• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.407-417
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• 2014

An arirang is the most famous Korean folk song and was registered in UNESCO(Unitied Nations Educational, Scientific and cultural Organization) as an intangible cultural heritage in 2012. Most arirangs are composed of text and refrain parts. Genealogy of the arirang was classified in refrain patterns by using multiple sequence alignment algorithm. There are two different refrain patterns, slow and fast melodies. Of 106 arirangs, 38 and 68 arirangs contain fast and slow melodies, respectively. 73 arirangs and 104 their key words were extracted from bipartate arirang network that composed of arirangs, text works, and their relationships. The correlation among the arirangs was analyzed from the selected arirangs and key words by using pairwise comparison matrix. Also, analysis of correlation among the arirnags was performed by stepwise removal of the single degree nodes from the bipartate arirang network In this study, arirangs were analyzed in genealogy and correlation among arirangs by using informatic algorithm and network technology, in which arirang research will be constructed a stepping stone for the popularization and globalization of the arirangs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3475-3489
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• 2014

Here we present a simple flame detection method for an infrared (IR) thermal camera based real-time fire surveillance digital signal processor (DSP) system. Infrared thermal cameras are especially advantageous for unattended fire surveillance. All-weather monitoring is possible, regardless of illumination and climate conditions, and the data quantity to be processed is one-third that of color videos. Conventional IR camera-based fire detection methods used mainly pixel-based temporal correlation functions. In the temporal correlation function-based methods, temporal changes in pixel intensity generated by the irregular motion and spreading of the flame pixels are measured using correlation functions. The correlation values of non-flame regions are uniform, but the flame regions have irregular temporal correlation values. To satisfy the requirement of early detection, all fire detection techniques should be practically applied within a very short period of time. The conventional pixel-based correlation function is computationally intensive. In this paper, we propose an IR camera-based simple flame detection algorithm optimized with a compact embedded DSP system to achieve early detection. To reduce the computational load, block-based calculations are used to select the candidate flame region and measure the temporal motion of flames. These functions are used together to obtain the early flame detection algorithm. The proposed simple algorithm was tested to verify the required function and performance in real-time using IR test videos and a real-time DSP system. The findings indicated that the system detected the flames within 5 to 20 seconds, and had a correct flame detection ratio of 100% with an acceptable false detection ratio in video sequence level.

• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.279-284
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• 2017

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative time delay between two or more received signals for the direct signal must be determined. Although the GCC (Generalized Cross-Correlation) method is the most popular technique, an approach based on CCA (Canonical Correlation Analysis) was also proposed for the TDE (Time Delay Estimation). In this paper, we propose a new adaptive algorithm based on CCA in order to utilized the sparsity in the eigenvector of CCA based time delay estimator. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue with log-sum regularization in order to utilize the sparsity in the eigenvector. We have performed simulations for several SNR(signal to noise ratio)s, showing that the new CCA based algorithm can estimate the time delays more accurately than the conventional CCA and GCC based TDE algorithms.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.201-206
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• 2011

FRUC (Frame Rate Up-Conversion) technique needs an effective frame interpolation algorithm using motion information between adjacent neighboring frames. In order to have good visual qualities in the interpolated frames, it is necessary to develop an effective detection and interpolation algorithms for occluded regions. For this aim, this paper proposes an effective occluded region detection algorithm through the adaptive forward and backward motion searches and also by introducing the minimum value of normalized cross-correlation coefficient (NCCC). That is, the proposed scheme looks for the location with the minimum sum of absolute differences (SAD) and this value is compared to that of the location with the maximum value of NCCC based on the statistics of those relations. And, these results are compared with the size of motion vector and then the proposed algorithm decides whether the given block is the occluded region or not. Furthermore, once the occluded regions are classified, then this paper proposes an adaptive interpolation algorithm for occluded regions, which still exist in the merged frame, by using the neighboring pixel information and the available data in the occluded block. Computer simulations show that the proposed algorithm can effectively classify the occluded region, compared to the conventional SAD-based method and the performance of the proposed interpolation algorithm has better PSNR than the conventional algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1638-1658
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• 2024

As a crucial development direction for the sixth generation of mobile communication networks (6G), Low Earth Orbit (LEO) satellite networks exhibit characteristics such as low latency, seamless coverage, and high bandwidth. However, the frequent changes in the topology of LEO satellite networks complicate communication between satellites, and satellite power resources are limited. To fully utilize resources on satellites, it is essential to determine the association between satellites before power allocation. To effectively address the satellite association problem in LEO satellite networks, this paper proposes a satellite association-based resource allocation algorithm. The algorithm comprehensively considers the throughput of the satellite network and the fairness associated with satellite correlation. It formulates an objective function with logarithmic utility by taking the logarithm and summing the satellite channel capacities. This aims to maximize the sum of logarithmic utility while promoting the selection of fewer associated satellites for forwarding satellites, thereby enhancing the fairness of satellite association. The problems of satellite association and power allocation are solved under constraints on resources and transmission rates, maximizing the logarithmic utility function. The paper employs an improved Kuhn-Munkres (KM) algorithm to solve the satellite association problem and determine the correlation between satellites. Based on the satellite association results, the paper uses the Lagrangian dual method to solve the power allocation problem. Simulation results demonstrate that the proposed algorithm enhances the fairness of satellite association, optimizes resource utilization, and effectively improves the throughput of LEO satellite networks.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.224-227
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• 1993

In this paper, a new LMS algorithm with a variable step size (VVS LMS) is presented. The change of step size .mu. at each iteration, which increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. The norm of the cross correlation between the estimation error and input signal is used. As a measure of the misadaptation degree. Simulation results are presented to compare the performance of the VSS LMS algorithm with the normalized LMS algorithm.

• Journal of Industrial Technology
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• v.13
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• pp.33-41
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• 1993

In this paper, a new LMS algorithm with a fuzzy variable step size (FVS LMS) is presented. The change of step size ${\mu}$, at each iteration which is increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. As a measure of the misadaptation degree, the norm of the cross correlation between the estimation error and input signal is used. Simulation results are presented to compare the performance of the FVSS LMS algorithm with the normalized LMS algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1549-1556
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• 2016

By increased moving speed of aircraft, estimating location of itself becomes more important than ever. This requirement is satisfied by appearance of GPS, however it is useless when signal reception from satellite is not good enough by interruption, for example, traffic jamming. Applying link for communication to additional positioning system is capable of providing relative position of aircraft. Estimating location with link for communication is done without additional equipment but with signal processing based on correlation of received signal. ESPRIT is one of the representative algorithm among them. Estimating correlation matrix is possible to have error since it includes average operation needs enough number of samples not impractical. Therefore we propose algorithm that defines, estimates and removes error matrix of correlation. Proposing algorithm shows better performance than previous one when transmitters are close.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1950-1963
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• 2016

A novel open-circuit fault diagnosis method for 3-phase 4-wire 3-level active power filters based on voltage error correlation is proposed in this paper. This method is based on observing the output pole voltage error of the active power filter through two kinds of algorithms. One algorithm is a voltage error analytical algorithm, which derives four output voltage error analytic expressions through the pulse state, current value and dc bus voltage, respectively, assuming that all of the IGBTs of a certain phase come to an OC fault. The other algorithm is a current circuit equation algorithm, which calculates the real-time output voltage error through basic circuit theory. A correlation is introduced to measure the similarity of the output voltage errors between the two algorithms, and OC faults are located by the maximum of the correlations. A FPGA has been chosen to implement the proposed method due to its fast prototyping. Simulation and experimental results are presented to show the performance of the proposed OC fault diagnosis method.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.523-530
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• 2014

Machine material and structural strain are critical factors for appraising mechanical properties and safety. Particularly in three and four-point bending tests, which appraise the deflection and flexural strain of an object due to external force, measurements are made by the crosshead movement or deflection meter of a universal testing machine. The Digital Image Correlation (DIC) method is one of the non-contact measurement methods. It uses the image analyzing method that compares the reference image with the deformed image for measuring the displacement and strain of the objects caused by external force. Accordingly, the advantage of this method is that the object's surface roughness, shape, and temperature have little influence. However, its disadvantage is that it requires extensive time to compare the reference image with the deformed image for measuring the displacement and strain. In this study, an algorithm is developed for DIC that can improve the speed of image analysis for measuring the deflection and strain of an object caused by a three-point bending load. To implement this algorithm for improving the speed of image analysis, LabVIEW 2010 was used. Furthermore, to evaluate the accuracy of the developed fast correlation algorithm, the deflection of an aluminum specimen under a three-point bending load was measured by using the universal test machine and DIC measurement system.