• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.45-49
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• 2004

A method for obtaining the power energy with high quality is to keep the power factor for a load as close to unity as feasible. In this paper, we present a new method to improve the power factor for a load. The proposed method uses fuzzy control techniques in order to determine how many parallel capacitors are to be connected to the load for the correction of the power factor.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.212-220
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• 2007

This paper proposes a method of avoiding obstacles and tracking a moving object continuously and simultaneously by using new concepts of virtual tow point and fuzzy danger factor for differential wheeled mobile robots. Since differential wheeled mobile robot has smaller degree of freedom to control and are non-holonomic systems, there exist multiple solutions (trajectories) to control and reach a target position. The paper proposes 'fuzzy danger factor' for obstacles avoidance, 'virtual tow point' to solve non-holonomic object tracking control problem for unique solution and three kinds of fuzzy logic controller. The fuzzy logic controller is policy decision controller with fuzzy danger factor to decide which controller's result is more valuable when the mobile robot is tracking a moving object with obstacles to be avoided.

• The Journal of Korean Society for Radiation Therapy
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• v.8 no.1
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• pp.149-159
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• 1996

This descriptive correlational study was undertaken in order to investigate the relationship of family support and personality with quality of life in patients receiving radiotherapy for cervix cancer and to provide basic data to help them improve a better quality of life. The subjects for this study Were 80 out-patients undergoing a radiation therapy at C university hospital in K-city, from April, 1992 to October, 1994. The data were obtained using a convenience sampling technique. The tools used for this study were Ro's quality of life scale, Kang's family support scale and Wallston & others health locus of control scale. The collected data were analyzed by the SAS program using percentage, mean, standard deviation, pearson's correlation coefficients. The result were as follows : 1. The total average score of the quality of life of the subjects was 138.95(minimum score 121-maximum score 164), item mean score(range 1-5) was 2.95. The total average score of the family support of the subjects was 32.55 (minimum score 16-maximum score 47), item mean score(range 1-5) was 2.95 The total average score of the health locus of control of the subjects was 37.00 (minimum score 24-maximum score 49), item mean score (range 1-6) was 3.36. 2 The results of the analysis of the relationship between the quality of life scale and the health locus of control were as follows : the total average score in the quality of life of internal locus of control scale was 136.97, the total average score in the quality of life of external locus of control scale was 144.90. 3. There was a significant positive correlation between the health locus of control and the quality of life(r = 0.2927, p<0.01). The result of the analysis of the relationship between the each factor in the quality of life and health locus of control were as follows : There were significant differences between the health locus of control and emotional state factor(r=0.1514, p<0.01), economic life factor(r=0.2560, p<0.05), self-esteem factor(r=0.2289, p<0.05), physical state and function factor(r=0.1455, p<0.05), relationship with neighbors factor(r=0.0754, p<0.05), relationship with family factor (r=0.3324, p<0.01). 4. There was a significant positive correlation between the family support and the quality of life(r=0.459, p<0.001). The result of the analysis of the relationship between the each factor in the quality of life and family support were as follows : there were significant differences between family support and emotional state factor (r=0.3891, p<0.01), self-esteem factor(r=0.2661, p<0.05), relationship with family factor (r=0.4353, p<0.001).

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.210-213
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• 2001

This study presents an effective variable forgetting factor method based on fuzzy logic to suppress frequency droop in extended integral load frequency control. The performance of the extended integral control is greatly dependent on the decaying factor. For an optimal or near optimal performance, it is necessary that the decaying factor as well as the feedback gains should be changed very quickly in response to changes in the system dynamics. However, because of its time-varing characteristic, the optimal decaying factor is difficult to be selected analytically. By adopting fuzzy set theory, the decaying factor can be determined quickly to respond to the variation of the feedback signals. This study builds a fuzzy rule base with use of the change of frequency and its rate as inputs. The computer simulation has been conducted for the single machine system. The simulation results show that the proposed fuzzy 1o81c based controller yields more improved control performance than the conventional PI controller.

• Journal of the Korea Safety Management & Science
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• v.8 no.1
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• pp.17-26
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• 2006

Basis frame-work's base in a semiconductor industry have gas, chemical, electricity and various facilities in bring to it. That it is a foundation by fire, power failure, blast, spill of toxicant huge by large size accident human and physical loss and damage because it can bring this efficient, connect with each kind mechanical, physical thing to prevent usefully need that control finding achievement factor of human factor of human action. Large size accident in a semiconductor industry to machine and human and it is involved that present, in system by safety interlock defect of machine is conclusion for error of behaviour. What is not construing in this study, do safety in a semiconductor industry to do improvement. Control human error analyzes in human control with and considers mechanical element and several elements. Also, apply achievement factor using O'conner Model by control method of human error. In analyze by failure mode effect using actuality example.

• Physical Therapy Korea
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• v.3 no.3
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• pp.82-91
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• 1996

Normal balance is defined as state in which the body is equlilibrium. It is complex motor control task, requring integration of sensory information, neural processing, and biomechanical factors. There are major two factors contribute to balance control, the neurological and the musculoskeletal. The neurological factor provides the sensory processing and motor output mechanisms that are the neurophysiological basis for response. The musculoskeletal factor provides the mechanical structure for response. When all components of two factors are operating effectively, the postural response should be appropriate and effective for good balance control. Therfore, balance can be influenced by above all factors. In addition, balance can be also influenced by muscle tone, hearing, physiological factors, and environmental factors. Physical therapists must understand factors of balance control so that we can accurately assess balance. Therefore, physical therapists have to develop useful balance measurement tools to evaluate balance.

• Journal of Power Electronics
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• v.3 no.3
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• pp.175-184
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• 2003

In this paper, a new control scheme of Class-E inverter for reducing the crest factor of electronic ballasts for fluorescent lamps using Pulse-Frequency-Modulation (PFM) is Introduced The lifetime of the lamps is guaranteed by decreasing the lamp crest factor and also voltage stress of the switch is significantly decreased by a new scheme although conventional Class-E Inverter is used In this paper. The proposed PFM control scheme didn't use any auxiliary circuit. The proposed control strategy is executed by feeding back the Input voltage, and the zero-voltage-switching (ZVS) is ensured by maintaining constant turn-off time of the switch Therefore, the control principles of proposed method are explained in detail and its validity is verified through several simulations and experimental results.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1122-1130
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• 2016

This paper presents a novel approach for achieving both a tight DC voltage regulation and a power factor control by applying the Reaching Law Sliding Mode Control (RL-SMC) and the conventional Sliding Mode Control (SMC). Applying these strategies on a matrix rectifier (MR) can achieve a unity grid side power factor when the DC load changes widely and it can provide a ripple-free output voltage that is easily affected by distortions of the three-phase ac voltage supply. Furthermore, by employing the reaching law on the SMC can solve the chatting problem of the sliding motion. Comparative Matlab simulations and experimental verifications for these strategies have been presented and discussed in this paper. The results show that by applying the SMC and RL-SMC on a MR can achieve a unity grid side power factor and a regulated ripple-free DC output.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1107-1111
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• 2004

As an information technology is developed, more intelligent system considering emotional factor for implementing the personality is required. In this paper, Reactive Learning Inference System considering emotional factor is proposed. Emotional Facter(E) is defined for a criterion for representing the personal preference. This system is designed to have functions of Reactive filtering by Emotional factor, Incremental learning, perception & inference and knowledge retrieval. This system is applied to the area for analysis of customer's tastes and its performance is analyzed and compared.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.231-238
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• 2023

For boost PFC (Power Factor Correction) converters, various control methods are being studied to achieve unity power factor and low THD (Total Harmonic Distortion) of AC input current. Among them, average current mode control, which controls the average value of the inductor current to follow the current reference, is the most widely used. However, nowadays, as advanced digital control becomes possible with the development of digital processors, predictive control of boost PFC converters is receiving attention. Predictive control is classified into predictive current mode control, which generates duty in advance using a predictive algorithm, and model predictive current control, which performs switching operations by selecting a cost function based on a model. Therefore, this paper simply explains the average current mode control, predictive current mode control, and model predictive current control of the boost PFC converter. In addition, current control under entire load and disturbance conditions is compared and analyzed through simulation.