• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.39-51
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• 2004

This study aims to suggest new algorithm, named as Simoo, in order to improve spatial conflicts and vector displacement between linear features in generalization of the linear features. Main principles of Simoo algorithm is adoption of simplification and smoothening methods. Tolerance conditions used in Simoo are perpendicular length, external angle, and average vertex length. Main characteristics of Simoo are the application of scale, cartographic refinement, minimization of logical errors, and maintenance of geographical properties. The Simoo was applied through comparison to existing Douglas-Peucker algorithm. Resultantly, maintenance ratios of line such as coastal line and stream network were over 97% in both algorithms. The elimination ratio of vertex points may be more effective in Douglas-Peucker than in Simoo. Spatial conflicts between linear features may be more minimized in Simoo. The curvature and smoothening of lines become decreased in scale in application of Simoo. Finally, Simoo algorithm may be more effective than Douglas-Peucker for cartographic generalization.

• Structural Engineering and Mechanics
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• v.78 no.1
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• pp.53-66
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• 2021

The determination of the damage index to reveal the performance level of a structure can constitute the seismic risk generalization approach based on the parametric analysis. This study implemented this concept to one kind of civil engineering structure that is the concrete gravity dam. Different cases of the structure exhibit their individual responses, which constitute different considerations. Therefore, this approach allows the parametric study of concrete as well as soil for evaluating the seismic nature in the generalized case. To ensure that the target algorithm applicable to most of the concrete gravity dams, a very simple procedure has been considered. In order to develop a correlated algorithm (by response surface methodology; RSM) between the ground motion and the structural property, randomized sampling was adopted through a stochastic method called half-fractional central composite design. The responses in the case of fluid-foundation-dam interaction (FFDI) make it more reliable by introducing the foundation as being bounded by infinite elements. To evaluate the seismic generalization of FFDI models, incremental dynamic analysis (IDA) was carried out under the impacts of various earthquake records, which have been selected from the Pacific Earthquake Engineering Research Center data. Here, the displacement-based damage indexed fragility curves have been generated to show the variation in the seismic pattern of the dam. The responses to the sensitivity analysis of the various parameters presented here are the most effective controlling factors for the concrete gravity dam. Finally, to establish the accuracy of the proposed approach, reliable verification was adopted in this study.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.148-154
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• 2021

Text-Independent speaker verification needs to extract text-independent speaker embedding to improve generalization performance. However, deep neural networks that depend on training data have the potential to overfit text information instead of learning the speaker information when repeatedly learning from the identical time series. In this paper, to prevent the overfitting, we propose a segment unit shuffling layer that divides and rearranges the input layer or a hidden layer along the time axis, thus mixes the time series information. Since the segment unit shuffling layer can be applied not only to the input layer but also to the hidden layers, it can be used as generalization technique in the hidden layer, which is known to be effective compared to the generalization technique in the input layer, and can be applied simultaneously with data augmentation. In addition, the degree of distortion can be adjusted by adjusting the unit size of the segment. We observe that the performance of text-independent speaker verification is improved compared to the baseline when the proposed segment unit shuffling layer is applied.

• Journal of Information Technology Services
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• v.22 no.5
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• pp.71-86
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• 2023

Recently, various geographic information systems have been used based on spatial information of geographic information systems. Accordingly, it is essential to produce a large-scale map as a small-scale map for various uses of spatial information. However, maps currently being produced have inconsistencies between data due to production timing and limitations in expression, and productivity efficiency is greatly reduced due to errors in products or overlapping processes. In order to improve this, various efforts are being made, such as publishing research and reports for automating domestic mapping, but because there is no specific result, it relies on editors to make maps. This is mainly done by hand, so the time required for mapping is excessive, and quality control for each producer is different. In order to solve these problems, technology that can be automatically produced through computer programs is needed. Research has been conducted to apply the rule base to geometric generalization. The algorithm tolerance setting applied to rule-based modeling is a factor that greatly affects the result, and the level of the result changes accordingly. In this paper, we tried to study the effectiveness of mapping according to tolerance setting. To this end, the utility was verified by comparing it with a manually produced map. In addition, the original data and reduction rate were analyzed by applying generalization algorithms and tolerance values. Although there are some differences by region, it was confirmed that the complexity decreased on average. Through this, it is expected to contribute to the use of spatial information-based services by improving tolerances suitable for small-scale mapping regulations in order to secure spatial information data that guarantees consistency and accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.77-86
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• 2004

In general, small-sized neural networks, even though they show good generalization performance, tend to fail to team the training data within a given error bound, whereas large-sized ones learn the training data easily but yield poor generalization. Therefore, a way of achieving good generalization is to find the smallest network that can learn the data, called the optimal-sized neural network. This paper proposes a new scheme for network pruning with ‘impact factor’ which is defined as a multiplication of the variance of a neuron output and the square of its outgoing weight. Simulation results of function approximation problems show that the proposed method is effective in regression.

• East Asian mathematical journal
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• v.31 no.4
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• pp.459-481
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• 2015

In this study, we investigated whether the theorem is established even if we replace a 'square' element in the Euclidean proof of the Pythagorean theorem with different figures. At this time, we used different figures as equilateral, isosceles triangle, (mutant) a right triangle, a rectangle, a parallelogram, and any similar figures. Pythagorean theorem implies a relationship between the three sides of a right triangle. However, the procedure of Euclidean proof is discussed in relation between the areas of the square, which each edge is the length of each side of a right triangle. In this study, according to the attached figures, we found that the Pythagorean theorem appears in the following three cases, that is, the relationship between the sides, the relationship between the areas, and one case that do not appear in the previous two cases directly. In addition, we recognized the efficiency of Euclidean proof attached the square. This proving activity requires a mathematical process, and a generalization of this process is a good material that can experience the diversity and rigor at the same time.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.293-301
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• 2001

This paper reviews three methods to compute a pointwise confidence interval of neuro-fuzzy models and compares their estimation perfonnanee through simulations. The eOITl.putation methods under consideration include stacked generalization using cross-validation, predictive error bar in regressive models, and local reliability measure for the networks employing a local representation scheme. These methods implemented on the neuro-fuzzy models are applied to the problems of simple function approximation and chaotic time series prediction. The results of reliability estimation are compared both quantitatively and qualitatively.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.2
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• pp.435-455
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• 2006

While numerous studies have empirically investigated user behavior in LIS research community, less research has attempted to examine such studies in methodological perspective. Reflecting this, relevant studies have suggested the need to develop methodological framework for such studies. This study conducted content analyses of user behavior studies recently published in JASIST and analyzed factors which affect the external validity of result of such researches. The findings revealed various types and cases related to the generalization of the study results. Based on these, a methodological framework for user behavior studies were suggested.

• Bulletin of the Korean Mathematical Society
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• v.22 no.2
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• pp.83-85
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• 1985

Let K be a real function field over a real closed field F. Then there exists an F-place .phi.:K.rarw.F.cup.{.inf.}. This is Lang's Existence of Rational Place Theorem (6). There is an equivalent version of Lang's Theorem in (4). That is, if K is a function field over a field F, then, for any ordering P$_{0}$ on F which extends to K, there exists an F-place .phi.: K.rarw.F'.cup.{.inf.} where F' is a real closure of (F, P$_{0}$). In [2], Knebusch pointed out the converse of the version of Lang's Theorem is also true. By a valuation theoretic approach to Lang's Theorem, we have found out the following generalization of Lang and Knebusch's Theorem. Let K be an arbitrary extension field of a field F. then an ordering P$_{0}$ on F can be extended to an ordering P on K if there exists an F-place of K into some real closed field R containing F. Of course R$^{2}$.cap.F=P$_{0}$. The restriction K being a function field of F is vanished, though the codomain of the F-place is slightly varied. Therefore our theorem is a generalization of Lang and Knebusch's theorem.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.217-224
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• 2011

This paper proposes DDPT(Dynamic Data Protection Technique) which solves the problem of private information exposure occurring in a dynamic database environment. The DDPT in this paper generates the MAG(Multi-Attribute Generalization) rules using multi-attributes generalization algorithm, and the EC(equivalence class) satisfying the k-anonymity according to the MAG rules. Whenever data is changed, it reconstructs the EC according to the MAC rules, and protects the identification exposure which is caused by the EC change. Also, it measures the information loss rates of the EC which satisfies the ${\ell}$-diversity. It keeps data accuracy by selecting the EC which is less than critical value and enhances private information protection.