• Journal of the Korean Wood Science and Technology
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• v.12 no.3
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• pp.3-8
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• 1984

It is shown that Paul and Jones' Rule of Mixtures modified by Smith and Cox's theory can be used for the fiber-reinforced, sulfur-based composites, when the constant for the linear regression equation is given. The computation results, programmed by Hewlett Packard 75C (HP 75C) using math rom pack for the linear regression form, expressed as $E_c=\frac{1}{3}aE_fV_f+bE_mV_m$, turn out to be a=3.27-3.54 b=-2.47~-2.80. This results indicate that the factors such as density of fiber mat and the amount of matrix used have nothing for affecting the numerical value of the constants a and b of the linear regression form. Conclusively this results also show that the Paul and Jones' Rule of Mixtures which has been used for the composites made by randomly-oriented long fiber can also be used for the composites made by short fiber with the same fiber orientation such as wood and lignocellulosic fibers.

• Korean Journal of Health Education and Promotion
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• v.13 no.2
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• pp.130-166
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• 1996

As compared with body height and body weight by ages and sexes, by means of the data reported under other researchers from 1967 to 1994 for 33 years, this study obtained the estimate value of body height and body weight by ages and sexes for the same period, and figured out prediction value of body height and body weight in the ages of between 6 and 14 from 1995 to 2000. These surveys and measurements took for one year from October 1st 1994 to September 30th. As shown in the 〈Table 1〉, in order to calculate the establishment, estimate value and prediction value of the chronological regression model of body height and body weight, by well-grounded 17 representative research papers, this research statistically tested propriety of liner regression model by the residual analysis in advance of being reconciled to simple liner regression model by the autonomous variable-year and the subordinate variable-body weight and measured prediction value, theoretical value from 1962 to 1994 by means of 2nd or 3rd polynomial regression model, with this redult did prediction value from 1995 to 2000. 1. Chronological Change of Body Height and Body Weight The analysis result from regression model of the chronological body height and body weight for the aged 6 - 16 in both sexes ranging from 1962 to 1994, corned from the 〈Table 2-20〉. On the one hand, the measurement value of respective researchers had a bit changes by ages with age growing, but the other hand, theoretical value, prediction value showed the regular increase by the stages and all values indicated a straight line on growth and development with age growing. That is, in case of the aged 6, males had 109.93cm in 1962 and females 108.93cm, but we found the increase that males had 1I8.0cm, females 1I3.9cm. In theoretical value, prediction value, males showed the increase from 109.88cm to 1I7.89cm and females from 109.27cm to 1I5.64cm respectively. There was the same inclination toward all ages. 2. Comparision to Measurement Value and Prediction Value of Body Height and Body Weight in 1994 As shown in the 〈Table 21〉, in case of body height, measurement value and prediction value of body height and body weight by ages and sexes almost showed the similiar inclination and poor grade, in case of body weight, prediction value in males had a bit low value by all ages, and prediction value in females had a high value in adolescence, to the contrary, a low value in adult. 3. Prediction Value of Body Height and Body Weight from 1995 to 2000 This research showed that body height and body weight remarkably increased in adolescence but slowly in adult. This study represented that Korean physique was on the increase and must be measured continually hereafter.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.800-802
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• 2000

In this paper, we propose the Self-Organizing Networks(SON) based on competitive Fuzzy Polynomial Neuron(FPN) for the optimal design of nonlinear process system. The SON architectures consist of layers with activation nodes based on fuzzy inference rules. Here each activation node is presented as FPN which includes either the simplified or regression Polynomial fuzzy inference rules. The proposed SON is a network resulting from the fusion of the Polynomial Neural Networks(PNN) and a fuzzy inference system. The conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as liner, quadratic and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership functions are studied. Chaotic time series data used to evaluate the performance of our proposed model.

• Journal of Families and Better Life
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• v.6 no.1
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• pp.39-50
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• 1988

The objectives of this study were (1) to find out if consumer attitude variables, that is, attitude on post-industrial age consumer value, attitude on consumerism, have significant effects on consumer role performance, (2) to find out if socio-demographic variables, that is, age, educational level, family income, social status, have significant effects on consumer role performance, (3) to examine the independent influences of variables related to each subarea consumer role performance. The data used in this study inclued 573 homemakers living in Seoul. Statistical methods were ANOVA and Multiple Regression Analysis. Major findings were as follows;1) consumer role performance and each subarea consumer role performance differed significantly according to all the variables related to consumer attitude. 2) All the socio-demographic variables had significant effects on consumer role performance. 3) Resulting from multiple regression analysis, consumer role performance and all the subarea consumer role performance had the positive liner relationships with the variables such as attitude on post-industrial age consumer value, attitude on consumerism, educational level, The most influencial variable was attitude on post-industrial age consumer value, and in turn educational level and attitude on consumerism.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.953-958
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• 2013

This study suggests a measurement error model based on skewed normal distribution instead of normal distribution to identify slope parameter properties in a simple liner regression model. We prove that the slope parameter in a simple linear regression model is underestimated.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1483-1490
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• 2004

To accomplish a project successfuly, we have to estimate develpment effort accurately. But, development effort is different to software size and operation environment. Usually, we made use of function point for estimating development effort. In this paper. we make use of 789 project data. It is related to development projects in 1990`s. We investigate the variable affecting development effort. Also, we exedcute multiple liner regression analysis for looking linear relation about variables. We find the regression equation for multistage by dividing PDR that influ-enced development effort step by step.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.371-378
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• 2003

The compression index of clay distributed in the west and south coast of the Korean Peninsula had been studied. Compression index was obtained from the conventional consolidation test, and was conducted accordingly to obtain the field virgin compression curve by means of Schmertmann's graphical correction. To examine a correlation closely between physical properties of soils($e_o$, LL, w) and compression index(Cc), linen. and non-linear regression analysis were employed based on the data collected from tests. The conclusions are as follows. The compression index obtained by means of Schmereann's graphical correction is about 1.16 times for the value of original oedometer test curve for U/D samples. Non-liner regression curve was preferable to establish a correlation equation rather than linear regression curve. All derived equations so far achieved have been summarized and given. However, linear equation is better for practical use so that part by part simplified linear equations were also suggested alternatively together with their own non-linear regression curve.

• Korean Journal of Adult Nursing
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• v.27 no.3
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• pp.273-282
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• 2015

Purpose: The objective of this study was to identify the predictors of self-care behaviors among elderly patients with hypertension using quantile regression method. Methods: A total of 253 elderly patients diagnosed with hypertension was recruited via 3 different medical clinics for the study. The quantile regression and a liner regression was conducted using Stata 12.0 program by analyzing predictors of self-care behaviors. Results: In the ordinary least square, self-efficacy, period of disease, and education level explained 42% of the variance in self-care activities. In the quantile regression, affecting predictors of self-care behaviors were self-efficacy for all quantiles, the period of disease for from 60% quantile to 90% quantile, education level for 20%, 30%, and 50% quantiles, economic status for 10%, 50%, and 60% quantiles, age for 10%, 70% quantiles, fatigue for 10% quantile, knowledge about hypertension for 10% and 20% quantiles, and depression for 30% and 40% quantiles. Conclusion: The affecting predictors of self-care behaviors among elderly with hypertension were different from the level of self-care behaviors. These results indicated the significance in assessing predictors according to the level of self-care behaviors when clinical nurses examine the patients' health behaviors and plan any intervention strategies. Specially, education level and knowledge about hypertension were the significant predictors of self-care activities for low quantiles. Clinical nurses may promote self-care activities of the given population though health education programs.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.84-92
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• 2021

Care services are a significant asset in human life. Care in its overall nature focuses on human needs and covers several aspects such as health care, homes, personal care, and education. In fact, care deals with many dimensions: physical, psychological, and social interconnections. Very little information is available on estimating the cost of care services that provided to orphans and abandoned children. Prediction of the cost of the care system delivered by governmental or non-governmental organizations to support orphans and abandoned children is increasingly needed. The purpose of this study is to analyze the care cost for orphanage organizations in Saudi Arabia to forecast the cost as well as explore the most influence factor on the cost. By using business analytic process that applied statistical and machine learning techniques, we proposed a model includes simple linear regression, Naive Bayes classifier, and Random Forest algorithms. The finding of our predictive model shows that Naive Bayes has addressed the highest accuracy equals to 87% in predicting the total care cost. Our model offers predictive approach in the perspective of business analytics.