The current study aims to identify the artistic expression as well as the aspects of artistic expression by the painting among the kindergarten children. In order to fulfill the research's goals, a sample of (400) children were chosen randomly from 19 public kindergartens of 6 directorates at Al-Rusafa and Al-Karkh in Baghdad city. The children were asked to draw a particular view. The researcher  has adopted  Al-Hamedawi scale  (2009) consisted of  (16) items, which was exposed to group of (25) experts in  psychology, education,  measurement and evaluation,  artistic  education by painting  and plastics  to show  the items reliability. As the researcher applied T-test  for&nbsp

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr

Objective(s): To determine the impact of instructional intervention program upon psychological health status for
women who undergo chemotherapy after mastectomy
Methodology: The sample consisted of (100) women, (50) considered as study group, and another (50) the control
group. A pre test was done for both groups (study and control), and then the study samples were exposed to an
instructional intervention and three-dimensional post tests and the length of time between each test 21 days in
the Institute and Hospital of Radiation and Nuclear Medicine. The questionnaire composed of three parts, first,
demographic information; include (age, educational level, type of family, occupation, marital status, and adequacy
of mo

This study aimed to detect Anaplasma phagocytophilum in horses through hematological and molecular tests. The 16S rRNA gene of the Anaplasma phagocytophilum parasite was amplified by polymerase chain reaction (PCR), then sequenced, and subjected to phylogenetic analysis to explore "Equine Granulocytic Anaplasmosis" (EGA) infection in three important gathering race horses areas in Baghdad governorate, Iraq. Blood samples were obtained from 160 horses of varying ages, three breeds, and both sexes, between January and December 2021. Prevalence and risk variables for anaplasmosis were analyzed using statistical odds ratio and chi-square tests. Results demonstrated that clinical anaplasmosis symptoms comprised jaundice, wei

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

Infectious diseases pose a global challenge, necessitating an exploration of novel methodologies for diagnostics and treatments. Since the onset of the most recent pandemic, COVID-19, which was initially identified as a worldwide health crisis, numerous countries experienced profound disruptions in their healthcare systems. To combat the spread of the COVID-19 pandemic, governments across the globe have mobilized significant efforts and resources to develop treatments and vaccines. Researchers have put forth a multitude of approaches for COVID-19 detection, treatment protocols, and vaccine development, including groundbreaking mRNA technology, among others.

This matter represents not only a scientific endeavor but also an essenti

In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when