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Toplam kayıt 8, listelenen: 1-8
Diagnosis and grading of vesicoureteral reflux on voiding cystourethrography images in children using a deep hybrid model
(Elsevier, 2021)
Background and objective
Vesicoureteral reflux is the leakage of urine from the bladder into the ureter. As a result, urinary tract infections and kidney scarring can occur in children. Voiding cystourethrography is the ...
Investigation and prediction of ethylene Glycol based ZnO nanofluidic heat transfer versus magnetic effect by deep learning
(Elsevier Ltd, 2021)
In this study, ZnO (zinc oxide) nanoparticle production was performed. Heat transfer coefficients (h) were measured for Ethylene Glycol Based ZnO nanofluids that were produced using pure water, ethanol, and ethylene glycol ...
Comparison of extreme learning machine and deep learning model in the estimation of the fresh properties of hybrid fiber-reinforced SCC
(Springer, 2021)
This paper studied the estimation of fresh properties of hybrid fiber-reinforced self-compacting concrete (HR-SCC) mixtures with different types and combinations of fibers by using two different prediction method named as ...
An improved residual-based convolutional neural network for very short-term wind power forecasting
(ELSEVIER, 2021)
An accurate forecast of wind power is very important in terms of economic dispatch and the operation of power systems. However, effectively mitigating the risks arising from wind power in power system operations greatly ...
Classification of thermoluminescence features of CaCO3 with long short-term memory model
(Wiley, 2021)
Calcium carbonate (CaCO3 ), a mineral commonly found in the Earth's crust, is mainly in the forms of calcite and aragonite. Calcite has the most stable type of thermodynamics at room temperature and ambient pressure. It ...
SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting
(Elsevier, 2021)
Photovoltaic (PV) power generation has high uncertainties due to the randomness and imbalance nature of solar energy and meteorological parameters. Hence, accurate PV power forecasts are essential in the operation of PV ...
Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features
(2021)
The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. ...
A novel deep learning-based feature selection model for improving the static analysis of vulnerability detection
(Springer, 2021)
The automatic detection of software vulnerabilities is considered a complex and common research problem. It is possible to detect several security vulnerabilities using static analysis (SA) tools, but comparatively high ...