We have presented the distribution of the exponentiated expanded power function (EEPF) with four parameters, where this distribution was created by the exponentiated expanded method created by the scientist Gupta to expand the exponential distribution by adding a new shape parameter to the cumulative function of the distribution, resulting in a new distribution, and this method is characterized by obtaining a distribution that belongs for the exponential family. We also obtained a function of survival rate and failure rate for this distribution, where some mathematical properties were derived, then we used the method of maximum likelihood (ML) and method least squares developed  (LSD)

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

The current research tackles the self-efficacy and its relation to the cognitive assessment for the daily disturbances for the University of Baghdad students. Two criteria have been adopted to achieve the objectives of the research. The sample of this study consists of 200 male and female students who were chosen randomly. The data were analyzed statistically, revealing that the university students owned their own self-efficacy as well as a cognitive assessment for the daily disturbances and they recognized them as self-threatening. The results also indicated the existence of a prediction activity in the field of the cognitive assessment to the daily disturbances selection. In light of the acquired results, the study recommends the neces

Radiotherapy is the branch of clinical medicine concerned with the application of ionizing radiation in the treatment of disease. And it is used to killing of cancer cells in a tissue using ionizing radiation while keeping the sparing of healthy cells at acceptable level. X-ray beams are used to deposit absorbed dose at depth within a patient at the site of the tumor. The aim of this work is studying the relationship between the depth dose and the field size in water phantom and homogenous actual planning. In our work, the dose distribution at different depths (zero-18 cm) deep at1cm interval treated with field size (10×10 and 20×20) cm2 were studied.
Results show that high similarity between water phantom and actual planning for th

Radiotherapy is the branch of clinical medicine concerned with the application of ionizing radiation in the treatment of disease. And it is used to killing of cancer cells in a tissue using ionizing radiation while keeping the sparing of healthy cells at acceptable level. X-ray beams are used to deposit absorbed dose at depth within a patient at the site of the tumor. The aim of this work is studying the relationship between the depth dose and the field size in water phantom and homogenous actual planning. In our work, the dose distribution at different depths (zero-18 cm) deep at1cm interval treated with field size (10×10 and 20×20) cm2 were studied. Results show that high similarity between water phantom and actual planning for

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

The inhibitive action of Reactive Red (RR31) dye against corrosion of carbon steel in 1M acetic acid solution has been studied using gravimetric method at temperature ranged (288-318)K. The antibacterial activity for the different concentrations of RR31 dye against different bacterial species was studied. The experimental data indicates that this dye acts as a potential inhibitor for carbon-steel in acetic acid medium and the protection efficiency increase with increasing (RR31) dye. The adsorption of (RR31) dye on the carbon steel surface was found to follow Langmuir adsorption isotherm. Thermodynamic data for the adsorption process such as Gibbs free energy change ∆Gads, enthalpy change ∆Hads, and entropy change ∆Sads were estima

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,