• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1283-1289
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• 2016

Electrical energy is the essential resource for modern society. Recently, the demand for power was significantly increased. Increase of power demand has lead to a decrease in the power quality. Power quality in modern society has been an important factor that can cause a major problem throughout the home and general industry. Therefore, we need a system for preventing the power quality problems. To avoid power issues, it is important that the measurement of the power quality and initial response. In this paper, we propose real-time power quality measurement system and harmonics monitoring system. We design the system using DM240001 board include dsPIC33FJ256GP710A of microchip. This system can adapt three-phase three-wire system. And optimized the algorithm, we can measure momentary changes of the power system. In addition, designed system can measure harmonics distortion like to VTHD, ITHD and ITDD for 31th harmonics.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.95-100
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• 2004

This paper represents the development of a CLS(Control Loading System) for a target a airplane (KT-1) with mechanical linkage reversible flight control system. The system is composed of mechanical frame, controller, sensing part to measure the force from the stick, driving system generating the reaction forces. The DS1103 DSP(Digital Signal Processor) of the dSpace Corp. was used as the controller. The control algorithm of the CLS and the operational environment including monitoring software and evaluation tools are described. The evaluation of the system was conducted according to the requirement specification. The results of the test were analyzed by comparing with the actual data of the target airplane.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.11-16
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• 2014

In this paper, the two-wheels robot using a predictive controller to maintain the balance of the posture control in real time have been examined. A reaction wheel pendulum control method is adopted to maintain the balance while the bicycle robot is driving. The objective of this research was to design and implement a self-balancing algorithm using the dsPIC30F4013 embedded processor. To calculate the attitude in ARS using 2 axis gyro(roll, pitch) and 3 axis accelerometers (x, y, z). In this study, the disturbance of the posture for the asymmetrical propose to overcome the predictive controller which was a problem in the control of a remote system by introducing the two wheels of the robot controller and the linear prediction of the system controller combines the simulation was performed. Also, the robust characteristic for realizing the goal of designing a loop filter too robust controller is designed so that satisfactory stability of the control system to improve stability of the system to minimize degradation of performance was confirmed.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.79-84
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• 1996

In this paper, adaptive correlator model using backpropagation neural network based on complex multilayer perceptron is presented for suppressing interference of narrow-band of direct sequence spread spectrum receiver in CDMA mobile communication systems. Recursive least square backpropagation algorithm with backpropagation error is used for fast convergence and better performance in adaptive correlator scheme. According to signal noise ratio and transmission power ratio, computer simulation results show that bit error ratio of adaptive correlator uswing backpropagation neural network improved than that of adaptive transversal filter of direct sequence spread spectrum considering of co-channel and narrow-band interference. Bit error ratio of adaptive correlator using backpropagation neural network is reduced about $10^{-1}$ than that of adaptive transversal filter where interference versus signal ratio is 5 dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1493-1498
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• 2000

In this paper, we introduce a modified interference cancellation scheme to overcome MAI in DS-CDMA. Among ICs(Interference Cancellers), PIC(Parallel IC) requires the more complexity, and SIC(Successive IC) faces the problems of the long delay time. Most of all, the adaptive detector achieves the good BER performance using the adaptive filter conducted iteration algorithm. so it requires many iterations. To resolve the problems of them, we propose an improved adaptive detector that the received signal removed MAI through the sorting scheme and the cancellation method are fed into the adaptive filter. Because the improved input signal is fed into the adaptive filter, it has the same BER performance only using smaller iterations than the conventional adaptive detector, and the proposed detector having adaptive filter requires less complexity than the other detectors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.201-211
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• 2022

According to the recent change in the cybersecurity paradigm, research on anomaly detection methods using machine learning and deep learning techniques, which are AI implementation technologies, is increasing. In this study, a comparative study on data preprocessing techniques that can improve the anomaly detection performance of a GRU (Gated Recurrent Unit) neural network-based intrusion detection model using NGIDS-DS (Next Generation IDS Dataset), an open dataset, was conducted. In addition, in order to solve the class imbalance problem according to the ratio of normal data and attack data, the detection performance according to the oversampling ratio was compared and analyzed using the oversampling technique applied with DCGAN (Deep Convolutional Generative Adversarial Networks). As a result of the experiment, the method preprocessed using the Doc2Vec algorithm for system call feature and process execution path feature showed good performance, and in the case of oversampling performance, when DCGAN was used, improved detection performance was shown.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.6
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• pp.13-23
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• 2008

In this study, a finite element (FE) model updating method based on the hybrid genetic algorithm (HGA) is proposed to improve the grillage FE model for plate girder bridges. HGA consists of a genetic algorithm (GA) and direct search method (DS) based on a modification of Nelder & Mead's simplex optimization method (NMS). Fitness functions based on natural frequencies, mode shapes, and static deflections making use of the measurements and analytical results are also presented to apply in the proposed method. In addition, a multi-objective function has been formulated as a linear combination of fitness functions in order to simultaneously improve both stiffness and mass. The applicability of the proposed method to girder bridge structures has been verified through a numerical example on a two-span continuous grillage FE model, as well as through an experimental test on a simply supported plate girder skew bridge. In addition, the effect of measuring error is considered as random noise, and its effect is investigated by numerical simulation. Through numerical and experimental verification, it has been proven that the proposed method is feasible and effective for FE model updating on plate girder bridges.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.338-343
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• 2004

In Block Matching Algorithm (BMA), a search pattern has a very important affect on the search time and the output quality. In this paper, we propose the HDS( Half Diamond Search) pattern based on the cross center-biased distribution property of a motion vector. At lust, the 4 points in the above, below, left, and right around the search center is calculated to decide the point of the MBD (Minimum Block Distortion). And an above point of the MBD is checked to calculate the SAD. If the SAD is less than the previous MBD, this process is repeated. Otherwise, the left and right points of MBD are calculated to decide the points that have the MBD between two points. These processes are repeated to the predicted direction for motion estimation. Experiments show that the speedup improvement of the proposed algorithm can be up to 23% while maintaining similar image quality.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8A
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• pp.1291-1297
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• 2001

본 논문에서는 DS-CDMA 환경의 다중 사용자 검출에서 문제시되는 다중 접속 간섭을 제거시켜주기 위해 사용되는 간섭 제거기에 대하여 소개한다. 기존의 간섭 제거 기술 중 병렬형 간섭 제거기는 장치적으로 복잡하고, 순차적 간섭 제거기는 지연 시간이 길다는 단점을 가지고 이다. 무엇보다도, 적응형 간섭 제거기는 수렴하기 위하여 많은 반복수가 필요하다. 우리는 이러한 간섭 제거기들의 성능을 개선시키기 위해서 CMA(Constant Modulus Algorithm)을 이용한 적응형 간섭 제거기에 간섭 제거 기법을 적용시킨 새로운 간섭 제거기를 제안한다. 제안된 간섭 제거기는 적응 필터 처리후 간섭 제거 기법을 적용시키기 때문에 동일한 BER(Bit Error Rate)을 얻고자 할 때 기존의 적응형 간섭 제거기에 비해 수렴을 위한 반복수를 줄여 준다. 그리고, 적응 필터를 사용함으로써 기존의 비선형 간섭 제거기에 비해 하드웨어적인 복잡도를 줄일 수 있는 효과가 있다.