• Journal of Korea Water Resources Association
• /
• v.56 no.12
• /
• pp.993-1003
• /
• 2023

Due to the increasing greenhouse gas emissions, the global mean temperature has risen by 1.1℃ compared to pre-industrial levels, and significant changes are expected in functioning of water supply systems. In this study, we assessed impacts of climate change and instreamflow management on water supply reliability in the Geum River basin, Korea. We proposed univariate climate response functions, where mean precipitation and potential evaporation were coupled as an explanatory variable, to assess impacts of climate stress on multiple water supply reliabilities. To this end, natural streamflows were generated in the 19 sub-basins with the conceptual GR6J model. Then, the simulated streamflows were input into the Water Evaluation And Planning (WEAP) model. The dynamic optimization by WEAP allowed us to assess water supply reliability against the 2020 water demand projections. Results showed that when minimizing the water shortage of the entire river basin under the 1991-2020 climate, water supply reliability was lowest in the Bocheongcheon among the sub-basins. In a scenario where the priority of instreamflow maintenance is adjusted to be the same as municipal and industrial water use, water supply reliability in the Bocheongcheon, Chogang, and Nonsancheon sub-basins significantly decreased. The stress tests with 325 sets of climate perturbations showed that water supply reliability in the three sub-basins considerably decreased under all the climate stresses, while the sub-basins connected to large infrastructures did not change significantly. When using the 2021-2050 climate projections with the stress test results, water supply reliability in the Geum River basin was expected to generally improve, but if the priority of instreamflow maintenance is increased, water shortage is expected to worsen in geographically isolated sub-basins. Here, we suggest that the climate response function can be established by a single explanatory variable to assess climate change impacts of many sub-basin's performance simultaneously.

• Progress in Medical Physics
• /
• v.25 no.3
• /
• pp.128-138
• /
• 2014

In gated radiation therapy (gRT), due to residual motion, beam delivery is intended to irradiate not only the true extent of disease, but also neighboring normal tissues. It is desired that the delivery covers the true extent (i.e. clinical target volume or CTV) as a minimum, although target moves under dose delivery. The objectives of our study are to validate if the intended dose is surely delivered to the true target in gRT and to quantitatively understand the trend of dose delivery on it and neighboring normal tissues when gating window (GW), motion amplitude (MA), and CTV size changes. To fulfill the objectives, experimental and computational studies have been designed and performed. A custom-made phantom with rectangle- and pyramid-shaped targets (CTVs) on a moving platform was scanned for four-dimensional imaging. Various GWs were selected and image integration was performed to generate targets (internal target volume or ITV) for planning that included the CTVs and internal margins (IM). The planning was done conventionally for the rectangle target and IMRT optimization was done for the pyramid target. Dose evaluation was then performed on a diode array aligned perpendicularly to the gated beams through measurements and computational modeling of dose delivery under motion. This study has quantitatively demonstrated and analytically interpreted the impact of residual motion including penumbral broadening for both targets, perturbed but secured dose coverage on the CTV, and significant doses delivered in the neighboring normal tissues. Dose volume histogram analyses also demonstrated and interpreted the trend of dose coverage: for ITV, it increased as GW or MA decreased or CTV size increased; for IM, it increased as GW or MA decreased; for the neighboring normal tissue, opposite trend to that of IM was observed. This study has provided a clear understanding on the impact of the residual motion and proved that if breathing is reproducible gRT is secure despite discontinuous delivery and target motion. The procedures and computational model can be used for commissioning, routine quality assurance, and patient-specific validation of gRT. More work needs to be done for patient-specific dose reconstruction on CT images.

• Asia pacific journal of information systems
• /
• v.24 no.2
• /
• pp.233-253
• /
• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Korean Journal of Food Science and Technology
• /
• v.32 no.4
• /
• pp.843-850
• /
• 2000

We have produced the microcapsule composed of ${\alpha}-tocopherol$ as a core material (Cm) and the gelatinized polysaccharide as a wall material (Wm). Firstly, we have developed a simple, sensitive, and quantitative analysis method of the microencapsulation product using 5% cupric acetate pyridine solution. We could then optimize all the conditions for the microencapsulation process such as the ratio of [Cm] to [Wm], the temperature of dispersion fluid, and the emulsifier concentration using response surface methodology (RSM). As for the microencapsulation of ${\alpha}-tocopherol$, the regression model equation for the yield of microencapsulation (YM, %) to the change of an independent variable could be predicted as follows : YM=99.77-1.76([Cm]:[Wm])-1.72$([Cm]\;:\;[Wm])^2$. From the ridge of maximum response, the optimum conditions for the microencapsulation of ${\alpha}-tocopherol$ were able to be determined as the ratio of [Cm] to [Wm] of 4.6:5.4(w/w), the emulsifier concentration of 0.49%, and dispersion fluid temperature of $25.5^{\circ}C$, respectively. Finally, the microcapsules produced under the optimal conditions were applied for the analysis of storage stability. The optimal conditions for the storage were found to be the values of pH 9.0 and $25{\sim}35^{\circ}C$. And the storage stability of the microcapsules containing ${\alpha}-tocopherol$ were higher than 99% for a week at pH 9.0 and $25^{\circ}C$.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.31 no.6
• /
• pp.434-449
• /
• 2019

In this study, we develop a new cross-shore sediment module which takes the effect of infra-gravity waves of bound mode, and boundary layer streaming on the sediment transport into account besides the well-known asymmetry and under-tow. In doing so, the effect of individual random waves occurring during the unit observation period of 1 hr on sediment transport is also fully taken into account. To demonstrate how the individual random waves would affect the sediment transport, we numerically simulate the non-linear shoaling process of random wavers over the beach of uniform slope. Numerical results show that with the consistent frequency Boussinesq Eq. the application of which is lately extended to surf zone, we could simulate the saw-tooth profile observed without exception over the surf zone, infra-gravity waves of bound mode, and boundary-layer streaming accurately enough. It is also shown that when yearly highest random waves are modeled by the equivalent nonlinear uniform waves, the maximum cross-shore transport rate well exceeds the one where the randomness is fully taken into account as much as three times. Besides, in order to optimize the free parameter K involved in the long-shore sediment module, we carry out the numerical simulation to trace the yearly shoreline change of Mang-Bang beach from 2017.4.26 to 2018.4.20 as well, and proceeds to optimize the K by comparing the traced shoreline change with the measured one. Numerical results show that the optimized K for Mang-Bang beach would be 0.17. With K = 0.17, via yearly grand circulation process comprising severe erosion by consecutively occurring yearly highest waves at the end of October, and gradual recovery over the winter and spring by swell, the advance of shore-line at the northern and southern ends of Mang-Bang beach by 18 m, and the retreat of shore-line by 2.4 m at the middle of Mang-Bang beach can be successfully duplicated in the numerical simulation.

• Journal of the Korean Wood Science and Technology
• /
• v.43 no.6
• /
• pp.851-860
• /
• 2015

The objective of this study was to manufacture the wood based roughage using lumber from thinning of oak and pitch pine (Pinus rigida). And the study also aimed to investigate a feed value evaluation of wood based roughages. To investigate the optimization condition of steam-digestion treatment for roughage, the wood chips of oak and pitch pine were steam-digestion treated at $160^{\circ}C$ under pressure 6 atm depending on treatment times (60 min, 90 min and 120 min) followed by the content of essential oils analyzed. The essential oil content of steam-digestion treated roughages for 90 min and 120 min were under 0.1 mL/kg. The evaluation of feed value was carried out from steam-digestion treated roughages for 90 min through feed chemical composition analysis, NRC (National research Council) modeling, ruminal degradability analysis and relative economic value analysis. The feed chemical compositions including DM (dry mater), CP (crude protein), EE (ether extract), NDF (neutral detergent fiber), ADF (acid detergent fiber), ADL (acid detergent lignin), NFC (nonfiber carbohydrate) in oak roughage were 95.4, 1.36, 3.11, 90.05, 83.85, 17.33, 6.50%, respectively, and in pitch pine roughage were 94.37, 1.33, 5.48, 87.89, 86.88, 30.56, 6.32%, respectively. Both roughages showed low level of protein and very high level of NDF. The TDN (total digestible nutrient) levels using NRC (2001) model in oak and pitch pine roughages were 40.55, 31.22%, respectively. The ruminal in situ dry matter degradability was higher in oak roughage (23.84%) than in pitch pine roughage (10.02%). The economic values of oak and pitch pine rough-ages were 235, and 210 \, respectively.

• Journal of Radiation Protection and Research
• /
• v.33 no.1
• /
• pp.13-20
• /
• 2008

The flow rate measurements in a multi-phase flow pipeline were evaluated quantitatively by means of a clamp-on sealed radioisotope based on a cross correlation signal processing technique. The flow rates were calculated by a determination of the transit time between two sealed gamma sources by using a cross correlation function following FFT filtering, then corrected with vapor fraction in the pipeline which was measured by the ${\gamma}$-ray attenuation method. The pipeline model was manufactured by acrylic resin(ID. 8 cm, L=3.5 m, t=10 mm), and the multi-phase flow patterns were realized by an injection of compressed $N_2$ gas. Two sealed gamma sources of $^{137}Cs$ (E=0.662 MeV, ${\Gamma}$ $factor=0.326\;R{\cdot}h^{-1}{\cdot}m^2{\cdot}Ci^{-1}$) of 20 mCi and 17 mCi, and radiation detectors of $2"{\times}2"$ NaI(Tl) scintillation counter (Eberline, SP-3) were used for this study. Under the given conditions(the distance between two sources: 4D(D; inner diameter), N/S ratio: $0.12{\sim}0.15$, sampling time ${\Delta}t$: 4msec), the measured flow rates showed the maximum. relative error of 1.7 % when compared to the real ones through the vapor content corrections($6.1\;%{\sim}9.2\;%$). From a subsequent experiment, it was proven that the closer the distance between the two sealed sources is, the more precise the measured flow rates are. Provided additional studies related to the selection of radioisotopes their activity, and an optimization of the experimental geometry are carried out, it is anticipated that a radioisotope application for flow rate measurements can be used as an important tool for monitoring multi-phase facilities belonging to petrochemical and refinery industries and contributes economically in the light of maintenance and control of them.

• Food Science and Preservation
• /
• v.24 no.5
• /
• pp.623-630
• /
• 2017

Functional compounds including flavonoids, anthocyanins, polyphneols and antioxidants were extracted from blue honeysuckle (Lonicera caerulea L.) using highly efficient microwave-assisted extraction. And extraction process was modeled and optimized according to response surface methodology (RSM). The independent variables ($X_n$) were ethanol concentration ($X_1$: 0, 25, 50, 75, 100%), irradiation time ($X_2$: 1, 3, 5, 7, 9 min), and microwave power ($X_3$: 60, 120, 180, 240, 300 W). Dependent variables ($Y_n$) were total flavonoid contents ($Y_1$), total anthocyanin contents ($Y_2$), total polyphenol contents ($Y_3$) and antioxidant activity ($Y_4$). Four-dimensional response surface plots were generated based on the fitted second-order polynomial models to get optimal conditions. Estimated optimal conditions for 4 responses were ethanol concentration of 54-72%, irradiation time of 7.1-7.6 min, and microwave power of 243-251 W. Ridge analysis predicted the maximal responses of total flavonoid content, total anthocyanin content, total polyphenol content and antioxidant activity were 38.00 mg RE/g, 6.80 mg CGE/g, 14.90 mg GAE/g, 89.10%, respectively. Verification experiment was carried out at predicted optimal conditions and experimental values for total flavonoid content, total anthocyanin content, total polyphenol content and antioxidant activity were 38.10 mg RE/g, 6.72 mg CGE/g, 14.91 mg GAE/g and 89.13%, respectively. No significant difference was observed between predicted and experimental values, indicating good fitness of fitted model and successful application of RSM.

• Journal of Korea Water Resources Association
• /
• v.41 no.12
• /
• pp.1219-1230
• /
• 2008

Stream inflows induced by flood runoffs have a higher density than the ambient reservoir water because of a lower water temperature and elevated suspended sediment(SS) concentration. As the propagation of density currents that formed by density difference between inflow and ambient water affects reservoir water quality and ecosystem, an understanding of reservoir density current is essential for an optimization of filed monitoring, analysis and forecast of SS and nutrient transport, and their proper management and control. This study was aimed to quantify the characteristics of inflow density current including plunge depth($d_p$) and distance($X_p$), separation depth($d_s$), interflow thickness($h_i$), arrival time to dam($t_a$), reduction ratio(${\beta}$) of SS contained stream inflow for different flood magnitude in Daecheong Reservoir with a validated two-dimensional(2D) numerical model. 10 different flood scenarios corresponding to inflow densimetric Froude number($Fr_i$) range from 0.920 to 9.205 were set up based on the hydrograph obtained from June 13 to July 3, 2004. A fully developed stratification condition was assumed as an initial water temperature profile. Higher $Fr_i$(inertia-to-buoyancy ratio) resulted in a greater $d_p,\;X_p,\;d_s,\;h_i$, and faster propagation of interflow, while the effect of reservoir geometry on these characteristics was significant. The Hebbert equation that estimates $d_p$ assuming steady-state flow condition with triangular cross section substantially over-estimated the $d_p$ because it does not consider the spatial variation of reservoir geometry and water surface changes during flood events. The ${\beta}$ values between inflow and dam sites were decreased as $Fr_i$ increased, but reversed after $Fr_i$>9.0 because of turbulent mixing effect. The results provides a practical and effective prediction measures for reservoir operators to first capture the behavior of turbidity inflow.

• KSBB Journal
• /
• v.17 no.1
• /
• pp.73-79
• /
• 2002

The method to optimize the microbial production of ethanol from CO using Clostridium ljungdahlii was developed. The kinetic parameter study on CO conversion with Clostridium ljungdahlii was carried out and maximum CO conversion rate of 37.14 mmol/L-hr-O.D. and $K_{m}$ / of 0.9516 atm were obtained. It was observed that method of two stage fermentation, which consists of cell growth stage and ethanol production stage, was effective to produce ethanol. When pH was shifted from 5.5 to 4.5 and ammonium solution was supplied to culture media as nitrogen source at ethanol production stage, the concentration of ethanol produced was increased 20 times higher than that without shift. Ethanol production from CO in a fermenter with Clostridium ljungdahlii was optimized and the concentration of ethanol produced was 45 g/L and maximun ethanol productivity was 0.75 g ethanol/L-hr.