This study aimed to identify the role of servant leadership in promoting organizational citizenship behaviors in a sample of faculties of the University of Alqadisiya .It tried to answer several questions represented its problem.

 The most important questions are the followings:

1- Is there enough perception among administrative leaders in the aforementioned faculties toward the concept of servant leadership? And under what level?                                    &

A novel ligand, (E)-5-((2-hydroxy-4,6-dimethylphenyl)diazenyl)-2,3-dihydrophthalazine-1,4- dione, was synthesized through the reaction of 3,5-dimethylphenol with the diazonium salt of 5-amino-2,3-dihydrophthalazine-1,4-dione. The ligand underwent characterization through the utilization of diverse spectroscopic methods, including UV-Vis, FT-IR, 13C, and 1H-NMR, alongside Mass spectroscopy and micro elemental analysis (Carbon, Hydrogen, Nitrogen, and Oxygen). Metal chelates of transition metals were prepared and analyzed using elemental analysis, mass spectra, atomic absorption, UV-Vis, FT-IR spectral analysis, as well as conductivity and magnetic measurements. The investigation into the compounds’ nature was conducted by utilizing mole r

         International companies are striving to reduce their costs and increase their profits, and these trends have produced many methods and techniques to achieve these goals. these methods is heuristic and the other Optimization.. The research includes an attempt to adapt some of these techniques in the Iraqi companies, and these techniques are to determine the optimal lot size using the algorithms Wagner-Whitin under the theory of constraints. The research adopted the case study methodology to objectively identify the problem of research, namely determining lot size optimal for each of the products of electronic measurement laboratory in Diyala and in light of the bottlenecks in w

The current study aimed at (identifying the impact of a proposed strategy based on the realistic mathematics theory in the mathematical interrelation among the third intermediate grade students), two samples from the third intermediate grade were tested in a school affiliated to Rusafa I General education Directorate in Baghdad for the academic year (2022-2021)the experimental group will study according to the proposed strategy and it consisted of (30) female students , the control group will study through the traditional method and the number of its students is (30), thus the study sample consisted of (60) female students, the two groups were equalized in the variables (age in months, intelligence, prior knowledge) and to achieve the study

In this work, a deep computational study has been conducted to assign several qualities for the graph ⁠. Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

synthesis, Composition, Spectral, Geometry and Antibacterial Applications ofMn(||),Ni(||),Co(||),Cu(||) and Hg(||) schiff Base complexes of N2O2 mixed donor with 1,10-phenanthroline