• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.155-162
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• 2008

In this paper we proposed a video watermarking algorithm based on a three dimension discrete wavelet transform (3D DWT) and direct spread spectrum (DSS). In the proposed method, the information watermark is embedded into followed frames, after sync watermark is embedded into the first frame. Input frames are divided into sub frames which are located odd row and even row. The sub frames are arranged as 3D frames, and transformed into 3D wavelet domain. In this domain the watermark is embedded using DSS. Existing video watermarking using 3D DWT is non-blind method but, proposed algorithm uses blind method. The experimental results show that the proposed algorithm is robust against frame cropping, noise addition, compression, etc. acquiring BER of 10% or below and sustains level of 40dB or above on the average.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.278-285
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• 2010

The difference between training and test environments is one of the major performance degradation factors in noisy speech recognition and many silence feature normalization methods were proposed to solve this inconsistency. Conventional silence feature normalization method represents higher classification performance in higher SNR, but it has a problem of performance degradation in low SNR due to the low accuracy of speech/silence classification. On the other hand, cepstral distance represents well the characteristic distribution of speech/silence (or noise) in low SNR. In this paper, we propose a Cepstral distance and Log-energy based Silence Feature Normalization (CLSFN) method which uses both log-energy and cepstral euclidean distance to classify speech/silence for better performance. Because the proposed method reflects both the merit of log energy being less affected with noise in high SNR and the merit of cepstral distance having high discrimination accuracy for speech/silence classification in low SNR, the classification accuracy will be considered to be improved. The experimental results showed that our proposed CLSFN presented the improved recognition performances comparing with the conventional SFN-I/II and CSFN methods in all kinds of noisy environments.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.249-255
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• 2014

Copy number variations(CNVs) are a recently recognized class of human structural variations and are associated with a variety of human diseases, including cancer. To find important cancer genes, researchers identify novel CNVs in patients with a particular cancer and analyze large amounts of genomic and clinical data. We present a tool called CNVDAT which is able to detect CNVs from NGS data and systematically analyze the genomic and clinical data associated with variations. CNVDAT consists of two modules, CNV Detection Engine and Sequence Analyser. CNV Detection Engine extracts CNVs by using the multi-resolution system of scale-space filtering, enabling the detection of the types and the exact locations of CNVs of all sizes even when the coverage level of read data is low. Sequence Analyser is a user-friendly program to view and compare variation regions between tumor and matched normal samples. It also provides a complete analysis function of refGene and OMIM data and makes it possible to discover CNV-gene-phenotype relationships. CNVDAT source code is freely available from http://dblab.hallym.ac.kr/CNVDAT/.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.447-454
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• 2007

To assess the port development and maritime traffic environment, the future traffic volume has been estimated using the number of inbound and outbound vessel for a specific port. The estimation of future traffic volume should be considered as an important factor to establish the degree of fairway congestion, the determination of fairway width and the operational role. Until now, the number of in and out vessel for the port has been only estimated mainly, but the type and size of inbound and outbound ships are different depending on the port's characteristics. So, it is difficult to estimate the future traffic volume using the change of only one item. This paper calculates the future traffic volume using the marine traffic characteristic factors as the number of coastal ship and ocean-going ship, the size of ship and the change of cargo volume per a ship etc. And it compared with the results of Artificial Neural Network(ANN) for accurate identification of nonlinear system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.33-39
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• 2007

LonWorks over IP (LonWorks/IP) virtual device network (VDN) is an integrated form of LonWorks device network and IP data network. LonWorks/IP VDN can offer ubiquitous access to the information on the factory floor and make it possible for the predictive and preventive maintenance on the factory floor. Timely response is inevitable for predictive and preventive maintenance on the factory floor under the real-time distributed control. The network induced uncertain time delay deteriorates the performance and stability of the real-time distributed control system on LonWorks/IP virtual device network. Therefore, in order to guarantee the stability and to improve the performance of the networked distributed control system the time-varying uncertain time delay needs to be compensated for. In this paper, under the real-time distributed control on LonWorks/IP VDN with uncertain time delay, a control scheme based on disturbance observer and ZPETC(Zero Phase Error Tracking Controller) phase lag compensator is proposed and tested through computer simulation. The result of the proposed control is compared with that of internal model controller (IMC) based on Smith predictor and disturbance observer. It is shown that the proposed control scheme is disturbance and noise tolerant and can significantly improve the stability and the tracking performance of the periodic reference. Therefore, the proposed control scheme is well suited for the distributed servo control for predictive maintenance on LonWorks/IP-based virtual device network with time-varying delay.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.610-620
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• 2022

An acoustic vector sensor can simultaneously receive vector quantities, such as particle velocity and acceleration, as well as acoustic pressure at one location, and thus it can be used as a single input multiple output receiver in underwater acoustic communication systems. On the other hand, vector signals received by a single vector sensor have different channel characteristics due to the azimuth angle between the source and receiver and the difference in propagation angle of multipath in each component, producing different communication performances. In this paper, we propose a channel parameter-based weighting method to improve the performance of an acoustic communication system using a single vector sensor. To verify the proposed method, we used communication data collected from the experiment conducted during the KOREX-17 (Korea Reverberation Experiment). For communication demodulation, block-based time reversal technique which is robust against time-varying channels were utilized. Finally, the communication results showed that the effectiveness of the channel parameter-based weighting method for the underwater communication system using a single vector sensor was verified.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.31-38
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• 2024

The digital phase-locked loop(DPLL) is one of the circuits composed of a digital detector, digital loop filter, voltage-controlled oscillator, and divider as a fundamental circuit, widely used in many fields such as electrical and circuit fields. A state estimator using various mathematical algorithms is used to improve the performance of a digital phase-locked loop. Traditional state estimators have utilized Kalman filters of infinite impulse response state estimators, and digital phase-locked loops based on infinite impulse response state estimators can cause rapid performance degradation in unexpected situations such as inaccuracies in initial values, model errors, and various disturbances. In this paper, we propose a two-layer Frobenius norm-based finite impulse state estimator to design a new digital phase-locked loop. The proposed state estimator uses the estimated state of the first layer to estimate the state of the first layer with the accumulated measurement value. To verify the robust performance of the new finite impulse response state estimator-based digital phase locked-loop, simulations were performed by comparing it with the infinite impulse response state estimator in situations where noise covariance information was inaccurate.