• Korean Journal of Optics and Photonics
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• v.14 no.1
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• pp.72-79
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• 2003

We proposed a noble algorithm using DOP (degree of polarization) not only as feedback signal but alto as feed-forward signal for the compensation of higher-order PMD effect. In the proposed algorithm, DOP after the first-order PMD compensation is considered as the indicator of the amount of residual higher-order PMD. This algorithm has the merit that DOF (degree of freedom) of the system can be limited to the level of the first-order PMD compensation system. Owing to the limited DOF, the reliability of the system can be enhanced and the complexity of the implementation can be degraded. For the analysis of the algorithm, we simulated the 10Gbps NRZ transmission system and obtained the result that the system outage probability can be reduced as much as three times with respect to the only first-order PMD compensation case.

• Journal of IKEEE
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• v.22 no.3
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• pp.578-584
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• 2018

Image segmentation has been presented in the various method in image interpretation and recognition, and the image is using separate the characteristics of the specific purpose. In this paper, we proposed an algorithm that separate image for feature points detected to high temperature in a Thermal infrared image. In order to improve the processing time, the proposed algorithm is implemented to FPGA Hardware Block using the Zynq-7000 Evaluation Board environment. The proposed High-Temperature Detection Algorithm and total FPGA blocks show a decrease of a processing time result from 16ms to 0.001ms, and from 50ms to 0.322ms respectively. It is also verified similar results of the PSNR to comparing software thermal testbench and hardware ones.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.579-580
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• 2015

Power frequency is one of important operational parameters evaluating reliability, stability, and measuring efficiency of power. Therefore, an accurate and fast estimate of the power frequency is required. The magnitude gains of cosine and sine filters become different when the power frequency is deviated from the nominal value. The proposed algorithm estimates the power frequency based on this. To demonstrate the performance of the proposed algorithm, RTDS and DSP are used. The simulation results show that the algorithm has not only a high level of robustness but also high measurement accuracy over a wide range of frequency changes. In addition, the algorithm was immune to harmonics and noise.

• Advances in Automotive Engineering
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• v.1 no.1
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• pp.143-152
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• 2018

In this study an economical image stitching algorithm for use in automotive industry is developed for retrofittable panoramic image assistance applications. The aim of this project is to develop a driving assistance system known as Panoramic Parking Assistance (PPA) which is cheap, retrofittable and compatible for every type of automobiles. PPA generates bird's eye view image using cameras installed on the automobiles. Image stitching requires to get bird's eye view position of the vehicle. Panoramic images are wide area images that cannot be available by taking one shot, attained by stitching the overlapping areas. To achieve correct stitching many algorithms are used. This study includes some type of these algorithms and presents a simple one that is economical and practical. Firstly, the mathematical model of a wide view of angle camera is provided. Then distorted image correction is performed. Stitching is implemented by using the SIFT and SURF algorithms. It has been seen that using such algorithms requires complex image processing knowledge and implementation of high quality digital processors, which would be impracticle and costly for automobile use. Thus a simpler algorithm has been developed to decrase the complexity. The proposed algorithm uses one matching point for every couple of images and has ease of use and does not need high power processors. To show the efficiency, images coming from four distinct cameras are stitched by using the algorithm developed for the study and usability for automotive application is analyzed.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1588-1593
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• 2008

This paper describes a real-time isometric pinch force prediction algorithm from surface electromyogram (sEMG) using multilayer perceptron (MLP) for human robot interactive applications. The activities of seven muscles which are observable from surface electrodes and also related to the movements of the thumb and index finger joints were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed using the recorded activities. Four muscles were selected for the force prediction by using the Fisher linear discriminant analysis among seven muscles, and the four muscle activities provided effective information for mapping sEMG to the pinch force. The MLP structure was designed to make training efficient and to avoid both under- and over-fitting problems. The pinch force prediction algorithm was tested on five volunteers and the results were evaluated using two criteria: normalized root mean squared error (NRMSE) and correlation (CORR). The training time for the subjects was only 2 min 29 sec, but the prediction results were successful with NRMSE = 0.112 ${\pm}$ 0.082 and CORR = 0.932 ${\pm}$ 0.058. These results imply that the proposed algorithm is useful to measure the produced pinch force without force sensors in real-time. The possible applications include controlling bionic finger robot systems to overcome finger paralysis or amputation.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.400-402
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• 2006

Matrix multiplication is an important problem in linear algebra. its main significance for combinatorial algorithms is its equivalence to a variety of other problems, such as transitive closure and reduction, solving linear systems, and matrix inversion. Thus the development of high-performance matrix multiplication implies faster algorithms for all of these problems. In this paper. we present a quantitative comparison of the theoretical and empirical performance of key matrix multiplication algorithms and use our analysis to develop a faster algorithm. We propose a Hybrid approach on Winograd's and Strassen's algorithms that improves the performance and discuss the performance of the hybrid Winograd-Strassen algorithm. Since Strassen's algorithm is based on a $2{\times}2$ matrix multiplication it makes the implementation very slow for larger matrix because of its recursive nature. Though we cannot get the theoretical threshold value of Strassen's algorithm, so we determine the threshold to optimize the use of Strassen's algorithm in nodes through various experiments and provided a summary shown in a table and graphs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.756-763
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• 2009

The Least Mean Square (LMS) algorithm is often used to restore signal corrupted by additive noise. A major defect of this algorithm is that the excess Mean Square Error (EMSE) increases linearly according to speech signal power. This result reduces the efficiency of performance significantly due to the large EMSE around the optimum value. Choosing a small step size solves this defect but causes a slow rate of convergence. The step size must be optimized to satisfy a fast rate of convergence and minimize EMSE. In this paper, the Instantaneous Gain Control (IGC) algorithm is proposed to deal with the situation as it exists in speech signals. Simulations were carried out using a real speech signal combined with Gaussian white noise. Results demonstrate the superiority of the proposed IGC algorithm over the LMS algorithm in rate of convergence, noise reduction and EMSE.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.1
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• pp.89-101
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• 2015

To satisfy civil aviation requirements using the Global Navigation Satellite System (GNSS), it is important to guarantee system integrity. In this work, we propose a fault detection algorithm for GNSS ephemeris anomalies. The basic principle concerns baseline length estimation with GNSS measurements (pseudorange, broadcasted ephemerides). The estimated baseline length is subtracted from the true baseline length, computed using the exact surveyed ground antenna positions. If this subtracted value differs by more than a given threshold, this indicates that an ephemeris anomaly has been detected. This algorithm is suitable for detecting Type A ephemeris failure, and more advantageous for use with multiple stations with various long baseline vectors. The principles of the algorithm, sensitivity analysis, minimum detectable error (MDE), and protection level derivation are described and we verify the sensitivity analysis and algorithm availability based on real GPS data in Korea. Consequently, this algorithm is appropriate for GNSS regional implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1790-1806
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• 2015

Utility-based routing is a special type of routing approach using a composite utility metric when making routing decisions in ad hoc and sensor networks. Previous studies on the utility-based routing all use fixed retry limit and a very simple distance related energy model, which makes the utility maximization less efficient and the implementation separated from practice. In this paper, we refine the basic utility model by capturing the correlation of the transmit power, the retry limit, the link reliability and the energy cost. A routing algorithm based on the refined utility model with adaptive transmit power and retry limit allocation is proposed. With this algorithm, packets with different priorities will automatically receive utility-optimal delivery. The design of this algorithm is based on the observation that for a given benefit, there exists a utility-maximum route with optimal transmit power and retry limit allocated to intermediate forwarding nodes. Delivery along the utility-optimal route makes a good balance between the energy cost and the reliability according to the value of the packets. Both centralized algorithm and distributed implementations are discussed. Simulations prove the satisfying performance of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.19-26
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• 2010

The Windows registry is a hierarchical database where the configuration data of a system or application programs is stored. In this paper, we presented and implemented a registry virtualization algorithm and measured its performance. The registry virtualization algorithm presented in the paper is called Copy-One-level On Write-Open(COOWO) that is a modified version of general Copy On Whte(COW) method to make it suitable for registry virtualization. In this paper, we implemented the proposed algorithm as a dynamically loadable library in Windows and applied it to many Windows application programs. This paper is meaningful since we described a registry virtualization algorithm in detail in situation where we can not find papers that describe the registry virtualization in detail, and we could find the performance of the algorithm can be used in the real applications.