• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.197-207
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• 2018

The radish skin and radish greens (mucheong) are an edible part of the radish. But they are removed before eating the radish and used as a byproduct or an animal feed material because of their tough and rough texture. This study was conducted to investigate the effect of supercritical heat-treated radish-extract on UV-induced Hos: HRM-2 wrinkled mouse animal model on anti-aging wrinkles. Supercritical heat-treated radish-extract was applied on the back of seven-weeks old HRM-2 mice. The effect of HRE on skin thickness, elasticity and wrinkle formation of the mice was observed by using UVB lamp to induce melanogenesis and wrinkle formation. As the result, increased depth of wrinkles was observed in the negative control group in comparison to the normal group. In contrast, decreased depth of wrinkles was observed in the radish-extract-free group compared to the negative control group. In the study of the effect of radish-extract on wrinkle-formation related gene expression and protein what protein expression, MMP-2 and MMP-2 gene expression significantly increased in the negative control group compared to the normal group. The gene expression reduced independence to the mass of radish-extract treated. Similar to quantitative results of mRNA expression, the expression of MMP-2 protein increased as a result of UVB-irradiation. The MMP-2 expression was inhibited in dependence to the mass of radish-extract treated. In conclusion, the supercritical heat-treated radish-extract has an effect on improving skin wrinkles not only when it is applied to the skin but also when orally ingested. Thus, it can be effectively used as a composition to health functional products. Thereafter, we can also conclude that radish, a food that does not show any side-effects even upon long-term intake, can reduce wrinkle formation as well as improve skin elasticity when taken regularly for a long period.

• Journal of the Korea Institute of Building Construction
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• v.9 no.5
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• pp.79-86
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• 2009

In a steel structure, spray-applied fire resistive materials are crucial in preventing structural strength from being weakened in the event of a fire. The quality control of such materials, however, is difficult for manual workers, who can frequently be in short supply. These skilled workers are also very likely to be exposed to environmental hazards. Problems with construction work such as this, which are specifically the difficulty of achieving quality control and the dangerous nature of the work itself, can be solved to some degree by the introduction of automated equipment. It is, however, very difficult to automate the work process, from operation to the selection of a location for the equipment, as the environment of a construction site has not yet been structured to accommodate automation. This is a fundamental study on the possibility of the automation of spray-applied fire resistive coating work. In this study, the linkability of the cutting-edge RTLS to an automation system is reviewed, and a scenario for the automation of spray-applied fire resistive coating work and system composition is presented. The system suggested in this study is still in a conceptual stage, and as such, there are many restrictions still to be resolved. Despite this fact, automation is expected to have good effectiveness in terms of preventing fire from spreading by maintaining a certain level of strength at a high temperature when a fire occurs, as it maintains the thickness of the fire-resistive coating at a specified level, and secures the integrity of the coating with the steel structure, thereby enhancing the fire-resistive performance. It also expected that if future research is conducted in this area in relation to a cutting-edge monitoring TRS, such as the ubiquitous sensor network (USN) and/or building information model (BIM), it will contribute to raising the level of construction automation in Korea, reducing costs through the systematic and efficient management of construction resources, shortening construction periods, and implementing more precise construction

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.82-92
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• 2007

In 2003, we evaluated biological water quality at twelve sites of Youngsan River using community analysis, fish compositions, and the Index of Biological Integrity (IBI). Of the twelve, four sites were the controls, which have no point sources in the upstream and the remaining eight sites were the impacted sites, which are influenced by wastewater treatment plant (WTP) and agro-industrial complex. Model values of the IBI, based on 12 sites data, averaged 28 (n=12, range: $18{\sim}44$), indicating fair poor condition according to the criteria of US EP A (1993). In the mean time, mean IBI in the control sites (S3, S5, S6, S11) was 42 (n=4, range: $38{\sim}44$), indicating a good condition, whereas mean IBI in the impacted sites was 21, indicating a poor condition. Mean IBI value in the control, thus, was greater by 2 fold than that in the WTP sites. The spatial pattern of IBI values was similar to the patterns of species diversity index and species richness index, except for Site 11, which was 1st order stream. Similarity analysis indicated that three groups were divided at the similarity level of 80%. One group was the streams influenced by wastewater and the other two groups were the pristine streams as the control, indicating that the stream health conditions are directly influenced by presence or absence of the point sources. Also, Pearson's correlation analysis showed that IBI values had negative correlation (r=0.899, p<0.001) with relative abundance of tolerance species, and had positive relation (r=0.890, p<0.001) with sensitive species. Overall, outcomes suggest that the point sources of the WTP might impact the species composition and ecological health, resulting in degradation of biological water quality.

• Korean Journal of Clinical Laboratory Science
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• v.50 no.3
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• pp.320-330
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• 2018

This study analyzed the curriculum and clinical practicum of the department of clinical laboratory science in Korea. The 2017 educational curricula of all 3-year and 4-year universities were analyzed. Clinical practice was conducted by a questionnaire. As a result of curriculum analysis, the 3-year curriculum was able to grasp the curriculum that focused on the national examinations of medical technologists, and the 4-year curriculum was open to a variety of subjects reflecting the changes in the future, but only at a few universities. In addition, the autonomous enrollment application made it possible to take a national examination without enrolling in courses that students find difficult in major courses. In the case of clinical practice, it was difficult to standardize in various practical institutes, practice periods, and practice credits. Therefore, it will be necessary to standardize the composition of the credits according to the duration of clinical practice and the duration of education. Moreover, is necessary to revise the curriculum in consideration of medical technologist job analysis and clinical field, and it will be necessary to standardize the curriculum and clinical practice model through the Medical Technologist Evaluation Center.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.26 no.1
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• pp.26-30
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• 1993

To suggest a thermal diffusivity predicting equation for mixed meat products, heat penetration curves of pork products containing filefish meat were plotted in the temperature range of $80.44{\sim}121.03^{\circ}C$, and thermal diffusivities were calculated from the heat penetration curves. The ground pork was mixed with minced filefish meat and some additives such as lard, isolated soy protein, $1.5\%$ of table salt and $2\%$ of polyphosphate to control the composition and texture of products, and then stuffed into a model can. The heat penetration curves were plotted using a thermocouple fixed at the slowest heating point of the can. At constant heating temperature, the thermal diffusivities of the products increased linearly with increasing moisture content. The values of the products with constant moisture content also increased linearly with increasing heating temperature. The thermal diffusivities of the products with moisture content of $51.47{\sim}80.20\%$ could be predicted by following equation: $${\alpha}_p=(3.045+0.59{\cdot}X_w){\cdot}{\alpha}_w+0.0098{\cdot}10^{-6}{\cdot}X_w-0.4287{\cdot}10^{-6},(m^2{\cdot}s^{-1})$$ Maximal differences of the thermal diffusivities predicted with this equation were in the range of ${\pm}0.8\%$ compared with the practical values. This equation and another predicting equation obtained from the previous study for the pork product without fish meat could be simplified as following one equation, and the maximal differences of the thermal diffusivities predicted with this equation for both products with and without fish meat were in the range of less than ${\pm}2.5\%$ $${\alpha}_p=(2.290+0.54{\cdot}X_w){\cdot}{\alpha}_w+0.0024{\cdot}10^{-6}{\cdot}X_w-0.3535{\cdot}10^{-6},(m^2{\cdot}s^{-1})$$

• Korean Journal of Fisheries and Aquatic Sciences
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• v.13 no.4
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• pp.179-183
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• 1980

The efficiency of energy transfer by a population of the farmed pacific oyster, Crassostrea gigas was studied during culture period of 10 months July 1979-April 1980, in Geoje-Hansan Bay near Chungmu City. Energy use by the farmed oyster population was calculated from estimates of half-a-month unit age specific natural mortality rate and data on growth, gonad output, shell organic matter production and respiration. Total mortality during the culture period was estimated approximate $36\%$ from data on survivor individual number per cluster. Growth may be dual consisted of a curved line during the first half culture period (July-November) and a linear line in the later half period (December-April). The first half growth was approximated by the von Bertalanffy growth model; shell height, $SH=6.33\;(1-e^{0.2421(t+0.54)})$, where t is age in half-a-month unit. In the later half growth period shell height was related to t by SH=4.44+0.14t. Dry meat weight (DW) was related to shell height by log $DW=-2.2907+2.589{\cdot}log\;SH,\;(2, and/or log $DW=-5.8153+7.208{\cdot}log\;SH,\;(5. Size specific gonad output (G) as calculated by condition index of before and after the spawning season, was related to shell height by $G=0.0145+(3.95\times10^{-3}{\times}SH^{2.9861})$. Shell organic matter production (SO) was related to shell height by log $SO=-3.1884+2.527{\cdot}1og\;SH$. Size and temperature specific respiration rate (R) as determined in biotron system with controlled temperature, was related to dry meat weight and temperature (T) by log $R=(0.386T-0.5381)+(0.6409-0.0083T){\cdot}log\;DW$. The energy used in metabolism was calculated from size, temperature specific respiration and data on body composition. The calorie contents of oyster meat were estimated by bomb calorimetry based on nitrogen correction. The assimilation efficiency of the oyster estimated directly by a insoluble crude silicate method gave $55.5\%$. From the information presently available by other workers, the assimilation efficiency ranges between $40\%\;and\;70\%$. Twenty seven point four percent of the filtered food material expressed by energy value for oyster population was estimated to have been rejected as pseudofaeces : $17.2\%$ was passed as faeces; $35.04\%$ was respired and lost as heat; $0.38\%$ was bounded up in shell organics; $2.74\%$ was released as gonad output, $2.06\%$ was fell as meat reducing by mortality. The remaining $15.28\%$ was used as meat production. The net efficiency of energy transfer from assimilation to meat production (yield/assimilation) of a farm population of the oyster was estimated to be $28\%$ during culture period July 1979-April 1980. The gross efficiency of energy transfer from ingestion to meat production (yield/food filtered) is probably between $11\%\;and\;20\%$.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.67-72
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• 2006

Injection of $CO_2$ into underground saline formations, due to their large storage capacity, is probably the most promising approach for the reduction of $CO_2$ emissions into the atmosphere. $CO_2$ storage must be carefully planned and monitored to ensure that the $CO_2$ is safely retained in the formation for periods of at least thousands of years. Seismic methods, particularly for offshore reservoirs, are the primary tool for monitoring the injection process and distribution of $CO_2$ in the reservoir over time provided that reservoir properties are favourable. Seismic methods are equally essential for the characterisation of a potential trap, determining the reservoir properties, and estimating its capacity. Hence, an assessment of the change in seismic response to $CO_2$ storage needs to be carried out at a very early stage. This must be revisited at later stages, to assess potential changes in seismic response arising from changes in fluid properties or mineral composition that may arise from chemical interactions between the host rock and the $CO_2$. Thus, carefully structured modelling of the seismic response changes caused by injection of $CO_2$ into a reservoir over time helps in the design of a long-term monitoring program. For that purpose we have developed a Graphical User Interface (GUI) driven rock physics simulator, designed to model both short and long-term 4D seismic responses to injected $CO_2$. The application incorporates $CO_2$ phase changes, local pressure and temperature changes. chemical reactions and mineral precipitation. By incorporating anisotropic Gassmann equations into the simulator, the seismic response of faults and fractures reactivated by $CO_2$ can also be predicted. We show field examples (potential $CO_2$ sequestration sites offshore and onshore) where we have tested our rock physics simulator. 4D seismic responses are modelled to help design the monitoring program.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.6
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• pp.750-763
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• 2018

This study conducted 10 sampling sites survey 4 times to determine the trophic structure and energy flow of marine ecosystems for Uljin marine ranching area, Korean East Sea from March to October 2013. Based on the ecological characteristics of biological species, one used the non-Metric Multidimensional Scaling method based on the similarity of species. A total of 19 classified species groups formed categories including, top predators, seabirds, large pelagic fishes, small pelagic fishes, rockfishes, pleuronectiformes, benthic fishes, semi-benthic fishes, cephalopods, benthic feeders, epifauna, bivalves, abalone, Cnidaria, zooplankton, benthic algae, microalgae, phytoplankton and detritus. The biomass, production/biomass, consumption/biomass, diet composition data of each species groups to input data used in Ecopath mode estimated the trophic structure and energy flow of marine ecosystems in the Uljin marine ranching area. One estimated each species groups on the trophic level from 1 to 5.687. The sum of all consumption was estimated at $229.7t/km^2/yr$ and the sum of all exports was as estimated $3,432.4t/km^2/yr$. Total system throughput was at $6,796.2t/km^2/yr$, and the sum of all production was estimated at $3,613.1t/km^2/yr$. Net system production according to these results was estimated at $3,490.3t/km^2/yr$ and total biomass (excluding detritus) was estimated at $167.3t/km^2/yr$ in the Uljin marine ranching area.

• Journal of Plant Biotechnology
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• v.42 no.1
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• pp.60-70
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• 2015

The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in different soybean cultivars. Total 153 lines of soybean (Glycine max Merrill) were examined by FT-IR spectroscopy. Quantification of fatty acids from the soybean lines was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region ($1,700{\sim}1,500cm^{-1}$), phosphodiester groups ($1,500{\sim}1,300cm^{-1}$) and sugar region ($1,200{\sim}1,000cm^{-1}$) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations ($R^2{\geq}0.97$) between predicted content of 5 individual fatty acids by PLS regression modeling from FT-IR spectra and measured content by GC. In external validation, palmitic acid ($R^2=0.8002$), oleic acid ($R^2=0.8909$) and linoleic acid ($R^2=0.815$) were predicted with good accuracy, while prediction for stearic acid ($R^2=0.4598$), linolenic acid ($R^2=0.6868$) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.