• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.110-116
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• 2017

This paper proposed a new real-time parameter tracking algorithm. Unlike the convenience algorithms, the proposed real-time parameter tracking algorithm can estimate parameters through three-phase voltage and electric current without coordination transformation, and does not need information on magnetic flux. Therefore, it can estimate parameters regardless of the change according to operation point and cross-saturation effect. In addition, as the quasi-real-time parameter tracking technique can estimate parameters through the four fundamental arithmetic operations instead of complicated algorithms such as numerical value analysis technique and observer design, it can be applied to low-performance DSP. In this paper, a new real-time parameter tracking algorithm is derived from three phase equation. The validity and usefulness of the proposed inductance estimation technique is verified by simulation and experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3055-3073
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• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2350-2352
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• 2004

This paper presents the implementation-tation of the real-time software GPS Receiver based on FFT and FLL assisted PLL tracking algorithm. The FFT(fast fourier transform) based GPS si-gnal acquisition scheme provides a fast TTFF(time to first fix) performance. The tracking based on FLL assisted PLL enables tracking of GPS signal in a high dynamic environment. The designed software GPS receiver uses the indexing method for generating replica carrier to reduce computation load. The performance of the implemented GPS receiver is evaluated using high-dynamic simulated data from a simulator and real static data.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.215-216
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• 2007

This paper presents a real-time scheduler for nuclear safety system. According to constraints and requirements of nuclear safety system, scheduler design analysis is done and algorithms are developed for implementation. Using DSP based hardware, a real-time scheduler is realized. Consequently, this paper shows the performance of periodical software through the monitoring program.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.61.2-61
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• 2001

The purpose of the initial alignment of a SDINS is to get a coordinate transformation matrix from the body frame to the navigation frame. The initial alignment is one of the most important processes in the navigation system since its error has a large influence on the navigation solution. In this paper, a real-time initial alignment algorithm for the SDINS is developed using the Kalman filter. The steady state error analysis is performed for the developed Kalman filter technique and the gyrocompass loop method. The performance of the developed alignment method is compared with the gyrocompass loop method through the real-time alignment experiments.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.183-192
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• 2017

k-nearest neighbor (K-NN) is a well-known classification algorithm, being feature space-based on nearest-neighbor training examples in machine learning. However, K-NN, as we know, is a lazy learning method. Therefore, if a K-NN-based system very much depends on a huge amount of history data to achieve an accurate prediction result for a particular task, it gradually faces a processing-time performance-degradation problem. We have noticed that many researchers usually contemplate only classification accuracy. But estimation speed also plays an essential role in real-time prediction systems. To compensate for this weakness, this paper proposes correlation coefficient-based clustering (CCC) aimed at upgrading the performance of K-NN by leveraging processing-time speed and plurality rule-based density (PRD) to improve estimation accuracy. For experiments, we used real datasets (on breast cancer, breast tissue, heart, and the iris) from the University of California, Irvine (UCI) machine learning repository. Moreover, real traffic data collected from Ojana Junction, Route 58, Okinawa, Japan, was also utilized to lay bare the efficiency of this method. By using these datasets, we proved better processing-time performance with the new approach by comparing it with classical K-NN. Besides, via experiments on real-world datasets, we compared the prediction accuracy of our approach with density peaks clustering based on K-NN and principal component analysis (DPC-KNN-PCA).

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.59-62
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• 2002

Before a developed digital Power System Stabilizer(PSS) is installed to real power system, an efficient trial test for installing PSS is needed. In this paper, the performance of developed digital PSS for a single hydro-turbine generator and infinite bus system has been investigated using Real Time Digital Simulator(RTDS) in order to install PSS to real power system practically. The test system was composed of RTDS, three phase voltage/current amplifier and the PSS and the test scheme provided a very efficient way to verify the design and control performance of a PSS to be applied to real power system. The trial installation test through AVR 3% step test and three fault analysis may be guaranteed to install PSS to real power system.

• Journal of Advanced Navigation Technology
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• v.19 no.3
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• pp.199-206
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• 2015

For real-time precise positioning, IGS provides ephemeris predictions (IGS ultra-rapid, IGU) and real-time ephemeris estimates (real-time service, RTS). Due to the RTS data latency, which ranges from 5 s to 30 s, a short-term prediction process is necessary before applying the RTS corrections. In this paper, the real-time performance of the RTS correction and IGU prediction are compared. The RTS correction availability for the GPS satellites observed in Korea is computed as 99.3%. The RTS correction is applied to broadcast ephemeris to verify the accuracy of the RTS correction. The 3D orbit RMS error of the RTS correction is 0.043 m. Prediction of the RTS correction is modeled as a polynomial, and then the predicted value is compared with the IGU prediction value. The RTS orbit prediction accuracy is nearly equivalent to the IGU prediction, but RTS clock prediction performance is 0.13 m better than the IGU prediction.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.167-176
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• 2023

This study presents the performance analysis of real-time orbit determination and prediction for navigation message generation of Regional Navigation Satellite System (RNSS). Since the accuracy of ephemeris and clock correction in navigation message affects the positioning accuracy of the user, it is essential to construct a ground segment that can generate this information precisely when designing a new navigation satellite system. Based on a real-time architecture by an extended Kalman filter, we simulated orbit determination and prediction of RNSS satellites in order to assess the accuracy of orbit and clock prediction and signal-in-space ranging errors (SISRE). As a result of the simulation, the orbit and clock accuracy was at 0.5 m and 2 m levels for 24 hour determination and six hour prediction after the determination, respectively. From the prediction result, we verified that the SISRE of RNSS for six hour prediction was at a 1 m level.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.10
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• pp.458-464
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• 1986

This paper introduces a method for design verification and performance evaluation of flight control system. The method is a real time hardware in the loop simulation using the hybrid computer and motion table facility. As a typical illustration, a roll control system of flight vehicle is applied. The simulation validity is demonstrated by comparing hardware test results with analog simulation results.