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 performance measures are used as a criterion to decide which classifier is the best one to detect the images with high accuracy. Eventually, the simulation results show that each classifier detect the damage/no damage image with different performance measures and then makes it easy to select the best one.
Due to the fact that living organisms do not exist individually, but rather exist in clusters interacting with each other, which helps to spread epidemics among them. Therefore, the study of the prey-predator system in the presence of an infectious disease is an important topic because the disease affects the system's dynamics and its existence. The presence of the hunting cooperation characteristic and the induced fear in the prey community impairs the growth rate of the prey and therefore affects the presence of the predator as well. Therefore, this research is interested in studying an eco-epidemiological system that includes the above factors. Therefore, an eco-epidemiological prey-predator model incorporating predation fear and
... Show MoreSoil defilement with "raw petroleum" is a standout amongst the most across the board and genuine ecological issues going up against both the industrialized and oil country like Iraq. Along these lines, the impact of "raw petroleum" on soil contamination is one of most critical subjects that review these days. The present examination expects to research "unrefined oil"effectson the mechanical and physical properties of clayey soils. The dirt examples were acquired from Al-Doura area in Baghdad city and arranged by the "Brought together Soil Grouping Framework (USCS)" as silty mud of low pliancy (CL). Research center tests were done on contaminated and unpolluted soil tests with same thickness. The dirtied tests are set up by blending
... Show MoreThe Halabja earthquake occurred on 12/11/2017 in Iraq, with a magnitude of 7.3 Mw, which happened in the Iraqi-Iranian borders. This earthquake killed and injured many people in the Kurdish region in the north of the country. There is no natural disaster more dangerous than earthquake, especially it occurs without warning, great attention must be paid to the impact of earthquakes on the soil and preparing for a wave of earthquakes. Numerical modeling using specific elements is considered a powerful tool to investigate the required behavior of structures in Geotechnical engineering, and the main objective of this is to assess the response of the Al-Wand dam to the Halabja earthquake, as this dam is located in an area that has been su
... Show MoreThis study gives an overview of the widely distributed herb plantain Plantago lanceolata and aqueous extraction of the plant, by study the effect of Plantago lanceolata aqueous extract on the hepatoprotective activity in albino female mice through measuring the three main liver enzymes aspartate transaminase (AST), alanine transaminase (ALT) and alkaline phosphatase (ALP) with the histological effect of extract on liver. Mice were separated into eight groups treated intraperitonially for seven days: (1) control, (2) CCl4 (0.02%), (3) aqueous extract (250 mg/kg), (4) aqueous extract (500 mg/kg), (5) CCl4 (0.02%) plus aqueous extract (250 mg/kg), (6) CCl4 (0.02%) plus aqueous extract (500 mg/kg),(7) aqueous extract (250 mg/kg) plus CCl4 (0.02
... Show MoreThe general assumption of linear variation of earth pressures with depth on retaining structures is still controversial; investigations are yet required to determine those distributions of the passive earth pressure (PEP) accurately and deduce the corresponding centroid location. In particular, for rigid retaining walls, the calculation of PEP is strongly dependent on the type of wall movement. This paper presents a numerical analysis for studying the influence of wall movement on the PEP distribution on a rigid retaining wall and the passive earth thrust location. The numerical predictions are remarkably similar to existing experimental works as recorded on scaled test models and ful
Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as a mechanism and encompasses
... Show More