In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Abstract:

The six Arab Gulf states (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, UAE) play a vital role, especially with its geographical location and natural  resources (oil and gas) as well as other cultural and civilizational elements, in achieving  global economic balance and more specifically global energy security, naturally  because of  these countries have a comparative advantage in the field of fossil energy (oil and gas), thus this sector becomes more attractive for local and international investments alike. Being  the energy sector a leader sector in the economic development process, and the basic factor to achieve savings and financial surpluses in thes

Banks face different types of banking risks that limit the performance of its functions and achieve its objectives, including the financial risk that is based on current research into two types including a credit and liquidity risks. And established credit risk due to the possibility of delaying the borrowers to fulfill their obligations to the bank when due or non-payments on according to the terms agreed upon, while liquidity risk arises as a result of the inability of the bank to fund the financial needs, any inability to provide cash to pay its obligations short on credit without achieving tangible loss or the inability to employ the funds properly and show the liquidity risk in the event of inadequate cash inflows to the bank for an

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Photoplethysmography (PPG) is a non-invasive optical technique that employs variations in light absorption produced by alteration in the blood volume in capillaries at the skin during the cardiac cycle. This study aims to understand factors related to PPG morphology; a hand-elevation, the study has modified blood flow to and from the finger was conducted in the laboratory. It is widely established that the position of the limb relative to the heart has an effect on blood flow in arteries and venous. Peripheral digital pulse wave (DPW) signals were obtained from 15 healthy volunteer participants during hand-elevation, and hand-lowering techniques wherein the right hand was lifted and lowered relative to heart level, while the left h

the use of diffrent concectration of Na and Mg ions were shown to causes in increase in the bindings at oncentration