• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.380-388
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• 2004

This study proposed an improved spike detection algorithm which automatically detects suitable spike threshold on the amplitude of surface electromyography(SEMG) signal during isometric contraction. The EMG data from the low back muscles was obtained in six channels and the proposed signal processing algorithm is compared with the median frequency and Gabriel's spike parameter. As a result, the reliability of spike parameter was inferior to the median frequency. This fact indicates that a spike parameter is inadequate for analysis of multi-channel EMG signal. Because of uncertainty of fixed spike threshold, the improved spike detection algorithm was proposed. It automatically detects suitable spike threshold depending on the amplitude of the EMG signal, and the proposed algorithm was able to detect optimal threshold based on mCFAR(modified Constant False Alarm Rate) in the every EMG channel. In conclusion, from the reliability points of view, neither median frequency nor existing spike detection algorithm was superior to the proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1003-1010
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• 2013

In this paper, TCP/IP based Machine-to-Machine (M2M) communication uses CDMA/GSM network for data communication. This communication method is widely used by offshore moored buoy for data transmission back to the system server. Due to weather and signal coverage, the TCP/IP M2M communication often experiences transmission failure and causing data losses in the server. Data losses are undesired especially for meteorological and oceanographic analysis. This paper discusses a software approach to minimize M2M data losses by handling transmission failure and re-attempt which meant to transmit the data for recovery. This implementation was tested for its performance on a meteorological buoy placed offshore.

• Journal of the Korean Home Economics Association
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• v.34 no.3
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• pp.219-232
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• 1996

This study is intended to find changing of upper body shape according to the increase of age of elderly women, to extract the factors which form the upper body shapes and to classify the upper body shapes and grasp the characteristics of each body type. The subject were 225 elderly women aged 55-79 years old. Data were analyzed by the multivariate method, especially factor and cluster analysis. The results are as follows: 1. The items of stature, weight and width and circumference of upper body decreased according to the increase of age. And, in the length items except the side neck point - the nipple point length decreased significantly. There were significant difference of upper body shape between age groups according to each group. 2. The shape of elderly women's upper body is determined the main 6 factors(the obesity of upper body, the shape of shoulder, the length of back side of upper body, the length of front side of upper body and the size of vertical direction between stature and arm and front neck width). 3. Elderly women have 4 types of upper body shapes, which are distributed evenly. The body type of Elderly woman changes from long and fat type to small and slim, type according to the increase of age.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.315-320
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• 2005

This paper is proposed adaptive fuzzy-neuro controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of nor measured between the motor speed and output of a reference model. The control performance of the adaptive fuzy-neuro controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.183-188
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• 2002

The forecast of a container traffic has been very important for port and development. Generally, Statistic methods, such as moving average method, exponential smoothing, and regression analysis have been much used for traffic forecasting. But, considering various factors related to the port affect the forecasting of container volume, neural network of parallel processing system can be effective to forecast container volume based on various factors. This study discusses the forecasting of volume by using the neural, network with back propagation learning algorithm. Affected factors are selected based on impact vector on neural network, and these selected factors are used to forecast container volume. The proposed the forecasting algorithm using neural network was compared to the statistic methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.6
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• pp.981-987
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• 2017

In this paper, we describe the LPM structure with a two-phase, which is not used previously, and explain its operation principle. In order to predict the accurate performance of LPM reduction model, finite element model was derived and the back EMF of LPM reduction model was measured and compared. In order to investigate the thrust and normal force of the LPM reduction model, a driving circuit capable of applying two-phase pulse currents was constructed and the performance was predicted in conjunction with the finite element analysis model. Finally, the design considering actual LPM size was performed. Since the size of the reduction model is small, the field could be made of a permanent magnet. However, it is almost impossible to manufacture a permanent magnet to match the size and capacity of a real LPM for a vehicle, in terms of cost and writing. Therefore, the actual vehicle LPM was replaced by wound type that generates a magnetic field by applying current to the field winding, and the final model was derived using the reaction surface method.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Journal of The Korea Institute of Healthcare Architecture
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• v.11 no.1
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• pp.33-41
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• 2005

The construction can proceed in different ways according to the acquired profitability of the hospital during the construction and to the features of departments or areas. This study is an analysis of remodeling construction processes to resolve major tasks of remodeling. The remodeling strategies gained from this study can be summed up as follows: 1) Remodeling work in hospitals involves the acquire relocation of space through extensive area renovations and then moving back to the space, and lastly working on the empty space. Thus, it is more advantageous in terms of construction work to demolish the existing buildings than to acquire the relocation space through extensions or renovations. That is, demolition after the maximum utilization of the existing buildings is the most desirable in terms of space availability. 2) The construction methods for remodeling are two: a method of carrying out construction by dividing the plane areas into several individual ones and of working on it floor by floor. In case of ward areas, and the outpatient area, the construction proceeds after securing the relocation space and partially setting construction areas in order to minimize the decrease in profitability due to the smaller number of beds and treatment rooms during construction. If the outpatient diagnosis/ treatment area and the supply area relocate together with the ward areas, there may be extra expenses. Thus, doing construction by area, while partially operating those areas or after relocating the whole areas.

• Journal of Soil and Groundwater Environment
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• v.19 no.1
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• pp.26-33
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• 2014

Uncertainty associated with a sampling method is very high in evaluating the degree of site contamination; therefore, such uncertainty affects the reliability of precise investigation and remediation verification. In particular, in evaluating a site for a small-sized filling station, underground utilities, such as connection pipes and oil storage tanks, make grid-unit sampling impossible and the resulting increase in uncertainty is inevitable. Accordingly, this study quantified the uncertainty related to the evaluation of the degree of contamination by total petroleum hydrocarbon and by benzene, toluene, ethylene, and xylene. When planning a grid aimed at detecting a hot spot, major factors that influence the increase in uncertainty include grid interval and the size and shape of the hot spot. The current guideline for soil sampling prescribes that the grid interval increase in proportion to the area of the evaluated site, but this heightens the possibility that a hot spot will not be detected. In evaluating a site, therefore, it is crucial to estimate the size and shape of the hot spot in advance and to establish a sampling plan considering a diversity of scenarios.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.834-839
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• 2004

In this paper, we have studied on the active vibration control of an automotive roof in passenger car's structure using piezoelectric material as the actuator and sensor attached on the surface of the automotive roof, As a control algorithm, negative velocity feedback control method is used in the study and the position of the sensor is almost attached on the nearest position of maximum normal stresses occurring while the roof is vibrating due to disturbance or exciting, Also, the actuator is attached on the other side mostly collocated to the sensor. The optimum positions have the maximum stresses of the roof which have been found in the result of the finite element analysis using Nastran software, As the fundamental experiments, a beam and plate have also been implemented to verify the performance of vibration suppression. Finally the experiment of the roof has been carried out and The roof experiment has just given a possibility to an active vibration control of the automotive structure still not applied for passenger cars.