• Journal of Food Hygiene and Safety
• /
• v.26 no.1
• /
• pp.57-63
• /
• 2011

This survey was conducted to develop an appropriate management for safety of children snacks. In this study, monitorings of food additives such as nine kinds of tar colors (tartrazine, sunset yellow FCF, brilliant blue FCF, indigo carmine, new coccine, amaranth, erythrosine, allura red and fast green FCF) which are sold at stationary store around the school, were performed. Eighty two samples (3 snacks, 71 candies, 4 chocolates and 4 beverages) were analyzed for tar colors. Results of risk assessment for tar colors were expressed as EDI (Estimated Daily Intake) comparing with ADI (Acceptable Daily Intake). The ratio of high risk group for tar color intake (95th) were 0-3.56%. The consumptions of tar colors from domestic and imported products for nine kinds of tar colors in candies were not significantly different. The results of this study indicated that each ED! of nine kinds of tar colors sold at stationary store around the school is much lower than each ADI in general. Consequently, the children snacks are thought to be safe for consumption.

• Journal of Food Hygiene and Safety
• /
• v.26 no.4
• /
• pp.448-453
• /
• 2011

This study was conducted to develop an appropriate management for safety of children snacks. In this study, monitorings of food additives such as four kinds of sweeteners (sodium saccharin, aspartame, acesulfame potassium, sucralose) which are sold in children snacks at stationary store around the school were performed. 92 samples (34 ice cakes, 52 beverages and 6 candies) were analyzed for sweeteners. Contents of 4 kinds of sweeteners in ice cakes, beverages and candies were 0.41, 0.47, 0.00 mg/kg for sodium saccharin, 0.00, 20.54, 197.09 mg/kg for aspartame, 0.00, 28.10, 0.00 mg/kg for acesulfame potassium, 9.99, 1.40, 0.00 mg/kg for sucralose. Results of risk assessment for sweeteners were expressed as EDI (Estimated Daily Intake) comparing with ADI (Acceptable Daily Intake). The ratio of high risk group for sweeteners intake (95th) were 0~2.66%. The results of this study indicated that each EDI of four kinds of sweeteners sold at stationary stores around the school is much lower than each ADI in general. Consequently, the children snacks are thought to be safe for consumption.

• Journal of Food Hygiene and Safety
• /
• v.24 no.2
• /
• pp.154-161
• /
• 2009

This survey was conducted to monitor the safety of children snacks circulated in a stationary store or small shop around the elementary school from March to October, 2008, in Gwangju. A total of 309 samples was tested. Of these samples, 254 were confectioneries, 41 were ready-to-eat foods like kimbap, 4 were beverages and 10 were the others like fishery products. 259 were domestic products and 50 were imported. By the origin of imported samples, 17 were from china, 6 from U.S.A., 5 from india and etc. We found out that in acid value, 2 cases of fried snacks(3.9 and 4.4) proved to exceed regulatory guidance(2.0). And among ready-to-eat foods, two kimbap had Staphylococcus aureus, and one had Escherichia coli. which microorganism could cause food poisoning.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.4
• /
• pp.263-270
• /
• 2017

The shipbuilding industry uses large stationary tanks to store low-pressure air, which is used to open and close large shut-off valves. However, when supplying air from the tank to a distant valve, there are problems related to the need for supplementary pipes and the pressure drop during transportation. In this study, a portable welded vessel for storing high-pressure nitrogen (11 kg, 10 L, and 50 bar) was designed to prevent air leakage and improve the convenience of workers. This pressure vessel was elliptical to reduce the number of welded parts, which are structurally weak. The thickness and ratio of the major and minor axes of the pressure vessel were calculated to verify its structure stability at the working pressure (50 bar), and that the proposed weight and capacity were satisfactory. The residual stress caused by the welding process was calculated by performing a transient thermal-structural coupled field analysis using the ANSYS parametric design language (APDL), and the fatigue life of the vessel was verified based on the Goodman criterion.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.1
• /
• pp.29-41
• /
• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_2
• /
• pp.1117-1132
• /
• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.