• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.171-183
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• 2016

Land Surface Temperature (LST) retrieved from Landsat 8 measured from 2013 to 2014 and it is corrected by surface temperature observed from ground. LST maps are retrieved from Landsat 8 calculate using the linear regression function between raw Landsat 8 LST and ground surface temperature. Seasonal and annual LST maps developed an average LST from season to annual, respectively. While the higher LSTs distribute on the industrial and commercial area in urban, lower LSTs locate in surrounding rural, sea, river and high altitude mountain area over Seoul and surrounding area. In order to correct the LST, linear regression function calculate between Landsat 8 LST and ground surface temperature observed 3 Korea Meteorological Administration (KMA) synoptic stations (Seoul(ID: 108), Incheon(ID: 112) and Suwon(ID: 119)) on the Seoul and surrounding area. The slopes of regression function are 0.78 with all data and 0.88 with clear sky except 5 cloudy pixel data. And the original Landsat 8 LST have a correlation coefficient with 0.88 and Root Mean Square Error (RMSE) with $5.33^{\circ}C$. After LST correction, the LST have correlation coefficient with 0.98 and RMSE with $2.34^{\circ}C$ and the slope of regression equation improve the 0.95. Seasonal and annual LST maps represent from urban to rural area and from commercial to industrial region clearly. As a result, the Landsat 8 LST is more similar to the real state when corrected by surface temperature observed ground.

• Tuberculosis and Respiratory Diseases
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• v.56 no.4
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• pp.393-404
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• 2004

Background : Nucleic acid hybridization has become an essential technique in the development of our understanding of gene structure and function. The quantitative analysis of hybridization has been used in the measurement of genome complexity and gene copy number. The filter hybridization assay is rapid, sensitive and can be used to measure RNAs complementary to any cloned DNA sequence. Methods : The authors assessed the accuracy, linearity, correlation coefficient and specificity of the hybridization depending on the added dose(0, 1, 5, and $10{\mu}g$) of non-specific rat spleen RNA to hybridization of surfactant protein A mRNA. Filter hybridization assays were used to obtain the equation of standard curve and thereby to quantitate the mRNA quantitation. Results : 1. Standard curve equation of filter hybridization assay between counts per minute (X) and spleen RNA input (Y) was Y=0.13X-19.35. Correlation coefficient was 0.98. 2. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) was Y=0.00066X-0.046. Correlation coefficient was 0.99. 3. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $1{\mu}g$ spleen RNA was Y=0.00056X-0.051. Correlation coefficient was 0.99. 4. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $5{\mu}g$ spleen RNA was Y=0.00065X-0.088. Correlation coefficient was 0.99. 5. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $10{\mu}g$ spleen RNA was Y=0.00051X-0.10. Correlation coefficient was 0.99. Conclusions : Comparison of cpm/filter in a linear range allowed accurate and reproducible estimation of surfactant protein A mRNA copy number irrespective of the addition dosage of non-specific rat spleen RNA over the range $0-10{\mu}g$.

• Tuberculosis and Respiratory Diseases
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• v.72 no.5
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• pp.433-440
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• 2012

Background: The pulmonary function test is the most basic test method to diagnosis lung disease. The purpose of this study was to research the correlation of the body mass index (BMI), the fat percentage of the body mass (fat%), the muscle mass, the fat-free mass (FFM) and the fat-free mass index (FFMI), waist-hip ratio (WHR), on the forced expiratory volume curve. Methods: Between March and April 2009, a total of 291 subjects were enrolled. There were 152 men and 139 female (mean age, $46.3{\pm}9.92$ years), and they were measured for the following: forced vital capacity (FVC), forced expiratory volume at 1 second ($FEV_1$), and forced expiratory flow during the middle half of the FVC ($FEF_{25-75}$) from the forced expiratory volume curve by the spirometry, and the body composition by the bioelectrical impedance method. Correlation and a multiple linear regression, between the body composition and pulmonary function, were used. Results: BMI and fat% had no correlation with FVC, $FEV_1$ in male, but FFMI showed a positive correlation. In contrast, BMI and fat% had correlation with FVC, $FEV_1$ in female, but FFMI showed no correlation. Both male and female, FVC and $FEV_1$ had a negative correlation with WHR (male, FVC r=-0.327, $FEV_1$ r=-0.36; p<0.05; female, FVC r=-0.175, $FEV_1$ r=-0.213; p<0.05). In a multiple linear regression of considering the body composition of the total group, FVC explained FFM, BMI, and FFMI in order ($r^2$=0.579, 0.657, 0.663). $FEV_1$ was explained only fat% ($r^2$=0.011), and $FEF_{25-75}$ was explained muscle mass, FFMI, FFM ($r^2$=0.126, 0.138, 0.148). Conclusion: The BMI, fat%, muscle mass, FFM, FFMI, WHR have significant association with pulmonary function but $r^2$ (adjusted coefficient of determination) were not high enough for explaining lung function.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.9-17
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• 2020

This study is a narrative research study to investigate the knowledge, attitudes and preventive behaviors of middle-aged adults with dementia and to identify related factors. The study subjects were a total of 230 middle-aged adults living in K and P cities, and data were collected from March 2018 to July 2019 using a structured questionnaire. Collected data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and multiple linear regression analysis using SPSS / WIN 23.0 program. As a result of the study, the knowledge of dementia was 9.97 out of 15, the attitude of dementia was 47.45 out of 60, and the prevention of dementia was 27.75 out of 36. Knowledge of dementia had a positive correlation with dementia attitude (r=.122, p=.050) and dementia prevention behavior (r=.122, p<.05). Factors affecting dementia prevention behavior include marital status (β=.129, p<.05), education level (β=.219, p<.000), and type of disease (β=-.108, p<.000), presence of religion (β =-. 219, p <.000), interest in dementia (β=.237, p<.000), presence of drinking (β=.317, p<.000), smokingPresence or absence (β=.235, p<.000) and knowledge of dementia β=.316, p<.000) were found to have a significant effect. Therefore, in order to improve dementia prevention behavior of middle-aged adults, it is necessary to develop customized education programs for middle-aged adults to practice knowledge of dementia, positive attitudes, and good lifestyle.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.325-336
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• 2020

This study identified the perception and coping ability of an emergency involving the elderly for facility directors in charge of services in long-term care facilities, and used it as basic data for developing educational programs and policy data for improving the ability of emergency facilities. The subjects were 192 directors of elderly care facilities and home care centers. Data were collected from March 15 to April 20, 2019 and analyzed using the SPSS WIN 25.0 program. Data analysis was performed using t-test, One-way ANOVA, Pearson's correlation coefficient, Scheffe, and multiple linear regression. The results revealed 97.4% of emergency experience, 6.16 points of emergency perception, and 62% of correct answers, and coping ability of an emergency was 69.61 ± 13.537. The negative correlation between emergency experience and ability to cope with emergencies(r=-.202, p= .005) was the long-term care facility type(β = 8.253, p<.001). Overall, an education program considering the type of long-term care facility is needed when applying emergency education for facility directors.

• Food Engineering Progress
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• v.22 no.4
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• pp.381-385
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• 2018

Various rheological methods to measure the hardness of instant cooked rice by a texture analyzer were investigated and compared. Specifically, instant white rice samples with a wide range of hardness were subjected to four different rheological tests with disk, cylinder, rod, and cone probe whose results were inter-correlated. All the measurements demonstrated that the hardness of instant rice was reduced with increasing moisture content and showed negatively linear relationships. Out of the four tests applied in this study, the highest coefficient of correlation ($R^2=0.9268$) was observed distinctly in the cone probe test, where both compressive and shear forces can be applied to deform individual rice grains. However, the cylinder probe test had the lowest coefficient of correlation ($R^2=0.7247$) because it may be ineffective in causing direct deformation of individual rice grains. Furthermore, when the hardness values (N) were converted to stress (Pa), highly linear correlations ($R^2{\approx}0.99$) were observed between the tests with similar probe geometry and force application.

• Journal of Korean Medicine Rehabilitation
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• v.29 no.3
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• pp.113-128
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• 2019

Objectives To evaluate the pattern identification tool for knee osteoarthritis and to investigate the relationship between pattern identification tool and knee ROM (range of motion), VAS (visual analog scale) and WOMAC (Western Ontario & McMaster Universities osteoarthritis index). Methods We studied 50 patients who are diagnosed as degenerative osteoarthritis. With one patient dropping out, total of 49 patient went through pattern identification tool. Re-test of the pattern identification tool was implemented after about a week. The reliability was analyzed by calculating ICC (intraclass correlation coefficient). Also, reliability of each pattern identification score was calculated along with influence factor and correlation between knee ROM, VAS and WOMAC. Results Reliability of the pattern identification tool was evaluated as 'poor agreement beyond chance' with ICC value of 0.396. Reliablility of each pattern identification score was calculated and four out of five were measured 'good' with one 'moderate' reliability. Two of inter-item consistency were 'good', two were 'acceptable' and one was 'questionable'. Correlation between each pattern identification and knee ROM showed 'clear negative linear relationship' with two patterns. VAS showed 'clear positivie linear relationship' with all five patterns. WOMAC showed 'positivie linear relationship' with all five patterns. Conclusions According to the results, pattern identification tool for knee osteoarthritis seems to have meaningful relationship with other agnedas. Also, further research is needed to develop the tool.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4296-4311
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• 1977

This study was conducted to derive an Instantaneous Unit Hydrograph for the accurate and reliable unitgraph which can be used to the estimation and control of flood for the development of agricultural water resources and rational design of hydraulic structures. Eight small watersheds were selected as studying basins from Han, Geum, Nakdong, Yeongsan and Inchon River systems which may be considered as a main river systems in Korea. The area of small watersheds are within the range of 85 to 470$\textrm{km}^2$. It is to derive an accurate Instantaneous Unit Hydrograph under the condition of having a short duration of heavy rain and uniform rainfall intensity with the basic and reliable data of rainfall records, pluviographs, records of river stages and of the main river systems mentioned above. Investigation was carried out for the relations between measurable unitgraph and watershed characteristics such as watershed area, A, river length L, and centroid distance of the watershed area, Lca. Especially, this study laid emphasis on the derivation and application of Instantaneous Unit Hydrograph (IUH) by applying Nash's conceptual model and by using an electronic computer. I U H by Nash's conceptual model and I U H by flood routing which can be applied to the ungaged small watersheds were derived and compared with each other to the observed unitgraph. 1 U H for each small watersheds can be solved by using an electronic computer. The results summarized for these studies are as follows; 1. Distribution of uniform rainfall intensity appears in the analysis for the temporal rainfall pattern of selected heavy rainfall event. 2. Mean value of recession constants, Kl, is 0.931 in all watersheds observed. 3. Time to peak discharge, Tp, occurs at the position of 0.02 Tb, base length of hlrdrograph with an indication of lower value than that in larger watersheds. 4. Peak discharge, Qp, in relation to the watershed area, A, and effective rainfall, R, is found to be {{{{ { Q}_{ p} = { 0.895} over { { A}^{0.145 } } }}}} AR having high significance of correlation coefficient, 0.927, between peak discharge, Qp, and effective rainfall, R. Design chart for the peak discharge (refer to Fig. 15) with watershed area and effective rainfall was established by the author. 5. The mean slopes of main streams within the range of 1.46 meters per kilometer to 13.6 meter per kilometer. These indicate higher slopes in the small watersheds than those in larger watersheds. Lengths of main streams are within the range of 9.4 kilometer to 41.75 kilometer, which can be regarded as a short distance. It is remarkable thing that the time of flood concentration was more rapid in the small watersheds than that in the other larger watersheds. 6. Length of main stream, L, in relation to the watershed area, A, is found to be L=2.044A0.48 having a high significance of correlation coefficient, 0.968. 7. Watershed lag, Lg, in hrs in relation to the watershed area, A, and length of main stream, L, was derived as Lg=3.228 A0.904 L-1.293 with a high significance. On the other hand, It was found that watershed lag, Lg, could also be expressed as {{{{Lg=0.247 { ( { LLca} over { SQRT { S} } )}^{ 0.604} }}}} in connection with the product of main stream length and the centroid length of the basin of the watershed area, LLca which could be expressed as a measure of the shape and the size of the watershed with the slopes except watershed area, A. But the latter showed a lower correlation than that of the former in the significance test. Therefore, it can be concluded that watershed lag, Lg, is more closely related with the such watersheds characteristics as watershed area and length of main stream in the small watersheds. Empirical formula for the peak discharge per unit area, qp, ㎥/sec/$\textrm{km}^2$, was derived as qp=10-0.389-0.0424Lg with a high significance, r=0.91. This indicates that the peak discharge per unit area of the unitgraph is in inverse proportion to the watershed lag time. 8. The base length of the unitgraph, Tb, in connection with the watershed lag, Lg, was extra.essed as {{{{ { T}_{ b} =1.14+0.564( { Lg} over {24 } )}}}} which has defined with a high significance. 9. For the derivation of IUH by applying linear conceptual model, the storage constant, K, with the length of main stream, L, and slopes, S, was adopted as {{{{K=0.1197( {L } over { SQRT {S } } )}}}} with a highly significant correlation coefficient, 0.90. Gamma function argument, N, derived with such watershed characteristics as watershed area, A, river length, L, centroid distance of the basin of the watershed area, Lca, and slopes, S, was found to be N=49.2 A1.481L-2.202 Lca-1.297 S-0.112 with a high significance having the F value, 4.83, through analysis of variance. 10. According to the linear conceptual model, Formular established in relation to the time distribution, Peak discharge and time to peak discharge for instantaneous Unit Hydrograph when unit effective rainfall of unitgraph and dimension of watershed area are applied as 10mm, and $\textrm{km}^2$ respectively are as follows; Time distribution of IUH {{{{u(0, t)= { 2.78A} over {K GAMMA (N) } { e}^{-t/k } { (t.K)}^{N-1 } }}}} (㎥/sec) Peak discharge of IUH {{{{ {u(0, t) }_{max } = { 2.78A} over {K GAMMA (N) } { e}^{-(N-1) } { (N-1)}^{N-1 } }}}} (㎥/sec) Time to peak discharge of IUH tp=(N-1)K (hrs) 11. Through mathematical analysis in the recession curve of Hydrograph, It was confirmed that empirical formula of Gamma function argument, N, had connection with recession constant, Kl, peak discharge, QP, and time to peak discharge, tp, as {{{{{ K'} over { { t}_{ p} } = { 1} over {N-1 } - { ln { t} over { { t}_{p } } } over {ln { Q} over { { Q}_{p } } } }}}} where {{{{K'= { 1} over { { lnK}_{1 } } }}}} 12. Linking the two, empirical formulars for storage constant, K, and Gamma function argument, N, into closer relations with each other, derivation of unit hydrograph for the ungaged small watersheds can be established by having formulars for the time distribution and peak discharge of IUH as follows. Time distribution of IUH u(0, t)=23.2 A L-1S1/2 F(N, K, t) (㎥/sec) where {{{{F(N, K, t)= { { e}^{-t/k } { (t/K)}^{N-1 } } over { GAMMA (N) } }}}} Peak discharge of IUH) u(0, t)max=23.2 A L-1S1/2 F(N) (㎥/sec) where {{{{F(N)= { { e}^{-(N-1) } { (N-1)}^{N-1 } } over { GAMMA (N) } }}}} 13. The base length of the Time-Area Diagram for the IUH was given by {{{{C=0.778 { ( { LLca} over { SQRT { S} } )}^{0.423 } }}}} with correlation coefficient, 0.85, which has an indication of the relations to the length of main stream, L, centroid distance of the basin of the watershed area, Lca, and slopes, S. 14. Relative errors in the peak discharge of the IUH by using linear conceptual model and IUH by routing showed to be 2.5 and 16.9 percent respectively to the peak of observed unitgraph. Therefore, it confirmed that the accuracy of IUH using linear conceptual model was approaching more closely to the observed unitgraph than that of the flood routing in the small watersheds.

• Korean Journal of Pharmacognosy
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• v.50 no.4
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• pp.318-323
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• 2019

This study was designed to establish the stability of EGHB010, a combined hot water extract of Paeoniae Radix and Glycyrrhizae Radix. Test of coliform groups, sensory evaluations, contents of moisture, and the amount of paeoniflorin and glycyrrhizin were determined during storage at 4, 25 and 35℃ for 6 months. Coliform groups were not observed and moisture contents were maintained about 3.0% during the storage period. Sensory characteristics including color, taste, texture and appearance were tested over 3 points throughout the entire storage period. It maintained the commercial value during the storage period. Contents of paeoniflorin and glycyrrhizin as indicator components were remained stably for the storage period. The shelf-life of EGHB010 based on a linear response to zero of sensory evaluation with the highest correlation coefficient was predicted. Finally, the shelf-life of EGHB010 was expected for about 3 years to consider in safety coefficient. The shelf-life data of EGHB010 can be used to develop a functional health ingredient.

• Mass Spectrometry Letters
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• v.4 no.1
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• pp.18-20
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• 2013

Headspace solid phase micro-extraction gas chromatography/flame ionization detection (HS-SPME-GC/FID) method was compared with headspace gas chromatography/mass selective detection (HS-GC/MS). Organic solvent-spiked urine as well as urine samples from workspace was analyzed under optimal condition of each method. Detection limit of each compound by HS-SPME-GC/FID was $3.4-9.5{\mu}g/L$, which enabled trace analysis of organic solvents in urine. Linear range of each organic solvent was $10-400{\mu}g/L$, with fair correlation coefficient between 0.992 and 0.999. The detection sensitivity was 4 times better than HS-GC/MS in selected ion monitoring (SIM) mode. Accuracy and precision was confirmed using commercial reference material, with accuracy around 90% and precision less than 4.6% of coefficient of variance. Among 48 urine samples from workplace, toluene was detected from 45 samples in the range of $20-324{\mu}g/L$, but no other solvents were found. As a method for trace analysis, SPME HS GC/FID showed high sensitivity for biological monitoring of organic solvent in urine.