• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.4
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• pp.302-307
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• 2014

To examine the trophic ecology of the ascidian Styela clava in an aquaculture system of Korea, stable carbon and nitrogen isotopes were analyzed monthly in S. clava, coarse ($>20{\mu}m$, CPOM) and fine particulate organic matters ($0.7<<20{\mu}m$, FPOM). CPOM (means: $-18.5{\pm}1.2$‰, $9.3{\pm}0.7$‰) were significantly higher ${\delta}^{13}C$ and ${\delta}^{15}N$ values than those ($-20.5{\pm}1.5$‰, $8.4{\pm}0.5$‰) of FPOM. S. clava had mean ${\delta}^{13}C$ and ${\delta}^{15}N$ values of $-18.9({\pm}1.7)$‰ and $11.6({\pm}0.7)$‰, respectively. S. clava were more similar to seasonal variations in ${\delta}^{13}C$ and ${\delta}^{15}N$ values of FPOM than those of CPOM, suggesting that they rely largely on the FPOM as a dietary source. In addition, our results displayed that the relative importance between CPOM and FPOM as dietary source for the ascidians can be changed according to the availability of each component in ambient environment, probably reflecting their feeding plasticity due to non-selective feeding irrespective of particle size. Finally, our results suggest that dynamics of pico- and nano-size plankton (i.e., FPOM) as an available nutritional source to S. clava should be effectively assessed to maintain and manage their sustainable aquaculture production.

• Journal of Astronomy and Space Sciences
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• v.25 no.4
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• pp.405-414
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• 2008

To better understand the physical processes that control the high-latitude lower thermospheric dynamics, we analyze the divergence and vorticity of the high-latitude neutral wind field in the lower thermosphere during the southern summertime for different IMF conditions. For this study the National Center for Atmospheric Research Thermosphere-Ionosphere Electrodynamics General Circulation Model (NCAR-TIEG CM) is used. The analysis of the large-scale vorticity and divergence provides basic understanding flow configurations to help elucidate the momentum sources that ulti-mately determine the total wind field in the lower polar thermosphere and provides insight into the relative strengths of the different sources of momentum responsible for driving winds. The mean neutral wind pattern in the high-latitude lower thermosphere is dominated by rotational flow, imparted primarily through the ion drag force, rather than by divergent flow, imparted primarily through Joule and solar heating. The difference vorticity, obtained by subtracting values with zero IMF from those with non-zero IMF, in the high-latitude lower thermosphere is much larger than the difference divergence for all IMF conditions, indicating that a larger response of the thermospheric wind system to enhancement in the momentum input generating the rotational motion with elevated IMF than the corresponding energy input generating the divergent motion. the difference vorticity in the high-latitude lower thermosphere depends on the direction of the IMF. The difference vorticity for negative and positive $B_y$ shows positive and negative, respectively, at higher magnetic latitudes than $-70^{\circ}$. For negative $B_z$, the difference vorticities have positive in the dusk sector and negative in the dawn sector. The difference vorticities for positive $B_z$ have opposite sign. Negative IMF $B_z$ has a stronger effect on the vorticity than does positive $B_z$.

• Economic and Environmental Geology
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• v.47 no.1
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• pp.39-48
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• 2014

In coastal region, estuaries have complex environments where dissolved and particulate matters are mixed with marine water and substances. Suspended sediment (SS) dynamics in coastal water, in particular, plays a major role in erosion/deposition processes, biomass primary production and the transport of nutrients, micropollutants, heavy metals, etc. Temporal variation in suspended sediment concentration (SSC) can be used to explain erosion/sedimentation patterns within coastal zones. Remotely sensed data can be an efficient tool for mapping SS in coastal waters. In this study, we analyzed the variation in SSC in coastal water using the Geostationary Ocean Color Imager (GOCI) and Landsat Enhanced Thematic Mapper Plus (ETM+) in Gyeonggi-bay. Daily variations in GOCI-derived SSC showed low values during ebb time. Current velocity and water level at 9 and 10 am is 37.6, 28.65 $cm{\cdot}s^{-1}$ and -1.23, -0.61 m respectively. Water level has increased to 1.18 m at flood time. In other words, strong current velocity and increased water level affected high SSC value before flood time but SSC decreased after flood time. Also, we compared seasonal SSC with the river discharge from the Han River and the Imjin River. In summer season, river discharge showed high amount, when SSC had high value near the inland. At this time SSC in open sea had low value. In contrast, river discharge amount from inland showed low value in winter season and, consequently, SSC in the open sea had high value because of northwest monsoon.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 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 Environmental Impact Assessment
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• v.30 no.3
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• pp.141-154
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• 2021

In this study, the effect of the restoration of Yaksa stream and the construction of an apartment complex by the urban renewal project in the Yaksa district of Chuncheon on air quality in the surrounding area was evaluated using computational fluid dynamics (CFD) model simulations. In orderto compare the impact of the project, wind and pollutant concentration fields were simulated using topographic data in 2011 and 2017, which stand for the periods before and after the urban renewal project, respectively. In the numerical experiments, the scenarios were set to analyze the effect of the construction of the apartment complex and the effect of stream restoration. Wind direction and wind speed data obtained from the Chuncheon Automated Synoptic Observing System (ASOS) were used as the inflow boundary conditions, and the simulation results were weighted according to the frequencies of the eight-directional inflow wind directions. The changes in wind speed and NO_X concentration distribution according to the changes in building and terrain between scenarios were compared. As a result, the concentration of NO_X emitted from the surrounding roads increased by the construction of the apartment complex, and the magnitude of the increase was reduced as the result of including the effect of stream restoration. The concentration of NO_X decreased around the restored stream, while the concentration increased significantly around the constructed apartment complex. The increase in the concentration of NO_X around the apartment complex was more pronounced in the place located in the rear of the wind direction to the apartment complex, and the effect remains up to the height of the building. In conclusion, it was confirmed that the relative arrangement of apartment complex construction and stream restoration in relation to the main wind direction of the target area was one of the major factors in determining the surrounding air quality.

• Journal of Astronomy and Space Sciences
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• v.22 no.2
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• pp.147-174
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• 2005

To understand the physical processes that control the high-latitude lower thermospheric dynamics, we quantify the forces that are mainly responsible for maintaining the high-latitude lower thermospheric wind system with the aid of the National Center for Atmospheric Research Thermosphere-Ionosphere Electrodynamics General Circulation Model (NCAR-TIEGCM). Momentum forcing is statistically analyzed in magnetic coordinates, and its behavior with respect to the magnitude and orientation of the interplanetary magnetic field (IMF) is further examined. By subtracting the values with zero IMF from those with non-zero IMF, we obtained the difference winds and forces in the high-latitude 1ower thermosphere(<180 km). They show a simple structure over the polar cap and auroral regions for positive($B_y$ > 0.8|$\overline{B}_z$ |) or negative($B_y$ < -0.8|$\overline{B}_z$|) IMF-$\overline{B}_y$ conditions, with maximum values appearing around -80$^{\circ}$ magnetic latitude. Difference winds and difference forces for negative and positive $\overline{B}_y$ have an opposite sign and similar strength each other. For positive($B_z$ > 0.3125|$\overline{B}_y$|) or negative($B_z$ < -0.3125|$\overline{B}_y$|) IMF-$\overline{B}_z$ conditions the difference winds and difference forces are noted to subauroral latitudes. Difference winds and difference forces for negative $\overline{B}_z$ have an opposite sign to positive $\overline{B}_z$ condition. Those for negative $\overline{B}_z$ are stronger than those for positive indicating that negative $\overline{B}_z$ has a stronger effect on the winds and momentum forces than does positive $\overline{B}_z$ At higher altitudes(>125 km) the primary forces that determine the variations of tile neutral winds are the pressure gradient, Coriolis and rotational Pedersen ion drag forces; however, at various locations and times significant contributions can be made by the horizontal advection force. On the other hand, at lower altitudes(108-125 km) the pressure gradient, Coriolis and non-rotational Hall ion drag forces determine the variations of the neutral winds. At lower altitudes(<108 km) it tends to generate a geostrophic motion with the balance between the pressure gradient and Coriolis forces. The northward component of IMF By-dependent average momentum forces act more significantly on the neutral motion except for the ion drag. At lower altitudes(108-425 km) for negative IMF-$\overline{B}_y$ condition the ion drag force tends to generate a warm clockwise circulation with downward vertical motion associated with the adiabatic compress heating in the polar cap region. For positive IMF-$\overline{B}_y$ condition it tends to generate a cold anticlockwise circulation with upward vertical motion associated with the adiabatic expansion cooling in the polar cap region. For negative IMF-$\overline{B}_z$ the ion drag force tends to generate a cold anticlockwise circulation with upward vertical motion in the dawn sector. For positive IMF-$\overline{B}_z$ it tends to generate a warm clockwise circulation with downward vertical motion in the dawn sector.

• Sleep Medicine and Psychophysiology
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• v.17 no.1
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• pp.41-49
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• 2010

Unlike the case of adult obstructive sleep apnea syndrome (OSAS), there was no consistent finding on the changes of sleep architecture in childhood OSAS. Further understanding of the sleep electroencephalogram (EEG) should be needed. Non-linear analysis of EEG is particularly useful in giving us a new perspective and in understanding the brain system. The objective of the current study is to compare the sleep architecture and the scaling exponent (${\alpha}$) from detrended fluctuation analysis (DFA) on sleep EEG between OSAS and normal children. Fifteen normal children (8 boys/7 girls, 6.0${\pm}4.3$2.2 years old) and twelve OSAS children (10 boys/2 girls, 6.4${\pm}4.3$3.4 years old) were studied with polysomnography (PSG). Sleep-related variables and OSAS severity indices were obtained. Scaling exponent of DFA were calculated from the EEG channels (C3/A2, C4/A1, O1/A2, and O2/A1), and compared between normal and OSAS children. No difference in sleep architecture was found between OSAS and normal controls except stage 1 sleep (%) and REM sleep latency (min). Stage 1 sleep (%) was significantly higher and REM latency was longer in OSAS group (9.3${\pm}4.3$4.3%, 181.5${\pm}4.3$59.9 min) than in controls (5.6${\pm}4.3$2.8%, 133.5${\pm}4.3$42.0 min). Scaling exponent (${\alpha}$) showed that sleep EEG of OSAS children also followed the 'longrange temporal correlation' characteristics. Value of ${\alpha}$ increased as sleep stages increased from stage 1 to stage 4. Value of ${\alpha}$ from C3/A2, C4/A1, O1/A2, O2/A1 were significantly lower in OSAS than in control (1.36${\pm}4.3$0.05 vs. 1.41${\pm}4.3$0.04, 1.37${\pm}4.3$0.04 vs. 1.41${\pm}4.3$0.04, 1.37${\pm}4.3$0.05 vs. 1.41${\pm}4.3$0.05, and 1.36${\pm}4.3$0.07 vs. 1.41${\pm}4.3$0.05, p<0.05). Higher stage 1 sleep (%) in OSAS children was consistent finding with OSAS adults. Lower $'{\alpha}'$ in OSAS children suggests decrease of self-organized criticality or the decreased piling-up energy of brain system during sleep in OSAS children.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.