• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.307-317
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• 2021

In recent years, global warming has led to frequent climate change-related problems, and elevated temperatures, among adverse climatic factors, represent a critical problem negatively affecting crop growth and yield. In this context, the present study examined the physiological traits of wheat plants grown under high temperatures. Specifically, the effects of elevated temperatures on seed development after heading were evaluated, and the vegetation indices of different organs were assessed using hyperspectral analysis. Among physiological traits, leaf greenness and OJIP parameters were higher in the high-temperature treatment than in the control treatment. Similarly, the leaf photosynthetic rate during seed development was higher in the high-temperature treatment than in the control treatment. Moreover, temperature by organ was higher in the high-temperature treatment than in the control treatment; consequently, the leaf transpiration rate and stomatal conductance were higher in the control treatment than in the high-temperature treatment. On all measuring dates, the weight of spikes and seeds corresponding to the sink organs was greater in the high-temperature treatment than in the control treatment. Additionally, the seed growth rate was higher in the high-temperature treatment than in the control treatment 14 days after heading, which may be attributed to the higher redistribution of photosynthates at the early stage of seed development in the former. In hyperspectral analysis, the vegetation indices related to leaf chlorophyll content and nitrogen state were higher in the high-temperature treatment than in the control treatment after heading. Our results suggest that elevated temperatures after the booting stage positively affect wheat growth and yield.

• 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 Marine Life Science
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• v.7 no.2
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• pp.196-204
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• 2022

This study observed changes in survival, growth performance and water quality for 90 days to confirm the possibility of Leiocassis ussuriensis farming using Biofloc technology (BFT) using Bacillus subtilis. Feed and molasses were added to the experimental tank to produce BFT water before planting the experiment, and B. subtilis was inoculated to stabilize the water quality for 40 days. The survival rate of the experimental fish was 92.7±3.2% in the control group and 95.8±3.3% in the BFT group. The Weight gain (WG) was 118.1±9.0% of the control and 197.7±15.6% of the BFT, and the Specific growth rate (SGR) was 0.87±0.5% of the control and 1.21±0.06% of the BFT. As for the feed efficiency, the control was 43.7±2.6% and the BFT was measured at 70.1±4.1%, indicating that the feed efficiency of the BFT was higher. As a result of measuring the water quality change during the experimental period, pH was reduced in both the control and the BFT, and Mixed Liquor Suspended Solids (MLSS) did not show any change in the control, but the BFT showed a significant increase at 90 days. NH₄⁺-N and NO₂^--N showed a significant increase from the 30 days of the experiment in the control, but showed no change in the BFT. In conclusion, as a result of applying the BFT system using B. subtilis to the process of cultivating Leiocassis ussuriensis, the water quality tended to stabilize, and the growth rate and feed efficiency were found to be higher than those of the control, confirmiWng that it had a positive effect.

• Journal of Food Hygiene and Safety
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• v.37 no.3
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• pp.143-148
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• 2022

This study was to investigate an analytical method for determining dieckol content in Ecklonia stolonifera extract. According to the guidelines of International Conference on Harmonization. Method validation was performed by measuring the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of dieckol using high-performance liquid chromatography-photodiode array. The results showed that the correlation coefficient of calibration curve (R²) for dieckol was 0.9997. The LOD and LOQ for dieckol were 0.18 and 0.56 ㎍/mL, respectively. The intra- and inter-day precision values of dieckol were approximately 1.58-4.39% and 1.37-4.64%, respectively. Moreover, intra- and inter-day accuracies of dieckol were approximately 96.91-102.33% and 98.41-105.71%, respectively. Thus, we successfully validated the analytical method for estimating dieckol content in E. stolonifera extract.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.2
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• pp.147-157
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• 2023

Centella asiatica extract is widely used as a raw material for cosmetics due to its various effects, but it is difficult to expect penetration into the skin due to its high molecular weight and low solubility. In order to solve these problems, lipid-based liposomes of various types were developed to increase skin absorption. Therefore, in this study, we tried to increase the skin absorption rate by preparing transfersomes using surfactants as edge activators in existing liposomes. Liposome and transfersomes containing Span 80 and Tween 20, 60, 80, and 85, respectively, were prepared using a high-pressure homogenizer, and we evaluated the particle size, polydispersity index, zeta potential, and skin absorption rate. As a result, there was almost no change in the physical properties of particle size, polydispersity index and zeta potential from 25 ℃ to 60 d, and the particle size of transfersomes containing Tween 20, 60, and 80 increased after 60 d at 45 ℃. Madecassoside, main substances of the Centella asiatica extract was used as an standard and madecassoside was measured and calculated when measuring the skin absorption rate using Franz diffusion cells. As a result, formulations containing Tween 20 were the most, whereas formulations containing Span 80 were the least. According to the skin absorption coefficient (Kp) value, all formulations showed 'very fast', and the absorption rate was similar or greater than that of liposomes, except for formulations containing Span 80. Through this, it was confirmed that the larger the HLB value of the nonionic surfactant, the smaller the particle size of the transfersome, and the increased skin absorption rate due to the increased flexibility of the vesicle membrane. Through this study, transfersome using surfactant as an edge activator can be expected to solve local skin problems not only as a cosmetic raw material or product, but also by increasing skin absorption.

• Tuberculosis and Respiratory Diseases
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• v.42 no.5
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• pp.744-751
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• 1995

Background: Asthma is an inflammatory disease because there are many inflammatory changes in the asthmatic airways. Axon reflex mechanisms may be involved in the pathogenesis of asthma. Sensory neuropeptides are involved in this inflammation, which is defined as neurogenic inflammation. Substance p, neurokinin A, and neurokinin B may be main neuropeptides of neurogenic inflammation in airways. These tachykinins act on neurokinin receptors. Three types of neurokinin receptors, such as $NK_1$, $NK_2$, and $NK_3$, are currently recognized, at which substance p, neurokinin A, and neurokinin B may be the most relevant natural agonist of neurogenic inflammation in airways. The receptor subtypes present in several tissues have been characterized on the basis of differential sensitivity to substance p, neurokinin A, and neurokinin B. Plasma extravasation and vasodilation are induced by substance p more potently than by neurokinin A, indicating NK1 receptors on endothelial cells mediate the response. But airway contraction is induced by neurokinin A more potently than by substance P, indicating the $NK_2$ receptors in airway smooth muscles. These receptors are used to evaluate the pathogenesis of brochial asthma. FK224 was identified from the fermentation products of Streptomyces violaceoniger. FK224 is a dual antagonist of both $NK_1$ and $NK_2$ receptors. Purpose: For a study of pathogenesis of bronchial asthma, the effect of FK224 on plasma extravasation induced by vagal NANC electrical stimulation was evaluated in rat airway. Method: Male Sprague-Dawley rats weighing 180~450gm were anesthetized by i.p. injection of urethane. Plasma extravasation was induced by electrical stimulation of cervical vagus NANC nerves with 5Hz, 1mA, and 5V for 2 minutes(NANC2 group) and for sham operation without nerve stimulation(control group). To evaluate the effect of FK224 on plasma extravasation in neurogenic inflammation, FK224(1mg/kg, Fujisawa Pharmaceutical Co., dissolved in dimethylsulphoxide; DMSO, Sigma Co.) was injected 1 min before nerve stimulation(FK224 group). To assess plasma exudation, Evans blue dye(20mg/kg, dissolved in saline) was used as a plasma marker and was injected before nerve stimulation. After removal of intravascular dye, the evans blue dye in the tissue was extracted in formamide($37^{\circ}C$, 24h) and quantified spectrophotometrically by measuring dye absorbance at 629nm wavelength. Tissue dye content was expressed as ng of dye per mg of wet weight tissue. The amount of plasma extravasation was measured on the part of airways in each groups. Results: 1) Vagus nerve(NANC) stimulation significantly increased plasma leakage in trachea, main bronchus, and peripheral bronchus compared with control group, $14.1{\pm}1.6$ to $49.7{\pm}2.5$, $17.5{\pm}2.0$ to $38.7{\pm}2.8$, and $12.7{\pm}2.2$ to $19.1{\pm}1.6ng$ of dye per mg of tissue(mean ${\pm}$ SE), respectively(p<0.05). But there was not significantly changed in lung parenchyma(p>0.05) 2) FK224 had significant inhibitory effect upon vagal nerve stimulation-induced airway plasma leakage in any airway tissues of rat,such as trachea, main bronchus, and peripheral bronchus compared with vagus nerve stimulation group, 49%, 58%, and 70%, respectively(p<0.05). Inhibitory effect of FK224 on airway plasma leakage in neurogenic inflammation was revealed the more significant in peripheral bronchus, but no significant in lung parenchyma. Conclusion: These results suggest that FK224 is a selective NK receptor antagonist which effectively inhibits airway plasma leakage induced by the endogenous neurotransmitters relased by neurogenic inflammation in rat airway. Tachykinin receptor antagonists may be useful in the treatment of brochial asthma.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Proceedings of the KSEEG Conference
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• 2001.05b
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• pp.42-63
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• 2001

The detail survey on the Songsanri tomb site including the Muryong royal tomb was carried out during the period from May 1 , 1996 to April 30, 1997. A quantitative analysis was tried to find changes of tomb itself since the excavation. Main subjects of the survey are to find out the cause of infiltration of rain water and groundwater into the tomb and the tomb site, monitoring of the movement of tomb structure and safety, removal method of the algae inside the tomb, and air controlling system to solve high humidity condition and dew inside the tomb. For these purposes, detail survery inside and outside the tombs using a electronic distance meter and small airplane, monitoring of temperature and humidity, geophysical exploration including electrical resistivity, geomagnetic, gravity and georadar methods, drilling, measurement of physical and chemical properties of drill core and measurement of groundwater permeability were conducted. We found that the center of the subsurface tomb and the center of soil mound on ground are different 4.5 meter and 5 meter for the 5th tomb and 7th tomb, respectively. The fact has caused unequal stress on the tomb structure. In the 7th tomb (the Muryong royal tomb), 435 bricks were broken out of 6025 bricks in 1972, but 1072 bricks are broken in 1996. The break rate has been increased about 250% for just 24 years. The break rate increased about 290% in the 6th tomb. The situation in 1996 is the result for just 24 years while the situation in 1972 was the result for about 1450 years. Status of breaking of bircks represents that a severe problem is undergoing. The eastern wall of the Muryong royal tomb is moving toward inside the tomb with the rate of 2.95 mm/myr in rainy season and 1.52 mm/myr in dry season. The frontal wall shows biggest movement in the 7th tomb having a rate of 2.05 mm/myr toward the passage way. The 6th tomb shows biggest movement among the three tombs having the rate of 7.44mm/myr and 3.61mm/myr toward east for the high break rate of bricks in the 6th tomb. Georadar section of the shallow soil layer represents several faults in the top soil layer of the 5th tomb and 7th tomb. Raninwater flew through faults tnto the tomb and nearby ground and high water content in nearby ground resulted in low resistance and high humidity inside tombs. High humidity inside tomb made a good condition for algae living with high temperature and moderate light source. The 6th tomb is most severe situation and the 7th tomb is the second in terms of algae living. Artificial change of the tomb environment since the excavation, infiltration of rain water and groundwater into the tombsite and bad drainage system had resulted in dangerous status for the tomb structure. Main cause for many problems including breaking of bricks, movement of tomb walls and algae living is infiltration of rainwater and groundwater into the tomb site. Therefore, protection of the tomb site from high water content should be carried out at first. Waterproofing method includes a cover system over the tomvsith using geotextile, clay layer and geomembrane and a deep trench which is 2 meter down to the base of the 5th tomb at the north of the tomv site. Decrease and balancing of soil weight above the tomb are also needed for the sfety of tomb structures. For the algae living inside tombs, we recommend to spray K101 which developed in this study on the surface of wall and then, exposure to ultraviolet light sources for 24 hours. Air controlling system should be changed to a constant temperature and humidity system for the 6th tomb and the 7th tomb. It seems to much better to place the system at frontal room and to ciculate cold air inside tombs to solve dew problem. Above mentioned preservation methods are suggested to give least changes to tomb site and to solve the most fundmental problems. Repairing should be planned in order and some special cares are needed for the safety of tombs in reparing work. Finally, a monitoring system measuring tilting of tomb walls, water content, groundwater level, temperature and humidity is required to monitor and to evaluate the repairing work.