• Journal of Sasang Constitutional Medicine
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• v.29 no.4
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• pp.336-346
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• 2017

Objectives The purpose of this study is to investigate the characteristics of low back pain and shoulder arm pain patients according to the Sasang Constitution. Method We classified Seventy-nine participants by their Sasang Constitution. We investigated various aspects of the participant's pain such as the location of pain, diseases and Syndrome Differentiation etc. then intended to confirm relationship the Sasang Constitution and these research items through the statistics analysis. Results The numbers of lower back pain patients was statistically higher in Soyangin group than any other groups and the number of shoulder arm pain patients was statistically higher in Taeeumin group or Eumin group (Taeeumin group and Soeumin group) than Soyangin group. The number of diabetes patients and obesity patients was statistically higher in Taeeumin lower back pain patients, and that of obesity patients was statistically higher in Taeeumin shoulder arm pain patients than any other groups. The numbers of shoulder arm pain patients due to blood stasis and lower back pain patients due to kidney deficiency were statistically higher in Soyangin group than any other groups. The numbers of shoulder arm pain patients due to phlegm fluid retention and lower back pain patients due to phlegm fluid retention were statistically higher in Taeeumin group than any other groups. Conculsions The characteristics of lower back pain and shoulder arm pain could be different according to Sasang constitution.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.229-238
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• 2006

Observed field behaviors are frequently different from the behaviors predicted in the design state due to several uncertainties involved in soil properties, numerical modeling, and error of measuring system even though a sophisticated numerical analysis technique is applied to solve the consolidation behavior of drainage-installed soft deposits. In this study, genetic algorithms are applied to back-analyze the soil properties using the observed behavior of soft clay deposit composed of multi layers that shows complex consolidation characteristics. Utilizing the program, one might be able to appropriately predict the subsequent consolidation behavior from the measured data in an early stage of consolidation of multi layered soft deposits. Example analyses for drainage-installed multi-layered soft deposits are performed to examine the applicability of proposed back-analysis method.

• IE interfaces
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• v.9 no.1
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• pp.53-62
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• 1996

The Delphi method is widely used for long and middle range forecasting in management science. It is a method by which the subjective data of experts are made to converge using statistical analysis. The Fuzzy Delphi Method(F.D.M.), anew application of the Delphi method using Triangular Fuzzy Numbers(T.F.N.), can help to predict the uncertainty, synthesize the opinion and calculation of those assumed dissemblance index and fuzzy distance. Furthermore, the programming of the F.D.M. process to feed paper and data back to experts can make them more accurately predict the various information.

• Proceedings of the KIEE Conference
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• 2001.10a
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• pp.116-118
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• 2001

This paper deals with characteristic analysis of a slotless PM linear motor using analytical method. In order to calculate voltage equations, back-EMF waveform and winding inductance are caculated by PM's magnetic field and winding's magnetic field respectively.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.1
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• pp.1-6
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• 2017

Recently, many motor analysis methods have been developed and studied. Among these methods, the finite element method(FEM) and the analytic method are most popular in field engineers because of the accuracy of FEM and the convenience and rapid analysis time of the analytic method. Contrary, the finite element method has a weakness in calculation time and it is not easy to obtain the instantaneous characteristics value of motor with the analytic method. In this paper, the authors proposes a novel method for calculating the instantaneous characteristics of motors with the magnetic slot equivalent circuit.

• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.203-205
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• 2003

This paper is proposed a newly developed approach to identify the mechanical speed of an induction motor based on artificial neural networks technique. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.9
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• pp.38-44
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• 2008

Light guide plate is one of most important components which are composed of back light unit, affecting the quality and performance of LCD. Average brightness and uniformity are especially key factors for designing the light guide unit. These qualities are affected and controlled by the pattern being attached to the back of light guide unit. In order to obtain high brightness and uniformity the optimized pattern design is adopted for LGP. In this study, optimized molding condition for LGP with 0.4 mm thickness was obtained by using the Moldflow simulation software and the optimized pattern for better brightness uniformity was designed for the thickness of the 0.4 mm by trial and error method. The brightness was measured for the different LGP thicknesses and the residual stress analysis was performed for 0.4 mmthickness by the photoelasticity and the results are compared with 0.5 mm, 0.6 mm thickness.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.656-659
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• 2000

Recently, the skeleton type 2-phase brushless DC motor has been used in electric home appliance for low price and low energy consumption. In this paper, we analyzed a skeleton type 2-phase BLDC motor using time-step finite element method. And the validity of analysis is confirmed by measuring the flux distribution on the surface of permanent magnet and back-EMF. As well, we have calculated the dynamic characteristics of target motor considering the Hall sensor position. So, we have found the optimum switching position, and improved efficiency of 2-phase BLDC motor.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.545-550
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed estimation and control of speed of induction motor using ANN Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.