• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.472-478
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• 2021

Background: The Legionella case detection and notification rate have increased in public artificial water environments where people visit, including large buildings, public baths, and hospitals. Objectives: In this study, the distribution of Legionella and its epidemiologic characteristics were analyzed in the water systems of public facilities in Chungcheongnam-do Province in South Korea. Methods: Culture and PCR analysis were performed on 2,991 environmental water system samples collected from 2017 to 2019, and associations with year, facilities, seasons, and temperature of water system were statistically analyzed by using R-Studio for Windows. Descriptive data was compared using chi-square tests and independent t-tests. Results: The detection rate of Legionella increased from 3.1% in 2017 to 10.3% in 2019, appearing most frequently in the order of public baths, large-scale buildings, hospitals, and apartments. It was detected mainly in summer from June to August, over 1.0×10³ CFU/L on average in 133 cases (66.5%). Lots of germs were detected in bathtub water, cooling tower water, and warm water (p<0.001), and it was detected at higher rates in the cities where multipurpose facilities were concentrated than in rural areas (p=0.018). Conclusions: This study suggests that continuous monitoring and control are required for Legionella in the water system environment of high risk facilities. Moreover, these results will be helpful to prepare efficient management plans to prevent the Legionellosis that occurs in Chungcheongnam-do Province.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Food Engineering Progress
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• v.15 no.4
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• pp.324-331
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• 2011

Hyperspectral reflectance imaging technology was used to predict internal quality of cherry tomatoes with the spectral range of 400-1000 nm. Partial least square (PLS) regression method was used to predict firmness, sugar content, and acid content. The PLS models were developed with several preprocessing methods, such as normalization, standard normal variate (SNV), multiplicative scatter correction (MSC), and derivative of Savitzky Golay. The performance of the prediction models were investigated to find the best combination of the preprocessing and PLS models. The coefficients of determination ($R^{2}_{p}$) and standard errors of prediction (SEP) for the prediction of firmness, sugar content, and acid content of cherry tomatoes from green to red ripening stages were 0.876 and 1.875kgf with mean of normalization, 0.823 and $0.388^{\circ}Bx$ with maximum of normalization, and 0.620 and 0.208% with maximum of normalization, respectively.

• Food Science of Animal Resources
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• v.39 no.3
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• pp.371-378
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• 2019

The objective of this study was to develop mathematical models for describing the kinetic behavior of Staphylococcus aureus (S. aureus) in seasoned beef jerky. Seasoned beef jerky was cut into 10-g pieces. Next, 0.1 mL of S. aureus ATCC13565 was inoculated into the samples to obtain 3 Log CFU/g, and the samples were stored aerobically at $10^{\circ}C$, $20^{\circ}C$, $25^{\circ}C$, $30^{\circ}C$, and $35^{\circ}C$ for 600 h. S. aureus cell counts were enumerated on Baird Parker agar during storage. To develop a primary model, the Weibull model was fitted to the cell count data to calculate Delta (required time for the first decimal reduction) and ${\rho}$ (shape of curves). For secondary modeling, a polynomial model was fitted to the Delta values as a function of storage temperature. To evaluate the accuracy of the model prediction, the root mean square error (RMSE) was calculated by comparing the predicted data with the observed data. The surviving S. aureus cell counts were decreased at all storage temperatures. The Delta values were longer at $10^{\circ}C$, $20^{\circ}C$, and $25^{\circ}C$ than at $30^{\circ}C$ and $35^{\circ}C$. The secondary model well-described the temperature effect on Delta with an $R^2$ value of 0.920. In validation analysis, RMSE values of 0.325 suggested that the model performance was appropriate. S. aureus in beef jerky survives for a long period at low storage temperatures and that the model developed in this study is useful for describing the kinetic behavior of S. aureus in seasoned beef jerky.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• Nutrition Research and Practice
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• v.16 no.5
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• pp.646-657
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• 2022

BACKGROUND/OBJECTIVES: The doubly labeled water (DLW) method is the gold standard for estimating total energy expenditure (TEE) and is also useful for verifying the validities of dietary evaluation tools. In this study, we compared the accuracy of total energy intakes (TEI) estimated by the 24-h diet recall method with TEE obtained using the doubly labeled water method. SUBJECTS/METHODS: This study involved 71 subjects aged 20-49 yrs. Over a 14-day period, three 24-h diet recalls per subject (2 weekdays and 1 weekend day) were used to estimate energy intakes, while TEE was measured using the DLW method. The paired t-test was used to determine the significance of differences between TEI and TEE results, and the accuracy of the 24-h recall method was determined by accuracy predictions percentage, root mean square error, and bias. RESULTS: Average study subject age was 33.4 ± 8.6 yrs. The association between TEI and TEE was positive and significant (r = 0.463, P < 0.001), and the difference between TEI (2,084.3 ± 684.2 kcal/day) and TEE (2,401.7 ± 480.3 kcal/day) was also significant (P < 0.001). In all study subjects, mean TEI was 12.0% (307.5 ± 629.3 kcal/day) less than mean TEE, and 12.2% (349.4 ± 632.5 kcal/day) less in men and 11.8% (266.7 ± 632.5 kcal/day) less in women. Rates of TEI underprediction for all study subjects, men, and women, were 60.5%, 51.4%, and 66.7%, respectively. CONCLUSIONS: This study shows that 24-h diet recall underreports energy intakes. More research is needed to corroborate our findings and evaluate the accuracy of 24-h recall with respect to additional demographics.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.459-469
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• 2010

This study is to develop a grid-based daily runoff model considering seasonal vegetation canopy condition. The model simulates the temporal and spatial variation of runoff components (surface, interflow, and baseflow), evapotranspiration (ET) and soil moisture contents of each grid element. The model is composed of three main modules of runoff, ET, and soil moisture. The total runoff was simulated by using soil water storage capacity of the day, and was allocated by introducing recession curves of each runoff component. The ET was calculated by Penman-Monteith method considering MODIS leaf area index (LAI). The daily soil moisture was routed by soil water balance equation. The model was evaluated for 930 $km^2$ Yongdam watershed. The model uses 1 km spatial data on landuse, soil, boundary, MODIS LAI. The daily weather data was built using IDW method (2000-2008). Model calibration was carried out to compare with the observed streamflow at the watershed outlet. The Nash-Sutcliffe model efficiency was 0.78~0.93. The watershed soil moisture was sensitive to precipitation and soil texture, consequently affected the streamflow, and the evapotranspiration responded to landuse type.

• Journal of Preventive Medicine and Public Health
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• v.57 no.3
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• pp.288-297
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• 2024

Objectives: This study explored the prevalence and predictors of alcohol and cannabis co-use among 9263 Filipino adolescents, using data from the 2019 Global School-based Student Health Survey (GSHS). Methods: We conducted a cross-sectional secondary analysis of the GSHS, targeting adolescents aged 13-17 years and excluding cases with incomplete data on alcohol and cannabis use. Our analysis employed the bivariate chi-square test of independence and multivariable logistic regression using Stata version 18 to identify significant predictors of co-use, with a p-value threshold set at 0.05. Results: The weighted prevalence of co-users was 4.2% (95% confidence interval [CI], 3.4 to 5.3). Significant predictors included male sex (adjusted odds ratio [aOR], 4.50; 95% CI, 3.31 to 6.10; p<0.001) and being in a lower academic year, specifically grade 7 (aOR, 4.08; 95% CI, 2.39 to 6.99; p<0.001) and grade 8 (aOR, 2.20; 95% CI, 1.30 to 3.72; p=0.003). Poor sleep quality was also a significant predictor (aOR, 1.77; 95% CI, 1.29 to 2.44; p<0.001), as was a history of attempted suicide (aOR, 5.31; 95% CI, 4.00 to 7.06; p<0.001). Physical inactivity was associated with lower odds of co-use (aOR, 0.45; 95% CI, 0.33 to 0.62; p<0.001). Additionally, non-attendance of physical education classes (aOR, 1.48; 95% CI, 1.06 to 2.05; p=0.021), infrequent unapproved parental checks (aOR, 1.37; 95% CI, 1.04 to 1.80; p=0.024), and lower parental awareness of free-time activities (aOR, 0.63; 95% CI, 0.45 to 0.87; p=0.005) were associated with higher odds of co-use. Factors not significantly linked to co-use included age group, being in grade 9, always feeling lonely, having no close friends, being bullied outside school, and whether a parent or guardian understood the adolescent's worries. Conclusions: The findings highlight the critical need for comprehensive interventions in the Philippines, addressing not only physical inactivity and parental monitoring but also focusing on sex, academic grade, participation in physical education classes, sleep quality, and suicide attempt history, to effectively reduce alcohol and cannabis co-use among adolescents.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.3
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• pp.258-263
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• 2023

Backgrounds/Aims: Hemangiomas are the most common benign liver lesions; however, they are usually asymptomatic and seldom require surgery. Enucleation and resection are the most commonly performed surgical procedures for symptomatic lesions. This study aims to compare the outcomes of these two surgical techniques. Methods: A retrospective analysis of symptomatic hepatic hemangiomas (HH) operated upon between 2000 and 2021. Patients were categorized into the enucleation and resection groups. Demographic profile, intraoperative bleeding, and morbidity (Clavien-Dindo Grade) were compared. Independent t-test and chi-square tests were used for continuous and categorical variables respectively. p-value of < 0.05 was considered significant. Results: Sixteen symptomatic HH patients aged 30 to 66 years underwent surgery (enucleation = 8, resection = 8) and majority were females (n = 10 [62.5%]). Fifteen patients presented with abdominal pain, and one patient had an interval increase in the size of the lesion from 9 to 12 cm. The size of hemangiomas varied from 6 to 23 cm. The median blood loss (enucleation: 350 vs. resection: 600 mL), operative time (enucleation: 5.8 vs. resection: 7.5 hours), and postoperative hospital stay (enucleation: 6.5 vs. resection: 11 days) were greater in the resection group (statistically insignificant). In the resection group, morbidity was significantly higher (62.6% vs. 12.5%, p = 0.05), including one mortality. All patients remained asymptomatic during the follow-up. Conclusions: Enucleation was simpler with less morbidity as compared to resection in our series. However, considering the small number of patients, further studies are needed with comparable groups to confirm the superiority of enucleation over resection.