• Food Science and Preservation
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• v.24 no.8
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• pp.1103-1112
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• 2017

This study was performed to investigate the effects of different cooking methods (boiling, roasting, stir-frying, and deep-frying) on folate retention in 6 kinds of mushrooms (Beech-, button-, Juda's ear-, oak-, oyster-, and winter-mushrooms) frequently consumed in Korea. In order to assure reliability of analytical data, trienzyme extraction-L casei method was verified and analytical quality control was also evaluated. Folate contents of mushrooms varied by 6.04-64.82 g/100 g depending on the type of mushrooms. and were significantly affected by cooking methods. Depending on cooking methods, folate contents of mushrooms decreased by 22-48%, 2-31%, and 17-56% for Juda's ear-, oak- and oyster-mushrooms, respectively, while 17-90% of folate was increased in Beech mushroom. Overall, the largest weight loss was found in boiled mushrooms, but the lowest one in deep-fried samples. True folate retention rates considering processing factor were less than 100% for all cooked mushrooms except for Beech samples. Overall, folate loss was the largest by boiling with water but the smallest by deep-frying. Both accuracy and precision of trienzyme extraction-L-casei method were excellent based on a recovery close to 100% and coefficient variations less than 3%. Quality control chart of folate analysis (n=26) obtained during the entire study and an international proficiency test (z-score=-0.5) showed that trienzyme extraction-L casei method is reliable enough for production of national folate database.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.603-614
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• 2021

Recently, the surface temperature in the seas around Korea has been continuously rising. This temperature rise causes changes in fishery resources and affects leisure activities such as fishing. In particular, high temperatures lead to the occurrence of red tides, causing severe damage to ocean industries such as aquaculture. Meanwhile, changes in sea temperature are closely related to military operation to detect submarines. This is because the degree of diffraction, refraction, or reflection of sound waves used to detect submarines varies depending on the ocean mixed layer. Currently, research on the prediction of changes in sea water temperature is being actively conducted. However, existing research is focused on predicting only the surface temperature of the ocean, so it is difficult to identify fishery resources according to depth and apply them to military operations such as submarine detection. Therefore, in this study, we predicted the temperature of the ocean mixed layer at a depth of 38m by using temperature data for each water depth in the upper mixed layer and meteorological data such as temperature, atmospheric pressure, and sunlight that are related to the surface temperature. The data used are meteorological data and sea temperature data by water depth observed from 2016 to 2020 at the IEODO Ocean Research Station. In order to increase the accuracy and efficiency of prediction, LSTM (Long Short-Term Memory), which is known to be suitable for time series data among deep learning techniques, was used. As a result of the experiment, in the daily prediction, the RMSE (Root Mean Square Error) of the model using temperature, atmospheric pressure, and sunlight data together was 0.473. On the other hand, the RMSE of the model using only the surface temperature was 0.631. These results confirm that the model using meteorological data together shows better performance in predicting the temperature of the upper ocean mixed layer.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.1-12
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• 2022

An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.903-913
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• 2021

In the flood season, the measurement of the river discharge has many restrictions due to reasons such as budget, manpower, safety, convenience in measurement and so on. In particular, when heavy rain events occur due to typhoons, etc., it is difficult to measure the amount of flood due to the above problems. In order to improve this problem, in this study, a method was developed that can measure the river discharge in a flood season simply and safely in a short time with minimal manpower by combining the functions of a drone and a surface velocity doppler radar. To overcome the mechanical limitations of drones caused by weather issues such as wind and rainfall derived from the measurement of the river discharge using the conventional drone, we developed a drone with P56 grade dustproof and waterproof performance, stable flight capability at a wind speed of up to 36 km/h, and a payload weight of up to 10 kg. Further, to eliminate vibration which is the most important constraint factor in the measurement with a surface velocity doppler radar, a damper plate was developed as a device that combines a drone and a surface velocity Doppler radar. The velocity meter DSVM (Dron and Surface Veloctity Meter using doppler radar) that combines the flight equipment with the velocity meter was produced. The error of ±3.5% occurred as a result of measuring the river discharge using DSVM at the point of Geumsan-gun (Hwangpunggyo) located at Bonghwang stream (the first tributary stream of the Geum River). In addition, when calculating the mean velocity from the measured surface velocity, the measurement was performed using ADCP simultaneously to improve accuracy, and the mean velocity conversion factor (0.92) was calculated by comparing the mean velocity. In this study, the discharge measured by combining a drone and a surface velocity meter was compared with the discharge measured using ADCP and floats, so that the application and utility of DSVM was confirmed.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.3
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• pp.208-218
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• 2012

Numerical simulation technique has been developed to calculate microwave backscattering from water surface. The simulation plays a role of a substitute for experiments. Validation of the simulation was shown by comparing with experimental results. Water area observations by microwave radar have been simulated to evaluate algorithms and systems. Furthermore, the simulation can be used to understand microwave scattering mechanism on the water surface. The simulation has applied to the various methods for water area observations, and the utilizations of the simulation are introduced in this paper. In the case of fixed radar, we show following examples, 1. Radar image with a pulse Doppler radar, 2. Effect of microwave irradiation width and 3. River observation (Water level observation). In addition, another application (4.Synthetic aperture radar image) is also described. The details of the applications are as follows. 1. Radar image with a pulse Doppler radar: A new system for the sea surface observation is suggested by the simulation. A pulse Doppler radar is assumed to obtain radar images that display amplitude and frequency modulation of backscattered microwaves. The simulation results show that the radar images of the frequency modulation is useful to measure sea surface waves. 2. Effect of microwave irradiation width: It is reported (Rheem[2008]) that microwave irradiation width on the sea surface affects Doppler spectra measured by a CW (Continuous wave) Doppler radar. Therefore the relation between the microwave irradiation width and the Doppler spectra is evaluated numerically. We have shown the suitable condition for wave height estimation by a Doppler radar. 3. River observation (Water level observation): We have also evaluated algorithms to estimate water current and water level of river. The same algorithms to estimate sea surface current and sea surface level are applied to the river observation. The simulation is conducted to confirm the accuracy of the river observation by using a pulse Doppler radar. 4. Synthetic aperture radar (SAR) image: SAR images are helpful to observe the global sea surface. However, imaging mechanisms are complicated and validation of analytical algorithms by SAR images is quite difficult. In order to deal with the problems, SAR images in oceanic scenes are simulated.

• Journal of Food Hygiene and Safety
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• v.31 no.1
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• pp.15-20
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• 2016

Malachite green was measured in 200 freshwater fish collected from local markets in Seoul using HPLC-DAD and LC-MS/MS. LC-MS/MS method was validated by linearity, accuracy, precision and limits of detection and quantification according to the CODEX's recommendation and HPLC-DAD method was applied according to the Food Code. Malachite green levels above the quantification limit of the LC-MS/MS were determined 18.5% (37) but just 1 fish was shown to contain malachite green by HPLC-DAD. Of 83 domestic fish, 21 fish were detected malachite green (25.3%). Of 117 fish from China, just 16 fish were detected malachite green (13.4%). In detection rate by species carp (35.0%), Crucian carp (30.4%), cat fish (28.0%), Korean bull head (23.8%), snake head (20.0%), eel (10.5%) and loach (7.8%) were in order. Especially, fish collected at summer were shown to contain malachite green frequently; the detection rate was 54.8%.

• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.33-40
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• 2013

From March 2012 to January 2013, this study was conducted as a part of the project for making a precise electronic ecological zoning map of vegetation on a highly reduced scale of 1 to 5,000 with a view to improving management efficiency of national parks and enlarging the availability of the data produced from the basic research monitoring the resources of national parks. For the research accuracy and rapidity, a vegetation map was specially created for the on-the-site-vegetation research. To make the map more meticulous, we categorized the vegetation database into five groups: broadleaved forest, coniferous forest, mixed forest, rock vegetation and miscellaneous one. After comparing the results of the data built for the vegetation research and the actual research findings, it was made clear that vegetation of both categories was almost the same in case of broad-leaved forest with 72.20% and 78.45% respectively, and also equivalent in other groups like, for example, coniferous forest (16.70%, 13.41%), mixed forest (9.50%, 7.49%) and rock vegetation (0.60%, 0.15%). According to the precise vegetation map produced from the research, the deciduous broad-leaved forest was the most widely prevalent type in the correlated hierarchical classification of vegetation, occupying 65.78% of the overall vegetation. It was followed by mountain valley forest (15.17%), coniferous forest (10.90%), and plantation forest (7.00%) in order. It is particularly noteworthy that Mt. Deogyusan national park has retained a very stable and versatile forest vegetation in the outstanding state since approximately 20% of the mountain turns out to belong to the I grade vegetation conservation classification which contains climax forests, unique vegetation, subalpine vegetation, matured stands which are older than 50 years and etc.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.3
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• pp.229-234
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• 2001

The EDXRF(Energy Dispersive X-ray Fluorescence Spectrometer) technique was applied to the determination of heavy metals in welding fume. The EDXRF method designed in this study was a non-destructive analysis method. Samples were analyzed directly by EDXRF without any pre-treatment such as digestion and dilution. The samples used to evaluate this method were laboratory samples exposed in a chamber connected with a welding fume generator. The samples were first analyzed using a non-destructive EDXRF method. The samples subsequently were analyzed using AAS method to verify accuray of the EDXRF method. The purpose of this study was to evaluate the possibility of the non-destructive analysis of heavy metals in welding fume by EDXRF. The results of this study were as follow: 1.When the samples were collected under the open-face sampling condition, a surface distribution of welding fume particles on sample filters was uniform, which made non-destructive analysis possible. 2. The method was statistically evaluated according to the NIOSH(National Institute for Occupational Safety and Health) and HSE(Health and Safety Executive) method. 3. The overall precision of the EDXRF method Was calculated at 3.45 % for Cr, 2.57 % for Fe and 3.78 % for Mn as relative standard deviation(RSD), respectively. The limits of detection were calculated at $0.46{\mu}g$/sample for Cr, $0.20{\mu}g$/sample for Fe and $1.14{\mu}g$/sample for Mn, respectively. 4. A comparison between the results of Cr, Fe, Mn analyzed by EDXRF and AAS was made in order to assess the accuracy of EDXRF method. The correlation coefficient between the results of EDXRF and AAS was 0.9985 for Cr, 0.9995 for Fe and 0.9982 for Mn, respectively. The overall uncertainty was determined to be ${\pm}12.31%$, 8.64 % and 11.91 % for Cr, Fe and Mn, respectively. In conclusion, this study showed that Cr, Fe, Mn in welding fume were successfully analyzed by the EDXRF without any sample pre-treatment such as digestion and dilution and a good correlation between the results of EDXRF and AAS was obtained. It was thus possible to use the EDXRF technique as an analysis method of working environment samples. The EDXRF method was an efficient method in a non-destructive analysis of heavy metals in welding fume.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• The Journal of Korean Society for Radiation Therapy
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• v.25 no.2
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• pp.181-186
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• 2013

Purpose: This study executed therapy plans on prostate cancer (homogeneous density area) and lung cancer (non-homogeneous density area) using radiation treatment planning systems such as $Pinnacle^3$ (version 9.2, Philips Medical Systems, USA) and Eclipse (version 10.0, Varian Medical Systems, USA) in order to quantify the difference between dose calculation according to density in IMRT. Materials and Methods: The subjects were prostate cancer patients (n=5) and lung cancer patients (n=5) who had therapies in our hospital. Identical constraints and optimization process according to the Protocol were administered on the subjects. For the therapy plan of prostate cancer patients, 10 MV and 7Beam were used and 2.5 Gy was prescribed in 28 fx to make 70 Gy in total. For lung cancer patients, 6 MV and 6Beam were used and 2 Gy was prescribed in 33 fx to make 66 Gy in total. Through two therapy planning systems, maximum dose, average dose, and minimum dose of OAR (Organ at Risk) of CTV, PTV and around tumor were investigated. Results: In prostate cancer, both therapy planning systems showed within 2% change of dose of CTV and PTV and normal organs (Bladder, Both femur and Rectum out) near the tumor satisfied the dose constraints. In lung cancer, CTV and PTV showed less than 2% changes in dose and normal organs (Esophagus, Spinal cord and Both lungs) satisfied dose restrictions. However, the minimum dose of Eclipse therapy plan was 1.9% higher in CTV and 3.5% higher in PTV, and in case of both lungs there was 3.0% difference at V5 Gy. Conclusion: Each TPS according to the density satisfied dose limits of our hospital proving the clinical accuracy. It is considered more accurate and precise therapy plan can be made if studies on treatment planning for diverse parts and the application of such TPS are made.