• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.111-115
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• 1994

In this paper, a variable time-scale modification using SOLA is proposed, which takes into consideration the different time-scaled characteristics of voiced and unvoiced speech. The conventional method performs time-scale modifiction at a uniform rate for all speech. For this purpose, voiced and unvoiced speech duration at various taling speeds were statistically analyzed. A clipping autocorrelation functio was applied to each analysis frame to detemine voiced and unvoiced speech to obtain respective variation rates. The results were used to perform variable time-scale modification to evaluate performance, a MOS test was conducted to compare the proposed voiced/unvoiced variable time-scale modification and the uniform SOLA method. Results indicate that the proposed method produces sentence quality superior to that of the conventional method.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.2
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• pp.235-242
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• 2004

The purpose of this study was to develop a scale for the evaluation of the subjective fabric hand. In order to find out the appropriate method for the evaluation, bipolar adjectives were compared to unipolar adjectives. One hundred female university students we.e selected as judges. They assessed 9 fabrics using the 9 point scale system for both bipolar and unipolar adjectives. When using the bipola. scale, judges responded more consistently showing smaller deviation among their responses. The Judges seemed to understand the meanings of adjectives in the bipolar scale more clearly than in the unipolar scale. Unipolar scale has twice the number of questions than bipolar scale does. Therefore. judges often felt bored responding to the questions using unipolar adjectives. If the appropriate antonym can be found through verified method, bipolar scale seems to have more advantages than unipolar scale.

• Interaction and multiscale mechanics
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• v.5 no.1
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• pp.27-40
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• 2012

The two-dimensional incompressible flow of a linear viscoelastic fluid we considered in this research has rapidly oscillating initial conditions which contain both the large scale and small scale information. In order to grasp this double-scale phenomenon of the complex flow, a multiscale analysis method is developed based on the mathematical homogenization theory. For the incompressible flow of a linear viscoelastic Maxwell fluid, a well-posed multiscale system, including averaged equations and cell problems, is derived by employing the appropriate multiple scale asymptotic expansions to approximate the velocity, pressure and stress fields. And then, this multiscale system is solved numerically using the pseudospectral algorithm based on a time-splitting semi-implicit influence matrix method. The comparisons between the multiscale solutions and the direct numerical simulations demonstrate that the multiscale model not only captures large scale features accurately, but also reflects kinetic interactions between the large and small scale of the incompressible flow of a linear viscoelastic fluid.

• Speech Sciences
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• v.3
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• pp.167-176
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• 1998

Conventional time-scale modification methods have the problem that as the modification rate gets higher the time-scale modified speech signal becomes less intelligible, because they ignore the effect of articulation rate on speech characteristics. Results of research on speech perception show that the timing information of transient portions of a speech signal plays an important role in discriminating among different speech sounds. Inspired by this fact, we propose a novel scheme for modifying the time-scale of speech. In the proposed scheme, the timing information of the transient portions of speech is preserved, while the steady portions of speech are compressed or expanded somewhat excessively for maintaining overall time-scale change. In order to identify the transient and steady portions of a speech signal, we employ a simple method using LPC cepstral distance between neighboring frames. The result of the subjective preference test indicates that the proposed method produces performance superior to that of the conventional SOLA method, especially for very fast playback case.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.92-95
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• 2011

The walls of modern train cars are required to have higher transmission loss since modern train have had high speed and light weight. The method based on Reverberation Chamber like KS F 2808 could be used to measure transmission loss. However, this method has difficulty in that constrained Standard of it requires extremely large facilities. Recently, the method based on Scale Reverberation Chamber is used as an alternative to Reverberation Chamber. The method of Scale Reverberation Chamber is known to be small and economical but it provides standing wave that directly influences measurement error. Therefore, this research is focus on predicting standing waves based on method of FFM and reducing measurement error by changing shape of chamber.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.13-20
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• 2013

In this paper, we propose a multi-scale crack detection method. This method uses decomposition, composition, and shape properties. It is based on morphology algorithm, crack features. We use a morphology operator which extracts patterns of crack. It segments cracks and background using opening and closing operations. Morphology based segmentation is better than existing integration methods using subtraction in detecting a crack it has small width. However, morphology methods using only one structure element could detect only fixed width crack. Thus, we use decomposition and composition methods. We use a decimation method for decomposition. After decomposition and morphology operation, we get edge images given by binary values. Our method calculates values of properties such as the number of pixels and the maximum length of the segmented region. We decide whether the segmented region belongs to cracks according to those data. Experimental results show that our proposed multi-scale crack detection method has better results than those of existing detection methods.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2359-2364
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• 2017

This paper proposes a scale factor based range estimation method using a sum of squares (SOS) method. Many previous studies measured distance by using a camera, which usually required two cameras and a long computation time for image processing. To overcome these disadvantages, we propose a range estimation method for an object using a single moving camera. A SOS-based Luenberger observer is proposed to estimate the range on the basis of the Euclidean geometry of the object. By using a scale factor, the proposed method can realize a faster operation speed compared with the previous methods. The validity of the proposed method is verified through simulation results.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.2
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• pp.217-224
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• 2005

A new roof edge detection method based on multi level scales of wavelet function is proposed in this paper roof edge and its direction are obtained in this new methods at one time. Besides. scale characteristics of detecting roof edge is analyzed. And a few new methods on fingerprint image pre-processing are described. A method segmenting foreground/background of fingerprint images is proposed, in which Prior estimation of direction field is not required any more. A segmentation method based on multi-scale roof edges is implemented. and the valid scale range of the method is defined. too. And the method is used to segment ridges and valleys in fingerprint images simultaneously The exact direction fields made up of the direction of each point in ridges can be obtained when detecting ridges exactly based on the roof edge detector, in comparison with the traditional coarse estimation of direction fields. Obviously. it will establish a solid foundation for the sequent fingerprint identification.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.1
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• pp.15-22
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• 2011

In this paper, cavitation patterns of model tests were compared with those of full-scale measurement for a propeller of crude oil carrier which was suffered from erosions on suction side of blade tip region. Cavitation tests were performed at design and ballast draft using model and full scale nominal wakes. A model ship and wire mesh method was used for the simulation of wake patterns of model nominal wakes. For the prediction of full-scale wake patterns, a RANS solver(Fluent 6.3) was used and wire mesh method was used for the simulation of the full scale wakes. Comparison results show that cavitation patterns using predicted full-scale wake patterns are closer to cavitation patterns of full-scale measurement at ballast draft condition. Also, cloud cavitations were observed on the position of eroded area at both full-scale measurement and cavitation tests using simulated full-scale wake patterns.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1113-1119
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• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.