• 한국멀티미디어학회논문지
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• 제14권6호
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• pp.711-718
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• 2011

얼굴인식과 같이 클래스의 수가 변하는 분류 문제에는 학습이 필요하지 않은 k-최근접이웃 분류기가 적합하다. 최근 학습 데이터의 분포를 반영하여 거리 척도를 학습하는 방법은 k 최근접이웃 분류기의 획기적 성능향상을 보고하였다. 거리척도학습 방법은 적용 분야에 따라 성능 개선 정도가 다르다. 본 논문에서는 얼굴인식에 대하여 주요 거리척도학습 방법의 성능을 비교한다. 공개 얼굴 데이터베이스에 대한 실험 결과는 성능 및 계산시간 측면에서 주성분 분석 기반의 마하라노비스 거리척도가 얼굴인식 문제에서는 여전히 좋은 선택이 될 수 있음을 보여준다.

• Nuclear Engineering and Technology
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• 제33권3호
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• pp.270-282
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• 2001

A simple measure of uncertainty importance based on normalized metric distance to quantify the entire change of cumulative distribution functions (CDFs) has been developed for use in probability safety assessments (PSAs). The metric distance measure developed in this study reflects the relative impact of distributional changes of inputs on the change of an output distribution, white most of the existing uncertainty importance measures reflect the magnitude of relative contribution of input uncertainties to the output uncertainty. Normalization is made to make the metric distance measure a dimensionless quantity. The present measure has been evaluated analytically for various analytical distributions to examine its characteristics. To illustrate the applicability and strength of the present measure, two examples are provided. The first example is an application of the present measure to a typical problem of a system fault tree analysis and the second one is for a hypothetical non-linear model. Comparisons of the present result with those obtained by existing uncertainty importance measures show that the metric distance measure is a useful tool to express the measure of uncertainty importance in terms of the relative impact of distributional changes of inputs on the change of an output distribution.

• 대한건축학회논문집:계획계
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• 제34권12호
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• pp.49-54
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• 2018

Applying metric(distance) factor as weighting to spatial syntax is known to not contribute to the explanatory power for the human movement behavior as compared to the geometric(angle) factor according to the negative results of several related studies. However, Kim & Piao (2017) assumed that there is not a problem of the metric factor itself but a problem of the way of applying the metric factor as weighting, and presented a new possibility of the metric factor as weighting by proposing and verifying the methods of applying the metric weighting, which are different from the existing ones. The purpose of this study is to propose advanced methods of applying the metric weighting to space syntax, and to verify whether they contribute to the improvement of explanatory power of space syntax analysis. In this paper, we propose functions for combined depth of distance-step that combine the distance-weighted depth function with the step depth function and apply them to axial segment analysis to check the improvement of explanatory power of them.

• 한국정보과학회논문지:시스템및이론
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• 제31권5_6호
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• pp.288-296
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• 2004

본 논문은 미분오차 척도를 이용하여 메쉬를 간략화 하는 새로울 알고리즘을 제안한다. 많은 간략화 알고리즘은 거리 오차 척도를 이용하였으나, 거리 오차 척도는 높은 곡률을 갖는 동시에 작은 거리오차를 갖는 지역에 대해서는 메쉬 간략화를 위한 정확한 기하학적 오차 측정이 어렵다. 본 논문은 간략화를 위해 새로운 오차 척도인 미분 오차 척도를 제안한다. 미분 오차 척도란 거리 오차 척도와 거리 오차의 1차 미분인 탄젠트 오차 척도, 그리고 거리 오차의 2차 미분인 곡률 오차 척도를 합하여 정의된 오차척도로서, 모델의 특징 부분의 형상을 최대한으로 보존 가능하다. 메쉬는 이산 표면이지만 알지 못하는 부드러운 표면의 불연속선형 근사로 표현될 수 있고, 이산 표면은 미분이 추정 가능하므로 미분 오차 척도라는 새로운 개념을 도입할 수 있다. 본 간략화 알고리즘은 반복적인 모서리 축약(Edge Collapse)에 바탕을 두고 있고, 미분 오차 척도를 이용하여 기하학적으로 원래의 형상이 잘 유지되는 새로운 점의 위치를 찾을 수 있다. 본 논문에서는 기존 방법보다 더 작은 기하학적인 오차와 높은 품질의 간략화 된 모델의 예를 보여준다.

• Genomics & Informatics
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• 제18권1호
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• pp.7.1-7.7
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• 2020

In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

• 한국CDE학회논문집
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• 제3권2호
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• pp.140-144
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• 1998

We propose the area between a pair of non-self-intersecting 2-D parametric curves with same endpoints as an alternative distance metric between the curves. This metric is used when d curve is approximated with another in a simpler form to evaluate how good the approximation is. The traditional set-theoretic Hausdorff distance can he defined for any pair of curves but requires expensive calculations. Our proposed metric is not only intuitively appealing but also very easy to numerically compute. We present the numerical schemes and test it on some examples to show that our proposed metric converges in a few steps within a high accuracy.

• Nonlinear Functional Analysis and Applications
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• 제28권2호
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• pp.557-570
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• 2023

The conceptions of generalized b-metric spaces or G_b-metric spaces and a generalized Ω-distance mappings play a key role in proving many important theorems in existence and uniqueness of fixed point theory. In this manuscript, we establish a new type of contraction namely, Ω_b(𝓗, 𝜃, s)-contraction, this contraction based on the concept of a generalized Ω-distance mappings which established by Abodayeh et.al. in 2017 together with the concept of 𝓗-simulation functions which established by Bataihah et.al [10] in 2020. By utilizing this new notion we prove new results in existence and uniqueness of fixed point. On the other hand, examples and application were established to show the importance of our results.

• Korean Journal of Mathematics
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• 제30권4호
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• pp.679-686
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• 2022

In this study, the concept of lacunary statistical convergence is studied in G-metric spaces. The G-metric function is based on the concept of distance between three points. Considering this new concept of distance, we examined the relationships between GS, GS_θ, Gσ₁ and GN_θ sequence spaces.

• Korean Journal of Mathematics
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• 제4권2호
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• pp.117-124
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• 1996

In this paper we define a new fuzzy metric $\tilde{\theta}$ of fuzzy number sequences, and prove that the space of convergent sequences of fuzzy numbers is a fuzzy complete metric space in the fuzzy metric $\tilde{\theta}$.

• Kyungpook Mathematical Journal
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• 제62권4호
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• pp.773-785
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• 2022

In this paper, we propose the notion of a distance between n points, called a g-metric, which is a further generalized G-metric. Indeed, it is shown that the g-metric with dimension 2 is the ordinary metric and the g-metric with dimension 3 is equivalent to the G-metric.