• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.132-143
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• 2017

While working in an industrial environment which requires extended periods of upright posture; workers tend to develop muscle fatigue due to the constant load on lower-limb muscles. In addition, when working while bending knees; muscle fatigue of lower back and hamstrings is increased due to the abnormal posture. This can lead to damage of muscles, induce musculoskeletal disorders, and reduce long-term working efficiency. Recent medical studies have shown that long-term working in an upright posture can induce musculoskeletal disorders such as foot fatigue, edema, pain and varicose veins. Likewise, medical and rehabilitation expenses have grown due to the increase in musculoskeletal conditions suffered by workers. For this problem, we aim to develop a device that can reduce the physical fatigue on the lower limbs by supporting the weight of workers during the extended periods of upright and bending postures in the industrial environments. In this paper, we have designed and manufactured a wearable weight support system; with a user intention algorithm that the users can maintain various postures. For validation of the developed system, we measured the muscle activity of the users wearing the system with EMG sensors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.451-459
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• 2007

RFID it reads information which is it writes, the semiconductor chip for and the radio frequency system which uses the hazard antenna it has built-in transmission of information it talks. Formation which is transmitted like this collection and America which it filtrates wey the RFID search service back to inform the location of the server which has commodity information which relates with an object past record server. The hazard where measurement analysis result the leader for electronic interference does not occur consequently together from with verification test the power level which is received from the antenna grade where it stands must maintain minimum -55dBm and the electronic interference will not occur with the fact that, antenna and reel his recognition distance the maximum 7m until the recognition which is possible but smooth hazard it must stand and and with the fact that it will do from within and and and 3-4m it must be used Jig it is thought.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.33-40
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• 2003

Criticality prediction models that determine whether a design entity is fault-prone or non fault-prone play an important role in reducing system development costs because the problems in early phases largely affect the quality of the late products. Real-time systems such as telecommunication systems are so large that criticality prediction is mere important in real-time system design. The current models are based on the technique such as discriminant analysis, neural net and classification trees. These models have some problems with analyzing causes of the prediction results and low extendability. This paper builds a new prediction model, GAM, based on Genetic Algorithm. GAM is different from other models because it produces a criticality function. So GAM can be used for comparison between entities by criticality. GAM is implemented and compared with a well-known prediction model, BackPropagation neural network Model(BPM), considering Internal characteristics and accuracy of prediction.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.23-30
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• 2007

RFID it reads information which is it writes, the semiconductor chip for and the radio frequency system which uses the hazard antenna it has built-in transmission of information it talks. Formation which is transmitted like this collection and America which it filtrates wey the RFID search service back to inform the location of the server which has commodity information which relates with an object past record server. The hazard where measurement analysis result the leader for electronic interference does not occur consequently together from with verification test the power level which is received from the antenna grade where it stands must maintain minimum -55dBm and the electronic interference will not occur with the fact that, antenna and reel his recognition distance the maximum 7m until the recognition which is possible but smooth hazard it must stand and and with the fact that it will do from within and and and 3-4m it must be used Jig it is thought.

• Journal of Sensor Science and Technology
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• v.12 no.6
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• pp.289-297
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• 2003

In this paper, we propose accurate classification method of an EEG signals during a mental tasks. In the experimental task, subjects achieved through the process of responding to visual stimulus, understanding the given problem, controlling hand motions, and select a key. To recognize the subjects' selection time, we analyzed with 4 types feature from the filtered brain waves at frequency bands of $\alpha$, $\beta$, $\theta$, $\gamma$ waves. From the analysed features, we construct specific rules for each subject meta rules including common factors in all subjects. In this system, the architecture of the neural network is a three layered feedforward networks with one hidden layer which implements the error back propagation learning algorithm. Applying the algorithms to 4 subjects show 87% classification success rates. In this paper, the proposed detection method can be a basic technology for brain-computer-interface by combining with discrimination methods.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.1
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• pp.45-52
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• 2003

A number of stress corrosion cracks in turbine rotor disk keyway in power plants have been found and the necessity has been raised to detect and evaluate the cracks prior to the catastrophic failure of turbine disk. By ultrasonic RF signal analysis and using a neural network based on bark-propagation algorithm, we tried to evaluate the location, size and orientation of cracks around keyway. Because RF signals received from each reflector have a number of peaks, they were processed to have a single peak for each reflector. Using the processed RF signals, scan data that contain the information on the position of transducer and the arrival time of reflected waves from each reflector were obtained. The time difference between each reflector and the position of transducer extracted from the scan data were then applied to the back-propagation neural network. As a result, the neural network was found useful to evaluate the location, size and orientation of cracks initiated from keyway.

• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.455-471
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• 2013

Active sonar has been commonly used to detect targets existing in the shallow water. When a signal is transmitted and returned back from a target, it has been distorted by various properties of acoustic channel such as multipath arrivals, scattering from rough sea surface and ocean bottom, and refraction by sound speed structure, which makes target detection difficult. It is therefore necessary to consider these channel properties in the target signal simulation in operational performance system of active sonar. In this paper, a monostatic active sonar system is considered, and the target echo, reverberation, and ambient noise are individually simulated as a function of time, and finally summed to simulate a total received signal. A 3-dimensional highlight model, which can reflect the target features including the shape, position, and azimuthal and elevation angles, has been applied to each multipath pair between source and target to simulate the target echo signal. The results are finally compared to those obtained by the algorithm in which only direct path is considered in target signal simulation.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.171-181
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• 2012

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.

• Journal of Biomedical Engineering Research
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• v.18 no.1
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• pp.25-36
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• 1997

To regulate cardiac output of the Total Artificial Heart(TAH) physiologically, the hemodynamic information must be toed back to the controller. So far, our group has developed an automatic cardiac output control algorithm using the motor current waveform, It is, however difficult to detect the preload level such as a filling status of ventricular inflow and the variation of atrial pressures within normal physiologic range(0-15 mmHg) by analyzing the motor current which simultaneously reflects the afterload effect. On the other hin4 the interventricular volume pressure(IVP) which is not influenced by arterload but by preload is a good information source for the estimation of preload states. In order to find the relationship between preload and IVP waveform, we set up the artificial heart system on the Donovan type mock circulatory system and measured the IVP waveform, right and left atrial pressures, inflow and outflow waveforms and the signals represented the information of moving actuator's position. We shows the feasibility of estimating the hemodynamic changes of inflow by using IVP waveform. fife found that the negative peak value of IVP waveform is linearly related to atrial pressures. And we also found that we could use the time to reach the negative peak in IVP waveform, the time to open outflow valve, the area enclosed IVP waveform as unfu parameters to estimate blood filling volume of diastole ventricle. The suggested method has advantages of avoiding thrombogenesis, bacterial niche formation and increasing longterm reliability of sensor by avoiding direct contact to blood.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.3
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• pp.53-61
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• 2006

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 nile 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 error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy-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.