Experienced organizations in recent years, significant challenges , especially with the spread of economic globalization, making it required to provide new and better through experience , creativity and innovation to achieve the quality and high-quality products of all kinds , in order to achieve the objectives of the study and to answer its questions tested the study in the woolen Industries sector in Baghdad . The study was applied to a sample of 30 people in the senior management and the middle and lower in the company (managers of sections  , and  managers of people , and managers of the units , and office managers ) and for the processing of data and information used several statistical methods and extracted result

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

The paper is devoted to solve nth order linear delay integro-differential equations of convolution type (DIDE's-CT) using collocation method with the aid of B-spline functions. A new algorithm with the aid of Matlab language is derived to treat numerically three types (retarded, neutral and mixed) of nth order linear DIDE's-CT using B-spline functions and Weddle rule for calculating the required integrals for these equations. Comparison between approximated and exact results has been given in test examples with suitable graphing for every example for solving three types of linear DIDE's-CT of different orders for conciliated the accuracy of the results of the proposed method.

Diabetes mellitus is a metabolic disorder categorized hyperglycemia resulting from defects in insulin secretion, insulin action or both. Protein tyrosine kinase (PTK) is an enzyme that catalyzes the transfer of phosphate groups from ATP to the tyrosine residues of many important proteins resulting in proteins phosphorylation. The aim of current study was to evaluate serum levels of protein tyrosine kinase enzyme and thyroid hormone (T3, T4and TSH) and to find the correlation between them in type 2 diabetes mellitus and diabetic nephropathy Iraqi patients. Methods: This study was conducted at The National Diabetes Center, Al-Mustansiriya University, Baghdad, Iraq and included 150 patients divided into three groups the first group included 50

Background: The immunogenetic predisposition
may be considered as an important factor for the
development of Type 1 Diabetes Mellitus (T1DM)
in association with the HLA antigens.
Objective:This study was designed to investigate
the role of HLA-class II antigens in the etiology of
type T1DM and in prediction of this disease in
siblings, and its effect on expression of glutamic
acid decarboxylase autoantibodies (GADA).
methods:Sixty children who were newly diagnosed
type 1 diabetes (diagnosed less than five months)
were selected. Their age ranged from 3-17 years.
Another 50 healthy siblings were available for this
study, their ages range from 3-16 years. Eighty
apparently healthy control subjects,

In the present study, magnet silica-coated Ag2WO4/Ag2S nanocomposites (FOSOAWAS) were fabricated via a multistep method to address the drawbacks related to single photocatalysts (pure Ag2WO4 and pure Ag2S) and to clarify the significant influence of semiconductor heterojunction on the enhancement of visible-light-driven organic degradation. Different techniques were performed to investigate the elemental composition, morphology, magnetic and photoelectrochemical properties of the fabricated FOSOAWAS photocatalyst. The FOSOAWAS photocatalyst (1 g/L) exhibited excellent photodegradation efficiency (99.5%) against Congo red dye (CR = 20 ppm) after 140 min of visible-light illumination. This result confirmed the ability of the heterojunction be