• Bulletin of the Korean Mathematical Society
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• v.34 no.3
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• pp.483-489
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• 1997

The $W^\phi$-spaces generalizing the $W^p$-spaces due to Pathak and Upadhyay are investigated and the Fourier transformations on these spaces are continuous.

• Bulletin of the Korean Mathematical Society
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• v.41 no.3
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• pp.427-434
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• 2004

The purpose of the paper is to correct erroneous proofs of two theorems of Walters ([1]) about the pressure of continuous transformations.

• Communications of the Korean Mathematical Society
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• v.21 no.4
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• pp.729-737
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• 2006

We study Ribaucour transformations on nondegenerate local isometric immersions of Riemannian space forms into Lorentzian space forms with flat normal bundles. They can be explained by dressing actions on the solution space of Lorentzian Grassmannian systems.

• Journal of the Korean Mathematical Society
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• v.45 no.6
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• pp.1577-1590
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• 2008

We study Ribaucour transformations on nondegenerate local isometric immersions of Lorentzian space forms into Lorentzian space forms with the same sectional curvatures which have flat normal bundles. They can be associated to dressing actions on the solution space of Lorentzian Grassmannian systems.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.3-43
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• 1998

Technical and business transformations are reshaping the business of Diesel engine builders, Diesel lubricant marketers and additive companies. Key issues facing engine builders and end users under these transformations include: -Emission regulations -Vehicle operating costs -Evolving business environments With these challenges come opportunities. For equipment builders and lubricant marketers, these include: -Lubricants meeting global performance requirements -High value lubricant applications -Profitable new businesses

• Communications of the Korean Mathematical Society
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• v.33 no.4
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• pp.1239-1248
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• 2018

Recently, many authors have obtained several hypergeometric identities involving hypergeometric functions of one and multi-variables such as the Appell's functions and Horn's functions. In this paper, we obtain several new transformations suitably by applying the fractional calculus operator to these hypergeometric identities, which was introduced recently by Tremblay.

• Communications of the Korean Mathematical Society
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• v.13 no.4
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• pp.817-823
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• 1998

In the present paper, we study conformal and projective Killing vector fields and infinitesimal Q-transformations on a quaternionic Kahlerian manifold, and prove that an infinitesimal conformal or projective automorphism in a compact quaternionic Kahlerian manifold is necessarily infinitesimal automorphism.

• Magazine of the Korean Society of Agricultural Engineers
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• v.34 no.4
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• pp.39-47
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• 1992

Derivation of reasonable design low flows was attempted by comparative analysis of design low flows was derived by Power and SMEMAX transformations for the normalizations of skewed distribution and by Type m extremal distribution presented in the first report of this study with annual low flows in the five watersheds of main river basins in Korea. The results were anslyzed and summarized as follows. 1.Basic statistics of annual low flows for the selected watersheds were calculated by using Power and SMEMAX transformations. 2.Power thansformation has found to be the best for the normalization of skewed distribution among others including log, square root and SMEMAX transformations. 3.Design low flows for the selected watersheds were derived by the Power and SMEMAX transformations. 4.Judging by the relative suitabilities of the Type III extremal distribution, Power and SMEMAX transformation, it was found that design low flows of all methods are closer to the observed data within 10 years of the return period and those of Power transformation can be acknowledzed as a reasonable one among others from the viewpoint of the median between values of Type m extremal distribution and SMEMAX transformation in addition to closing the observed than others over 10 years of the return period.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.349-363
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• 2024

Compositional data refers to data where the sum of the values of the components is a constant, hence the sample space is defined as a simplex making it impossible to apply statistical methods developed in the usual Euclidean vector space. A natural approach to overcome this restriction is to consider an appropriate transformation which moves the sample space onto the Euclidean space, and log-ratio typed transformations, such as the additive log-ratio (ALR), the centered log-ratio (CLR) and the isometric log-ratio (ILR) transformations, have been mostly conducted. However, in scenarios with sparsity, where certain components take on exact zero values, these log-ratio type transformations may not be effective. In this work, we mainly suggest an alternative transformation, that is the square-root transformation which moves the original sample space onto the directional space. We compare the square-root transformation with the log-ratio typed transformation by the simulation study and the real data example. In the real data example, we applied both types of transformations to the USG% data obtained from NBA, and used a density based clustering method, DBSCAN (density-based spatial clustering of applications with noise), to show the result.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.31-40
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• 2008

We generally use lower-dimensional transformations to convert high-dimensional sequences into low-dimensional points in similar sequence matching. These traditional transformations, however, show different characteristics in indexing performance by the type of time-series data. It means that the selection of lower-dimensional transformations makes a significant influence on the indexing performance in similar sequence matching. To solve this problem, in this paper we propose a hybrid approach that integrates multiple transformations and uses them in a single multidimensional index. We first propose a new notion of hybrid lower-dimensional transformation that exploits different lower-dimensional transformations for a sequence. We next define the hybrid distance to compute the distance between the transformed sequences. We then formally prove that the hybrid approach performs the similar sequence matching correctly. We also present the index building and the similar sequence matching algorithms that use the hybrid approach. Experimental results for various time-series data sets show that our hybrid approach outperforms the single transformation-based approach. These results indicate that the hybrid approach can be widely used for various time-series data with different characteristics.