• Journal of Korean Society for Atmospheric Environment
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• 제24권E2호
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• pp.92-101
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• 2008

The objective of this study is to evaluate and improve the capability of the Weather Research and Forecasting (WRF) model in simulating fog and visibility in local airports over Korea. The WRF model system is statistically evaluated for the 48-fog cases over Korea from 2003 to 2006. Based on the 4-yr evaluations, attempts are made to improve the simulation skill of fog and visibility over Korea by revising the statistical coefficients in the visibility algorithms of the WRF model. A comparison of four existing visibility algorithms in the WRF model shows that uncertainties in the visibility algorithms include additional degree of freedom in accuracy of numerical fog forecasts over Korea. A revised statistical algorithm using a linear-regression between the observed visibility and simulated hydrometeors and humidity near the surface exhibits overall improvement in the visibility forecasts.

• 경영과학
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• 제17권2호
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• pp.39-54
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• 2000

This paper presents a causal forecasting model using guided genetic algorithm in continuous manufacturing process. The guide genetic algorithm(GGA) is an extended genetic algorithm(GA) using penalty function and population diversity index to increase forecasting accuracy. GGA adds to the canonical GA the concept of a penalty function to avoid selecting the unproductive chromosomes and to make a proper searching direction. Also, GGA modifies the current population using the similarity of chromosomes to avoid falling into the trap of local optimal solution. For investigation GGA performance, we used a set of real data that was collected in local glass melting processes, and experimental results show the proposed model results in the better forecasting accuracy than linear regression model and canonical GA.

• 전기학회논문지
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• 제59권8호
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• pp.1497-1505
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• 2010

The present study was performed to investigate the effect of aging on muscular activity of older subjects under the condition of fixed load muscle contraction. SEMG signals were recorded from old (46 women) and young (45 women) groups performing sustained isometric elbow flexion contraction with a fixed load during 30 seconds. Linear regression and mean square error (MSE) analysis with four characteristic variables (ARV, RMS, MDF, MNF) were used to compare the age-related difference (of local muscle fatigue and fluctuation of the amplitude and frequency) in the SEMG signal. The main results can be summarized as follows: During sustained muscle contraction with a fixed load: i) the MSE values of amplitude (ARV, RMS) and frequency (MDF, MNF) variables were more than 30% higher for the young than for the old adults; ii) the measures of local muscle fatigue (slope of the MDF and MNF) indicated greater fatigue in the old; and iii) the rate of increase of the SEMG amplitude was higher for the young than the old.

• Management Science and Financial Engineering
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• 제16권1호
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• pp.1-16
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• 2010

In Nigeria, Igbemo-Ekiti is synonymous with a popular local rice which, nevertheless, is characterized with contaminations. Efforts of Government through the Agricultural Development Project (ADP) to improve rice quality in the state, have failed to yield the desired results. This study, therefore, reports the peculiar factors influencing the processing of rice in Igbemo-a major local producing town in Ekiti State, Nigeria. 72 respondents were interviewed, which was a census of the rice processors in 21 residential quarters of the town. Using the multiple linear regression models for analysis, the study discovered that; (i) status of the processors, (ii) expenditure on processing (iii) training acquired before commencing work, and (iv) storage facilities are crucial factors impacting rice processing activities in the town. The paper canvasses for policy measures based on research findings.

• International Journal of Contents
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• 제15권3호
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• pp.47-54
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• 2019

The purpose of this study is to explore the factors affecting the community well-being of residents through empirical analysis. Rather than just identifying the variables that promote residents' subjective happiness, we focused on factors affecting residents' living condition. In order to empirically investigate the influencing factors, we constructed the analysis data using the Gyeonggi-do survey. We analyzed it by using linear regression analysis. Through the effects of influencing factor analyzed, we could find implications for public project's priority in budget distribution. It could be suggested that local public projects for residents should be focused on improving programs such as job satisfaction, resident health, and neighborhood relations in order to effectively raise community well-being level.

• Journal of the Korean Data and Information Science Society
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• 제21권1호
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• pp.51-59
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• 2010

일반화선형모형에서 회귀함수가 하나의 불연속점을 가질 때, Huh (2009)는 하나의 모수를 가지는 지수족의 가능도함수를 한쪽방향커널을 이용하여 그 불연속점의 위치와 점프크기를 추정하였다. 이 논문에서는 미지의 불연속점 수 q개를 가지는 회귀함수인 경우에, Huh (2009)가 제안한 점프크기 추정량의 점근분포를 이용한 가설검정법을 소개하고, 그 가설검정법을 이용한 불연속점 수를 추정하는 알고리듬을 제안하고, 모의실험을 통하여 추정의 정도를 알아보고자 한다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.179-182
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• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• 보건교육건강증진학회지
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• 제22권2호
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• pp.77-95
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• 2005

Objectives: This study measured the extent of local legislators' support for tobacco control policies and identified the predictors of that. Methods: Local legislators, from 21 Gu in Seoul Metropolitan City, underwent a self-administrated questionaire during the 6-week period from December 1, 2004 to January 15, 2005. Multiple linear regression model was used to assess relationships between five groups of variables(political factors including political ideology, personal characteristics, tobacco experiences, tobacco knowledge, contact with local health officers) and support for tobacco control policies based on an 11-item scale. Results: The rates of support for 'penalizing merchants who sell cigarettes to minors' and 'instituting a law mandating that parents should not smoke in a car when children are present' were highest as 87.5% and 82.0% respectively, and those for 'increasing price of cigarettes' and 'regulating stores that sell cigarettes' were lowest as 52.2% and 51.7% respectively. Support was higher among local legislators who thought government had a duty to promote healthy life styles, knew second-hand smoke could cause lung cancer, knew tobacco caused more deaths than alcohol. Support among ex-smokers and nonsmokers was higher than current smokers. Conclusions: The findings indicate that local legislators who oppose tobacco control measures may not be opposed to tobacco control per se, but are more generally opposed to a government role in health promotion, Thus, Tobacco control advocates need to be more attentive to the way tobacco control issues are framed for particular legislators. Further, they could work to increase tobacco knowledge among local legislators.

• Earthquakes and Structures
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• 제3권1호
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• pp.1-15
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• 2012

An empirical predictive relationship correlating bracketed duration to earthquake magnitude, site-to-source distance, and local site conditions (i.e. rock vs. stiff soil) for stable continental regions of North America is presented herein. The correlation was developed from data from 620 horizontal motions for central and eastern North America (CENA), consisting of 28 recorded motions and 592 scaled motions. The bracketed duration data was comprised of nonzero and zero durations. The non-linear mixed-effects regression technique was used to fit a predictive model to the nonzero duration data. To account for the zero duration data, logistic regression was conducted to model the probability of zero duration occurrences. Then, the probability models were applied as weighting functions to the NLME regression results. Comparing the bracketed durations for CENA motions with those from active shallow crustal regions (e.g. western North America: WNA), the motions in CENA have longer bracketed durations than those in the WNA. Especially for larger magnitudes at far distances, the bracketed durations in CENA tend to be significantly longer than those in WNA.

• 대한산업공학회지
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• 제28권3호
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• pp.331-343
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• 2002

This paper proposes a fuzzy rule-based model as a means to build usability models between emotional satisfaction and design variables of consumer products. Based on a subtractive clustering algorithm, this model obtains partially overlapping rules from existing data and builds multiple local models each of which has a form of a linear regression equation. The best subset procedure and cross validation technique are used to select appropriate input variables. The proposed technique was applied to the modeling of luxuriousness, balance, and attractiveness of office chairs. For comparison, regression models were built on the same data in two different ways; one using only potentially important variables selected by the design experts, and the other using all the design variables available. The results showed that the fuzzy rule-based model had a great benefit in terms of the number of variables included in the model. They also turned out to be adequate for predicting the usability of a new product. Better yet, the information on the product classes and their satisfaction levels can be obtained by interpreting the rules. The models, when combined with the information from the regression models, are expected to help the designers gain valuable insights in designing a new product.