It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the

Oil price forecasting has captured the attention of both researchers and academics because of the unique characteristics of crude oil prices and how they have a big impact on a lot of different parts of the economic value of the product. As a result, most academics use a lot of different ways to predict the future. On the other hand, researchers have a hard time because crude oil prices are very unpredictable and can be affected by many different things. This study uses support vector regression (SVR) with technical indicators as a feature to improve the prediction of the monthly West Texas Intermediate (WTI) price of crude oil. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) measur

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

Technological development in recent years leads to increase the access speed in the networks that allow a huge number of users watching videos online. Video streaming is one of the most popular applications in networking systems. Quality of Experience (QoE) measurement for transmitted video streaming may deal with data transmission problems such as packet loss and delay. This may affect video quality and leads to time consuming. We have developed an objective video quality measurement algorithm that uses different features, which affect video quality. The proposed algorithm has been estimated the subjective video quality with suitable accuracy. In this work, a video QoE estimation metric for video strea

   Neural stem cells (NSCs) are progenitor cells which have the ability to self‑renewal and potential for differentiating into neurons, oligodendrocytes, and astrocytes. The in vitro isolation, culturing, identification, cryopreservation were investigated to produce neural stem cells in culture as successful sources for further studies before using it for clinical trials. In this study, mouse bone marrow was the source of neural stem cells. The results of morphological study and immunocytochemistry of isolated cells showed that NSCs can be produced successfully and maintaining their self‑renewal and successfully forming neurosphere for multiple passages. The spheres preserved their morphology in culture and cryopreserved t

The main objective of this study is to experimentally investigate the effect of the CMC polymeric drag reducer on the pressure drop occurred along the annulus of the wellbore in drilling operation and investigate the optimum polymer concentration that give the minimum pressure drop. A flow loop was designed for this purpose consist from 14 m long with transparent test section and differential pressure transmitter that allows to sense and measure the pressure losses along the test section. The results from the experimental work show that increasing in polymer concentration help to reduce the pressure drop in annulus and the optimum polymer concentration with the maximum drag reducing is 0.8 kg/m³. Also increasing in flow rate a

Background: Venous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), presents an extra challenge in the management of patients with cancer, given the increase in morbidity and mortality in having both conditions. Cancer patients are well known to have a high risk of VTE; particularly; those who have had major surgery, chemotherapy and/or hormonal therapy. These groups of patients need to understand the risk factors and the prophylactic measures to prevent developing VTE. This review aims to provide an overview of the literature on cancer patients’ understanding of VTE and their experiences of cancer-associated thrombosis (CAT).

Method: A scoping review wa