• Asian Oncology Nursing
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• v.3 no.2
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• pp.103-111
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• 2003

The purpose of this study was to identify the effect of imagery therapy on "coping mechanism and type C personality of the women with mastectomy. To achieve this purpose, 2 hours sessions of imagery therapy were given to the patients with breast cancer twice a week for 6 weeks. The period of data collection was from July, 7th to August, 12th 2002. The participants were 30 patients, 15 experimental group, 15 control group who were treated at the G University hospital in J City. This study was designed using a quasi-experimental approach with non-equivalent Pre test-Post test Design. The themes for the Imagery Therapy Program were composed of Leuner's(1969) 12 Imagery Themes: flower, green-field, stream, mountain, house, woods, significant figures, rose, lion, ideal self-image, cave and volcano. The data were analyzed with ${\chi}2-test$ and MANOVA using the SPSS program. The course of image change of the 12 imagery themes was analyzed by content analysis. The results of this study are as follows: First Hypothesis, 'The score of type C personality in the women with mastectomy who received imagery therapy will be significantly lower than that of the control group' was supported(p<.05). Second Hypothesis, 'The score of coping mechanism' in the women with mastectomy who received imagery therapy will be significantly higher than that of the control group' was rejected. In conclusion, imagery therapy is suggested as an effective nursing intervention to change type C personality of the women with mastectomy, but not effective to improve coping mechanism. Therefore, the program for the women with mastectomy should be developed to change their coping mechanism, method of problem solving and Quality of life.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.3
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• pp.303-311
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• 2013

This research deals with the analysis and design of a driving mechanism for an automatic pneumatic drug injector, which can precisely control the injection volume using a relatively simple friction-driven mechanism, without any complicated control system. Through a dynamic analysis, the effects of the design parameters of the driving mechanism associated with the geometry, spring stiffness, and fiction are analyzed, and the results are reflected in a proto-type drug injector design, which is under development for mass production. A test is performed to assess the durability of the mechanism for up to one million operations, and comparison of its displacement after one million operations, verifies the mechanism's durability.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.3
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• pp.215-223
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• 2002

This paper investigates the adaptive control of a fuzzy logic based speed and flux controller fur a vector controlled induction motor drive. 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 model reference adaptive control(MRAC) fuzzy controller is evaluated by simulation for various operating conditions. The validity of the Proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system.

• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.697-726
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• 1999

In this paper we develop a now procedure to control stepsize for linear multistep methods applied to semi-explicit index 1 differential-algebraic equations. in contrast to the standard approach the error control mechanism presented here is based on monitoring and contolling both the local and global errors of multistep formulas. As a result such methods with the local-global stepsize control solve differential-algebraic equation with any prescribed accuracy (up to round-off errors). For implicit multistep methods we give the minimum number of both full and modified Newton iterations allowing the iterative approxima-tions to be correctly used in the procedure of the local-global stepsize control. We also discuss validity of simple iterations for high accuracy solving differential-algebraic equations. Numerical tests support the the-oretical results of the paper.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.1
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• pp.133-140
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• 2012

In this study, a reliable control scheme with PID combined controller will be considered. The combined controller in this study is PID algorithm with parameters tuned by using ILC (iterative learning control) approach. The controller was applied to the vibration isolator using an induction motor which works as an actuator. This isolator is developed to eliminate the influence of vibration from rotating machineries on the small ship. The NI cRIO real time controller with FPGA is loaded to get or generate control signals. Crank mechanism which converts rotating energy into translational force is adopted and the relation between control force and torque generated from actuator is also analyzed. A Labview program is composed for controlling practice. Experimental results will be described to show the effectiveness of the proposed control schemes.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1823-1833
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• 2006

An immune algorithm is a kind of evolutional computation strategies, which is developed in the basis of a real immune mechanism in the human body. Recently, scientific or engineering applications using this scheme are remarkably increased due to its significant ability in terms of adaptation and robustness for external disturbances. Particularly, this algorithm is efficient to search optimal parameters against complicated dynamic systems with uncertainty and perturbation. In this paper, we investigate an immune algorithm embedded Proportional Integral Derivate (called I-PID) control, in which an optimal parameter vector of the controller is determined offline by using a cell-mediated immune response of the immunized mechanism. For evaluation, we apply the proposed control to mitigation of vibrations for nonlinear structural systems, cased by external environment load such as winds and earthquakes. Comparing to traditional controls under same simulation scenarios, we demonstrate the innovation control is superior especially in robustness aspect.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.98-104
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• 2000

One of the main features of ABR service is the employment of a rate-based flow control mechanism, and congestion control plays an important role in the effective and stable operation of ATM networks Feedback from the network switches to the end system gives users the information necessary to adjust transmission rates appropriately according to the current networks load. Congestion controls by feedback mechanism are classified as EFCI and ER mode. We analyze the performance of EFCI and ER and propose a new ABR traffic control strategy by integrating EFCI and ER modes to improve the traditional traffic control. Through the distributed simulation. the performance improved by the proposed control strategy is analyzed.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.501-503
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• 2005

The improvement of load following operation of the thermal power plant is influenced to the electrical quality. Analysis of boiler, turbine, and governor system, and the study of control algorithm are preceded. The thermal power plant is operated by various control systems. In the case of faulty governor system, it takes long days to solve the problem and impossible to repair the mechanism without outage. A non-planned out-age is taken into consideration because of economical power production. In this paper, to clear the continuous swings of an old turbine governor system(YEOSU #1), the trend, the control logic, and the hydraulic mechanism are analyzed, and then the control circuit with ADAPT function and the 1st order lag circuit are inserted and modified. After that, the power plant comes to automatic governor control operation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11A
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• pp.867-875
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• 2003

Current end-to-end congestion control depends only on the information of end points (using three duplicate ACK packets) and generally responds slowly to the network congestion. This mechanism can't avoid TCP global synchronization in which TCP congestion window size is fluctuated during congestion period. Furthermore, if RTT(Round Trip Time) is increased, three duplicate ACK packets are not correct congestion signals because congestion might already disappear and the host may send more packets until it receives three duplicate ACK packets. Recently there are increasing interests in solving end-to-end congestion control using AQM(Active Queue Management) to improve the performance of TCP protocols. AQM is a variation of RED-based congestion control. In this paper, we first evaluate the effectiveness of the current AQM schemes such as RED, CHOKe, ARED, FRED and SRED, over traffic with different rates and over traffic with mixed responsive and non-responsive flows, respectively. In particular, CHOKe mechanism shows greater unfairness, especially when more unresponsive flows exist in a shared link. We then propose a new AQM scheme using CHOKe mechanism, called DQC(Double Queue CHOKe), which uses two FIFO queues before applying CHOKe mechanism to adaptive congestion control. Simulation shows that it works well in protecting congestion-sensitive flows from congestion-causing flows and exhibits better performances than other AQM schemes. Also we use partial state information, proposed in LRURED, to improve our mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1478-1481
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• 2005

As the model of most practical system cannot be obtained, the practice of typical control method is limited. Accordingly, numerous artificial intelligence control methods have been used widely. Fuzzy control and neural network control have been an important point in the developing process of the field. This paper is proposed adaptive fuzzy-neural network based on the vector controlled interior permanent magnet synchronous motor drive system. The fuzzy-neural network is first utilized for the speed control. A model reference adaptive scheme is then proposed in which the adaptation mechanism is executed using fuzzy-neural network. Also, this paper is proposed estimation of speed of interior permanent magnet synchronous motor using artificial neural network 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 analysis results to verify the effectiveness of the new method.