence of numerous virtual voltage vectors. This paper proposes an improved finite control set model-free predictive control using DSVM to reduce the computational burden. First, model-free deadbeat current control is used to generate the reference voltage vector. Then, based on the principle that the voltage vector closest to the reference voltage vector minimizes the cost function, the optimal voltage vector is obtained in an effective way which avoids evaluation of the cost function. Additionally, in order to implement double-objective control, a two-level decisional cost function is designed to sequentially reduce the stator currents tracking error and the inverter switching frequency. The effectiveness of the proposed control is validated based on experimental tests.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1201-1208
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• 2010

In this paper, we propose an image encryption method using two linear MLCA(Maximum Length Cellular Automata). The encryption method first sets arbitrary 8 bit initial values. Next, we create high quality PN(pseudo noise) sequences by converting rows and columns with the set initial values. hen we generate a basis image using the set PN sequences. Lastly, the final image with high encryption level is produced by XOR operation of the basis image and the original image. In order to verify that the proposed method has the high encryption level, we performed histogram and stability analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.953-955
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• 2009

In this paper, we propose an image encryption method using two linear MLCA(Maximum Length Cellular Automata). The encryption method first sets arbitrary 8 bit initial values. Next, we create high quality PN(pseudo noise) sequences by converting rows and columns with the set initial values. Then we generate a basis image using the set PN sequences. Lastly, the final image with high encryption level is produced by XOR operating the basis image and the original image. In order to verify that the proposed method has the high encryption level, we performed histogram and stability analysis.