• 제어로봇시스템학회논문지
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• 제6권7호
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• pp.551-558
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• 2000

In this paper a systematic approach to automatic classificationi of power system harmonic disturbances is proposed where the proposed approach consists of the following three steps:(i) detecting and localizing each harmonic disturbance by applying discrete wavelet transform(DWT) (ii) extracting an efficient feature vector from each detected disturbance waveform by utilizing FFT and principal component analysis (PCA) along with Fisher's criterion and (iii) classifying the corresponding type of each harmonic disturbance by recognizing the pattern of each feature vector. To demonstrate the performance and applicability of the proposed classification procedure some simulation results obtained by analyzing 8-class power system harmonic disturbances being generated with Matlab power system blockset are also provided.

• Maxillofacial Plastic and Reconstructive Surgery
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• 제27권6호
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• pp.559-564
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• 2005

Beckwith-Wiedemann syndrome is an autosomal dominant growth excess disorder, which occurs with a reported incidence of 1 in 13,700 to 1 in 17,000 live births. It constitutes a discrete clinicopathologic entity characterized by macroglossia, abdominal wall defects (omphalocele), visceromegaly, gigantism, hemihypertrophy, hypoglycemia, and the increased risk of solid tumor development from multiple cell lines. A macroglossia is a key component of the syndrome, and can lead to cosmetic, functional and psychologic disorder. This report shows a 5-year-old patient with Beckwith-Wiedemann syndrome, who had macroglossia and received reduction glossectomy.

• Structural Engineering and Mechanics
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• 제40권6호
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• pp.745-762
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• 2011

Damage detection methodologies based on the direct examination of the nonlinear-nonstationary characteristics of the structure dynamic response may play an important role in online structural health monitoring applications. Different signal processing based damage detection methodologies have been proposed based on the uncovering of spikes in the high frequency component of the structural response obtained via Discrete Wavelet transforms, Hilbert-Huang transforms or high pass filtering. The performance of these approaches in systems subjected to different types of excitation is evaluated in this paper. It is found that in the case of random excitations, like earthquake accelerations, the effectiveness of such methodologies is limited. An alternative damage detection approach using the Continuous Wavelet Transform (CWT) is also evaluated to overcome this limitation. Using the CWT has the advantage that the central frequencies at which it operates can be defined by the user while the frequency bands of the detail functions obtained via DWT are predetermined by the sampling period of the signal.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.387-391
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• 2006

Insight into behaviour of pedestrians as well as tools to assess passenger flow conditions are important in for instance planning and geometric design of railway station under regular and safety-critical circumstances. Algorithm for passenger flow analysis based on DEM(Discrete Element Method) is newly developed. There are lots of similarity between particle-laden two phase flow and passenger flow. The velocity component of 1st phase corresponds to the unit vector of calculation cell, each particle to passenger, volume fraction to population density and the particle velocity to the walking velocity, etc. And, the walking velocity of passenger is also represented by the function of population density. Key algorithms are developed to determine the position of passenger, population density and numbering to each passenger. To verify the effectiveness of new algorithm, passenger flow analysis for the basic models of railway station is conducted.

• 한국통신학회논문지
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• 제25권3B호
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• pp.557-564
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• 2000

This paper presents a watermarking algorithm for embedding visually recognizable pattern (Mark, Logo, Symbol, stamping or signature) into the image. first, the color image(RGB model)is transformed in YCbCr model and then the Y component is transformed into 3-level wavelet transform. Next, the values are assembled with pattern watermark. PN(pseudo noise) code at spread spectrum communication method and mutilevel watermark weights. This values are inserted into discrete wavelet domain. In our scheme, new calculating method is designed to calculate wavelet transform with integer value in considering the quantization error. and we used the color conversion with fixed-point arithmetic to be easy to make the hardware hereafter. Also, we made the new solution using mutilevel threshold to robust to common signal distortions and malicious attack, and to enhance quality of image in considering the human visual system. the experimental results showed that the proposed watermarking algorithm was superior to other similar water marking algorithm. We showed what it was robust to common signal processing and geometric transform such as brightness. contrast, filtering. scaling. JPEG lossy compression and geometric deformation.

• 대한전기학회논문지:전력기술부문A
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• 제54권12호
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• pp.561-566
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• 2005

This paper introduces a compression technique for power qualify disturbance signal via discrete wavelet transform(DWT). The proposed approach is based on a previous estimation of the stationary component of power quality disturbance signal, so that it could be subtracted from the original signal in order to reduce a dynamic range of signal and generate transient events signal, which is subsequently applied to the compression technique. The compression techniques is performed through the difference signal decomposition, thresholding of wavelet coefficients, and signal reconstruction. It presents the relation between compression efficiency and threshold. It shouts that the wavelet transform leads to a power quality data compression approach with high compression efficiency, small compression error and good de-nosing effect.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.79-81
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• 1993

We have proposed a new technology compensating reactance component of line and load. Because capacity of SC is static, it is not appropriate to varing reactance and causes SSR problems. TCSC is introduced for the flecxible control of reactance of SC. If SC voltage is varied when the capacitor current is constant, it can be considered that capacity of SC was varied. SO capacity of SC can be controlled by controlling the voltage of SC. Control reference voltage of SC can be obtained from the condition that sum of reactive powers in all parts is zero.

• 전기학회논문지
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• 제57권8호
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• pp.1454-1463
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• 2008

Blind source separation by independent component analysis (ICA) has applied in signal processing, telecommunication, and image processing to recover unknown original source signals from mutually independent observation signals. Neural networks are learned to estimate the original signals by unsupervised learning algorithm. Because the outputs of the neural networks which yield original source signals are mutually independent, then mutual information is zero. This is equivalent to minimizing the Kullback-Leibler convergence between probability density function and the corresponding factorial distribution of the output in neural networks. In this paper, we present a learning algorithm using information theory and higher order statistics to solve problem of blind source separation. For computer simulation two deterministic signals and a Gaussian noise are used as original source signals. We also test the proposed algorithm by applying it to several discrete images.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 춘계학술발표대회
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• pp.562-565
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• 2018

A wide range of IoT applications use information collected from networks of sensors for monitoring and controlling purposes. However, the frequent appearance of fault data makes it difficult to extract correct information, thereby sending incorrect commands to actuators that can threaten human privacy and safety. For this reason, it is necessary to have a mechanism to detect fault data collected from sensors. In this paper, we present a trend-adaptive multi-scale principal component analysis (Trend-adaptive MS-PCA) model for data fault detection. The proposed model inherits advantages of Discrete Wavelet Transform (DWT) in capturing time-frequency information and advantages of PCA in extracting correlation among sensors' data. Experimental results on a real dataset show the high effectiveness of the proposed model in data fault detection.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.639-645
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• 2019

This paper proposes a salient chromagram components extraction method based on the temporal discrete cosine transform of a chromagram block to improve cover song retrieval accuracy. The proposed salient chromagram emphasizes tonal contents of music, which are well-preserved between an original song and its cover version, while reducing the effects of timbre difference. We apply the proposed salient chromagram extraction method as a preprocessing step for the Fourier-transform based cover song matching. Experiments on two cover song datasets confirm that the proposed salient chromagram improves the cover song search accuracy.