This paper presents a new and effective procedure to extract shadow regions of high- resolution color images. The method applies this process on modulation the equations of the band space a component of the C1-C2-C3 which represent RGB color, to discrimination the region of shadow, by using the detection equations in two ways, the first by applying Laplace filter, the second by using a Kernel Laplace filter, as well as make comparing the two results for these ways with each other's. The proposed method has been successfully tested on many images Google Earth Ikonos and Quickbird images acquired under different lighting conditions and covering both urban, roads. Experimental results show that this algorithm which is simple and effective t

Background: Non-traumatic Intracerebral Hemorrhage (ICH) results from rupture of blood vessels in the brain. ICH categories can also be considered as being either lobar in location or within the deep white matter. Although hypertension is a major risk factor for ICH in general[11], it is commonly considered to be associated more with patients having deep than with those having lobar haemorrhage.
Objectives: We investigate the relationship between hypertension and deep versus lobar intracerebral hemorrhage (ICH).
Methods: a retrospective review of records of 163 patients aged 18-89 years admitted to Al-Kadhimiya Teaching Hospital (January 2008 - October 2010) and diagnosed with ICH.
Results: There was no significant relationship

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

The personal drama in particular, and one of the key elements underlying the dramatic structure to convey ideas and visions presented by the author when writing the text of the dramatic fall after that on the way out the submission form that suits the proposals of the text and processors directorial would push the wheel of dramatic structure to the front. So take the maker of the artwork (writer) undertook the transfer of those events and personalities in art presumed sometimes real and sometimes, in order to enrich the art inspired by the human reality through the ages, and full of its themes and ideas that led to the development experiences of peoples experiences of living. Therefore, we find it important to research in the characters

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

      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

A variety of new phenolic Schiff bases derivatives have been synthesized starting from Terephthaladehyde compound, all proposed structures were supported by FTIR, 1H-NMR, 13C-NMR, Elemental analysis, some derivatives evaluated by Thermal analysis (TGA).

This paper aims to study the chemical degradation of Brilliant Green in water via photo-Fenton (H2O2/Fe2+/UV) and Fenton (H2O2/Fe2+) reaction. Fe- B nano particles are applied as incrustation in the inner wall surface of reactor. The data form X- Ray diffraction (XRD) analysis that Fe- B nanocomposite catalyst consist mainly of SiO2 (quartz) and Fe2O3 (hematite) crystallites. B.G dye degradation is estimated to discover the catalytic action of Fe- B synthesized surface in the presence of UVC light and hydrogen peroxide. B.G dye solution with 10 ppm primary concentration is reduced by 99.9% under the later parameter 2ml H2O2, pH= 7, temperature =25°C within 10 min. It is clear that pH of the solution affects the photo- catalytic degradation

     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each M