• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1363-1373
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• 2014

In this study, a hybrid multi-cup electric cupping system (HMECS) was proposed, based on the ancient cupping method. HMECS consisted of several cups that could be used simultaneously to treat different areas of the patient's body. Each cup was equipped with its own pump and pressure-monitoring system. Moreover, the vacuum pressure of the cups was controlled using fuzzy logic. Through automated control of the vacuum pressure, long-term relief of muscle tightness was achieved. To develop a scientific foundation for this alternative treatment, we compared the VAS(Visual Analog Scale) and ODI(Oswestry Disability Index) scores from conventional basic cupping to the VAS and ODI scores for our proposed HMECS. The improvement rate in the VAS and ODI scores using HMECS after three treatments was higher than that achieved by basic cupping. These results, combined with the convenience offered by enhanced IT capabilities, should increase the popularity of this device among an aging society, and facilitate the opportunity to further explore the potential of Oriental medical practices.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.89-93
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• 2002

This paper introduces a vision-based on-line fabric inspection methodology of woven textile fabrics. Current procedure for determination of fabric defects in the textile industry is performed by human in the off-line stage. The advantage of the on-line inspection system is not only defect detection and identification, but also 벼ality improvement by a feedback control loop to adjust set-points. The proposed inspection system consists of hardware and software components. The hardware components consist of CCD array cameras, a frame grabber and appropriate illumination. The software routines capitalize upon vertical and horizontal scanning algorithms characteristic of a particular deflect. The signal to noise ratio (SNR) calculation based on the results of the wavelet transform is performed to measure any deflects. The defect declaration is carried out employing SNR and scanning methods. Test results from different types of defect and different style of fabric demonstrate the effectiveness of the proposed inspection system.

• Journal of IKEEE
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• v.23 no.2
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• pp.716-721
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• 2019

A novel switching differentiator-based backstepping controller for uncertain pure-feedback nonlinear systems is proposed. Using asymptotically convergent switching differentiator, time-derivatives of the virtual controls are directly estimated in every backstepping design steps. As a result, the control law has an extremely simple form and asymptotical stability of the tracking error is guaranteed regardless of parametric or unstructured uncertainties and unmatched disturbances in the considered system. It is required no universal approximators such as neural networks or fuzzy logic systems that are adaptively tuned online to cope with system uncertainties. Simulation results show the simplicity and performance of the proposed controller.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.12
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• pp.1220-1226
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• 2012

This paper proposes a novel type of tactile device utilizing magnetorheological(MR) fluid which can be applicable for haptic master of minimally invasive surgery(MIS) robotic system. The salient feature of the controllability of rheological properties by the intensity of the magnetic field(or current) makes this potential candidate of the tactile device. As a first step, an appropriate size of the tactile device is designed and manufactured via magnetic analysis. Secondly, in order to determine proper input magnetic field the repulsive forces of the real body parts such as hand and neck are measured. Subsequently, the repulsive forces of the tactile device are measured by dividing 5 areas. The final step of this work is to obtain desired force in real implementation. Thus, in order to demonstrate this goal a neuro-fuzzy logic is applied to get the desired repulsive force and the error between the desired and actual force is evaluated.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.233-237
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• 2012

In this paper, We propose a control system which compensate a output of a main Neual Network using a RTDNN(Recurrent Time Delayed Neural Network) with a FLC(Fuzzy Logic Controller)After a learn of main neural network, it can occur a Over shoot or Under shoot from a disturbance or a load variations. In order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. We can confirm good response characteristics of proposed neural network controller by the results of simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1595-1601
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• 2018

The biggest obstacle to the commercialization of small and medium size microgrid (MG) is the reliability and economics of MG operation and maintenance. In this paper, we propose an autonomous operation method that is implemented as an application program installed in the MG operating system in emergency situations. The proposed algorithm consists of four steps of distinction, recognition, determination and control of emergency situations that can occur in MG. A fuzzy-based situation decision algorithm has been proposed to eliminate the barriers of autonomous operation in actual emergency situation such as occurrence of bad data and communication delay. In addition, countermeasures have been suggested for cases where multiple emergency situations have occurred in combination. The proposed algorithm was tested in a 500kW actual microgrid site of a university. Through the test, the validity of the proposed method and its applicability to practical MG operation are verified.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• Smart Structures and Systems
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• v.23 no.1
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• pp.91-106
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• 2019

Adopting sloped rolling-type isolation devices underneath a raised floor system has been proved as one of the most effective approaches to mitigate seismic responses of the protected equipment installed above. However, pounding against surrounding walls or other obstructions may occur if such a base-isolated raised floor system is subjected to long-period excitation, leading to adverse effects or even more severe damage. In this study, real-time hybrid simulation (RTHS) is adopted to assess the control performance of a smart base-isolated raised floor system as it is an efficient and cost-effective experimental method. It is composed of multiple sloped rolling-type isolation devices, a rigid steel platen, four magnetorheological (MR) dampers, and protected high-tech equipment. One of the MR dampers is physically tested in the laboratory while the remainders are numerically simulated. In order to consider the effect of input excitation characteristics on the isolation performance, the smart base-isolated raised floor system is assumed to be located at the roof of a building and the ground level. Four control algorithms are designed for the MR dampers including passive-on, switching, modified switching, and fuzzy logic control. Six artificial spectrum-compatible input excitations and three slope angles of the isolation devices are considered in the RTHS. Experimental results demonstrate that the incorporation of semi-active control into a base-isolated raised floor system is effective and feasible in practice for high-tech industry.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.37-43
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• 2003

Current Internet system of the entrance exam information to the university that is depending on searching key to solve the overloaded problem in the network and DB server or other tools to support HTML edit, haven't satisfied user's wants by supplying uniformed searching system. So this thesis will establish EEIS(Entrance Examination Information System) to prevent database overload phenomena when many users request a great amount of data at the same time and improve the decrease of speed and overload problem in DB server. EEIS playa role of bridge between outside client and DB server by placing VVS(Virtual View Server) between web server and DB server. By that method this system give users several usefulness in convenience and variety by supplying realtime data searching function to user. EEIS also give inner system manager more efficiency and speed in control the management system by solving those problem. This system is design and implementation to satisfy user's desire and give them more convenience and bring up the confidence of university that adopt this system at the end.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.3
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• pp.224-232
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• 2006

The paper proposes the artificial neural network(ANN) sensorless control of induction motor drive with adaptive fuzzy logic controller(AFLC). Also, this paper proposes the speed control of induction motor using AFC and estimation of speed 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 proposed control algorithm is applied to induction motor drive system controlled AFLC and him controller. And this paper is proposed the results to verify the effectiveness of the AFLC and ANN controller.