• Phonetics and Speech Sciences
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• v.6 no.4
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• pp.91-99
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• 2014

Speaking styles tend to have an influence on spectral characteristics of produced speech. There are not many studies on the spectral characteristics of speech because of complicated processing of too much spectral data. The purpose of this study was to examine spectral characteristics and formant bandwidths of English vowels produced by nine American males with different speaking styles: clear or conversational styles; high- or low-pitched voices. Praat was used to collect pitch-corrected long-term averaged spectra and bandwidths of the first two formants of eleven vowels in the speaking styles. Results showed that the spectral characteristics of the vowels varied systematically according to the speaking styles. The clear speech showed higher spectral energy of the vowels than that of the conversational speech while the high-pitched voice did the same over the low-pitched voice. In addition, front and back vowel groups showed different spectral characteristics. Secondly, there was no statistically significant difference between B1 and B2 in the speaking styles. B1 was generally lower than B2 when reflecting the source spectrum and radiation effect. However, there was a statistically significant difference in B2 between the front and back vowel groups. The author concluded that spectral characteristics reflect speaking styles systematically while bandwidths measured at a few formant frequency points do not reveal style differences properly. Further studies would be desirable to examine how people would evaluate different sets of synthetic vowels with spectral characteristics or with bandwidths modified.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3207-3213
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• 2011

Most methods of color constancy, which is the ability to determine the object color regardless of the scene illuminant, have failed to meet our expectation of their performance especially about low-illuminated scenes. Some methods with high performance need to be developed, but we must, above all else, obtain experimental images for analyzing the required circumstances or evaluating the methods. Therefore, the paper produces new sets of images so that they can be used in the development of color constancy methods suitable for low-illuminated scenes. These sets are composed of two parts: one part of images which are synthesized with spectral power distribution(SPD) of illuminants, spectral reflectance curve of reflectances, and sensor response functions of camera; the other part of images where the intensity of each image is adjusted at the uniform rate. In an experiment, the use of the sets takes an advantage that its result images are analyzed and evaluated quantitatively as their ground truth data are known in advance.

• Journal of the Korean Mathematical Society
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• v.48 no.6
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• pp.1203-1223
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• 2011

In this paper, the authors investigate the structure of operators similar to normaloid and transloid operators. In particular, we characterize the interior of the set of operators similar to normaloid (transloid, respectively) operators. This gives a concise spectral condition to determine when an operator is similar to a normaloid or transloid operator. Also it is proved that any Hilbert space operator has a compact perturbation with transloid property. This is used to give a negative answer to a problem posed by W. Y. Lee, concerning Weyl's theorem.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.557-567
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• 2006

This paper proves the invariability of reachable sets for the linear control system with positive isolated spectrum points in case where the principal operator generates $C_0-semigroup$ and derives the approximate controllability for the semilinear control system by using spectral operators with respect to isolated spectrum points.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.892-894
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• 2005

Graph partitioning provides an important tool for data clustering, but is an NP-hard combinatorial optimization problem. Spectral clustering where the clustering is performed by the eigen-decomposition of an affinity matrix [1,2]. This is a popular way of solving the graph partitioning problem. On the other hand, semidefinite relaxation, is an alternative way of relaxing combinatorial optimization. issuing to a convex optimization[4]. In this paper we present a semidefinite programming (SDP) approach to graph equi-partitioning for clustering and then we use eigen-decomposition to obtain an optimal partition set. Therefore, the method is referred to as semidefinite spectral clustering (SSC). Numerical experiments with several artificial and real data sets, demonstrate the useful behavior of our SSC. compared to existing spectral clustering methods.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.733-738
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• 2008

Using an information of dimensions of divergence points, we give full information of dimensions of the completely decomposed class of the lower(upper) distribution sets of a self-similar Cantor set. Further using a relationship between the distribution sets and the subsets generated by the lower(upper) local dimensions of a self-similar measure, we give full information of dimensions of the subsets by the local dimensions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.205-208
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• 1997

Traditionally, classification of remote sensed image data is one of the important works for image data analysis procedure. So, many researchers devote their endeavor to increasing accuracy of analysis, also, many classification algorithms have been proposed. In this paper, we propose new classification method for remote sensed image data that use rough set theory. Using indiscernibility relation of rough sets, we show that can classify image data very easily.

• Kyungpook Mathematical Journal
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• v.61 no.2
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• pp.371-381
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• 2021

In this paper, we attempt to obtain sufficient conditions for the existence of tight wavelet frame sets in locally compact abelian groups. The condition is generated by modulating a collection of characteristic functions that correspond to a generalized shift-invariant system via the Fourier transform. We present two approaches (for stationary and non-stationary wavelets) to construct the scaling function for L²(G) and, using the scaling function, we construct an orthonormal wavelet basis for L²(G). We propose an open problem related to the extension principle for Riesz wavelets in locally compact abelian groups.

• Bulletin of the Korean Chemical Society
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• v.19 no.12
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• pp.1326-1333
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• 1998

The study of coupled relaxation for methyl spin system in 2,6-dichlorotoluene was performed on the basis of the magnetization mode formalism. Using five initial perturbing pulse sequences, eight experimntal data sets were obtained, which were fitted with theoretical expressions with nine spectral density parameters. The same experiment was carried out at both 50.3 MHz and 125.6 MHz in carbon frequency. The measured spectral densities at both fields are similar in the exception of that related with carbon random field term. Furthermore, from the dipolar spectral density, the physical values may be extracted depending on the model of molecular reorientation. For example, it was assumed that the molecular framework undergoes asymmetric diffusive rotational process and methyl group reorients by either diffusive rotation about its symmetry axis or jump among internal rotational potential minima.