피톤치드(모노테르펜) 농도 예측을 위한 회귀분석 기반 모델식 -춘천 수리봉을 중심으로- (Regression Analysis-based Model Equation Predicting the Concentration of Phytoncide (Monoterpenes) - Focusing on Suri Hill in Chuncheon -)
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- 한국환경보건학회지
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- 제47권6호
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- pp.548-557
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- 2021
Background: Due to the emergence of new diseases such as COVID-19, an increasing number of people are struggling with stress and depression. Interest is growing in forest-based recreation for physical and mental relief. Objectives: A prediction model equation using meteorological factors and data was developed to predict the quantities of medicinal substances generated in forests (monoterpenes) in real-time. Methods: The concentration of phytoncide and meteorological factors in the forests near Chuncheon in South Korea were measured for nearly two years. Meteorological factors affecting the observation data were acquired through a multiple regression analysis. A model equation was developed by applying a linear regression equation with the main factors. Results: The linear regression analysis revealed a high explanatory power for the coefficients of determination of temperature and humidity in the coniferous forest (R2=0.7028 and R2=0.5859). With a temperature increase of 1℃, the phytoncide concentration increased by 31.7 ng/Sm3. A humidity increase of 1% led to an increase in the coniferous forest by 21.9 ng/Sm3. In the deciduous forest, the coefficients of determination of temperature and humidity had approximately 60% explanatory power (R2=0.6611 and R2=0.5893). A temperature increase of 1℃ led to an increase of approximately 9.6 ng/Sm3, and 1% humidity resulted in a change of approximately 6.9 ng/Sm3. A prediction model equation was suggested based on such meteorological factors and related equations that showed a 30% error with statistical verification. Conclusions: Follow-up research is required to reduce the prediction error. In addition, phytoncide data for each region can be acquired by applying actual regional phytoncide data and the prediction technique proposed in this study.
Near infrared spectroscopy (NIRS) was applied to determination of the lipid content of the compost during the compost fermentation of tofu (soybean0curd) refuse. The absorption of lipid observed at 5 wavelengths, 1208, 1712, 1772, 2312 and 2352 nm on the second derivative spectra. To formulated a calibration equation, a multiple linear regression analysis was carried out between the near-infrared spectral data and on the lipid content in the calibration sample set (sample number, n=60) obtained using Soxhlet extraction method. The value of the multiple correlation coefficient (R) was 0.975 when using the wavelengths of 1208 and 1712 nm were used in the calibration equation. To validate the calibration equation obtained, the lipid content in the validation sample set (n=35) not used for formulating the calibration equation was calculated using the calibration equation, and compared with the value obtained using the Soxhlet extraction method. Good agreement was observed between the results of the Soxhlet extraction method and those values of the NIRS method. The simple correlation coefficient (r) and standard error of prediction (SEP) were 0.964 and 0.815 %, respectively. suitability of the lipid content as an indicator of the compost fermentation of tofu refuse was also studied. The decrease of the lipid content in the compost corresponded to the decrease of the total dry weight of the compost in the composter. The lipid content was a significant indicator of the compost fermentation. The NIRS method was applied to measure the time course of the lipid content in the compost fermentation and good results were obtained. The study indicates that NIRS is a useful method for process management of the compost fermentation of tofu refuse.
The majority of studies on breastfeeding consists of descriptive correlational studies identifying the incidence and correlates of breastfeeding. The theory of planned behavior has been shown to yield great predictive power for behavioral goals over which individuals have only limited control such as improving school grades and weight loss. The purpose of this study was to test the "theory of planned behavior" in the prediction of breastfeeding of mothers who delivered vaginally, One hundred mothers who delivered vaginally in one general hospital in Seoul and one general hospital and three private hospitals in Taejeon participated in this study. The instruments used for data collection in this study were developed by the researchers following the guidelines suggested by Ajzen & Fishbein(1980) and Ajzen & Madden(1986). The instruments included measurement of attitude, subjective norm, perceived behavioral control and intention. The collected data were analyzed using descriptive statistics, Pearson product moment correlation, hierachical multiple regression and logistic regression. The results are as follows ; 1. Intention to breastfeed correlated significantly with attitude, subjective norm and perceived behavioral control. Both attitude and subjective norm did not make a significant contribution to the prediction of intention, but the addition of perceived behavioral control to the regression equation greatly improved the model's predictive power, increasing the R²from .05 to .52. 2. Intention to breastfeed alone had a significant predictive effect on actual breastfeeding, resulting in a regression coefficient of .16(X²=8 60, p<.01), but when perceived behavioral control was added to the equation, intention was not a significant predictive variable and only perceived behavioral control showed significant predictive power on actual breastfeeding, resulting in a regression coefficient of .12(X²=4.69, p<.05). In sum, breastfeeding behavior lent only partial support to the second version of the theory of planned behavior, and because perceived behavioral control had a strong effect on intention to breastfeed and actual breastfeeding, It would be desirable to develop nursing intervention programs which focus on strengthening the perceived behavioral control for the promotion of breastfeeding.
This study is aimed at the application of the apparel size system to be applied for the Internet shopping mall in Korea. Especially this is focused on the presumption of the body measurement according to the age groups and the figure groups. In this regard, a sizing system is to be developed that could be used to approach consumers more easily and provide more fitness and accuracy in terms of size. The target study was on a group of women nineteen to forty-nine years of age. The 4th National Anthropometry Survey data were used in the examination. The results in the study are as follows ; (1) On the Internet apparel shopping malls in relation with this study, no matter what size in the ready-to-wear enterprises was selected by the consumers who once put their information in the member registration, the most appropriate sizes for them are automatically given and transferred to the order forms of chosen enterprises with aid of internal programs of the internet webpage. In addition, when consumers enter their body sizes in the units that are familiar to them, such as inches or centimeters, the units are automatically programed so that they can be converted for the sake of convenience. ; (2) To extract an estimation equation of body size through Multiple Regression Analysis, the circumferences of chest and hip could be presumed by stature, weight, and waist circumference of which most consumers were well aware. For more accurate regression equations, groupings were made in the three categories of age(19∼29/30∼39/40∼49) and in the three body types(Type N, A and H). Then, the regression equations were established for three sectors,