• 보건교육건강증진학회지
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• 제23권3호
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• pp.65-83
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• 2006

Objectives: This is one of the first efforts to describe incidence of alcohol-related problems and to identify environmental correlates associated with them among colleges. Methods: Date were collected by a sample of 105 college administrators who are in charge of student affairs in colleges nationwide through self-administrated questionnaire. Both logistic and linear multiple regression analyses were employed to identify the correlates associated with alcohol-related problems. Results: Most of colleges(76.6%) under study reported to have at least one alcohol-related problem in previous years. Interpersonal violence was alcohol-related problem taken placed most frequently, followed by making noise episode, having property damaged and motor vehicle accidents. Logistic regression analysis identified factors associated with incidents of alcohol related problems. They included being private colleges, numbers of prevention activities, product promotion and marketing by alcohol industry and alcohol accessibility to drinking context. Multiple regression analyses showed that correlates associated with numbers of alcohol-related problems included being a private college, being located in rural area, having drinking density, product promotion and availability of alternative activities to drinking. Conclusions: Environmental correlates were associated with incidence of alcohol related problems in colleges nationwide. Policy implications were discussed.

• 대한교통학회지
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• 제26권2호
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• pp.35-46
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• 2008

본 연구는 지방부의 교통사고 특성을 분석하고 사고모형을 개발하는데 그 목적이 있다. 이를 위해 본 연구에서는 청주시와 청원군의 신호교차로를 중심으로 다중선형, 포아송 및 음이항회귀모형을 개발하는데 중점을 두고 있다. 분석된 주요 연구결과는 다음과 같다. 첫째, 사고특성 분석을 통해 지방부 교통사고의 특성이 요인별로 파악되었다. 둘째, 통계적으로 설명력이 높은 4개의 사고모형이 개발되었다. 마지막으로 평균차로폭차($X_2$)와 교차로간거리 ($X_{11}$)가 지방부의 특성을 반영할 수 있는 특정변수로 밝혀졌다.

• 정보처리학회논문지D
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• 제11D권7호
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• pp.1483-1490
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• 2004

소프트웨어분야에서 성공적인 프로젝트를 완수하기 위해서는 프로젝트를 완수하는데 필요한 개발노력이 정확히 추정되어야 한다. 그러나 이러한 개발노력은 소프트웨어의 크기나 여러 가지 운영환경의 영향으로 인해 프로젝트에 따라서 총 개발 노력의 규모는 차이가 있다. 일반적으로 기존의 연구는 개발노력을 추정하기 위하여 소프트웨어 규모인 기능점수(FP ; Function Point)를 이용하였다. 본 연구를 위해서 1990년대에 개발된 789개의 소프트웨어 개발 프로젝트들에 관련된 데이터를 이용하였다. 실험을 통해서 개발노력에 영향을 미치는 변수를 조사하였다. 또한 변수사이에 선형적인 관계를 조사하기 위하여 다중회귀분석을 실시하였다. 이 경우 전체의 데이터를 이용하는 것이 아니라 프로젝트 인도비율(PDR ; Project Delivery Rate : Hours/FP)을 다단계로 나누어서 각 단계별로 개발노력에 영향을 미치는 변인을 찾아내고 가장 이상적인 회귀식으로 도출하였다.

• 한국운동역학회지
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• 제30권1호
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• pp.83-91
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• 2020

Objective: The study aimed to develop a functional performance index that evaluates the functional performance of Parkinson's patients, i.e., to integrate biomechanical measurements of walking, balance, muscle strength and tremor, and to use multiple linear regression with stepwise methods to identify the most suitable predictors for the progression of disease. Method: A total of 60 subjects were tested for sub-variables of four factors: walking, balance, isometric strength and hand tremors. Potential independet variables were extracted through correlation analysis of the sub-variables and dependent variables, Hoehn & Yahr scale. And then, a stepwise multiple regression analysis using the potential independent variables was performed to identify predictor of Hoehn & Yahr scale. Results: First, the results of the study showed that physical composition and gait had a relatively more correlated with the progression of the disease, compared to balance and hand tremor. Second, Parkinson's functional performance is characterized by dynamic pattern of walking, such as foot clearance and turning angle (TA) of walking, and a high-explained regression model is completed. Conclusion: The study emphasized the importance of walking variables and body composition in minor pathological features compared to Parkinson's patient's balancing ability and hand tremor. Specifically, it revealed that dynamic walking patterns functionally characterize patients. The results are worth considering when assessing functional performance related to the progression of the disease at the site.

• 아태비즈니스연구
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• 제12권1호
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• pp.87-100
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• 2021

Purpose - This study aims to examine the antecedents of willingness to pay in the domain of duty free shop. Design/methodology/approach - This study chooses willingness to pay as explained variable. The candidates of explanatory variables are price fairness, brand awareness, employee service, product diversity, and crowding. This study uses survey to explore the linear relation between variables. This research collected data using online panel data collection service. The number of valid observation is 265. The research targe is Lotte duty free store. Statistical analysis was for statistical inference. To attain the information of survey respondents, frequency analysis is employed. Next, this study implemented exploratory factor analysis and reliability to ensure both validity and reliability of measurement items. This study executed multiple regression analysis to test research hypotheses Findings - Regrading results, brand awareness, employee service, and product diversity are positively associated with willingness to pay of duty free shop product. Moreover, the results of regression analysis suggest the inverted-U shape association between crowding and willingness to pay. However, price fairness appeared as non-significant variable to account for willingness to pay in the multiple regression analysis. Originality - This study contributes to the literature by examining duty free shop customers more.

• 가정과삶의질연구
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• 제24권2호
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• pp.73-92
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• 2006

This paper investigates the causal relationships between financial attitudes, spending behaviors and the financial satisfaction of adolescent consumers. The study used Cronbach' $\alpha$, t-test, one-way ANOVA, Duncan's multiple range test, multiple regression and path analysis for statistical analysis and applied it to 1,252 questionnaires. The results are summarized as follows: Path analysis revealed that the financial satisfaction of adolescents had a direct linear relationship with variables such as grade, sex, financial attitudes. (financial situation compared to past and financial situation compared to others) and types of spending behaviors (planned, conspicuous and excessive). Planned spending behavior was the most influential variable on financial satisfaction. Planned spending behavior had positive linear relationship with the attitude toward the past financial situation. Conspicuous spending behavior had positive linear relationships with the attitudes toward the past financial situation and the financial situation compared to others. However, it showed negative relationship with the attitude toward a future financial situation. Impulsive spending behavior had a positive relationship with the attitude toward others' financial situation. Excessive spending had a positive relationship with the attitude toward a past financial situation but showed a negative relationship to the attitude toward others' financial situation.

• Bulletin of the Korean Chemical Society
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• 제27권2호
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• pp.211-218
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• 2006

This work deals with 24 substances composed of nitrogen-containing heterocycles. The relationships between the chromatographic retention factor (k) and those physicochemical properties which are relevant in quantitative structure-properties relationship (QSPR) studies, such as the polarizability $(\alpha)$, molar refractivity (MR), lipophilicity (logP), dipole moment $(\mu)$, total energy $(E_{tot})$, heat of formation $(\Delta H_f)$, molecular surface area $(S_M)$, and binding energy $(E_b)$, were investigated. The accuracy of the simple linear regressions between the chromatographic retention and the descriptors for all of the compounds was satisfactory (correlation coefficient, $0.8 \leq r \leq 1.0$). The QSPR models of these nitrogen-containing heterocyclic compounds could be predicted with a multiple linear regression equation having the statistical index, r = 1.000. This work demonstrated the successful application of the multiple linear approaches through the development of accurate predictive equations for retention factors in liquid chromatography.

• 한국지구과학회지
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• 제38권4호
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• pp.283-292
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• 2017

본 연구에서는 서울지역의 지상 미세먼지($PM_{2.5}$) 농도를 산출하기 위하여 경험적인 모델들을 개발하였다. 연구에 이용한 자료는 2012년 1월 1일부터 2013년 12월 31일까지이며 Terra와 Aqua위성의 MODIS센서에서 산출되는 에어로졸 광학두께, 옹스트롬 지수, 기상변수들과 행성경계층두께와 관련된 6개의 다중 선형 회귀모델들의 차이를 분석하였다. 그 결과 에어로졸 광학두께와 옹스트롬 지수, 상대습도, 풍속, 풍향, 행성경계층두께, 기온 자료를 입력 자료로 사용한 $M_6$모델이 가장 좋은 결과를 보였다. 통계적인 분석에 따르면 $M_6$ 모델을 사용하여 계산된 $PM_{2.5}$와 관측된 $PM_{2.5}$농도 사이의 결과는 상관계수(R=0.62)와 평균제곱근오차($RMSE=10.70{\mu}gm^{-3}$)이다. 또한 산출된 계절별 지표면 $PM_{2.5}$농도는 여름철(R=0.38)과 겨울철(R=0.56)보다 봄(R=0.66)과 가을철(R=0.75)에 상대적으로 더 좋은 상관 관계를 보였다. 이러한 결과는 에어로졸 광학두께의 계절별 관측 특성으로 인한 것으로써 다른 계절에 비하여 여름과 겨울철 에어로졸 광학두께 관측이 구름과 눈/얼음 표면에 의한 관측 제한과 오차를 가져온 것으로 분석되었다. 따라서 본 연구에서 사용한 경험적 다중선형회귀 모델은 위성에서 산출된 에어로졸 광학두께 자료가 지배적인 변수로 작용하며 $PM_{2.5}$산출 결과들을 향상시키기 위해서는 추가적인 기상 변수를 이용해야 할 것이다. 또한 경험적 다중선형회귀 모델을 이용하여 $PM_{2.5}$를 산출한 결과는 인공위성 자료로부터 대기환경 감시를 가능하게 하는 방법이 될 수 있어 유용할 것이다.

• 한국환경보건학회지
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• 제42권4호
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• pp.280-292
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• 2016

Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.

• 한국대기환경학회지
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• 제19권6호
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• pp.701-717
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• 2003

The objective of this study was to extensively estimate the air quality trends of the study area by surveying con-centration trends in months or seasons, after analyzing the mass concentration of PM-10 samples and the inorganic lements, ion, and total carbon in PM-10. Also, the study introduced to apply the PMF (Positive Matrix Factoriza-tion) model that is useful when absence of the source profile. Thus the model was thought to be suitable in Korea that often has few information about pollution sources. After obtaining results from the PMF modeling, the existing sources at the study area were qualitatively identified The PM-10 particles collected on quartz fiber filters by a PM-10 high-vol air sampler for 3 years (Mar. 1999∼Dec.2001) in Kyung Hee University. The 25 chemical species (Al, Mn, Ti, V, Cr, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Ce, Pb, Si, N $a^{#}$, N $H_4$$^{+}$, $K^{+}$, $Mg^{2+}$, $Ca^{2+}$, C $l^{[-10]}$ , N $O_3$$^{[-10]}$ , S $O_4$$^{2-}$, TC) were analyzed by ICP-AES, IC, and EA after executing proper pre - treatments of each sample filter. The PMF model was intensively applied to estimate the quantitative contribution of air pollution sources based on the chemical information (128 samples and 25 chemical species). Through a case study of the PMF modeling for the PM-10 aerosols. the total of 11 factors were determined. The multiple linear regression analysis between the observed PM-10 mass concentration and the estimated G matrix had been performed following the FPEAK test. Finally the regression analysis provided source profiles (scaled F matrix). So, 11 sources were qualitatively identified, such as secondary aerosol related source, soil related source, waste incineration source, field burning source, fossil fuel combustion source, industry related source, motor vehicle source, oil/coal combustion source, non-ferrous metal source, and aged sea- salt source, respectively.ively.y.