• Journal of the Korean Geotechnical Society
• /
• v.15 no.2
• /
• pp.153-164
• /
• 1999

The solubilization of BTEX was evaluated in aqueous surfactant solutions with and without several additives. Anionic surfactant(Sodium Dodecyl Sulfate, SDS) and nonionic surfactants (NEODOL(equation omitted)25-3 and $SOFTANOL\circledR-90$ were used as test surfactants. The effects of surfactant HLB(Hydrophile-Lipophile Balance) Number and hydrocarbon molar volume and polarity of BTEX on the MSR(Molar Solubilization Ratio), micelle-water partition coefficient of BTEX, and CMC(C,itical Micelle Concentration) were investigated. Optimizing treatment conditions applicable to enhanced solubilization was also studied by manupulating salinity or electrolyte control with additives of ethyl alcohol, hydrotrope, and electrolyte solution. The most effective surfactant for solubilization was found $SOFTANOL\circledR-90$, since HLB number of 13.6 is similar to those values of BTEX ranging between 11.4 and 12.2, which was also proved experimentally. Ethyl alchohol of 3% was the most effective additives in reducing CMC and improving solubilization among the conditions using SDS, NEODOL(equation omitted)25-3, and $SOFTANOL\circledR-90$ with three additives. The partitioning of BTEX between surfactant micelles and aqueous solutions was characterized by a mole fraction micelle-phase/aqueous phase partion coefficient, $K_m$. Values of log $K_m$. for BTEX compounds in surfactant solutions of this study range from 2.95 to 3.76(100mM SDS) and 2.95 to 3.49(117mM $SOFTANOL\circledR-90$. Log $K_m$ appears to be a linear function of log $K_{ow}$ for SDS and $SOFTANOL\circledR-90$. A knowledge of partitioning of BTEX in aqueous surfactant system can be a prerequisite for the understanding of the behavior of hydrophobic organic compounds in soil-water systems in which surfactants play a role in remediation of contaminated soil and facilitated transport.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.177-192
• /
• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of Korea Port Economic Association
• /
• v.30 no.4
• /
• pp.69-89
• /
• 2014

The business performance of port industry is steadily getting worse due to international environmental regulation. The port industry should be prepared according to ambient condition change. IMO(International Maritime Organization) is tightening up environmental regulation of vessel and maritime industry field. ECA(Emission Control Area), starting with the Baltic, has initialized and has been expanded. Korea must strengthen the control of vessel in accordance with IMO's restriction, if Korea is designated as emission control area. These situations cause the expansion of LNG-fuelled ships. Add to the larger trend of ships, Korean government should be done a preemptive action against LNG bunkering industry. This study proposes the concept of floating offshore LNG bunkering system and is conducted its economic feasibility evaluation based on empirical analysis. We examine the theoretical foundation and basic information via "A Planning Study on the Engineering Development of Floating Offshore LNG Bunkering Terminal" in 2013 and we evaluate the business potential by using the report above mentioned. The results of this study are as follows. The values of B/C analysis are between 0.679 and 2.516 depending on market share and R&D contributiveness. In case of 10.9%(market share), if market share are 50% and 60%, the value of B/C analysis are 0.697 and 0.837 respectively. Except in two cases, all remaining values are over 1.0. Moreover, the research is conducted sensitivity analysis to remove the project uncertainty. In order to maintain economical validity, a project manager have to establish business strategies which are not to cause increase of expense and sustain market share and R&D contributiveness in the scenario with normal levels.

• Journal of Life Science
• /
• v.21 no.1
• /
• pp.146-154
• /
• 2011

In this study, physiological changes in a thermotolerant yeast Saccharomyces cerevisiae KNU5377 cell exposed to 48-hour alcohol fermentation at $40^{\circ}C$ were investigated. After 12 hours of alcohol fermentation at $40^{\circ}C$, the $C_{16:1}$ unsaturated acid of plasma membrane increased to 1.5 times more than the $C_{16:0}$ saturated fatty acid, and to about 2 times more for the $C_{18:1}$ unsaturated fatty acid. Fermentation at both $30^{\circ}C$ and $37^{\circ}C$ fermentation showed the same pattern as that done at $40^{\circ}C$. The pH of the alcohol-fermentation medium was reduced to pH 4.1 from a starting pH of 6.0 through the 12-hr fermentation and then maintained this level during the continuing fermentation. With the process of fermentation, the remaining glucose was reduced, but its amount remaining during the $40^{\circ}C$-fermentation was less reduced than those fermented at $30^{\circ}C$ and $37^{\circ}C$. In the study investigating the changing pattern of cellular proteins in the alcohol-fermenting cells, the SDS-PAGE and 2-D data indicated the most expressed dot was phosphoglycerate kinase, which is one enzyme involved in glycolysis. Why this enzyme was most expressed in the cells exposed to unfavorable conditions such as high temperature, increasing concentration of produced alcohol and long time exposure to other stress factors remains unsolved.

• Journal of Dairy Science and Biotechnology
• /
• v.32 no.2
• /
• pp.121-129
• /
• 2014

This study was carried out to investigate the quality characteristics of protein enriched fermented milk made with whey and soybean flour. Protein-enriched fermented milk was prepared as follows: Soybean flour was added before fermentation. No synthetic aroma was added. The fermentation starter culture was ABT-4 (Chr. Hansen). Whey protein was added after fermentation. Sensory evaluation indicated that sample containing soybean flour amount of 5% were better than other samples. The pH values and titratable acidities of stored protein-enriched fermented milk and fermented milk, respectively, were not remarkably different. Crude protein was more than 3 times higher in protein-enriched fermented milk (8.77%) than in fermented milk (2.49%). The crude fat content of protein-enriched fermented milk was not remarkably different compared to that of fermented milk. Dietary fiber was more than 2.7 times higher in protein-enriched fermented milk (1.67%) than in fermented milk (0.62%), and the free amino acid content was more than 14 times higher in protein-enriched fermented milk (37.9%) than in fermented milk (2.6%).

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.35 no.6
• /
• pp.639-643
• /
• 2002

Water quality, bacterial phase and fish growth rate were analyzed in the process of artificial seed production of flounder (Paralichtys oliraceus) larvae to investigate the water quality in rearing tank using Ultra Filtration System (UES). Sand Filtration System (SFS) and Ultra Filtration System (Ins) were set up in the experimental group. For the analysis of water quality, pH, salinity, DO, SS, COD, $NH_{4}^{+},\;NO_{2}^{-},\;NO^-,\;DIN$ (dissolved inorganic nitrogen) and DU (dissolved inorganic phosphate) were measured. There was no data difference between SFS group and UES group in most analysis items, but the UEs group showed low salinity and low 55 values, such that salinity was $33.5\%_{\circ}$ in SES group and $30.2\%_{\circ}$ in WS group and 55 was 15.5 mL/L in SES group and 7.0 mL/L for UPS group. For changes in bacterial phase and TBC (Total Bacterial Counts), in SES group, 6$\times$10^{5}CFU/mL in seawater decreased to the ratio of about 116, and TBC, Genus Vibrio and bacteria in the Genus Acinetobacter and Genus Micrococcus sharply increased after nine days, while stable bacterial phase was maintained low in UES group during the experiment except for Genus Ajteromonas. In the growth of the larvae, fish length was 17.0 mm (SGR 14.0) in the SES group and 18.8 mm (SGR 14.3) in the UFS group. It is concluded that when water is supplied for artificial seed production with WS, stabilization of water quality condition and inhibition of bacterial multiplication are possible. When production environment becomes stable, stable growth of fish becomes possible by reduction of environmental stress.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_2
• /
• pp.1117-1132
• /
• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

• Journal of Wetlands Research
• /
• v.15 no.1
• /
• pp.149-157
• /
• 2013

The weirs built so far are mainly overflow type weirs overflowing to the upstream. Main advantages of overflow type weirs are, effective water resources management and easy design, construction and maintenance due to many accumulated studies. However, due to the special feature of the overflow type weir where water overflows through the upstream of the weir, the silt coming from the upstream is not discharged to the downstream of the weir. This increases the river bed and reduces the reservoir capacity, and as a result, the weir loses its function. A underflow type weir with a water gate has been implemented in order to solve such sediment deposit and weir maintenance problems. However due to the design problem of recently constructed underflow type weirs, the river bed of the downstream of a weir has been scoured. And this leds to a structural problem. In this study, the flow characteristics of overflow type weirs and underflow type weir, hydraulic jump length analysis depending on change of water depth and the amount of specific energy loss generated per unit length depending on a weir type have been compared and analyzed, for the effective design and management of the weirs. The experiment results show that, when identical upstream conditions of underflow type weir and an overflow type weir were maintained, the hydraulic jump length was up to twice longer with Fr(Froude number) 3.5 of the hydraulic jump length at the underflow type weir, and the hydraulic jump length gradually decreased as the downstream water depth increased. The comparative analysis result of the amount of specific energy loss generated per unit length showed that the amount of energy loss per unit length was twice higher for an overlfow type weir than a underflow type weir. Therefore, in case of a underflow type facility, an additional energy reduction facility is determined to be necessary for safety of water construction structures.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.7 no.4
• /
• pp.267-285
• /
• 2002

Dok Island, a Pliocene volcano, lies in the southwestern part of the East Sea. Most the work to date have focused primarily on the petrolography of the island, and as a result, the morphological characteristics and internal structure of the volcanic edifices of the Dok Island remain poorly understood. To provide better constraints on these features, bathymetric data with multibeam echo sounder, 32-channel seismic and 3D gravity modeling were used in this study. Three positive topographic highs are present in the study area, and these highs satisfy the seamount criteria. They are named as Dokdo, Tamhae, and Donghae seamounts. 32-channel seismic survey was conducted to investigate the sediment thickness of the area, which shows that there are no sediments near the summit of seamounts. Away from the seamounts, however, sediment becomes thick(>2000 m) toward the western part of the study area, and sediments in the northern and southern parts are about 1000 m thick. Free-Air gravity anomalies in this study generally follow the bathymetric feature with less than -20 mGal at the western part, but increase towards the seamounts. In the summit of the Dokdo Seamount, anomalies reach over 120 mGal, and in Tamhae and Donghae seamounts, the peak anomaly shows 90 and 70 mGals, respectively. All seamounts have an isolated volcanic conduit in their centre and show regional compensation root with 0.5～1.5 km thickness. The flat-topped summit of the seamounts is probably caused by wave truncation, indicating the sea level at the time of formation of the flat-topped geometry. Comparison between the present-day sea level and subsidence level during the opening of the East Sea suggests that the seamounts in the study area have subsided by 200～300 m after the formation. Furthermore, it implies that the seamounts formed over 12～10 Ma.

• Journal of Bio-Environment Control
• /
• v.28 no.4
• /
• pp.461-470
• /
• 2019

This study was carried out to quantify the drought stress in grafted watermelon seedlings non-destructively by using chlorophyll fluorescence (CF) imaging technique rather than the visual judgment. Six-day old watermelon seedlings were grown under uniform irrigation for 3 days, and then given drought stress. Afterward, the sensor for the measurement of water content in plug tray cell unit was used to classify the drought-stress level into nine groups from D1 (53.0%, sufficient moisture state) to D9 (15.7%, extremely dry stress), and the 16 CF parameters were measured. In addition, re-irrigation was performed on the drought stressed seedlings(D5 - D9) to determine the growth and photosynthesis recovery level, which was not confirmed by visual judgment. The kinetic curve patterns of CF in three different drought stressed seedling groups were found to be different for the early detection of drought stress. All the 16 CF parameters decreased continuously with exposure to drought stress and drastically decreased from D5 (32.1%) where the visual judgment was possible. The fluorescence decline ratio (Rfd_Lss) started to decrease from the initial drought stress level (D5 - D6), and the Maximum PSII quantum yield (Fv/Fm) was significantly decreased in the later extreme drought stress range (D7 - D9) by re-irrigation recovery test. Thus, Rfd_Lss and Fv/Fm parameters were finally selected as potent indicators of growth and photosynthesis recovery in the initial and later stages of drought stress. Also, to the differences in the numerical values of the individual chlorophyll fluorescence parameters, the drought stress level was intuitively confirmed through the image. These results indicate that Rfd and Fv/Fm can be considered as potential CF parameters for the detection of low and extremely high drought stress, respectively. Furthermore, Fv/Fm can be considered as the best CF parameters for recovery at re-irrigation.