• International Journal of Contents
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• v.10 no.3
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• pp.9-16
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• 2014

Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.992-999
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• 2009

The pulse transit time(PTT), which is determined by measuring the electrocardiogram(ECG) and pulse wave, gives comprehensive information about the cardiovascular system. However, a little movement of body and/or inaccurate pressure applied to skin during the measurement of pulse wave leads to acquire incorrect results. To overcome such problem, we developed an integrated sensor system which makes it possible to measure ECG, pressure pulse wave(PPW) and photoplethysmograph(PPG) at the same time. Futhermore, we implemented a new metal electrode which enables to continuously measure ECG. We verified that both integrated sensor system and new electrode provide useful effect.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1042-1046
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• 2011

In this paper, we analyze the STO (Symbol Timing Offset) problem in conventional ZP-OFDM (Zero Padding-Orthogonal Frequency Division Multiplexing) systems and propose a robust ZP-OFDM system with bi-directional overlap-add scheme to overcome the problem. The proposed ZP-OFDM system is able to preserve the orthogonality between subcarriers and reduce the interference from other ZP-OFDM symbols due to the BOA scheme, which exploits both ZP intervals of the previous and the current ZP-OFDM symbols, even though serious STOs result from inaccurate symbol timing synchronization. Simulation results verify that the proposed ZP-OFDM system is superior to the conventional ZP-OFDM system.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.37-39
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. Since the background noise presenting to record will introduce disturbance while we just want to get the stationary parameters to represent the corresponding speech section, in particular, a major source of error in automatic recognition system of isolated words is the inaccurate detection of beginning and ending boundaries of test and reference templates, thus we must find potent method to remove the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two simple time-domain measurements - short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Comparing with the conventional methods based on short-time energy and short-time zero-crossing rate, the novel approach based on time-domain Lyapunov Exponents(LEs) is low complexity and suitable for Digital Isolated Word Recognition System.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.6
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• pp.404-404
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• 2000

The receiving responses of a bistatic GPR system are analyzed by using three-dimensional FDTD method and equivalent network model. The conventional delta-gap feed model may be inaccurate because of neglecting the impedance matching characteristics between the antenna and the transmission line. In this paper, the feed model is improved by considering the physical characteristics of the actual GPR. The actually received voltage is calculated by employing the equivalent network model in angular frequency-domain, which is composed by using the results of three-dimensional FDTD analysis for an actual bistatic GPR system. The validity of the presented model is assured by showing the convergence of the computed results to the measured data.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.6
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• pp.44-53
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• 2000

The receiving responses of a bistatic GPR system are analyzed by using three-dimensional FDTD method and equivalent network model. The conventional delta-gap feed model may be inaccurate because of neglecting the impedance matching characteristics between the antenna and the transmission line. In this paper, the feed model is improved by considering the physical characteristics of the actual GPR. The actually received voltage is calculated by employing the equivalent network model in angular frequency-domain, which is composed by using the results of three-dimensional FDTD analysis for an actual bistatic GPR system. The validity of the presented model is assured by showing the convergence of the computed results to the measured data.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.6
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• pp.72-84
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• 2000

The test patterns for path delay faults consist of two patterns. So in order to test the delay faults, a new weight generation algorithm that is different from the weight generation algorithm for stuck-at faults must be applied. When deterministic test patterns for weight calculation are used, the deterministic test patterns must be divided into several subsets, so that Hamming distances between patterns are not too long. But this method makes the number of weight sets too large in delay testing, and may generate inaccurate weights. In this pater, we perform fault simulation without pattern partition. Experimental results for ISCAS 89 benchmark circuits prove the effectiveness of the new weight generation algorithm proposed in this paper.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.318-320
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localitzation technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.62-71
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• 2017

In order to attract foreign tourists, it is important to understand what factors on domestic tour spots are critically considered and how they are evaluated after visit. However, most of the researches on tour business have collected information from tourists through survey on a small number of tourists, which leads to inaccurate and biased conclusion. In this paper, we suggest a data-driven methodology to figure out tourists' satisfaction factors and estimate sentiment scores on them. To do so, we collected review comments data from popular web site. Latent dirichlet allocation is employed to extract key factors and elastic net is used to estimate sentiment scores. Then, an aggregated evaluation score is generated by combining the factors and the sentiment scores per topics. Our proposed method can be used to recommend travel schedules with themes and discover new spots.