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

 Polymer composite materials were prepared by mixing epoxy resin with sand particles in three different grain size (150-300 ), (300-600 ) and (600- 1200) μm . The weight of epoxy was 15%, 20%, 25% and 30% of the total weight. Compression  strength and flexural strength tests were carried out for the prepared samples .The percentages of epoxy resin at 20% wt and 25% wt showed best mechanical properties for all grain sizes .These percentages were adopted to fill the void between particles sand which have two different size ranges (150-600) μm and {(150-300) & (600-1200)} μm respectively to obtain more dense material. The results showed that the strength of polymer composite at 20% resin is higher than 25% resin. The

One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues

Many diseases can produce cardiac overload, of these disease hypertension, valve disease congenital anomaly in addition to many other disease. One of the most common diseases causing left ventricle overload is hypertension. A long term hypertension can cause myocardium hypertrophy leading to changes in the cardiac contractility and reduced efficiency. The investigations were carried out using conventional echocardiography techniques in addition to the tissue Doppler imaging (TDI) from which many noninvasive measurements can be readily obtained. The study has involved the effect of hypertension on the myocardium stiffness index through the measurement of early diastolic filling (E) and the early velocity of lateral mitral annulus (E

Many diseases can produce cardiac overload, of these disease hypertension, valve disease congenital anomaly in addition to many other disease. One of the most common diseases causing left ventricle overload is hypertension. A long term hypertension can cause myocardium hypertrophy leading to changes in the cardiac contractility and reduced efficiency. The investigations were carried out using conventional echocardiography techniques in addition to the tissue Doppler imaging (TDI) from which many noninvasive measurements can be readily obtained. The study has involved the effect of hypertension on the myocardium stiffness index through the measurement of early diastolic filling (E) and the early velocity of lateral mitral annulus (E_a

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

Background: The problem of difficult gallbladder is not clearly defined and associated with real missing of therapeutic approaches that decreased morbidity. Moreover, the difficult gallbladder was reported as a contributing risk factor for biliary injury due to raised difficulty in surgical dissection within Calot’s triangle. The aim of this study is to determine the surgical outcomes of the open fundus-first cholecystectomy in lowering the rate of lethal intraoperative risks.

Subjects and Methods: Our prospective study conducted during the period of January 2019 to December 2022 at Ibn Sina specialized hospital, Khartoum, Sudan, for two hundred and fifty-three patients underw