• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.361-368
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• 2016

While dimension reduction methods on high dimensional data have been widely studied, research on dimension reduction methods for high dimensional streaming data with concept drift is limited. In this paper, we review incremental dimension reduction methods and propose a method to apply dimension reduction efficiently in order to improve classification performance on high dimensional streaming data with concept drift.

• Journal of electromagnetic engineering and science
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• v.17 no.4
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• pp.241-243
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• 2017

In this paper, we have presented an equation for estimating the gain of a Fabry-Perot cavity (FPC) antenna with a finite dimension. When an FPC antenna has an infinite dimension and its height is half of a wavelength, the maximum gain of that FPC antenna can be obtained theoretically. If the FPC antenna does not have a dimension sufficient for multiple reflections between a partially reflective surface (PRS) and the ground, its gain must be less than that of an FPC antenna that has an infinite dimension. In addition, the gain of an FPC antenna increases as the dimension of a PRS increases and becomes saturated from a specific dimension. The specific dimension where the gain starts to saturate also gets larger as the reflection magnitude of the PRS becomes closer to one. Thus, it would be convenient to have a gain equation when considering the dimension of an FPC antenna in order to estimate the exact gain of the FPC antenna with a specific dimension. A gain versus the dimension of the FPC antenna for various reflection magnitudes of PRS has been simulated, and the modified gain equation is produced through the curve fitting of the full-wave simulation results. The resulting empirical gain equation of an FPC antenna whose PRS dimension is larger than $1.5{\lambda}_0$ has been obtained.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.13-22
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• 1998

Fractals which represent many of the sets in various scien-tific fields as well as in nature is geometrically too complicate. Then we usually use Hausdorff dimension to estimate their geometrical proper-ties. But to explain the fractals from the hausdorff dimension induced by the Euclidan metric are not too sufficient. For example in digi-tal communication while encoding or decoding the fractal images we must consider not only their geometric sizes but also many other fac-tors such as colours densities and energies etc. So in this paper we define the dimension matrix of the sets by redefining the new metric.

• Journal of Korea Water Resources Association
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• v.31 no.5
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• pp.587-597
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• 1998

Researchers have suggested that the fractal dimension of the stream length is uniform in all the streams of the basin and the estimates of the fractal dimension are in between 1.09 and 1.13 which may be considerably large values. In this study, the fractal dimension for the Ieemokjung subbasin streams in the Pyungchang River basin which is one of the IHP representative basins in Korea are estimated for each stream order using three scale maps of a 1/50,000, 1/25,000, and 1/5,000. As a result, the fractal dimension of the stream length is different by stream order and the fractal dimension of all streams shows a lower value in comparison to that of the previous studies. As a result of the fractal dimension estimation for the Ieemokjung subbasin streams, we found that the fractal dimension of the stream length shows different estimates in stream orders. The fractal dimension of 1st and 2nd order stream is 1.033, and the fractal dimension of 3rd and 4th order stream is 1.014. This result is different from the previous studies that the fractal dimension of the stream length is uniform in all streams of the basin. The fractal dimension for a whole stream length is about 1.027. Therefore, the previous estimates of 1.09 and 1.13 suggested as the fractal dimension of the stream length may be overestimated in comparison with estimated value in this study.

• Journal of Environmental Science International
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• v.11 no.9
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• pp.915-923
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• 2002

Recently, GIS(Geographic Information System) is used to extract various hydrological factors from DEM(Digital Elevation Model) in river basin. Therefore, this study aims at the determination of river fractal dimension using DEM. In this paper, the main-stream length in river basin was grid-analyzed for each scale(1/5,000, 1/25,000, 1/50,000) and each cell size(5m$\times$5m, l0m$\times$l0m, 20m$\times$20m, 30m$\times$30m, 40m$\times$40m, 50m$\times$50m, 60m$\times$60m, 70m$\times$70m, 80m$\times$80m, 90m$\times$90m, 100m$\times$l00m, 120m$\times$120m, 150m$\times$150m) using GIS. Also, fractal dimension was derived by analyzing correlation among main-stream lengths, scale, and cell size which were calculated here. The result of calculating fractal dimension for each cell size shows that the fractal dimension on the main-stream length is 1.028.

• Bulletin of the Korean Mathematical Society
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• v.51 no.2
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• pp.519-530
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• 2014

Let (R,m) be a Noetherian local ring and M a finitely generated R-module. For an integer s > -1, we say that M is Cohen-Macaulay in dimension > s if every system of parameters of M is an M-sequence in dimension > s introduced by Brodmann-Nhan [1]. In this paper, we give some characterizations for Cohen-Macaulay modules in dimension > s in terms of the Noetherian dimension of the local cohomology modules $H^i_m(M)$, the polynomial type of M introduced by Cuong [5] and the multiplicity e($\underline{x}$;M) of M with respect to a system of parameters $\underline{x}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1346-1353
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• 2001

This paper presents an algorithm for the design of 2 dimension separable denominator digital filter(SDDF). The proposed algorithm is based on the reduced dimensional decomposition not only 2 dimension SDDF's but also of given 2 dimension specification. The frequency domain design of 2 dimension separable denominator digital filters based on the reduced dimensional decomposition can be realized when the given 2 dimension frequency specification are optimally decomposed into a pair of 1 dimension digital filter specification via singular value decomposition. the algorithm is computationally efficient and numerically stable. In case of the low pass filter, the approximation error of the proposed design algorithm is $e_{m}$=5.17, $e_{r1}$ =8.78, $e_{r2}$=7.34, while in case of band pass filter, the approximation error is $e_{m}$=13.00, $e_{r1}$=62.76, $e_{r2}$=62.7676.7676

• Bulletin of the Korean Mathematical Society
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• v.49 no.5
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• pp.1067-1079
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• 2012

Let M be a right R-module, (S, ${\leq}$) a strictly totally ordered monoid which is also artinian and ${\omega}:S{\rightarrow}Aut(R)$ a monoid homomorphism, and let $[M^{S,{\leq}}]_{[[R^{S,{\leq}},{\omega}]]$ denote the generalized inverse polynomial module over the skew generalized power series ring [[$R^{S,{\leq}},{\omega}$]]. In this paper, we prove that $[M^{S,{\leq}}]_{[[R^{S,{\leq}},{\omega}]]$ has the same uniform dimension as its coefficient module $M_R$, and that if, in addition, R is a right perfect ring and S is a chain monoid, then $[M^{S,{\leq}}]_{[[R^{S,{\leq}},{\omega}]]$ has the same couniform dimension as its coefficient module $M_R$.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.519-526
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• 2019

Response dimension reduction in a sufficient dimension reduction (SDR) context has been widely ignored until Yoo and Cook (Computational Statistics and Data Analysis, 53, 334-343, 2008) founded theories for it and developed an estimation approach. Recent research in SDR shows that a semi-parametric approach can outperform conventional non-parametric SDR methods. Yoo (Statistics: A Journal of Theoretical and Applied Statistics, 52, 409-425, 2018) developed a semi-parametric approach for response reduction in Yoo and Cook (2008) context, and Yoo (Journal of the Korean Statistical Society, 2019) completes the semi-parametric approach by proposing an unstructured method. This paper theoretically discusses and provides insightful remarks on three versions of semi-parametric approaches that can be useful for statistical practitioners. It is also possible to avoid numerical instability by presenting the results for an orthogonal transformation of the response variables.

• Journal of Oral Medicine and Pain
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• v.8 no.1
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• pp.121-126
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• 1983

This study is conducted with a view to make correct sexual differentiation by the utilization of discriminant functions. For that purpose were randomly sampled out 148 young adults testes, comprising 67 males and 81 females, ranging from 15 through 18 years fo age. Based on the values made available from the measurement of 6 items corresponding to the maxillary cast models, a statistical analysis was made to abstract feasible discriminant functions. The results findings are as follows: 1. The mean value by sex indicates, in all items, higher one in male group than in female group. 2. Through the measurement were defined as singnificant items in sexual differentiation the bucco-lingual dimensions of canine, 1st-molar, 2nd molar, and 1st bimolat width. 3. Derived from the value from measurement items were discriminant functions with the intention of applying them to sexual differentiation, as follows: 1) Y=-25.4112+0.7513BL3+0.3298BL4-0.2854BL5+0.7350BL6-0.3482BL7+0.2893AW (as tested by Method I) 2)Y=-25.0628+0.7737BL3+0.7468BL6-0.3885BL5+0.2951AW(as tested by Method II) BL3 : Bucco-lingual dimension of upper canine BL4 : Bucco-lingual dimension of upper first prmolar BL5 : Bucco-lingual dimension of upper second premolar BL5 : Bucco-lingual dimension of upper first molar BL6 : Bucco-lingual dimension of upper second molar AW : Upper first bimolar width 4. Sexual defferentiation in terms of descriminant functions represented a probility of 74.6%.