• Journal of Environmental Science International
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• v.17 no.6
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• pp.633-645
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• 2008

In order to investigate the variations and corelation among $PM_{10},\;PM_{2.5}\;and\;PM_1$ concentrations, the hourly concentrations of each particle sizes of 300nm to $20{\mu}m$ at a city, Gangneung in the eastern mountainous coast of Korean peninsula have been measured by GRIMM aerosol sampler-1107 from March 7 to 17, 2004. Before the influence of the Yellow Dust event from China toward the city, $PM_{10},\;PM_{2.5}\;and\;PM_1$, concentrations near the ground of the city were very low less than $35.97{\mu}g/m^3,\;22.33{\mu}g/m^3\;and\;16.77{\mu}g/m^3$, with little variations. Under the partial influence of the dust transport from the China on March 9, they increased to $87.08{\mu}g/m^3,\;56.55{\mu}g/m^3\;and\;51.62{\mu}g/m^3$. $PM_{10}$ concentration was 1.5 times higher than $PM_{2.5}$ and 1.85 times higher than $PM_1$. Ratio of $(PM_{10}-PM_{2.5})/PM_{2.5}$ had a maximum value of 1.49 with an averaged 0.5 and one of $(PM_{2.5}-PM_1)/PM_1$ had a maximum value of 0.4 with an averaged 0.25. $PM_{10}\;and\;PM_{2.5}$ concentrations were largely influenced by particles smaller than $2.5{\mu}m\;and\;1{\mu}m$ particle sizes, respectively. During the dust event from the afternoon of March 10 until 1200 LST, March 14, $PM_{10},\;PM_{2.5}\;and\;PM_1$ concentrations reached $343.53{\mu}g/m^3,\;105{\mu}g/m^3\;and\;60{\mu}g/m^3$, indicating the $PM_{10}$ concentration being 3.3 times higher than $PM_{2.5}$ and 5.97 times higher than $PM_1$. Ratio of $(PM_{10}-PM_{2.5})/PM_{2.5}$ had a maximum value of 7.82 with an averaged 3.5 and one of $(PM_{2.5}-PM_1)/PM_1$, had a maximum value of 2.8 with an averaged 1.5, showing $PM_{10}\;and\;PM_{2.5}$ concentrations largely influenced by particles greater than $2.5{\mu}m\;and\;1{\mu}m$ particle sizes, respectively. After the dust event, the most of PM concentrations became below $100{\mu}g/m^3$, except of 0900LST, March 15, showing the gradual decrease of their concentrations. Ratio of $(PM_{10}-PM_{2.5})/PM_{2.5}$ had a maximum value of 3.75 with an averaged 1.6 and one of $(PM_{2.5}-PM_1)/PM_1$ had a maximum value of 1.5 with an averaged 0.8, showing the $PM_{10}$ concentration largely influenced by corse particles than $2.5{\mu}m$ and the $PM_{2.5}$ by fine particles smaller than $1{\mu}m$, respectively. Before the dust event, correlation coefficients between $PM_{10},\;PM_{2.5}\;and\;PM_1$, were 0.89, 0.99 and 0.82, respectively, and during the dust event, the coefficients were 0.71, 0.94 and 0.44. After the dust event, the coefficients were 0.90, 0.99 and 0.85. For whole period, the coefficients were 0.54, 0.95 and 0.28, respectively.

• Journal of Bio-Environment Control
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• v.21 no.3
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• pp.271-275
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• 2012

The average annual and winter ambient air temperatures in Korea have risen by $0.7^{\circ}C$ and $1.4^{\circ}C$, respectively, during the last 30 years. The continuous rise in temperature presents a challenge in growing certain horticultural crops. Chinese cabbage, one most important cool season crop, may well be used as a model to study the influence of climate change on plant growth, because it is more adversely affected by elevated temperatures than warm season crops. This study examined the influence of transplanting time, nitrogen fertilizer level and climate parameters, including air temperature and growing degree days (GDD), on the performance of a Chinese cabbage cultivar (Chunkwang) during the spring growing season to estimate crop yield under the unfavorable environmental conditions. The chinese cabbage plants were transplanted from Apr. 8 to May 13, 2011 when 3~4 leaves were occurred, at internals of 7 days and cultivated with 3 levels of nitrogen fertilization. The data from plants transplanted on Apr. 22 and 29, 2012 were used for the prediction of yield as affected by planting date and nitrogen fertilization for spring production. In our study, plant dry weight was higher when the seedlings were transplanted on 15th (168 g) than on 22nd (139 g) of April. There was no significant difference in the yield when plants were grown with different levels of nitrogen fertilizer. The values of correlation coefficient ($R^2$) between GDD and number of leaves, and between GDD and dry weight of the above-ground plant parts were 0.9818 and 0.9584, respectively. Nitrogen fertilizer did not provide a good correlation with the plant growth. Results of this study suggest that the GDD values can be used as a good indicator in predicting the top biomass yield of Chinese cabbage.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.53-62
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• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.525-536
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• 2014

In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.

• Journal of Korea Water Resources Association
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• v.51 no.3
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• pp.247-261
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• 2018

The purpose of this study is to evaluate the groundwater level behavior of Geum river basin ($9,645.5km^2$) under future climate change scenario projection periods (2020s: 2010~2039, 2050s: 2040~2069, 2080s: 2070~2099) using SWAT (Soil and Water Assessment Tool). Before future evaluation, the SWAT was calibrated and validated using 11 years (2005~2015) daily multi-purpose dam inflow at 2 locations (DCD, YDD), ground water level data at 5 locations (JSJS, OCCS, BEMR, CASS, BYBY), and three years (2012~2015) daily multi-function weir inflow at 3 locations (SJW, GJW, BJW). For the two dam inflow and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.57~0.67 and 0.87~0.94, and the coefficient of determination ($R^2$) was 0.69~0.73 and 0.63~0.73 respectively. For the three weir inflow and storage, the NSE was 0.68~0.70 and 0.94~0.99, and the $R^2$ was 0.83~0.86 and 0.48~0.61 respectively. The average $R^2$ for groundwater level was from 0.53 to 0.61. Under the future temperature increase of $4.3^{\circ}C$ and precipitation increase of 6.9% in 2080s (2070~2099) based on the historical periods (1976~2005) from HadGEM3-RA RCP 8.5 scenario, the future groundwater level shows decrease of -13.0 cm, -5.0 cm, -9.0 cm at 3 upstream locations (JSJS, OCCS, BEMR) and increase of +3.0 cm, +1.0 cm at 2 downstream locations (CASS, BYBY) respectively. The future groundwater level was directly affected by the groundwater recharge by the future seasonal spatial variation of rainfall in the watershed.

• Korean journal of applied entomology
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• v.53 no.4
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• pp.375-380
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• 2014

The sweetpotato whitefly (SPW), Bemisia tabaci Gennadius, is a major pest in tomato greenhouses on Jeju Island because they transmit viral diseases. To develop practical sampling methods for adult SPWs, yellow-color sticky traps were used in commercial tomato greenhouses throughout the western part of Jeju Island in 2011 and 2012. On the basis of the size and growing conditions in the tomato greenhouses, 20 to 30 traps were installed in each greenhouse for developing a sampling plan. Adult SPWs were more attracted to horizontal traps placed 60 cm above the ground than to vertical trap placed 10 cm above the plant canopy. The spatial patterns of the adult SPWs were evaluated using Taylor's power law (TPL) and Iwao's patchiness regression (IPR). The results showed that adult SPWs were aggregated in each surveyed greenhouse. In this study, TPL showed better performance because of the coefficient of determination ($r^2$). On the basis of the fixed-precision level sampling plan using TPL parameters, more traps were required for higher precision in lower SPW densities per trap. A sequential sampling stop line was constructed using TPL parameters. If the treatment threshold was greater than 10 maximum adult SPWs on a trap, the required traps numbered 15 at a fixed-precision level of 0.25. In estimating the mean density per trap, the proportion of traps with two or more adult SPWs was more efficient than whole counting: ${\ln}(m)=1.19+0.90{\ln}(-{\ln}(1-p_T))$. The results of this study could be used to prevent the dissemination of SPW as a viral disease vector by using accurate control decision in SPW management programs.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.122-126
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• 2010

Purpose: F-18-FPCIT that shows strong familiarity with DAT located at a neural terminal site offers diagnostic information about DAT density state in the region of the striatum especially Parkinson's disease. In this study, we altered the iteration and subset and measured SUV${\pm}$SD and Contrasts from phantom images which set up to specific iteration and subset. So, we are going to suggest the appropriate range of the iteration and subset. Materials and Methods: This study has been performed with 10 normal volunteers who don't have any history of Parkinson's disease or cerebral disease and Flangeless Esser PET Phantom from Data Spectrum Corporation. $5.3{\pm}0.2$ mCi of F-18-FPCIT was injected to the normal group and PET Phantom was assembled by ACR PET Phantom Instructions and it's actual ratio between hot spheres and background was 2.35 to 1. Brain and Phantom images were acquired after 3 hours from the time of the injection and images were acquired for ten minutes. Basically, SIEMENS Bio graph 40 True-point was used and True-X method was applied for image reconstruction method. The iteration and Subset were set to 2 iterations, 8 subsets, 3 iterations, 16 subsets, 6 iterations, 16 subsets, 8 iterations, 16 subsets and 8 iterations, 21 subsets respectively. To measure SUVs on the brain images, ROIs were drawn on the right Putamen. Also, Coefficient of variance (CV) was calculated to indicate the uniformity at each iteration and subset combinations. On the phantom study, we measured the actual ratio between hot spheres and back ground at each combinations. Same size's ROIs were drawn on the same slide and location. Results: Mean SUVs were 10.60, 12.83, 13.87, 13.98 and 13.5 at each combination. The range of fluctuation by sets were 22.36%, 10.34%, 1.1%, and 4.8% respectively. The range of fluctuation of mean SUV was lowest between 6 iterations 16 subsets and 8 iterations 16 subsets. CV showed 9.07%, 11.46%, 13.56%, 14.91% and 19.47% respectively. This means that the numerical value of the iteration and subset gets higher the image's uniformity gets worse. The range of fluctuation of CV by sets were 2.39, 2.1, 1.35, and 4.56. The range of fluctuation of uniformity was lowest between 6 iterations, 16 subsets and 8 iterations, 16 subsets. In the contrast test, it showed 1.92:1, 2.12:1, 2.10:1, 2.13:1 and 2.11:1 at each iteration and subset combinations. A Setting of 8 iterations and 16 subsets reappeared most close ratio between hot spheres and background. Conclusion: Findings on this study, SUVs and uniformity might be calculated differently caused by variable reconstruction parameters like filter or FWHM. Mean SUV and uniformity showed the lowest range of fluctuation at 6 iterations 16 subsets and 8 iterations 16 subsets. Also, 8 iterations 16 subsets showed the nearest hot sphere to background ratio compared with others. But it can not be concluded that only 6 iterations 16 subsets and 8 iterations 16 subsets can make right images for the clinical diagnosis. There might be more factors that can make better images. For more exact clinical diagnosis through the quantitative analysis of DAT density in the region of striatum we need to secure healthy people's quantitative values.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4323-4337
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• 1977

The study was to estimate the effect of the rise of water temperature in the warm water pool and to make contribution to the establishment of reducing to a damage of cool water as well as to the planning for warm water pool. This observation was performed in Wudu warm water pool located at Wudu-Dong of Chuncheon for two years from 1975 to 1976. The results were showed as follows; 1. The daily variation of water temperature was the least for inset (No.1; 0.6$^{\circ}C$) the second for middle overflow (No2: 3$^{\circ}C$, No.3; 2.3$^{\circ}C$) and another for outflet (No.4; 3.6$^{\circ}C$, No.5; 3.8$^{\circ}C$) And the highest reaching time of water temperature in each block was later about 1 hour than the time at which air temperature happend in the daytime. So, the variation of water temperature was sensitive to the variation of air temperature 2. The monthly variation of water temperature at each measuring point was plotted to be increased with increase in air temperature till August (Mean monthly rising degree; No.1; 1.15$^{\circ}C$, No.2; 1.7$^{\circ}C$, No.3; 1.73$^{\circ}C$, No.4; 2.08$^{\circ}C$, No.5; 2.0$^{\circ}C$), and expressed gradually descended influence upon water temperature after August. 3. The mean temperature of inflow folwed in warm Water pool was 7.5∼12.5$^{\circ}C$, and outflow temperature was described as 13.4∼22.5$^{\circ}C$ to be climbed. And So, the rising interval of water temperature was shown as 6.7∼10.4$^{\circ}C$. 4. The correlation between the rising of water temperature and the weather condition was found out highly significant. As the result, their correlation coefficents of water temperature depending on mean air temperature, ground temperature, wind velocity and relative humidity were to be 0.93, 0.90, - 0.83 and 0.71 respectively. But there was no confrimation of the correlation on the clouds, sunlight time, volume of evaporation, and heat capacity of horizontal place. 5. The water temperature of balance during the period of rice growing in Chuncheon district was shown as table 10, and the mean of whole period was calculated as about 23.7$^{\circ}C$. 6. The observed value of the outflow temperature passed through the warm water pool was higher than that of computed, the mean difference between two value was marked as 1.15$^{\circ}C$ for blockl, 1.18$^{\circ}C$ for block2, and 0.47$^{\circ}C$ for block3, respectivly. Therefore, the ratio on the rising degree between the observed and computed were shown as 53%, 44%, and 18%, mean 38% through each block warm water pool (referring item $\circled9$ of table 11,12, and 13). Accordingly, formula (4) in order to fit for each block warm water pool was transfromed as follow; {{{{ { theta }_{w } - { theta }_{ 0} =[1-exp LEFT { { 1-(1+2 varphi )} over {cp } CDOT { A} over { q} RIGHT } ] TIMES ( { theta }_{w } - { theta }_{ 0}) TIMES C }}}} Here, correction coefficinent was computed 1.38, and being substituted 1.38 for C in preceding formula, the expected water temperature will be calculated to be able to irrigate the rice paddy. As the result, we can apply the coefficient in order to plan and to construct a new warm water pool.

• Restorative Dentistry and Endodontics
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• v.30 no.2
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• pp.112-120
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• 2005

This study was done to evaluate whether there were any differences in microleakage of class V composite restorations according to restoration site and cavity size. Total sixty-four restorations were made in molar teeth using Esthet-X. Small ($2\;{\times}\;2\;{\times}\;1.5\;mm$) and large ($4{\times}2{\times}1.5\;mm$) restorations were made at the buccal/lingual surface and the proximal surface each. After 1,000 times of thermocycling ($5^{\circ}\;-\;55^{\circ}C$), resin replica was made and the percentage of marginal gap to the whole periphery of the restoration was estimated from SEM evaluation. Thermocycled tooth was dye penetrated with $50\%$ silver nitrate solution. After imbedding in an auto-curing resin, it was serially ground with a thickness of 0.25 mm. Volumetric microleakage was estimated after reconstructing three dimensionally. Two-way ANOVA and independent T-test for dye volume, Mann-Whitney U test for the percentage of marginal gap, Spearman's rho test for the relationship between two techniques were used, The results were as follows : 1. The site and size of the restoration affected on the microleakage of restoration. Namely, much more leakage was seen in the proximal and the large restorations rather than the buccal/lingual and the small restorations. 2. Close relationship was found between two techniques (Correlation coefficient = 0.614/ P = 0.000). Within the limits of this study, it was noted that proximal and the large restorations leaked more than buccal/lingual and the small restorations. Therefore, it should be strictly recommended large exposure of margins should be avoided by reducing unnecessary tooth reduction.