Objectives: The study aimed to clarify the role of Al-Sayyid Al-Ajall and his family in the service of the Mongol Empire. They worked to develop its administrative and military institutions, benefiting from their extensive experience in administration, politics, economics, and urban affairs. Due to their capabilities, they received the patronage of Genghis Khan and subsequent generations, earning the confidence of the ruling Mongol authority. As a result, they were granted significant powers within the state.       Methods: The study relied on the analytical method to analyze historical texts, compare them with others, and discuss them accurately. Results: The study yielded several results, including the minister's keen interes

سها علي حسين, هويدة إسماعيل إبراهيم, Journal of Physical Education, 2017 - Cited by 1

This paper depends on sheding some litgt on the characteristics of political
relations between the arab and the Persian during the reign of sassane kings.
"Ardashir the first, shahbour the first, shahbour the second, Bahram the fifth; kisra
Anushrwan and kisrah abruis"
And who rulled the Persian before the Islamic conquest and were adopted in this studym
as a model. It was possible to get some information from invaluable refereces in order to
arrive at a clear image as regards the nature of these relations. These relations were
differently political according to the circumstances of ruling, interests and the personality
of those kings.

Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

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

Abstract The goal of current study was to identify the relationship between addiction of self-images (Selfie) and personality disorder of narcissus, and the difference of significance the relationship between addiction self-images (selfie) and personality disorder narcissus at students of Mustansiriya university, addiction self- images (selfie) defined: a photograph that one has taken of oneself, typically one taken with a smartphone or webcam and shared via social media, edit and down lowed to social networking sites, and over time, the replacement of normal life virtual world, which is accompanied by a lack of a sense of time, and the formation of repeated patterns increase the risk of social and personal problems. To achieve the goals

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it