• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.33-40
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• 2009

This paper presents the high performance control of interior permanent magnet synchronous motor(IPMSM) using space vector(SV) PWM method based on hybrid artificial intelligent(HAI) controller. The HAI controller combines the advantages between adaptive fuzzy control and neural network The SV PWM method is applied to a speed control system of motor in the industry field until now and is feasible to improve harmonic rate of output current, switching frequency and response characteristics. This HAI controller is used instead of conventional PI controller in order to solve problems happening when calculating a reference voltage. The HAI controller improves speed performance by hybrid combination of reference model-based adaptive mechanism method, fuzzy control and neural network. This paper analyzes response characteristics of parameter variation, steady-state and transient-state using proposed HAI controller and this controller compares with conventional fuzzy neural network(FNN) and PI controller. Also, this paper proves validity of HAI controller.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.43-52
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• 2018

This paper presents the performance of a Phase Shift Full Bridge (PSFB) converter with inductive load and a new current control scheme to improve dynamic response of output current with various inductive loads. Enhanced dynamic model is used which includes leakage inductance and inductive load. Effect of changing of inductive load was analyzed in detail. Proposed current control scheme is designed based on phase margin specifications. As a result, the proposed current control scheme helps to improve the dynamic response in comparison with the existing current control scheme. The performance of the designed controller is verified by a 500 A PSFB converter. The results will be utilized for high current applications with high inductive load such as superconducting devices.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.473-482
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• 2007

Network-based IDS(Intrusion Detection System) gathers network packet data and analyzes them into attack or normal. They raise alarm when possible intrusion happens. But they often output a large amount of low-level of incomplete alert information. Consequently, a large amount of incomplete alert information that can be unmanageable and also be mixed with false alerts can prevent intrusion response systems and security administrator from adequately understanding and analyzing the state of network security, and initiating appropriate response in a timely fashion. So it is important for the security administrator to reduce the redundancy of alerts, integrate and correlate security alerts, construct attack scenarios and present high-level aggregated information. False alarm rate is the ratio between the number of normal connections that are incorrectly misclassified as attacks and the total number of normal connections. In this paper we propose a false alarm classification model to reduce the false alarm rate using classification analysis of data mining techniques. The proposed model can classify the alarms from the intrusion detection systems into false alert or true attack. Our approach is useful to reduce false alerts and to improve the detection rate of network-based intrusion detection systems.

• Journal of Advanced Navigation Technology
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• v.20 no.1
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• pp.79-85
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• 2016

Network traffic is increased rapidly, due to mobile and social network, such as smartphones and facebook, in recent web environment. In this paper, we improved web response time of existing system using direct buffer of NIO and DMA. This solved the disadvantage of JAVA, such as CPU performance reduction due to the blocking of I/O, garbage collection of buffer. Key values circulated many data due to priority change put on a hash map operated easily and apply a priority modification algorithm. Large response data is separated and stored at a fast direct buffer and improved performance. This paper showed that the proposed method using NIO was much improved performance, in many test situations of cache hit and cache miss.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.344-346
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• 2018

Air pollution has become a social issue. Particularly, interest in fine dust is increasing. Various kinds of sensors are being used to measure fine dust. The most commonly used infrared detection dust sensors operate by sensing the diffraction of light through an infrared receiver and sensing the light reflected by the dust in the air. However, this method has a drawback in which accurate data analysis is difficult due to deviation caused by the noise during measurement. In order to overcome such drawbacks, in this thesis, a low pass filter algorithm of FIR(Finite Impulse Response) filter was designed and implemented.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.214-221
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• 1998

A new control approach using neural network for the robust position control of a BRUSHLESS direct drive(BLDD) motor is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust BLDD motor system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system will be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained by error back-propagation at each sample period to accommodate the possible variations in the parameters or load torque. And the state space analysis is performed to obtain the state feedback gains systematically. In addition, the robustness is also obtained without affecting overall system response.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.897-901
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• 2011

This paper presents a TS (Takagi-Sugeno) type FLC (Fuzzy Logic Controller) with only 3 rules. The choice of parameters of FLC is very difficult job on design FLC controller. Therefore, the choice of appropriate linguistic variable is an important part of the design of fuzzy controller. However, since fuzzy controller is nonlinear, it is difficult to analyze mathematically the affection of the linguistic variable. So this choice is depend on the expert's experience and trial and error method. In the design of the system, we use a variety of response characteristics like stability, rising time, overshoot, settling time, steady-state error. In particular, it is important for a stable system design to predict the steady-state error because the system's steady-state response of the system is related to the overall quality. In this paper, we propose the method to choose the consequence linear equation's parameter of T-S type FLC in the view of steady-state error. The parameters of consequence linear equations of FLC are tuned according to the system error that is the input of FLC. The full equation of T-S type FLC is presented and using this equation, the relation between output and parameters can represented. As well as the FLC parameters of consequence linear equations affect the stability of the system, it also affects the steady-state error. In this study, The system according to the parameter of consequence linear equations of FLC predict the steady-state error and the method to remove the system's steady-state error is proposed using the prediction error value. The simulation is carried out to determine the usefulness of the proposed method.

• The Journal of Korean Association of Computer Education
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• v.3 no.2
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• pp.31-37
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• 2000

We developed a test bank system which dynamically adjusts to students' achievement levels. In order to dynamically calculate the student's achievement level, our system uses the question-response theory which is usually adopted to CAT. The system proposes appropriate questions depending on the students' achievement levels so that they can do self-directed and individualized learning. The system consists of pre-test, main learning, and review stages. In the pre-test stage, the intellectual level of the student is examined to determine the starting point in the main stage. In the main learning stage, individualized learning is performed. Finally, a review session is added to re-examine the questions that the student gave wrong answers. The output from the learning process of the system is not the usual test scores but the level of the student's intellectual ability which is produced through the question-response theory. The intellectual ability level index objectively measures the degree of improvement of the student's learning ability.

• KIEAE Journal
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• v.7 no.4
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• pp.147-152
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• 2007

Numerous non-destructive tests(NDT) to assess the safety of real structures have been developed. System identification(SI) techniques using dynamic responses and behaviors of structural systems become an outstanding issue of researchers. However the conventional SI techniques are identified to be non-practical to the complex and tall buildings, due to limitation of the availability of an accurate data that is magnitude or location of external loads. In most SI approaches, the information on input loading and output responses must be known. In many cases, measuring the input information may take most of the resources, and it is very difficult to accurately measure the input information during actual vibrations of practical importance, e.g., earthquakes, winds, micro seismic tremors, and mechanical vibration. However, the desirability and application potential of SI to real structures could be highly improved if an algorithm is available that can estimate structural parameters based on the response data alone without the input information. Thus a technique to estimate structural properties of building without input measurement data and using limited response is essential in structural health monitoring. In this study, shaking table tests on three-story plane frame steel structures were performed. Out-put only model analysis on the measured data was performed, and the dynamic properties were inverse analyzed using least square method in time domain. In results damage detection was performed in each member level, which was performed at story level in conventional SI techniques of frequency domain.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.47-58
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• 2011

MTI filter is used to separate target signal from clutter in many radar signal processing. By suppressing clutter before CFAR detection, the detection performance can be improved. As a radar system designed, a design engineer generally takes averaged SNR and CNR into account and does not include the effect of MTI filter's frequency response. In practice, when the signals including clutter are pass through the filter, SNR is widely varying according to target velocity and CNR is also varying according to clutter center frequency and spectrum spreading. In this paper, we have derived the relationship between the MTI filter's frequency response and a target's velocity and a clutter's spectrum characteristics. With the variation of SNR and CNR at the filter output, the detection performance of CFAR has been analyzed by the simulation and has made certain of their influences on the performance.