• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.28-35
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• 2010

This paper presents new Adaptive Linear Combination Structure (ADALINE) for tracking/estimating voltage-current phasor and frequency of power system. To estimate the phasors and frequency from sampled data, the algorithm assumes that orthogonal coefficients and speed of angular frequency of power system are unknown parameters. With adequate sampled data, the estimation problem can be considered as a linear weighted least squares (LMS) problem. In addition to determining the phasors (orthogonal coefficients), the procedure estimates the power system frequency. The main algorithm is verified through a computer simulation and data from field. The proposed algorithm is tested with transient and dynamic behaviors during power swing, a step change of frequency upon islanding of small generators and disconnection of load. The algorithm shows a very high accuracy, robustness, fast response time and adaptive performance over a wide range of frequency, from 10 to 2000 Hz.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.1
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• pp.115-126
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• 1999

As the processing speed of communication and computer system has been improved, high speed data processing is required to correct error of data. In this paper, decoding algorithm which is applicable to the wireless communication system is proposed and encoder and decoder are designed by using the proposed decoding algorithm. We design the encoder and decoder by using the VHDL(VHSIC Hardware Description Language) and simulate the designed encoder and decoder by using V-system. Designed algorithm is synthesized by using synopsys tools and is made to one chip by means of XILINX XC4010EPC84-4. When 20MHz was used as the input clock, data arrival time was 29.20ns and data require time was 48.70ns.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.125-132
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• 2002

We study clustering algorithm for sequences of categorical values. Clustering is a data mining problem that has received significant attention by the database community. Traditional clustering algorlthms deal with numerical or categorical data points. However, there exist many important databases that store categorical data sequences. In this paper we introduce new similarity measure and develope a hierarchical clustering algorithm. An experimental section shows performance of the proposed approach.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.15 no.2
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• pp.1-8
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• 2007

In this research, algorithm and software for the medium frequency signal analysis of DGPS(Differential Global Positioning System) station were developed. Based on new MF(Medium Frequency) algorithm, the software of NDGPS(National DGPS) signal analysis was developed for coverage analysis. Predicted MF propagation data from this software was compared to the measurement data for the verification of a developed MF algorithm. GIS(Geographic Information System) techniques including digital map with elevation data were used because MF propagation is closely related to ground conductivity, mountains, building intensity.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.1
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• pp.55-61
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• 2003

The Data Encryption Standard(DES) has been a worldwide standard for over 20 years. DES is one of the block encryption techniques which ciphers 64-bit input data blocks using a 56-bit private key. The DES algorithm transforms 64-bit input in a series of steps into a 64-bit output. Thus, it is impossible to deduce the plaintext from the ciphertext which encrypted by this algorithm without the key. This paper presents an implementation of RFID roader system using the DES algorithm. An implemented system enhances the credibility of the encryption algorithm by using the Cipher Block Chining(CBC). Experimental results also show that the implemented system has better performance over the conventional commercial product.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.287-293
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• 2018

This paper presents a satellite relative navigation strategy for formation flying, which chooses an appropriate navigation algorithm according to the operating environment. Not only global positioning system (GPS) measurements, but laser measurements can also be utilized to determine the relative positions of satellites. Laser data is used solely or together with GPS measurements. Numerical simulations were conducted to compare the relative navigation algorithm using only laser data and laser data combined with GPS data. If an accurate direction of laser pointing is estimated, the relative position of satellites can be determined using only laser measurements. If not, the combined algorithm has better performance, and is irrelevant to the precision of the relative angle data between two satellites in spherical coordinates. Within 10 km relative distance between satellites, relative navigation using double difference GPS data makes more precise relative position estimation results. If the simulation results are applied to the relative navigation strategy, the proper algorithm can be chosen, and the relative position of satellites can be estimated precisely in changing mission environments.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.9
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• pp.449-456
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• 2005

The preventive diagnostic technique prevents transformers from power failure through giving alarm and observing transformers in service. And it helps to establish the plan for optimum maintenance of the transformer as well as to find location or cause of fault using accumulated data. Data detection and experience of the preventive diagnostic system need to establish the preventive diagnostic algorithm regarding interrelationship between detected data and deterioration of equipment. Therefore in-depth analysis about the preventive diagnosis system is required. KEPCO has adopted the preventive diagnostic system at nine 345kV substations since 1997. Techniques for component sensors of the preventive diagnosis system were settled but diagnosis algorithm, diagnostic criteria and practical use of accumulated data are not yet established. This paper, to build up the base of preventive diagnostic algorithm for the Power transformer. investigated the preventive diagnostic criteria for the power transformer.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.838-841
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• 2005

DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.137-147
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• 2015

In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.7
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• pp.560-566
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• 2002

The fault detection and diagnosis technology may be applied in order to decrease the energy consumption and the maintenance cost of the air-conditioning system. In this study, two different types of faults in the air-conditioning system, such as the condenser fouling and the evaporator fan slowdown, were considered. The neural network algorithm combined with data preprocessor was developed and applied to detect the faults of the real system. Test results show that this method is very effective to detect the faults in the air-conditioning system. Therefore, this developed method can be used for the development of the air-conditioner fault detection system.