The purpose of the current research is to identify the reality and applicability of the entrepreneurial approach in its dimensions (creative, proactive, independent, risk tolerant, offensive) and its impact on the success factors of the project (organizational commitment, communication, project team, project monitoring) Access to information, treatment, storage), which is a significant and important link in the success and development of industrial projects with the possibility of studying and analyzing the provision of the appropriate environment for this.

 the research started from a problem expressed by a number of intellectual and practical questions aimed at answering them as well as To answer a

DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio

Objectives: the study aims to assess nurses' practices toward chemotherapy-induced peripheral neuropathy (CIPN) for children at the hematology center, and to determine the effectiveness of the health education program on nurses' practices toward CIPN, and to find out the relationships between the effectiveness of Health education program and demographic characteristics of nurses.

Methodology: Use quasi-experimental design in the study (a design that divides the sample into two groups, a study group and a control group, with data collection in three stages). This study was conducted at a hematology center in Baghdad city for the period (from December 16^th, 2019 to 8^th May 202

The research aims to verify the role of the Human Resources Strategic Management (HRSM) in enhancing the strategic success factors for talent (SSFT) in the General Tourism Authority by distributing a questionnaire consisting of (36) paragraphs on an intentional sample represented by the higher departments as it reached (50) and the sample valid for testing was (44) Person and to test the relationships between the two research variables, the researchers used statistical methods represented by (Bartlett test / mean / simple regression coefficient / difference coefficient, alpha- cronbachAch, confirmatory factor Analysis ) through the statistical program (SPSS v.23 & AMOS v.23). In enhancing the factors of success for talent management in the

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial