• IEIE Transactions on Smart Processing and Computing
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• 제2권4호
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• pp.203-207
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• 2013

The appropriate handling of motion artifacts is essential for clinical diagnosis in magnetic resonance imaging (MRI). In many cases, motion is an inherent part of MR images because it is difficult to control during MR imaging. As the motion in the human body occur in a deformable manner, they are difficult to deal with. This paper proposes a novel detection method for periodically moving regions to produce MR images with less motion artifacts. When the data is acquired by the radial trajectory, the proposed method can extract the deformable region easily using the difference in the modulated sinograms, which have different periodic phase terms. The simulation results applied to the various cases confirmed the good performance of the proposed method.

• 한국통신학회논문지
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• 제21권9호
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• pp.2456-2469
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• 1996

A digital satellite communication channel has a nonlinearity with memory due to saturation characeristis of the high poer amplifier in the satellite and transmitter/receiver linear filter used in the overall system. In this paper, we propose a complex radial basis function network(CRBFN) based adaptive equalizer for compensation of nonlinearities in digital satellite communication channels. The proposed CRBFN untilizes a complex-valued hybrid learning algorithm of k-means clustering and LMS(least mean sequare) algorithm that is an extension of Moody Darken's algorithm for real-valued data. We evaluate performance of CRBFN in terms of symbol error rates and mean squared errors nder various noise conditions for 4-PSK(phase shift keying) digital modulation schemes and compare with those of comples pth order inverse adaptive Volterra filter. The computer simulation results show that the proposed CRBFN ehibits good equalization, low computational complexity and fast learning capabilities.

• 한국지능시스템학회논문지
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• 제13권5호
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• pp.606-613
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• 2003

As a technical method for controlling chaotic dynamics, this paper presents a predictive control for chaotic systems based on radial basis function networks(RBFNs). To control the chaotic systems, we employ an on-line identification unit and a nonlinear feedback controller, where the RBFN identifier is based on a suitable NARMA real-time modeling method and the controller is predictive control scheme. In our design method, the identifier and controller are most conveniently implemented using a gradient-descent procedure that represents a generalization of the least mean square(LMS) algorithm. Also, we introduce a projection matrix to determine the control input, which decreases the control performance function very rapidly. And the effectiveness and feasibility of the proposed control method is demonstrated with application to the continuous-time and discrete-time chaotic nonlinear system.

• Journal of Electrical Engineering and Technology
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• 제6권5호
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• pp.666-670
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• 2011

In this paper, a method for detecting broken rotor bar and stator winding fault in a low voltage squirrel-case induction motor using an air-gap flux variation analysis is proposed to develop a simple and low cost diagnosis technique. To measure the leakage flux in radial direction, a radial flux sensor is designed as a search coil and installed between stator slots. The proposed method is able to identify two kinds of motor faults by calculating load condition of motors and monitoring abnormal signals those are related with motor faults. Experimental results obtained on 7.5kW three-phase squirrel-cage induction motors are discussed to verify the performance of the proposed method.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.888-892
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• 2014

In the design of the rotor of an interior permanent magnet synchronous motor (IPMSM), the bridge between the permanent magnets helps prevent the scattering of permanent magnets and pole pieces during high-speed operation. In the design of a motor, if the bridge is too thick, its performance will be largely degraded because of flux leakage. Additionally, if the bridge is too thin, its mechanical safety cannot be guaranteed. Thus, an accurate analysis method is required to determine the thickness of the bridge. Conventional stress analysis methods determine the thickness of the bridge by only considering the centrifugal force of the rotors. In this study, however, a method that additionally considers the radial force generated by the air-gap flux density based on the conventional methods is proposed and reflected in the design of a traction motor for electric vehicles. Finally, the validity of this study is verified through a reliability test related to high-speed operation.

• Interaction and multiscale mechanics
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• 제5권2호
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• pp.131-144
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• 2012

We study a radial basis function collocation method (RBFCM) to discretize a coupled nonlinear Schr$\ddot{o}$dinger equation (CNLSE) that governs a two dimensional rotating Bose-Einstein condensate (BEC) with an angular momentum rotation term. We exploit a RBFCM-continuation method (RBFCM-CM) to trace the solution curve of the CNLSE. We compare the performance of the RBFCM-CM with the FEM-CM. We observe that the RBFCM-CM is very robust in a coarse grid for resolving the ground state solution with many vortices when the angular momentum rotation is close to the limit. Numerical results demonstrate the efficiency and accuracy of the RBFCM-CM for computing the superfluid density of the ground level of the BEC.

• Clinics in Shoulder and Elbow
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• 제23권4호
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• pp.183-189
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• 2020

Background: The purpose of the current study was to investigate short- to mid-term outcomes and complications following radial head replacement (RHR) for complex radial head fractures and to identify factors associated with clinical outcomes. Methods: Twenty-four patients with complex radial head fractures were treated by RHR. The mean age of the patients was 49.8 years (range, 19-73 years). Clinical and radiographic outcomes were evaluated for a mean follow-up period of 58.9 months (range, 27-163 months) using the visual analog scale (VAS) score for pain, the Mayo elbow performance score (MEPS), the quick disabilities of the arm, shoulder and hand (Quick-DASH) score, and serial plain radiographs. Complications were also evaluated. Results: At the final follow-up, the mean VAS score, MEPS, and Quick-DASH score were 0.6±1.1, 88.7±11.5, and 19.4±7.8, respectively. The mean range of motion was 132.7° of flexion, 4.7° of extension, 76.2° of pronation, and 77.5° of supination. Periprosthetic lucency was observed in six patients (25%). Heterotopic ossification was observed in four patients (16.7%). Arthritic change of the elbow joint developed in seven patients (29.2%). Capitellar wear was found in five patients (20.8%). Arthritic change of the elbow joint was significantly correlated with MEPS (P=0.047). Four cases of complications (16.6%) were observed, including two cases of major complications (one stiffness with heterotopic ossification and progressive ulnar neuropathy and one stiffness) and two cases of minor complications (two transient ulnar neuropathy). Conclusions: RHR for the treatment of complex radial head fractures yielded satisfactory short- to mid-term clinical outcomes, though radiographic complications were relatively high.

• 전기학회논문지
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• 제62권4호
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• pp.544-553
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• 2013

In this paper, we propose the pattern classifier of Radial Basis Function Neural Networks(RBFNNs) for diagnosis of 3-phase partial discharge. Conventional methods map the partial discharge/noise data on 3-PARD map, and decide whether the partial discharge occurs or not from 3-phase or neutral point. However, it is decided based on his own subjective knowledge of skilled experter. In order to solve these problems, the mapping of data as well as the classification of phases are considered by using the general 3-PARD map and PA method, and the identification of phases occurring partial discharge/noise discharge is done. In the sequel, the type of partial discharge occurring on arbitrary random phase is classified and identified by fuzzy clustering-based polynomial Radial Basis Function Neural Networks(RBFNN) classifier. And by identifying the learning rate, momentum coefficient, and fuzzification coefficient of FCM fuzzy clustering with the aid of PSO algorithm, the RBFNN classifier is optimized. The virtual simulated data and the experimental data acquired from practical field are used for performance estimation of 3-phase partial discharge pattern classifier.

• Computers and Concrete
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• 제22권4호
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• pp.419-437
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• 2018

The compressive strength of self-compacting concrete (SCC) containing fly ash (FA) is highly related to its constituents. The principal purpose of this paper is to investigate the efficiency of hybrid fuzzy radial basis function neural network with biogeography-based optimization (FRBFNN-BBO) for predicting the compressive strength of SCC containing FA based on its mix design i.e., cement, fly ash, water, fine aggregate, coarse aggregate, superplasticizer, and age. In this regard, biogeography-based optimization (BBO) is applied for the optimal design of fuzzy radial basis function neural network (FRBFNN) and the proposed model, implemented in a MATLAB environment, is constructed, trained and tested using 338 available sets of data obtained from 24 different published literature sources. Moreover, the artificial neural network and three types of radial basis function neural network models are applied to compare the efficiency of the proposed model. The statistical analysis results strongly showed that the proposed FRBFNN-BBO model has good performance in desirable accuracy for predicting the compressive strength of SCC with fly ash.

• 대한기계학회논문집B
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• 제22권5호
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• pp.640-650
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• 1998

Pumping performances of a helical molecular drag dump(MDP) and of a radial MDPs are numerically analyzed by using the direct simulation Monte Carlo (DSMC) method. A helical- and radial-MDP have rotating pumping channels cut on a cylinder and on a disk, respectively. For a helical MDP, the present results agree quantitatively with the previously known numerical results. For radial MDPs, both of the Type 1 (having pumping channels cut on the stationary disk) and of the Type 2 (having pumping channels cut on the rotating disk) are analyzed to predict their performances for various parameters, i.e., the radius of curvature center of the channel wall, the depth of the channel, the clearance between housing and disk, and the rotating speed. The results show that the performance of the Type 2 is superior to that of the Type 1, and that for all types the pumping efficiency decreases as the clearance increases. Also, the radial type MDP has larger leakage losses in the direction of pumping channel than does the helical one.