Construction of Dependence Structure for Rainfall Stations by Joining Time Series Models with Copula Method

Copula model has applied in various hydrologic studies, however, most analyses conducted does not considering the non-stationary conditions that may exist in the time series. To investigate the dependence structure between two rainfall stations at Johor Bahru, two methods have been applied. The first method considers the non-stationary condition that exists in the data, while the second method assumes stationarity in the time series data. Through goodness-off-fit (GOF) and simulation tests, performance of both methods are compared in this study. The results obtained in this study highlight the importance of considering non-stationarity conditions in the hydrological data.

Copula method of the kinematic accuracy of cylindrical roller bearing

The kinematic accuracy of cylindrical rollers bearing isn’t only influenced by the dimensional and form precision of its parts, but also more influenced by the cooperation among them. For cylindrical rollers bearing, the main indices of the kinematic accuracy are the ending beat and the radial run out of bearings. There must be dependent relationship between the cooperative action among the parts of bearings and the ending beat or the radial run out of bearings. This relationship is hardly expressed by mathematical formula. However, because the parts dimension deviation and the run out of bearings follow statistic law and have their distribution characteristics, while the copula joint distribution function can connect the run out of bearings with multiple parts dimension accuracy, the copula function is introduced to analyze the dependent relationship between bearing parts cooperative action and its kinematic accuracy. Based on the copula function of statistic theory, the kinematic accuracy of bearings can be forecast by parts geometric accuracy.

CRYOPRESERVATION OF ALPACA SPERMATOZOA OBTAINED VIA POST COPULA IN A TRIS EXTENDER WITH EGG YOLK FROM THREE AVIAN SPECIES.

The objective of this study was to evaluate the cryopreservation of alpaca spermatozoa obtained via post copula in a Tris extender with egg yolk from three avian species. Forty samples of eight alpacas were collected by the post-copula method. After the collection, we proceeded to evaluate sperm volume, color, motility and concentration. The 25 samples with volume 1 ml and total motility 60% were mixed to form pool (5 samples/pool), divided into three aliquots and diluted in Tris-base with 20% egg yolk from three avian species (hen, quail, paw). These diluted samples were refrigerated for 1,5 h at 5 °C. Once this temperature was reached, the 5% glycerol basic dilutor was added, balanced for 20 min, packed in 0,5 mL straws and frozen in liquid nitrogen vapours for 20 min. The thawed samples were evaluated at different incubation times at 37 °C: 0; 1,5 and 3 h. All parameters of fresh and thawed sperm quality were analyzed using the GLM procedure (ANOVA). The samples collected (fresh) showed a motility of 69,1%, viability of 82,8%, membrane functionality of 77,9% and acrosomal integrity of 85,8%. After the cooling process, no differences were observed between the different egg yolk when comparing the sperm characteristics evaluated (p>0,05). At thawing, motility and acrosomal integrity were superior (p<0,05) when hen and quail were used compared to paw egg yolk. At 1,5 and 3 h of incubation, motility and acrosomal integrity were superior (p<0,05) in the samples with hen and quail with respect to paw. In conclusion, the use of hen and quail provided better cryoprotective action than paw egg yolk in cryopreserved alpaca sperm and incubated at 37°C for 3 h

Do Derivatives Hinder the Financial Contagion? A Case Study of Developed Countries’ Stock Markets

The main purpose of this study is to test the effect of the derivative instruments on financial contagion in developed countries including France, Germany, South Korea, Spain, the Netherlands and the United Kingdom, considering the United States as the source of the crisis. Therefore, at first, existence of the contagion in the markets was investigated using the ARMA-GARCH-COPULA method, and then, the effect of the derivative instruments on the contagion for the selected countries was examined during the time period 01: 2007: to 08:2018. The results confirm the negative effect of the derivatives on the contagion.

Tracking the Uncertainty Propagation Process Between Hydrological Forecasting and Reservoir Real-Time Optimal Operation

The inherent uncertainty in hydrological forecasting poses a challenge for reservoir real-time optimal operation. In this paper, a stochastic framework is proposed to track the uncertainty propagation process between hydrological forecasting and reservoir operation. The framework simulates the comprehensive uncertainty of hydrological forecasts in the form of ensemble forecasts and scenario trees. Based on the derived analytic relationship between the performance metric Nash-Sutcliffe efficiency coefficient (NSE) and forecast uncertainty probability distribution, we use three methods (two are commonly used classical methods and one is the Gaussian copula method) simultaneously to generate inflow forecast ensembles. Compared with the two classical methods, the Gaussian copula method additionally takes into account the temporal correlation of reservoir inflows. Then, the neural gas method is employed to transform the generated ensembles into a scenario tree, which is further used as an input for reservoir stochastic optimization. To improve the adaptability to uncertainties in inflow forecasts, we establish a stochastic optimization model that optimizes the expectation of objective values over all scenarios. Meanwhile, we propose a parallel differential evolution (DE) algorithm based on parallel computing techniques for solving the stochastic optimization model efficiently. Risk assessment is performed to capture the uncertainty and corresponding risk associated with the reservoir optimal decision. The proposed framework is demonstrated in a flood control reservoir system in China. Furthermore, we conduct several numerical experiments to explore the effect of forecast uncertainty level and temporal correlation on reservoir real-time optimal operation. The results indicate that the temporal correlation of inflows must be considered in inflow stochastic simulation and reservoir stochastic optimization, otherwise the operational risk is likely to be overestimated or underestimated, thus leading to operation failures. Based on the risk simulation surface, reservoir operators can examine the robustness of operational decisions and thus make more reliable final decisions.

Correlation Analysis of Influencing Factors and the Monthly Displacement Increment of a Hydrodynamic Landslide Using a Pseudo-Maximum-Likelihood-Estimation-Mixed-Copula Approach

Heavy rainfall and changes in the water levels of reservoirs directly affect the degree of landslide disasters in major hydropower project reservoir areas. Correlation analyses of rainfall- and water-level fluctuations with landslide displacement changes can provide a scientific basis for the prevention and early warning of landslide disasters in reservoir areas. Because of the shortcomings of the traditional correlation analysis based on linear assumptions, this study proposed the use of a pseudo-maximum-likelihood-estimation-mixed-Copula (MLE-M-Copula) method instead of linear assumptions. We used the Bazimen landslide in the Three Gorges Reservoir Area as a case study to carry out the correlation analysis of the rainfall, water-level fluctuations, and landslide displacement. First, we selected several appropriate influencing factors to construct four candidate Copula models and estimated the parameters using the pseudo-MLE method. After the goodness-of-fit test, we selected the M-Copula model as the optimal model and used this model to study correlations between the monthly displacement increment of the landslide and influencing factors. We then established the joint distribution functions of these correlations. We computed and analyzed the overall and tail correlations between the displacement increment and the influencing factors, and we constructed the conditional probability distribution of the monthly displacement increment for different given conditions. The results showed that the pseudo-MLE-M-Copula method effectively quantified the correlation between the rainfall, reservoir-level fluctuations, and landslide displacement changes, and we obtained the return periods and value at risk of the influencing factors of the Bazimen landslide under different rainfall conditions and reservoir-level changes. Furthermore, the tail correlations between the monthly displacement increment of the landslide and the rainfall- and reservoir-level changes were higher than the overall correlations.

TIN-Copula bias correction of climate modeled daily maximum temperature in the MENA region

&lt;p&gt;Over the last decades, the use of climate models in the projection and assessment of future climate conditions, both on global and regional scales, has become common practice. However, inevitable biases between the simulated model output and observed conditions remain, mainly due to the variable nature of the atmospheric system, and limitations in representing sub-grid-scale processes that need to be parameterized. The present study aims to test a new approach for increasing the accuracy of daily climate model output. We apply the recently introduced TIN-Copula statistical method to the results of a state-of-the-art global Earth System Model (Hadley Centre Global Environmental Model version 3 - HadGEM3). The TIN-Copula approach is a combination of Triangular Irregular Networks and Copulas that focuses on modeling the whole dependence structure of the studied variables. The study area of the current application is the Middle East and North Africa (MENA) region, a prominent global climate change hot-spot. Considering the lack of accurate and consistent observational records in the MENA, we used the ERA5 reanalysis dataset as a reference. The results of the study reveal that the TIN-Copula method significantly improves the simulation of maximum temperature, both on annual and seasonal time scales. Specifically, the HadGEM3 model tends to overestimate the ERA5 temperature data in the major part of the MENA region. This overestimation is mainly evident for the lower values of the studied data sets during all seasons, while in summer the overestimation is found in the whole data set. However, after the use the TIN-Copula method, the differences between the simulated maximum temperature and the ERA5 data were minimized in more than the 85% of the studied grids.&lt;/p&gt;