• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.1
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• pp.90-100
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• 2021

In the north and northeast of Cheonsu Bay, short-term fluctuations of surface water temperature are large owing to shallow water depth, weak current, and freshwater runoff. However, in the south of the bay, water temperature fluctuations are small owing to the inflow of offshore water by tidal currents. The water temperature in the north of the bay is higher in spring and summer than in the south of the bay, but lower in autumn and winter. During spring season, the fluctuation in the northern surface water temperature is the highest. The temperature fluctuations owing to tides are in phase with the tide in autumn and winter, and in the reverse phase with the tide in spring and summer. The dominant periods of water temperature fluctuations are half a day, daily, 15 days, and 1 month owing to the tide and 7 to 10 days, which are estimated based on atmospheric factors. Half a day and daily water temperature fluctuations are also highly correlated with air temperature and wind fluctuations. The sea area where water temperature fluctuations are highly correlated is divided into the north and south of the bay. The fluctuation phase is faster in the north of the bay than in the south or in the center.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.2 no.2
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• pp.109-114
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• 1998

The induction of crassulacean acid metabolism(CAM) characterized by day/night acid fluctuation was investigated in leaves from 10 days exposure to elevated $CO_2$ concentration(1,000 ${\mu}L\;L^{-1}CO_2).$ For Pereskia aculeata, have $C_3-like$ gas exchange pattern in well watered condition and shift into CAM-like in water stress, showed a more typical CAM-like diurnal acid fluctuation. Whereas the massive diurnal fluctuation of acidity in typical CAM of Kalanchoe rosea was declined. The effect of short-term exposure to various concentrations of $CO_2$ on titratable acidity in P. aculeata and K. rosea was also investigated. To investigate the response of various $CO_2$ concentrations, four different $CO_2$ levels(350, 700, 1,000 and 1,500 ${\mu}L\;L^{-1})$ were imposed for 24hr and measured the titratable acidity at 06:00, when the acidity was maximum, and 14:00, when the acidity was minimum. The accumulation of acid in P. aculeata was enhanced markedly by higher concentration of $CO_2,$ while the level of acidity in f rosea did not highly respond to $CO_2.$ A notable difference between P. aculeata and K. rosea was the response of de-acidification to a higher concentration of $CO_2$ Increasing with $CO_2,$ the degree of do-acidification of P. auleata was increased while that of K. rosea was depressed.

• Nuclear Engineering and Technology
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• v.52 no.7
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• pp.1429-1435
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• 2020

Applying an accurate parametric prediction model to identify abnormal or false pressurizer water levels (PWLs) is critical to the safe operation of marine pressurized water reactors (PWRs). Recently, deep-learning-based models have proved to be a powerful feature extractor to perform high-accuracy prediction. However, the effectiveness of models still suffers from two issues in PWL prediction: the correlations shifting over time between PWL and other feature parameters, and the example imbalance between fluctuation examples (minority) and stable examples (majority). To address these problems, we propose a cost-sensitive mechanism to facilitate the model to learn the feature representation of later examples and fluctuation examples. By weighting the standard mean square error loss with a cost-sensitive factor, we develop a Cost-Sensitive Long Short-Term Memory (CSLSTM) model to predict the PWL of PWRs. The overall performance of the CSLSTM is assessed by a variety of evaluation metrics with the experimental data collected from a marine PWR simulator. The comparisons with the Long Short-Term Memory (LSTM) model and the Support Vector Regression (SVR) model demonstrate the effectiveness of the CSLSTM.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.

• Journal of the korean society of oceanography
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• v.37 no.4
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• pp.224-231
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• 2002

Vertical distributions of coprostanol (5$\beta$-cholestan-3$\beta$-ol) and other sterols were investigated in the intertidal sediment of Shinbul island in the Han River estuary to estimate the short-term variations of fecal contamination in association with reclamation activity which caused a construction of tidal barrier and emigration of residents from the island. Quantitative contributions of coprostanol in total sterol (9.87-15.84%) and in total organic carbon (82.0-157.7 $\mu\textrm{g}$ g$^{-1}$ OC) implied that a substantial amount of organic matter associated with fecal pollutants was introduced into the sediment. The highest contribution of coprostanol to organic carbon that was observed between 0.3-0.9 cm depth seemed to be associated with increased human activities for the reclamation project of the island. The ratio of coprostanol to organic carbon decreased within 0.3 cm depth, which indicated decreased fecal contamination after the emigration of residents from the island. The results suggested that measurement of coprostanol could relevantly reflect short-term fluctuation of fecal contamination in the sediment of the Han River estuary.

• Clinical and Experimental Pediatrics
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• v.45 no.9
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• pp.1114-1119
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• 2002

Purpose : The purposes of this study were to determine short- and long-term fractal correlation behavior of heart rates during daily activity in patients with neurocardiogenic syncope. Methods : Twenty five patients with histories of neurocardiogenic syncope episodes were included. Their analogue 24h ambulatory Holter electrocardiograms were analyzed. The tape was digitized and the digitized electrocardiograms were partioned into sections of one hour. Then their RR intervals were measured and 20,000 points of RRI were used. To quantify the fractal correlation behavior, we employed the detrended fluctuation analysis, and short-term($n{\leq}16$, ${\alpha}_1$) and long-term(n>16, ${\alpha}_2$) fractal scaling exponents were calculated. Results : When compared to control, 24-hour average values of ${\alpha}_1$ and all ${\alpha}_1$ values at quarters of each day were significantly higher in patients with syncope. On the contrary, their 24-hour average value of ${\alpha}_2$ and all ${\alpha}_2$ values at quarters of each day were lower in patients with syncope. However, statistical significances were found in 24-hour average value of ${\alpha}_2$ and in ${\alpha}_2$ value at MN-6AM. Conclusion : In the syncope patients with neurocardiogenic syncope, short-term fractal scaling exponents of RR interval was significantly high throughout the day. Therefore, their RR intervals were smoother in the short term scale and had a tendency to continue in the same direction of increase or decrease, which may contribute to persistent decrease in heart rate during a syncopal attack.

• Journal of the Korea Institute of Building Construction
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• v.12 no.1
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• pp.108-114
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• 2012

Escalation method examining the changes in price index has been widely utilized in public construction projects. The previous escalation method determined estimated changes in price based on the average unit price of contract items over a period of time. In relation to this method, the issue has been raised that the fluctuation rates of previous method show different trends compared with other related price indices, as the influence of the small group of contract items with large unit prices overwhelms the others. This research suggested an improved escalation method which estimates the fluctuation rate by examining the changes in CCI (construction cost index) and applies it to the total amount or the partial amount deducted for labor cost in price escalation for previous bid price method. To verify the improvement, a case study is conducted on an educational facility, and the fluctuation rate was estimated in two different base periods (short term, long term). The results over the long term showed similar tendencies to those of related price indices, as well as significant differences in fluctuation rates compared to those of the previous method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.23 no.4
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• pp.46-52
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• 1981

The aim at this study has the stochastic hydrological analysis for the annual mean discharge and monthly discharge which were observed at Lobith of River Rhine in the Netherlands from 1901 to 1972. After this study was analysed by computer IBM 370 and Hewlett Parkard 9800, the results were as follows; 1.When 72 data was divided into two groups of subsample data as 36 data, they do not have their properties to be non-homogeneous and inconsistent due to F-test and t-test. 2.The credit limits of the serial correlation coefficient was fluctuated $\pm$0. 231 which was shown in Fig. 3. at significant level 99% by Anderson's test. 3.The correlogram at short term was shown to be no short-term persistence as Fig. 3. 4.Since the correlogram at long term has displayed that Hurst's coefficient was 0.6144 between 0.6 and 0.7, it was to be no long-term persistence. 5.The stochastic model with annual discharge of this River Rhine was shown with $\chi$t=2195+483. 8 $\varepsilon$t as $\chi$t=$\mu$+oet and $\varepsilon$t=$_1$ø$\varepsilon$t-$_1$+ζt where t=1,2,3,..., ζt is an independent series with mean zero and variance (1-ø2), $\varepsilon$t is the dependent series, and 4' is the parameter of the model. 6.The serial correlation coefficient of monthly discharge was explained as $\chi$$_1$ = 0.34 . sin(6-$\pi$t+$\pi$) as Fig.4. and the River Rhine has no large fluctuation and smoothly changed during that time.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.726-737
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• 2017

The use of energy storage systems (ESSs) has become a feasible solution to solve the wind power intermittency issue. However, the use of ESSs increases the system cost significantly. In this paper, an optimal power flow control scheme to minimize the ESS capacity is proposed by using the zero-phase delay low-pass filter which can eliminate the phase delay between the dispatch power and the wind power. In addition, the filter time constant is optimized at the beginning of each dispatching interval to ensure the fluctuation mitigation requirement imposed by the grid code with a minimal ESS capacity. And also, a short-term power dispatch control algorithm is developed suitable for the proposed power dispatch based on the zero-phase delay low-pass filter with the predetermined ESS capacity. In order to verify the effectiveness of the proposed power management approach, case studies are carried out by using a 3-MW wind turbine with real wind speed data measured on Jeju Island.

• Ocean and Polar Research
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• v.32 no.1
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• pp.41-52
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• 2010

Daily samples were collected during summer in order to analyse changes in the mesozooplankton community and to identify the major environmental factors that may influence mesozooplankton abundance in Jangmok Bay. A single site in the bay was sampled 47 times from July to September 2003. Mesozooplankton community, hydrographic (watertemperature, salinity, dissolvedoxygen) and biological (chlorophyll-a, ciliates densities, Noctiluca scintillans densities) factors were determined. The mesozooplankton abundance varied remarkably from 954 to $14,816\;inds.\;m^{-3}$. The six taxa of Evadne tergestina, barnacle nauplii and cypris, Paracalanus parvus s.1., Acartia omorii, Penilia avirostris and Sagitta crassa dominated numerically, contributing 86% of total mesozooplankton abundance. Stepwise multiple linear regression analysis was applied to find correlation between environmental factors and fluctuation in the abundance of dominant species and mesozooplankton. A. omorii was significantly correlated with temperature and N. scintillans densities. E. tergestina was correlated with temperature, salinity, and ciliate densities, whereas P. avirostris was correlated with temperature and dissolved oxygen. Among the environmental factors, mesozooplankton abundance correlated most strongly with N. scintillans densities. Accordingly, N. scintillans may be a key player in controlling the fluctuation of mesozooplankton abundance as a strong competitor for same food resources.