• 대한수학교육학회지:학교수학
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• 제18권3호
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• pp.611-623
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• 2016

본 연구는 2009 개정 수학과 교육과정의 <기초수학>, <수학I>, <수학II>와 교과서를 토대로 용어 기호의 정의에서 학생들이 어려움을 겪을 수 있는 점을 짚어 보고 용어 기호의 선정과 앞으로의 개선 과제를 제안하였다. 현재 지적된 문제점을 개선할 수 있는 과제로 교육과정 개발에서 용어 기호에 대한 심도 있는 분석과 논의가 필요하고 그 결과가 공개될 필요가 있으며, 교과서 검정에서 용어 및 기호에 대한 기준을 적절히 마련하기 위해 노력할 필요가 있고, 수학 용어 및 기호의 정의 방법에서 학교급간 정의방법의 차이, 특히 초등학교와 중등학교의 정의 방법의 차이를 검토할 필요가 있으며, 수학과 교육과정에서 용어 기호의 교체나 교과서에 소개할 방안을 고려할 것을 제안하였다.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.73-84
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• 2020

Existing studies disagree over the core predictors of firm-level financial choices in developing countries. The general practice only validates the traditional capital structure model, which leads to inconsistency and a lack of novelty. This study removed overfitting issues among existing factors and presented the most reliable and advanced capital structure model in Pakistani firms. The panel data include 368 Pakistani companies from 19 non-financial sectors over the period 2004 to 2017. We apply Akaike and Bayesian Information Criteria to remove overfitting issues among inconsistent proxies in the capital structure model. The fixed effects regression is used for basic results and the Generalized Method of Moments is applied to control the endogeneity. Besides the conventional proxies, we report that credit rating, distance from bankruptcy, managerial concentration, and institutional quality are the most advanced capital structure determinants in Pakistan. These predictors remain significant across firm size and growth levels. Also, the findings confirm that new predictors are reliable to define capital structure dynamics and improve the speed of adjustment in overall and sub-sample analysis. The major findings suggest that managers and policymakers should consider these advanced predictors to design their financial settings in firms.

• 농업과학연구
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• 제49권3호
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• pp.607-617
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• 2022

As the number of households raising pets increases, the pet food industry is also growing. Since pets cannot express their intention explicitly, it appears that the owner's perception mainly affects the selection of products related to pets. In this study, consumers were categorized based on their interest in food choices and the factors influencing their interest in pet food were empirically analyzed. For the analysis, a cluster analysis, factor analysis, and Tobit analysis were conducted using consumer survey data for raising companion animals. The major findings of the study were as follows. As a result of the factor analysis and cluster analysis using questions for consumers' food consumption choices, consumer types were classified into high-interest, low-interest, and practical-seeking types. The degree of interest in pet food was high in the order of high-interest, practical-seeking, and low-interest type. Demographic characteristics such as gender, education, and household type correlate with differences in the degree of interest in pet food, and the food selection criteria of consumers also affect the degree of interest in pet food. These results show that consumers who are more interested in their food choices are more interested in pet food, and this will make possible to know pet owner's purchasing behavior for pet food.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2007년도 춘계학술대회
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• pp.241-247
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• 2007

Multi-criteria decision making is deducing the relativistic importance in the criterion of decision making and each alternative which is able to make a variety of choices measures the preferred degree in the series of low-ranking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fun-diametral problem decision maker should solve for multi-criteria decision making is evaluating a set of activities which are considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we study about effective consumer preference to towels made of paper according to the three kinds of intensities of products from some domestic company, using the AHP.

• 한국초등과학교육학회지:초등과학교육
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• 제37권2호
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• pp.188-205
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• 2018

For STEM education science teachers usually choose topics which are related to both science and other disciplinary contents. Nevertheless it is not clear for the teachers to adopt what kind of criteria for their choices. Interdisciplinary teaching is not a mixture of science content with another one from different disciplines as resources for the content teaching. Instead the criteria and perspectives for the integration need to be clearly defined. In this study we investigated how to integrate science and other disciplines in terms of interdisciplinary teaching. Family resemblance approach by Wittgenstein, recently revised by Erduran and Dagher, was applied to comparative analysis of science, math, and physical education curriculum documents in Korea. Aim and value, methodological rules and methods, knowledge, and activities in each discipline were compared and analyzed with the view of FRA. Results of the study described alternative criteria of how to find appropriate topics for interdisciplinary teaching.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 춘계공동학술대회
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• pp.123-131
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• 2006

Multi-criteria decision making is deducing the relative importance in the criterion of decision making and each alternative which is able to making a variety of choices measures the preferred degree in the series of low-raking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fundamental problem decision maker solve for multi-criteria decision making is evaluating a set of activities which are considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we are the eigenvector methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.129-142
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• 2017

In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes.

• 대한안전경영과학회지
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• 제8권4호
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• pp.205-218
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• 2006

Multi-criteria decision making is deducing the relative importance in the criterion of decision making and each alternative which is able to making a variety of choices measures the preferred degree in the series of town ranking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fundamental problem decision maker solve for multi-criteria decision making is evaluating a set of activities which an considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we use the compensatory models for the optimal decision making. For the purpose of optimal decision making, the data of five different car models are used in Europe.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제2권1호
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• pp.41-60
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• 1998

This paper derives a consistent and bias corrected extension of Akaike's Information Criterion (AIC), $AIC_{bc}$, based on Kullback-Leibler information. This criterion has terms that penalize the overparametrization more strongly for small and large samples than that of AIC. The overfitting problem of the asymptotically efficient model selection criteria for small and large samples will be overcome. The $AIC_{bc}$ also provides a consistent model order selection. Thus, it is widely applicable to data with small and/or large sample sizes, and to cases where the number of free parameters is a relatively large fraction of the sample size. Relationships with other model selection criteria such as $AIC_c$ of Hurvich, CAICF of Bozdogan and etc. are discussed. Empirical performances of the $AIC_{bc}$ are studied and discussed in better model order choices of a linear regression model using a Monte Carlo experiment.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권3호
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• pp.215-223
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• 2005

An electrical machine for a high-speed flywheel for energy storage in large hybrid electric vehicles is described. Design choices for the machine are motivated: it is a radial-flux external-rotor permanent-magnet synchronous machine without slots in the stator iron and with a shielding cylinder. An analytical model of the machine is briefly introduced whereafter optimization of the machine is discussed. Three optimization criteria were chosen: (1) torque; (2) total stator losses and (3) induced eddy current loss on the rotor. The influence of the following optimization variables on these criteria is investigated: (1) permanent-magnet array; (2) winding distribution and (3) machine geometry. The paper shows that an analytical model of the machine is very useful in optimization.