• 대한산업공학회지
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• 제42권5호
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• pp.327-336
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• 2016

Prediction of customer failure rates plays an important role for establishing appropriate management policies and improving the profitability for industries. For these reasons, many LCD (Liquid crystal display) manufacturing industries have attempted to construct prediction models for customer failure rates. However, most traditional models are based on the parametric approaches requiring the assumption that the data follow a certain probability distribution. To address the limitation posed by the distributional assumption underpinning traditional models, we propose using parameter-free data mining models for predicting customer failure rates. In addition, we use various information associated with product attributes and field return for more comprehensive analysis. The effectiveness and applicability of the proposed method were demonstrated with a real dataset from one of the leading LCD companies in South Korea.

• Wind and Structures
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• 제18권6호
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• pp.619-631
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• 2014

This paper proposes new criteria to fix hidden neuron in Multilayer Perceptron Networks for wind speed prediction in renewable energy systems. To fix hidden neurons, 101 various criteria are examined based on the estimated mean squared error. The results show that proposed approach performs better in terms of testing mean squared errors. The convergence analysis is performed for the various proposed criteria. Mean squared error is used as an indicator for fixing neuron in hidden layer. The proposed criteria find solution to fix hidden neuron in neural networks. This approach is effective, accurate with minimal error than other approaches. The significance of increasing the number of hidden neurons in multilayer perceptron network is also analyzed using these criteria. To verify the effectiveness of the proposed method, simulations were conducted on real time wind data. Simulations infer that with minimum mean squared error the proposed approach can be used for wind speed prediction in renewable energy systems.

• Archives of Plastic Surgery
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• 제47권3호
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• pp.203-208
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• 2020

Vascular anomalies are congenital localized abnormalities that result from improper development and maintenance of the vasculature. The lesions of vascular anomalies vary in location, type, and clinical severity of the phenotype, and the current treatment options are often unsatisfactory. Most vascular anomalies are sporadic, but patterns of inheritance have been noted in some cases, making genetic analysis relevant. Developments in the field of genomics, including next-generation sequencing, have provided novel insights into the genetic and molecular pathophysiological mechanisms underlying vascular anomalies. These insights may pave the way for new approaches to molecular diagnosis and potential disease-specific therapies. This article provides an introduction to genetic testing for vascular anomalies and presents a brief summary of the etiology and genetics of vascular anomalies.

• Earthquakes and Structures
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• 제14권6호
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• pp.551-565
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• 2018

Experimental testing is considered the most realistic approach to obtain a detailed representation of the nonlinear behaviour of masonry-infilled reinforced concrete (RC) structures. Among other applications, these tests can be used to calibrate the properties of numerical models such as simplified macro-models (e.g., strut-type models) representing the masonry infill behaviour. Since the significant cost of experimental tests limits their widespread use, alternative approaches need to be established to obtain adequate data to validate the referred simplified models. The proposed paper introduces a detailed finite element modelling strategy that can be used as an alternative to experimental tests to represent the behaviour of masonry-infilled RC frames under earthquake loading. Several examples of RC infilled frames with different infill configurations and properties subjected to cyclic loading are analysed using the proposed modelling approach. The comparison between numerical and experimental results shows that the numerical models capture the overall nonlinear behaviour of the physical specimens with adequate accuracy, predicting their monotonic stiffness, strength and several failure mechanisms.

• Mycobiology
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• 제48권4호
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• pp.321-325
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• 2020

A Colletotrichum species was isolated from leaves of Cymbidium exhibiting symptoms of anthracnose. In this study, the isolates obtained were identified based on recent taxonomic approaches for the genus Colletotrichum. The identity of the causal pathogen was confirmed using morphological data and phylogenetic analysis of combined multi-gene dataset (internal transcribed spacer, glyceraldehyde 3-phosphate dehydrogenase, chitin synthase-1, actin, histone3, beta-tubulin, and calmodulin). Pathogenicity testing revealed that the isolates were pathogenic to Cymbidium. Based on these results, the fungal pathogen occurring on Cymbidium orchids was identified as Colletotrichum cymbidiicola, which is a newly recorded species in Korea.

• 한국안전학회지
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• 제11권1호
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• pp.11-15
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• 1996

For the assessment of fracture behaviors of structural components, various fracture mechanics parameters have been applied to date. New approaches to analyze structural fracture performance under elastic-plastic condition have been proposed by the development of testing methods for characterization of material behavior which is defying to the analysis by conventional fracture parameters. In this study, on the assumption that, initiation of crack propagation of a piping materials occurs when the crack tip strain field reaches "the local fracture strain", following two major issues are discussed ; 1) The relationship between the critical value of J-integral($J_{IC}$) and the local fracture strain (${\varepsilon}_c$) in uniaxial tensile test in the region of maximum reduction area was described. 2) To proved the validity of above relations a series of tests were performed under various temperature and on the different piping materials.materials.

• 산업경영시스템학회지
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• 제8권11호
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• pp.1-16
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• 1985

기업이 생산하고 있는 생산고추세를 이익도표에 의해서 그 유동상태를 수식화 함으로서 경영활동의 흐름을 과학화하면서 사실의 파악을 체계화하는 연구로서 이제까지의 연구에서는 이들이 폐쇄적이며 개별적인 부문활동으로만 전개됨으로서 전사적 경영이 결여되면서 생산활동에 대한 기업수익과의 상관분석이 불가능했던 것이나 본 연구에서는 이익도표와 생산고추세를 통합함으로서 새로운 체계를 마련하는 동시에 사전분석기법을 개발하고자 시도한 것이다.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제22권2호
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• pp.83-97
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• 2019

Science, Technology, Engineering, and Mathematics (STEM) education has been at the forefront of K-12 curricula in the technology-rich 21st century, with emphasis on how these fields reinforce each other in preparing students for a dynamic future. However, there is a need for greater attention to STEM education research in the mathematics education community, in particular to pedagogical approaches that facilitate integrating the mathematics component of STEM education. Toward this end, the authors report the outcomes of a Project-based Learning (PBL) unit in which upper elementary students integrated STEM elements by researching, crafting, testing, and evaluating kites they created by applying scientific knowledge of aerodynamics and mathematical knowledge of polygons, surface area, graphs, and data analysis. This unit, which the authors developed, implemented, and assessed, demonstrates how STEM subjects and in particular mathematics can be effectively integrated in upper elementary school classrooms through PBL.

• Communications for Statistical Applications and Methods
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• 제26권1호
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• pp.57-67
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• 2019

Income distribution is a major concern in economic theory. In regional economics, it is often of interest to compare income distributions in different regions. Traditional methods often compare the income inequality of different regions by assuming parametric forms of the income distributions, or using summary statistics like the Gini coefficient. In this paper, we propose a nonparametric procedure to test for heterogeneity in income distributions among different regions, and a K-means clustering procedure for clustering income distributions based on energy distance. In simulation studies, it is shown that the energy distance based method has competitive results with other common methods in hypothesis testing, and the energy distance based clustering method performs well in the clustering problem. The proposed approaches are applied in analyzing data from China Health and Nutrition Survey 2011. The results indicate that there are significant differences among income distributions of the 12 provinces in the dataset. After applying a 4-means clustering algorithm, we obtained the clustering results of the income distributions in the 12 provinces.

• 대한수학회지
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• 제59권2호
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• pp.217-233
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• 2022

Although machine learning shows state-of-the-art performance in a variety of fields, it is short a theoretical understanding of how machine learning works. Recently, theoretical approaches are actively being studied, and there are results for one of them, margin and its distribution. In this paper, especially we focused on the role of margin in the perturbations of inputs and parameters. We show a generalization bound for two cases, a linear model for binary classification and neural networks for multi-classification, when the inputs have normal distributed random noises. The additional generalization term caused by random noises is related to margin and exponentially inversely proportional to the noise level for binary classification. And in neural networks, the additional generalization term depends on (input dimension) × (norms of input and weights). For these results, we used the PAC-Bayesian framework. This paper is considering random noises and margin together, and it will be helpful to a better understanding of model sensitivity and the construction of robust generalization.