• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.35-45
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• 2009

Emergency medical center(EMC) is the place for patients who need medical treatment immediately due to a disease, childbirth, or all sorts of accidents. Currently, most of EMCs use temporary beds because regular EMC beds cannot afford to serve all incoming patients. However, since it decreases the quality of service(QoS) of EMC patients and their guardians and efficiency of the EMC, some improvements are highly required to diminish the usage of temporary beds. The system duration time is one of the typical QoSs. This thesis proposes the information which is critical to make a better decision for cut down the number of temporary beds without sacrificing QoS of patients. The key point is to control the duration time of medical treatments for the consultation and hospitalization process, since it is the major reason of overcrowding in EMC and the usage of temporary beds. In this paper, we proposed an Arena simulation model reflecting real world substantially. Arena is one of the most widely accepted simulation softwares in the world. Using the developed model, we can obtain the optimal EMC operation parameters through simulation experiments. Optquest, included in the Arena, is used to make the developed simulation model collaborate with an optimization model. The results showed one can determine the set of optimal operation parameters decreasing the required number of temporary beds without deteriorating EMC patient's QoS.

• Progress in Medical Physics
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• v.11 no.1
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• pp.49-57
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• 2000

New method about the dose optimization problem in radiation treatment was researched. Since all conditions are more complex and there are more relevant variables, the solution of three-dimensional treatment planning is much more complicate than that of current two-dimensional one. There(ore, in this study, as a method to solve three-dimensional dose optimization problem, the considered variables was minized and researched by reducing the domain that solutions can exist and pre-determining the important beam parameters. First, the dangerous beam range that passes critical organ was found by coordinate transformation between linear accelerator coordinate and patient coordinate. And the beam size and rotation angle for rectangular collimator that conform tumor at arbitrary beam position was also determined. As a result, the available beam position could be reduced and the dependency on beam size and rotation angle, that is very important parameter in treatment planning, totally removed. Therefore, the resultant combinations of relevant variables could be greatly reduced and the dose optimization by objective function can be done with minimum variables. From the above results, the dose optimization problem was solved for the two-dimensional radiation treatment planning useful in clinic. The objective function was made by combination of dose gradient, critical organ dose and dose homogeniety. And the optimum variables were determined by applying step search method to objective function. From the dose distributions by optimum variables, the merit of new dose optimization method was verified and it can be implemented on commercial radiation treatment planning system with further research.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.10
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• pp.1139-1146
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• 2012

An alternative approach for topology optimization of steady incompressible Navier-Stokes flow problems is presented by using P1 nonconforming finite elements. This study is the extended research of the earlier application of P1 nonconforming elements to topology optimization of Stokes problems. The advantages of the P1 nonconforming elements for topology optimization of incompressible materials based on locking-free property and linear shape functions are investigated if they are also valid in fluid equations with the inertia term. Compared with a mixed finite element formulation, the number of degrees of freedom of P1 nonconforming elements is reduced by using the discrete divergence-free property; the continuity equation of incompressible flow can be imposed by using the penalty method into the momentum equation. The effect of penalty parameters on the solution accuracy and proper bounds will be investigated. While nodes of most quadrilateral nonconforming elements are located at the midpoints of element edges and higher order shape functions are used, the present P1 nonconforming elements have P1, {1, x, y}, shape functions and vertex-wisely defined degrees of freedom. So its implentation is as simple as in the standard bilinear conforming elements. The effectiveness of the proposed formulation is verified by showing examples with various Reynolds numbers.

• Journal of IKEEE
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• v.20 no.2
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• pp.181-183
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• 2016

In this work, the merged PiN Schottky(MPS) diodes based silicon carbide(SiC) have been optimized and designed for 1200V diodes by 2D-atlas simulation tool. We investigated the optimized characteristics of SiC MPS diodes such as breakdown voltage and specific on-resistance by varying the doping concentrations of P-Grid/epi-layer and space of P-Grid, which are the most important parameters. The breakdown voltage and specific on-resistance, based on Baliga's Figure Of Merit (BFOM), have been compared with and the SiC-based MPS diodes show improved BFOMs with low values of specific on-resistance and high breakdown voltage. It has been demonstrated 1,200 V SiC MPS diodes will find useful applications in high voltage energy-efficient devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2719-2730
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• 2009

In this paper, we implement the measurement functionality for performance measurements of EDGE (Enhanced Data Rates for GSM Evolution) terminal by using software. Generally speaking, the receiving algorithms in normal MODEM cannot be used directly to a measurement system due to the lack of accuracy. Therefore, we propose a new receiver algorithm for precise EDGE signal measurements. In the proposed algorithm, 2-stage (coarse stage, fine stage) parameters estimation (symbol-timing, frequency offset, carrier phase) scheme is used. To improve the estimation accuracy, we increase the number of the received signal samples by interpolation. The proposed EDGE signal measurement algorithm can be used for verifying the hardware measurement system, and also can be used for the commercial systems through software optimization.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.4
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• pp.266-269
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• 2018

A compact Q-band waveguide-to-microstrip transition for UAV(Unmanned Aerial Vehicle) radiometer applications is presented. The key features of this transition are simplicity, compactness, easy matching, and lower sensitivity to the dimensions and fabrication tolerances. The simple E-plane patch-type design is insensitive to the backshort cavity enclosure and misalignment between the waveguide and microstrip substrate. The primary parameters are optimized using a three-dimensional(3D) electromagnetic simulator(ANSYS HFSS). It exhibited better than 20-dB return loss at mid-band frequencies with less than 1-dB insertion loss for the back-to-back transition, and a return loss better than 15 dB over the frequency range of 36 GHz to 42 GHz.

• Korean Journal of Cognitive Science
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• v.12 no.1_2
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• pp.77-89
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• 2001

Applying perceptual hierarchy of facial feature points, a neural network model for recognizing facial expressions was designed. Input data were convolution values of 150 facial expression pictures by Gabor-filters of 5 different sizes and 8 different orientations for each of 39 mesh points defined by MPEG-4 SNHC (Synthetic/Natural Hybrid Coding). A set of multiple regression analyses was performed with the rating value of the affective states for each facial expression and the Gabor-filtered values of 39 feature points. The results show that the pleasure-displeasure dimension of affective states is mainly related to the feature points around the mouth and the eyebrows, while a arousal-sleep dimension is closely related to the feature points around eyes. For the filter sizes. the affective states were found to be mostly related to the low spatial frequency. and for the filter orientations. the oblique orientations. An optimized neural network model was designed on the basis of these results by reducing original 1560(39x5x8) input elements to 400(25x2x8) The optimized model could predict human affective rating values. up to the correlation value of 0.886 for the pleasure-displeasure, and 0.631 for the arousal-sleep. Mapping the results of the optimized model to the six basic emotional categories (happy, sad, fear, angry, surprised, disgusted) fit 74% of human responses. Results of this study imply that, using human principles of recognizing facial expressions, a system for recognizing facial expressions can be optimized even with a a relatively little amount of information.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.3
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• pp.32-39
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• 2009

In this paper, system optimization design technique of an impulse ground penetrating image radar (GPIR) in time domain is proposed to improve depth resolution of the system. For the purpose, time domain analysis method of key components such as impulse generator and UWB antenna is explained and by simulation, parameters of each component are determined. In particular, by standardizing the impulse signal, spectrum efficiency of a radiated impulse signal is improved and a U-shaped planar dipole antenna for a UWB antenna is developed. By equipping a parabolic metal reflector with the proposed antenna, external noise is prevented and the ability of radiating an input impulse into ground is improved. In addition, to remove ringing effect of the propose antenna which causes serious degradation of the system performance, resistors are loaded at the edge of the antenna and then Tx and Rx UWB antennas are optimized by simulation in time domain. For images of targets buried under the ground migration technique is applied and influence of tough ground surface on distortion of received impulse signals is reduced using technique of noise and signal distortion reduction in time domain and its time resolution is enhanced. To verify the design optimization procedure, a prototype of an GPIR and an artificial test field are made. Measurement results show that the resolution of the system designed is as good as that of a theoretical model.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.8-14
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• 2002

In this paper, we realized a real-time text-independent speaker recognition system using gaussian mixture model, and applied frame level likelihood normalization method which shows its effects in verification system. The system has three parts as front-end, training, recognition. In front-end part, cepstral mean normalization and silence removal method were applied to consider speaker's speaking variations. In training, gaussian mixture model was used for speaker's acoustic feature modeling, and maximum likelihood estimation was used for GMM parameter optimization. In recognition, likelihood score was calculated with speaker models and test data at frame level. As test sentences, we used text-independent sentences. ETRI 445 and KLE 452 database were used for training and test, and cepstrum coefficient and regressive coefficient were used as feature parameters. The experiment results show that the frame-level likelihood method's recognition result is higher than conventional method's, independently the number of registered speakers.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.