The current research aims at testing the relationship between organizational immunity and preventing administrative and financial corruption (AFC) in Iraq. The Statistical Package for the Social Sciences program (R& SPSS) was used to analyse the associated questionnaire data. The research problem has examined how to activate the functions of the organizational immune system to enable it to face organizational risks, attempt to prevent administrative and financial corruption, and access the mechanisms by which to develop organizational immunity. A sample of 161 individuals was taken who worked in the Directorate General of Education, Karbala. Also, it was concluded to a lack of memory function for organizational immunity. In a

Cr2O3 thin films have been prepared by spray pyrolysis on a glass substrate. Absorbance and transmittance spectra were recorded in the wavelength range (300-900) nm before and after annealing. The effects of annealing temperature on absorption coefficient, refractive index, extinction coefficient, real and imaginary parts of dielectric constant and optical conductivity were expected. It was found that all these parameters increase as the annealing temperature increased to 550°C.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Background: The incidence of maternal mortality in
placenta previa accrete is 7%,and its preoperative
diagnosis is of a great value.
Objective: to evaluate the efficacy of transabdominal
color Doppler ultrasound in diagnosing placenta
previa accreta and inccreta. Color Doppler imaging
criteria used in: includes diffuse parenchymal
placental lacunar flow, focal intra parenchymal
placental lacunar flow and bladder uterine serosa
interphase hyper-vascularity.
Design: Prospective study on patients from
January2007 to January 2008.
Patients and method: 48patients with one caesarean
section or more and with persistent anterior placenta
previa diagnosed by transabdominal ultrasound were
examined by c

In this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different informative prior distributions represented by erlang and inverse levy prior distributions and non-informative prior for the shape parameter of Poisson distribution. The maximum likelihood estimator (MLE) of the Poisson distribution has also been derived. A simulation study has been fulfilled to compare the accuracy of the Bayes estimates with the corresponding maximum likelihood estimate (MLE) of the Poisson distribution based on the root mean squared error (RMSE) for different cases of the