• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.337-357
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• 2021

Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.

• Food Engineering Progress
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• v.14 no.3
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• pp.208-216
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• 2010

Lab scale experiments were conducted in order to assess the applicability of $CaCO_{3}$-alginate beads as neutralizer for the high cell density cultivation and prepare the direct vat inoculation cultures of isolated sourdough lactic acid bacteria. With increasing the amount of bead and decreasing the diameter of bead in acidic solution, the neutralizing effect of $CaCO_{3}$-alginate bead became higher. In batch process with $CaCO_{3}$-alginate beads, Lactobacillus amylovorus DU-21 isolated from sourdough showed the highest viable cell counts and optical density in MRS broth. The values of viable cell counts and optical density were 9.996 log CFU/mL and 3.97, respectively. Experiments on the conditions which increase viability during lyophilization were carried out and the following results were obtained; 15% glycerol revealed the high cryoprotective effect on the concentrated cultures during lyophilization among the two cryoprotective agents. Consequently, $CaCO_{3}$-alginate beads and 15% glycerol were found to be useful not only to cultivate Lactobacillus amylovorus DU-21 but also to preserve strain.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.573-579
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• 2019

The purpose of this study is predicted easily the entrance surface dose (ESD) in chest digital radiography. We used two detector type such as flat-panel detector (FP) and IP (Imaging plate detector). ESD was measured at each exposure condition combined tube voltage with tube current using dosimeter, after attaching on human phantom, it was repeated 3 times. Phantom images were evaluated independently by three chest radiologists after blinding image. Dose-area product (DAP) or exposure index (EI) was checked by Digital Imaging and Communications in Medicine (DICOM) header on phantom images. Statistical analysis was performed by the linear regression using SPSS ver. 19.0. ESD was significant difference between FP and IP($85.7{\mu}Gy$ vs. $124.6{\mu}Gy$, p=0.017). ESD was positively correlated with image quality in FP as well as IP. In FP, adjusted R square was 0.978 (97.8%) and linear regression model was $ESD=0.407+68.810{\times}DAP$. DAP was 4.781 by calculating the $DAP=0.021+0.014{\times}340{\mu}Gy$. In IP, adjusted R square was 0.645 (64.5%) and linear regression model was $ESD=-63.339+0.188{\times}EI$. EI was 1748.97 by calculating the $EI=565.431+3.481{\times}340{\mu}Gy$. In chest digital radiography, the ESD can be easily predicted by the DICOM header information.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.77-89
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• 2021

In this study, a method has been proposed to improve the performance of hydraulic property estimation model developed by Jeong et al. (2020). In their study, low-dimensional features of the annual groundwater level (GWL) fluctuation patterns extracted based on a Denoising autoencoder (DAE) was used to develop a regression model for predicting hydraulic properties of an aquifer. However, low-dimensional features of the DAE are highly dependent on the precipitation pattern even if the GWL is monitored at the same location, causing uncertainty in hydraulic property estimation of the regression model. To solve the above problem, a process for generating the GWL fluctuation pattern for conditioning the precipitation is proposed based on a conditional variational autoencoder (CVAE). The CVAE trains a statistical relationship between GWL fluctuation and precipitation pattern. The actual GWL and precipitation data monitored on a total of 71 monitoring stations over 10 years in South Korea was applied to validate the effect of using CVAE. As a result, the trained CVAE model reasonably generated GWL fluctuation pattern with the conditioning of various precipitation patterns for all the monitoring locations. Based on the trained CVAE model, the low-dimensional features of the GWL fluctuation pattern without interference of different precipitation patterns were extracted for all monitoring stations, and they were compared to the features extracted based on the DAE. Consequently, it can be confirmed that the statistical consistency of the features extracted using CVAE is improved compared to DAE. Thus, we conclude that the proposed method may be useful in extracting a more accurate feature of GWL fluctuation pattern affected solely by hydraulic characteristics of the aquifer, which would be followed by the improved performance of the previously developed regression model.

• Economic and Environmental Geology
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• v.53 no.6
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• pp.667-675
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• 2020

An Alum-sludge based adsorbent (ASBA) was synthesized by the hydrothermal treatment of alum sludge obtained from settling basin in water treatment plant. ASBA was applied to remove fluoride and arsenic in artificially-contaminated aqueous solutions and mine drainage. The mineralogical crystal structure, composition, and specific surface area of ASBA were identified. The result revealed that ASBA has irregular pores and a specific surface area of 87.25 ㎡ g-1 on its surface, which is advantageous for quick and facile adsorption. The main mineral components of the adsorbent were found to be quartz(SiO2), montmorillonite((Al,Mg)2Si4O10(OH)2·4H2O) and albite(NaAlSi3O8). The effects of pH, reaction time, initial concentration, and temperature on removal of fluoride and arsenic were examined. The results of the experiments showed that, the adsorbed amount of fluoride and arsenic gradually decreased with increasing pH. Based on the results of kinetic and isotherm experiments, the maximum adsorption capacity of fluoride and arsenic were 7.6 and 5.6 mg g-1, respectively. Developed models of fluoride and arsenic were suitable for the Langmuir and Freundlich models. Moreover, As for fluoride and arsenic, the increase rate of adsorption concentration decreased after 8 and 12 hr, respectively, after the start of the reaction. Also, the thermodynamic data showed that the amount of fluoride and arsenic adsorbed onto ASBA increased with increasing temperature from 25℃ to 35℃, indicating that the adsorption was endothermic and non-spontaneous reaction. As a result of regeneration experiments, ASBA can be regenerated by 1N of NaOH. In the actual mine drainage experiment, it was found that it has relatively high removal rates of 77% and 69%. The experimental results show ASBA is effective as an adsorbent for removal fluoride and arsenic from mine drainage, which has a small flow rate and acid/neutral pH environment.

• The Journal of Korean society of community based occupational therapy
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• v.10 no.3
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• pp.37-52
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• 2020

Objective : This study was conducted to identify occupational therapists working in public health centers, the characteristics and actual conditions of occupational therapists in the community, and use them as basic data on occupational therapists in the community as of 2020. Methods : 77 questionnaires were replied by e-mail from OTs work at nationwide health public centers. Job characteristics and status were analysed by descriptive statistics and check correlation between job satisfaction and other factors. Results : Most survey respondents were female(77.9%) and 20-30(96.1%).. Some occupational therapists worked for dementia related team(72.7%) and others worked for like visiting care, health care, and rehabilitation center etc. Rate of experiences of public health center was 1-2 years(67.5%), the most common type of contract was flexible part-time worker(61%) and work intensity(94.8%) and satisfaction of work was very high(85.7%). The highest difficulty of their job was budget administrative work(26.7%) and of non-work difficulty was inequality under contracts(27.2%). They usually participated at dementia shelter, visiting OT, group OT. Difficulty of their job was high in budget administration, dementia shelters, and visiting work treatments. Goals of treatment were high in improvement of cognitive ability and, family support. Frequency of treatment was high in improvement of cognitive therapy, family support, and evaluation. Occupational therapy targets for health centers were dementia, the general elderly, and adult brain lesions, including those for ordinary people, psychiatric disorders and children. It was found that the primary occupations for evaluation were nurses (35.7%) and occupational therapists (33.7%), and that MMSE-DS, SGDS, and SMCQ were used a lot. Conclusion : This study could identify the job characteristics and status of community OTs. We hope that this result could be basic data for building expertise and role for community OTs in changing situations like community cares.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1465-1483
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• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.85-103
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• 2023

The in-situ remediation of a solidified stratum containing a large amount of fine-texture material like clay or organic matter in contaminated soil faces limitations such as increased remediation cost resulting from decreased purification efficiency. Even if the soil conditions are good, remediation generally requires a long time to complete because of non-uniform soil properties and low permeability. This study assessed the remediation effect and evaluated the field applicability of a methodology that combines pneumatic fracturing, vacuum extraction, and plasma blasting (the PPV method) to improve the limitations facing existing underground remediation methods. For comparison, underground remediation was performed over 80 days using the experimental PPV method and chemical oxidation (the control method). The control group showed no decrease in the degree of contamination due to the poor delivery of the soil remediation agent, whereas the PPV method clearly reduced the degree of contamination during the remediation period. Remediation effect, as assessed by the reduction of the highest TPH (Total Petroleum Hydrocarbons) concentration by distance from the injection well, was uncleared in the control group, whereas the PPV method showed a remediation effect of 62.6% within a 1 m radius of the injection well radius, 90.1% within 1.1~2.0 m, and 92.1% within 2.1~3.0 m. When evaluating the remediation efficiency by considering the average rate of TPH concentration reduction by distance from the injection well, the control group was not clear; in contrast, the PPV method showed 53.6% remediation effect within 1 m of the injection well, 82.4% within 1.1~2.0 m, and 68.7% within 2.1~3.0 m. Both ways of considering purification efficiency (based on changes in TPH maximum and average contamination concentration) found the PPV method to increase the remediation effect by 149.0~184.8% compared with the control group; its average increase in remediation effect was ~167%. The time taken to reduce contamination by 80% of the initial concentration was evaluated by deriving a correlation equation through analysis of the TPH concentration: the PPV method could reduce the purification time by 184.4% compared with chemical oxidation. However, the present evaluation of a single site cannot be equally applied to all strata, so additional research is necessary to explore more clearly the proposed method's effect.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.1
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• pp.65-74
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• 2023

This study compared the surface roughness and microbial adhesion characteristics of Omnichroma, a novel composite resin developed using "smart chromatic technology", with those of two other conventional composite resins with different filler compositions. A total of 144 specimens were fabricated using 3 types of composite resins: Omnichroma (nano-spherical), Filtek Z350XT (nanofill), and Tetric N-Ceram (nanohybrid) and, divided into 3 groups of 48. Finishing was performed using tungsten carbide burs. Specimens were then divided into 3 subgroups using different polishing methods: Control, SofLex, and PoGo. Surface roughness was analyzed quantitatively and qualitatively using an atomic force microscope and a scanning electron microscope. Microbial adhesion was assessed by culturing Streptococcus mutans on the specimens for 24 hours and then measuring colony-forming units attached to the upper surface. The surface roughness (Ra) of Omnichroma was 0.123 ㎛ after finishing, and it exhibited a smooth surface compared to the other resins. However, after polishing, there were no significant differences in the surface roughness between the three composite groups, regardless of the polishing methods. The surfaces of the Control subgroups were significantly rougher than those of the SofLex subgroups in all 3 composite groups. However, except for Tetric N-Ceram, there were no significant differences between the Control and PoGo subgroups in the other composite groups. Microbial adhesion assessment showed no significant differences between any of the 3 composite resin subgroups; however, Omnichroma exhibited higher microbial adhesion than the other two composites. No significant correlation was observed between surface roughness and microbial adhesion.