• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• Geophysics and Geophysical Exploration
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• v.19 no.4
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• pp.220-227
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• 2016

Marine seismic data have not only primary signals from subsurface but also ghost signals reflected from the sea surface. The ghost decreases temporal resolution of seismic data because it attenuates specific frequency components. For eliminating the ghost signals effectively, the exact ghost delaytimes and reflection coefficients are required. Because of undulation of the sea surface and vertical movements of airguns and streamers, the ghost delaytime varies spatially and randomly while acquiring seismic data. The reflection coefficient is a function of frequency, incidence angle of plane-wave and the sea state. In order to estimate the proper ghost delaytimes considering these characteristics, we compared the ghost delaytimes estimated with L-1 norm, L-2 norm and kurtosis of the deghosted trace and its autocorrelation on synthetic data. L-1 norm of autocorrelation showed a minimal error and the reflection coefficient was calculated using Kirchhoff approximation equation which can handle the effect of wave height. We applied the estimated ghost delaytimes and the calculated reflection coefficients to remove the source and receiver ghost effects. By removing ghost signals, we reconstructed the frequency components attenuated near the notch frequency and produced the migrated stack section with enhanced temporal resolution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of The Korean Association For Science Education
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• v.38 no.5
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• pp.705-720
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• 2018

The purpose of this study is to shed light on the meaning and value of interest (in Korean 'Jae-mi') in science education through literature analysis. Literature analyses were conducted on literature related to interest in various fields such as Korean language, psychology, philosophy, and education. Specifically, this study discussed the meaning of interest, the characteristics of the context of experiencing interest, the educational value of interest in science education, and the direction of science education to realize the value of interest. First, it was found that interest is an experience of emotional activation that can be felt through interaction with a specific object, and it is an emotional experience caused by the complex combination of various psychological factors, which is oriented sense, relationship, self, and object. Second, to understand the context of experience of interest, we conducted a topic modeling analysis with 1173 research articles related to interest. As a result of the analysis, it was confirmed that the context of interest is closely related with playfulness. And we addressed that this kind of playfulness is also found in science. Third, the educational values of interest in science education were discussed. In science education, fun is not only an instrumental value to induce science learning behavior, it is also one of the universal experiences that learners feel lively in science teaching-learning, and driving force of individual students' emotional development related to science. The students' active attitude to feel interest lead to creative thinking and action. Finally, we argued that the interest that should be aimed in science education should be active interest and experienced at trial and error, not passive interest induced by external stimuli. And science education culture should be encouraged to respect those who enjoy science. In particular, this study discussed the importance of each student's unique interest experience based on the philosophy of philosopher Deleuze (1976).

• Journal of Nutrition and Health
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• v.51 no.6
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• pp.567-579
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• 2018

Purpose: This study examined the mediation effects of dietary habits, nutrient intake, daily life in the relationship between the working hours of Korean shift workers and metabolic syndrome. Methods: Data were collected from the sixth (2013-2015) Korea National Health and Nutrition Examination Survey (KNHANES). The stochastic regression imputation was used to fill missing data. Statistical analysis was performed in Korean shift workers with metabolic syndrome using the SPSS 24 program for Windows and a structural equation model (SEM) using an analysis of moment structure (AMOS) 21.0 package. Results: The model fitted the data well in terms of the goodness of fit index (GFI) = 0.939, root mean square error of approximation (RMSEA) = 0.025, normed fit index (NFI) = 0.917, Tucker-Lewis index (TLI) = 0.984, comparative fit index (CFI) = 0.987, and adjusted goodness of fit index (AGFI) = 0.915. Specific mediation effect of dietary habits (p = 0.023) was statistically significant in the impact of the working hours of shift workers on nutrient intake, and specific mediation effect of daily life (p = 0.019) was statistically significant in the impact of the working hours of shift workers on metabolic syndrome. On the other hand, the dietary habits, nutrient intake and daily life had no significant multiple mediator effects on the working hours of shift workers with metabolic syndrome. Conclusion: The appropriate model suggests that working hours have direct effect on the daily life, which has the mediation effect on the risk of metabolic syndrome in shift workers.

• Korean Journal of Food Science and Technology
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• v.49 no.3
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• pp.274-278
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• 2017

In this study, predictive mathematical models were developed to estimate the kinetics of Staphylococcus aureus growth in processed meat product galbitang. Processed meat product galbitang was inoculated with 0.1 mL of S. aureus culture and stored at 4, 10, 20, $37^{\circ}C$. The ${\mu}_{max}$ (maximum specific growth rate) and LPD (lag phase duration) values were calculated. The primary model was used to develop a response surface secondary model. The growth parameters were analyzed using the square root model as a function of storage temperature. The developed model was confirmed by calculating RMSE (Root Mean Square Error) values as statistic parameters. The LPD decreased, but ${\mu}_{max}$ increased with an increase in the storage temperature. At 4, 10, 20 and $37^{\circ}C$, $R^2$ was 0.99, 0.98, 0.99 and 0.99, respectively; RMSE was 0.39. The developed predictive growth model can be used to predict the risk of S. aureus contamination in processed meat product galbitang; hence, it has potential as an input model for the risk assessment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Herbal Formula Science
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• v.15 no.2
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• pp.9-19
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• 2007

Nineteen Medicaments of Mutual Antagonism currently belong to pharmaceutical incompatibility and some of them cannot be used in a same prescription: if they are used in a prescription, the treatment effect is rather reduced or toxic response may be produced. Therefore. inthisstudy, it was intended to look about how Nineteen Medicaments of Mutual Antagonism were defined through survey of literatures and to review the meaning and clinical potential. According to "Sinnongbonchogyeong," "Medicaments contain the substance that suppress toxins and the toxins may be removed with use of mutual restraint or mutual detoxication substances" and they have been used in terms of this concept. Since Tang and Song era, mutual restraint and mutual inhibition were confused and were difficult to be distinguished. In terms of pharmaceutical incompatibility, the original meaning of mutual restraint was deteriorated in "Sinnongbonchogyeong". That is. mutual restraint has been used as the concept of mutual inhibition or incompatibility. When various literatures were reviewed. it could be found that Nineteen Medicaments of Mutual Antagonism were firstly included in the phrases of songs and then in "seven emotion." It could be supposed that Nineteen Medicaments of Mutual Antagonism was created based on the clinical experiences of the author and the influence of doctors. Such supposition means indicates that the interactions among medicaments could effectively be applied and mutual restraint did not belong to pharmaceutical incompatibility. However. many doctors used mutual restraint and mutual inhibition in clinical practice with no distinguishment since Song era and. especially, it is supposed that. when medicaments were used with mixing. the pharmaceutical incompatibility of "Nineteen Medicaments of Mutual Antagonism" or "Eighteen Incompatible Medicaments" were emphasized and influenced on the efficacy of pharmaceutical preparations or acted as an obstacle in treating diseases. That is. an error was transferred: mutual restraint and mutual inhibition were not distinguished and were discretionally added or deleted through common people or professionals with no specific verification. The pharmaceutical preparations that belong to Nineteen Medicaments of Mutual Antagonism belong to pharmaceutical incompatibility but. when reviewed various literatures and clinical reports. they are not thought to be the ones that can never be used. Therefore. systematic literature review and experimental research should be performed.

• Analytical Science and Technology
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• v.15 no.4
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• pp.365-372
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• 2002

In this study, inorganic elemental distribution in Korean adult human tissue of liver, lung, muscle, kidney, rib and thyroid has been investigated. These tissues were collected from human's body within 48 hours after their death according to IAEA's recommended method, dried by freeze drying method and then pulverized. Neutron activation analysis was applied to these samples to determine the concentrations of 5 major elements of Ca, Mg, Na, K, and Cl and 12 trace elements of Mn, I, Sr, As, Br, Co, Cr, Cs, Fe, Rb, Se, and Zn. To confirm accuracy of analytical result was performed using three kinds of standard reference materials and resulted that the relative error is within 10% for the most of elements and the Z-score indicating a performance of analysis is within 2. The elemental distribution shows that the major elements are distributed homogeneously with a specific concentration and that the trace elements shows a distribution of different concentration with kinds of tissue and their age. Particularly, iodine shows higher concentration with 1000 ${\mu}g/g$ in thyroid, and calcium and strontium show the concentration with 15.9% and 84.4 ${\mu}g/g$ in rib, respectively.

• Journal of Wetlands Research
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• v.16 no.3
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• pp.327-336
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• 2014

Submerged thin walls are extreme case of submerged rectangular blocks, and could be used for many purposes in rivers or coastal zones, e.g. to tsunami. To understand flow characteristics including flow and pressure fields around a specific submerged thin wall a numerical model was applied which includes computation of hydrodynamic pressure on ${\sigma}$-coordinate. ${\sigma}$-coordinate has strong merits for simulation of subcritical flow over mild-sloped beds. On the other hand ${\sigma}$-coordinate is quite poor to treat sharp structures on the bed. There have been a few trials to incorporate dynamic pressure in ${\sigma}$-coordinate by some researchers. One of the previous approaches includes process of sloving the Poisson equation. However, the above method includes many high-order terms, and requires long cpu for simulation. Another method SOLA was developed by Hirt et al. for computation of dynamic pressure, but it was valid for straight grid system only. Previous SOLA was modified for ${\sigma}$-coordinate for the present purpose and was adopted in a model system, CST3D. Computed flow field shows reasonable behaviour including vorticity is much stronger than the upstream and downstream of the structure. The model was verified to laboratory experiments at a 2DV flume. Time-average flow vectors were measured by using one-dimensional electro-magnetic velocimeter. Computed flow field agrees well with the measured flow field within 10 % error from the speed point of view at 5 profiles. It is thought that the modified SOLA scheme is useful for ${\sigma}$-coordinate system.