• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.495-502
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• 2006

The importance of the bandwidth selection has been more emphasized than the kernel function selection for nonparametric frequency analysis since the interpolation is more reliable than the extrapolation method. However, when the extrapolation method is being applied(i.e. recurrence interval more than the length of data or extreme probabilities such as $200{\sim}500$ years), the selection of the kernel function is as important as the selection of the bandwidth. So far, the existing kernel functions have difficulties for extreme value estimations because the values extrapolated by kernel functions are either too small or too big. This paper suggests a Modified Cauchy kernel function that is suitable for both interpolation and extrapolation as an improvement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.35-40
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• 2011

The complex-valued blind algorithm based on a set of randomly generated symbols and Euclidean distance can take advantage of information theoretic learning and cope with the channel phase rotation problems. On the algorithm, in this paper, the effect of kernel size has been studied and a kernel-modified version of the algorithm that rearranges the forces between the information potentials by kernel-modification has been proposed. In simulation results for 16 QAM and complex-channel models, the proposed algorithm show significantly enhanced performance of symbol-point concentration and no phase rotation problems caused by the complex channel models.

• ETRI Journal
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• v.36 no.3
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• pp.333-342
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• 2014

Most hyper-ellipsoidal clustering (HEC) approaches use the Mahalanobis distance as a distance metric. It has been proven that HEC, under this condition, cannot be realized since the cost function of partitional clustering is a constant. We demonstrate that HEC with a modified Gaussian kernel metric can be interpreted as a problem of finding condensed ellipsoidal clusters (with respect to the volumes and densities of the clusters) and propose a practical HEC algorithm that is able to efficiently handle clusters that are ellipsoidal in shape and that are of different size and density. We then try to refine the HEC algorithm by utilizing ellipsoids defined on the kernel feature space to deal with more complex-shaped clusters. The proposed methods lead to a significant improvement in the clustering results over K-means algorithm, fuzzy C-means algorithm, GMM-EM algorithm, and HEC algorithm based on minimum-volume ellipsoids using Mahalanobis distance.

• Communications of the Korean Mathematical Society
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• v.35 no.1
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• pp.125-136
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• 2020

In this article, we discuss classes of generalized functions for certain modified integral operator of Bessel-type involving Fox's H-function kernel. We employ a known differentiation formula of Fox's H-function to obtain the definition and properties of the distributional modified Bessel-type integral. Further, we derive a smoothness theorem for its kernel in a complete countably multi-normed space. On the other hand, using an appropriate class of convolution products, we derive axioms and establish spaces of modified Boehmians which are generalized distributions. On the defined spaces, we introduce addition, convolution, differentiation and scalar multiplication and further properties of the extended integral.

• Nuclear Engineering and Technology
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• v.46 no.2
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• pp.263-272
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• 2014

Scattering source calculations using conventional spherical harmonic expansion may require lots of computation time to treat full-coupled three-dimensional photon-electron transport in a highly anisotropic scattering medium where their scattering cross sections should be expanded with very high order (e.g., $P_7$ or higher) Legendre expansions. In this paper, we introduce a modified scattering kernel approach to avoid the unnecessarily repeated calculations involved with the scattering source calculation, and used it with parallel computing to effectively reduce the computation time. Its computational efficiency was tested for three-dimensional full-coupled photon-electron transport problems using our computer program which solves the multi-group discrete ordinates transport equation by using the discontinuous finite element method with unstructured tetrahedral meshes for complicated geometrical problems. The numerical tests show that we can improve speed up to 17~42 times for the elapsed time per iteration using the modified scattering kernel, not only in the single CPU calculation but also in the parallel computing with several CPUs.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.469-471
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• 2000

본 논문에서는 모멘트 항을 추가한 수정된 kernel-adatron 알고리즘을 제안하고 이른 support vector machines의 학습기법으로 이용하였다. 이는 기울기상승법에서 일어나는 최적해로의 수렴에 따른 발진을 억제하여 그 수렴 속도를 좀더 개선시키는 모멘트의 장점과 kernel-adatron 알고리즘의 구현용이성을 그대로 살리기 위함이다. 제안된 학습기법의 SVM을 실제 200명의 암환자를 2부류(초기와 악성)로 분류하여 문제에 적용하여 시뮬레이션한 결과, Cambell등의 kernel-adatron 알고리즘을 이용한 SVM의 결과와 비교할 때 학습시간과 시험 데이터의 분류률에서 더욱 우수한 성능이 있음을 확인할 수 있었다.

• Journal of the Korean Society for Library and Information Science
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• v.15
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• pp.197-224
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• 1988

The kernel technique in game theory is introduced and modified in the notion of super kernel, which creates searching maps through the hierarchic clustering technique. The results show more Improved retrieval efficiency in terms of precision and recall.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.31 no.1
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• pp.49-55
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• 1986

To obtain basic information required for improving grain yield of the two modified opaque-2 synthetics, which have been developed at College of Agr., Chungnam National Univ. in 1980 and named as Puyo No.2 and No.3, physical kernel characteristics of the two synthetics were fully investigated and results obtained are as follows: Puyo No.2 synthetics had a smaller kernel size with lighter weight than the Puyo No.3. The Puyo No.2 synthetics had higher kernel density than the Puyo No.3 with large Kernel size. The Puyo No.2 had kernels with heterogenous endosperm phenotypes. Some kernels had mottled patches on endosperm, while other kernels 1/2 and 1/2 phenotypes. All the modified opaque-2 synthetics had somewhat lighter endosperm weight than the normal check hybrid. The Puyo No.2 synthetics with smaller kernel size had more germ portion compared with large kernel, Puyo No.3. The Puyo No.2 had shown also typical endosperm texture when observed under microscope after cutting by glass knife. The lysine content of the Puyo No.2 was higher than those of other varieties studied. Breeding schemes to improve the yield capacity of the two modified opaue-2 synthetics were discussed.

• Bulletin of the Korean Mathematical Society
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• v.53 no.6
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• pp.1845-1856
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• 2016

In this paper our aim is to study the classical Bessel-Struve kernel. Monotonicity and log-convexity properties for the Bessel-Struve kernel, and the ratio of the Bessel-Struve kernel and the Kummer confluent hypergeometric function are investigated. Moreover, lower and upper bounds are given for the Bessel-Struve kernel in terms of the exponential function and some $Tur{\acute{a}}n$ type inequalities are deduced.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.749-755
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• 2009

Support vector classification (SVC) provides more complete description of the lin-ear and nonlinear relationships between input vectors and classifiers. In this paper. we propose the sparse kernel classifier to solve the optimization problem of classification with a modified hinge loss function and absolute loss function, which provides the efficient computation and the sparsity. We also introduce the generalized cross validation function to select the hyper-parameters which affects the classification performance of the proposed method. Experimental results are then presented which illustrate the performance of the proposed procedure for classification.