• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.137-151
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• 2017

The space between urban buildings becomes a waterway during rain events and requires a boundary condition in numerical calculations on grids to separate overland storm flows from building areas. Minimization of the building data distortion as a boundary condition is a necessary step for generating accurate calculation results. A building generalization is used to reduce the distortion of building shapes and areas during a raster conversion. The objective of this study was to provide the appropriate threshold value for building generalization and grid size in a numerical calculation. The impact of building generation on the connectivity of urban storm waterways were analyzed for a general residential area. The building generalization threshold value and the grid size for numerical analysis were selected as the independent variables for analysis, and the number and area of sinks were used as the dependent variables. The values for the building generalization threshold and grid size were taken as the optimal values to maximize the building area and minimize the sink area. With a 3 m generalization threshold, sets of $5{\times}5m$ to $10{\times}10m$ caused 5% less building area and 94.4% more sink area compared to the original values. Two sites representing general residential area types 2 and 3 were used to verify building generalization thresholds for improving the connectivity of storm waterways. It is clear that the recommended values are effective for reducing the distortion in both building and sink areas.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.19-31
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• 2022

In Machine learning, we usually divide the entire data into training data and test data, train the model using training data, and use test data to determine the accuracy and generalization performance of the model. In the case of models with low generalization performance, the prediction accuracy of newly data is significantly reduced, and the model is said to be overfit. This study is about a method of generating training data based on central limit theorem and combining it with existed training data to increase normality and using this data to train models and increase generalization performance. To this, data were generated using sample mean and standard deviation for each feature of the data by utilizing the characteristic of central limit theorem, and new training data was constructed by combining them with existed training data. To determine the degree of increase in normality, the Kolmogorov-Smirnov normality test was conducted, and it was confirmed that the new training data showed increased normality compared to the existed data. Generalization performance was measured through differences in prediction accuracy for training data and test data. As a result of measuring the degree of increase in generalization performance by applying this to K-Nearest Neighbors (KNN), Logistic Regression, and Linear Discriminant Analysis (LDA), it was confirmed that generalization performance was improved for KNN, a non-parametric technique, and LDA, which assumes normality between model building.

• Bulletin of the Korean Mathematical Society
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• v.51 no.1
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• pp.229-235
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• 2014

We enumerate black and white colored d-ary trees with no leftmost ${\square}$-edges, which is a generalization of hybrid binary trees. Then the multi-colored hybrid d-ary trees with the same condition is studied.

• Communications of the Korean Mathematical Society
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• v.14 no.1
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• pp.217-222
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• 1999

The aim of this research is to provide a generalization of the well-known, interesting and useful identity due to Preece by using classical Dixon`s theorem on a sum of \ulcornerF\ulcorner.

• The Pure and Applied Mathematics
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• v.6 no.1
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• pp.33-37
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• 1999

We obtain a generalization of Behera and Panda's result on nonlinear scalar case to the vector version.

• Journal of the Chungcheong Mathematical Society
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• v.14 no.1
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• pp.105-111
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• 2001

The purpose of this paper is to give a new generalization of the well-known common fixed point theorem due to Markov-Kakutani in general settings.

• Honam Mathematical Journal
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• v.35 no.2
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• pp.163-171
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• 2013

By extending the negatively quadrant dependence, the paper puts forth the concept of extended negative quadrant dependence. A generalization of the second Borel-Cantelli lemma is obtained under extended negative quadrant dependence. Some applications are also introduced.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.5 no.2
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• pp.117-136
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• 2001

A generalization of Ostrowski integral inequality for mappings whose derivatives are bounded and applications for general quadrature formulae are given.

• Bulletin of the Korean Chemical Society
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• v.16 no.10
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• pp.952-957
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• 1995

In order to ease the treatment of anisotropic potential when developing the variational RRKM theory, we applied Fano-Racah's recoupling theory to the multipole-multipole interaction, resulting in the great simplification of the anisotropic potentials. The treatment appears as a generalization of Keesom transformation in case of dipole-dipole interaction and provides us with great insights to the characteristics of tensorial interactions in the multipole-multipole interaction system.

• Kyungpook Mathematical Journal
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• v.58 no.4
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• pp.599-613
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• 2018

We study a generalization of the classical Pentagonal Number Theorem and its applications. We derive new identities for certain infinite series, recurrence relations and convolution sums for certain restricted partitions and divisor sums. We also derive new identities for Bell polynomials.