• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.135-143
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• 2006

This study presents the results of a series of laboratory scale slope failure experiments aimed at clarifying the process and the condition leading to the initiation of rainfall-induced slope failures. For the evaluation of hydrologic response of the model slopes in relation the process of failure initiation, measurements were focused on the changes in volumetric water content during the initiation process. The process leading to failure initiation commences by the development of a seepage face. It appears reasonable to conclude that slope failures are a consequence of the instability of seepage area formed at the slope surface during rainfall period. Therefore, this demonstrates the importance of monitoring the development seepage area for useful prediction about the timing of a particular failure event. The hydrologic response of soil slopes leading to failure initiation is characterized by three phases (phase I, II and III) of significant increase in volumetric water content in association with the ingress of wetting front and the rise of groundwater level within the slope. The period of phase III increase in volumetric water content can be used to initiate advance warning towards a failure initiation event. Therefore, for the concept outlined above, direct and continuous monitoring of the change in volumetric water content is likely to provide the possibility for the development of a reliable and effective means of predicting the occurrence of rainfall-induced slope failures.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.587-596
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• 2014

Soil moisture is one of the most important interests in hydrological response and the interaction between the land surface and atmosphere. Estimation of Antecedent Wetness Conditions (AWC) which is soil moisture condition prior to a rainfall in the basin should be considered for rainfall-runoff prediction. In this study, Soil Wetness Index (SWI), Antecedent Precipitation Index ($API_5$), remotely sensed Soil Moisture ($SM_{rs}$), and 5 days ground Soil Moisture ($SM_{g5}$) were selected to estimate the AWC at four study area in the Korean Peninsula. The remotely sensed soil moisture data were taken from the AMSR-E soil moisture archive. The maximum potential retention ($S_{obs}$) was obtained from direct runoff and rainfall using Soil Conservation Service-Curve Number (SCS-CN) method by rainfall data of 2011 for each study area. Results showed the great correlations between the maximum potential retention and SWI with a mean correlation coefficient which is equal to -0.73. The results of time length representing the time scale of soil moisture showed a gap from region to region. It was due to the differences of soil types and the characteristics of study area. Since the remotely sensed soil moisture has been proved as reasonable hydrological variables to predict a wetness in the basin, it should be continuously monitored.

• Food Science of Animal Resources
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• v.30 no.3
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• pp.487-494
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• 2010

Cooked pork can be easily contaminated with Staphylococcus aureus during carriage and serving after cooking. This study was performed to develop growth prediction models of S. aureus to assure the safety of cooked pork. The Baranyi and Gompertz primary predictive models were compared. These growth models for S. aureus in cooked pork were developed at storage temperatures of 5, 15, and $25^{\circ}C$. The specific growth rate (SGR) and lag time (LT) values were calculated. The Baranyi model, which displayed a $R^2$ of 0.98 and root mean square error (RMSE) of 0.27, was more compatible than the Gompertz model, which displayed 0.84 in both $R^2$ and RMSE. The Baranyi model was used to develop a response surface secondary model to indicate changes of LT and SGR values according to storage temperature. The compatibility of the developed model was confirmed by calculating $R^2$, $B_f$, $A_f$, and RMSE values as statistic parameters. At 5, 15 and $25^{\circ}C$, $R^2$ was 0.88, 0.99 and 0.99; RMSE was 0.11, 0.24 and 0.10; $B_f$ was 1.12, 1.02 and 1.03; and $A_f$ was 1.17, 1.03 and 1.03, respectively. The developed predictive growth model is suitable to predict the growth of S. aureus in cooked pork, and so has potential in the microbial risk assessment as an input value or model.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.4
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• pp.588-594
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• 1997

In this study, the shelf-life of Kochujang during storage was predicted through physicochemical and sensory analyses. Amino nitrogen, lightness, characteristics of surface color, pH and number of viable cell counts in Kochujang decreased during storage, while ammonia nitrogen, titratable acidity and viscosity increased. Among the physicochemical analyses, amino nitrogen content exhibited the highest correlation with sensory score. The marginal amounts of amino nitrogen was 170.6mg%. Degradation rate of amino nitrogen was a first order reaction. Q$_{10}$-value and the activation energy of Kochujang during storage were 1.80 and 8.6kca1/mol, respectively. The shelf-life Predicted of Kochujang at each storage temperature was calculated. The shelf-life predicted was 467 days at 1$0^{\circ}C$, 261 days at 2$0^{\circ}C$ and 133 days at 35$^{\circ}C$.

• Food Science and Preservation
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• v.12 no.4
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• pp.344-349
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• 2005

Microwave-assisted process (MAP) was applied to extract antioxidant-related components from Thymus quinquecostatus var. japonica Hara. Microwave power(2,450 MHz, $0{\sim}160$ W) and extraction time($1{\sim}5\;min$) were used as independent variables($X_i$) for central composite design to yield 10 different extraction conditions. Response surface methodology was applied to predict optimum extraction conditions for dependent variables of extracts, such as total yield, total phenolics, flavonoid, and electron donation ability depending on different powers and extraction times of MAP. Determination coefficients($R^2$) of regression equations for dependent variables were higher than 0.93 excluding that of total phenolics, and microwave power was predicted more influential than extraction time in MAP (p<0.05). The optimal extraction time for each dependent variable was ranged from 3.36 to 4.97 min, but microwave power showed wide ranges depending on variables. The superimposed contour maps for maximized dependent variables illustrated extraction conditions of 64 to 100 W in microwave power and 2.9 to 4.0 min in extraction time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.439-447
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• 2019

In this study, experiments were conducted to establish appropriate measures for slopes with high risk of collapse and to obtain results for minimizing slope collapse damage by detecting the micro-displacement of soil in advance by installing a laser sensor and a vibration sensor in the landslide reduction model experiment. Also, the behavior characteristics of the soil layer due to rainfall and moisture ratio changes such as pore water pressure and moisture were analyzed through a landslide reduction model experiment. The artificial slope was created using granite weathering soil, and the resulting water ratio(water pressure, water) changes were measured at different rainfall conditions of 200mm/hr and 400mm/hr. Laser sensors and vibration sensors were applied to analyze the surface displacement, and the displacement time were compared with each other by video analysis. Experiments have shown that higher rainfall intensity takes shorter time to reach the limit, and increase in the pore water pressure takes shorter time as well. Although the landslide model test does not fully reflect the site conditions, measurements of the time of detection of displacement generation using vibration sensors show that the timing of collapse is faster than the method using laser sensors. If ground displacement measurements using sensors are continuously carried out in preparation for landslides, it is considered highly likely to be utilized as basic data for predicting slope collapse, reducing damage, and activating the measurement industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.7-13
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• 2019

This study aims to develop a FE Model to simulate dissimilar friction stir welding and to address its potential for fundamental analysis and practical applications. The FE model is based on Coupled Eulerian-Lagrangian approach. Multiphysics systems are calculated using explicit time integration algorithm, and heat generations by friction and inelastic heat conversion as well as heat transfer through the bottom surface are included. Using the developed model, friction stir welding between an Al6061T6 plate and an AZ61 plate were simulated. Three simulations are carried out varying the welding parameters. The model is capable of predicting the temperature and plastic strain fields and the distribution of void. The simulation results showed that temperature was generally greater in Mg plates and that, as a rotation speed increase, not the maximum temperature of Mg plate increased, but did the temperature of Al plate. In addition, the model could predict flash defects, however, the prediction of void near the welding tool was not satisfactory. Since the model includes the complex physics closely occurring during FSW, the model possibly analyze a lot of phenomena hard to discovered by experiments. However, practical applications may be limited due to huge simulation time.

• Translational and Clinical Pharmacology
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• v.26 no.4
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• pp.160-165
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• 2018

Indobufen ($Ibustrin^{(R)}$), a reversible inhibitor of platelet aggregation, exists in two enantiomeric forms in 1:1 ratio. Here, we characterized the anti-platelet effect of S- and R-indobufen using response surface modeling using $NONMEM^{(R)}$ and predicted the therapeutic doses exerting the maximal efficacy of each enantioselective S- and R-indobufen formulation. S- and R-indobufen were added individually or together to 24 plasma samples from drug-naïve healthy subjects, generating 892 samples containing randomly selected concentrations of the drugs of 0-128 mg/L. Collagen-induced platelet aggregation in platelet-rich plasma was determined using a Chrono-log Lumi-Aggregometer. Inhibitory sigmoid $I_{max}$ model adequately described the anti-platelet effect. The S-form was more potent, whereas the R-form showed less inter-individual variation. No significant interaction was observed between the two enantiomers. The anti-platelet effect of multiple treatments with 200 mg indobufen twice daily doses was predicted in the simulation study, and the effect of S- or R-indobufen alone at various doses was predicted to define optimal dosing regimen for each enantiomer. Simulation study predicted that 200 mg twice daily administration of S-indobufen alone will produce more treatment effect than S-and R-mixture formulation. S-indobufen produced treatment effect at lower concentration than R-indobufen. However, inter-individual variation of the pharmacodynamic response was smaller in R-indobufen. The present study suggests the optimal doses of R-and S-enantioselective indobufen formulations in terms of treatment efficacy for patients with thromboembolic problems. The proposed methodology in this study can be applied to the develop novel enantio-selective drugs more efficiently.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1273-1282
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• 2018

Recently, active research on the Arctic Ocean has been conducted due to the influence of global warming and new Arctic ship route. Although previous studies already calculated quantitative extent of sea ice using passive microwave radiometers, melting at the edge of sea ice and surface roughness were hardly considered due to low spatial resolution. Since Sentienl-1A/B data in Extended Wide (EW) mode are being distributed as free of charge and bulk data for Arctic sea can be generated during a short period, the entire Arctic sea ice data can be covered in high spatial resolution by mosaicking bulk data. However, Sentinel-1A/B data in EW mode, especially in HV polarization, needs significant radiometric correction for further classification. Thus, in this study, we developed algorithms that can correct thermal noise and scalloping effects, and confirmed that Arctic sea ice and open-water were well classified using the corrected dual-polarization SAR data.

• Journal of Platform Technology
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• v.8 no.3
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• pp.10-21
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• 2020

Partial discharge occurs a lot in high-voltage power equipment such as switchgear, transformers, and switch gears. Partial discharge shortens the life of the insulator and causes insulation breakdown, resulting in large-scale damage such as a power outage. There are several types of partial discharge that occur inside the product and the surface. In this paper, we design a predictive model that can predict the pattern and probability of occurrence of partial discharge. In order to analyze the designed model, learning data for each type of partial discharge was collected through the UHF sensor by using a simulator that generates partial discharge. The predictive model designed in this paper was designed based on CNN during deep learning, and the model was verified through learning. To learn about the designed model, 5000 training data were created, and the form of training data was used as input data for the model by pre-processing the 3D raw data input from the UHF sensor as 2D data. As a result of the experiment, it was found that the accuracy of the model designed through learning has an accuracy of 0.9972. It was found that the accuracy of the proposed model was higher in the case of learning by making the data into a two-dimensional image and learning it in the form of a grayscale image.