In the name of of Allah the Merciful

Introduction:

Praise be to Allah, Lord of the Worlds, and prayers and peace be upon our master Muhammad and his family and companions.

After

I have looked at a part of the jurisprudence of Hajj jurisprudence, which is needed now, especially after it facilitated travel to perform Hajj and Umrah, so the need was an advocate and a list for writing in it, which is beneficial to Hajj, Umrah and the guide.

And this important part is the things that contravene the woman's man in the Hajj and after the search and tracking found that there are ten things that get the violati

The Audit evedances represent the reconciliation tools between the Financial data shown on financial statements, and the level of satisfaction level of the Auditor about these statements. According that, the Auditor try to achieve the highest quantity of These evidances, and the most satisfactive of it…, but that will be so hard sometimes, when the internal controlling system is not good, and when the Auditor had some satisfied evidences, but not sharp… So, this research comes to inspect the relation between the quantity, and the level of satisfaction, and argument to prove that evidences gives. This research assumes that getting enough evidences leads to reduce faults, improves the auditing operation, and avoids risks. The research

Understanding, promoting, and teaching media literacy is an important societal challenge. STEM educators are increasingly looking to incorporate 21st century skills such as media literacy into core subject education. In this paper we investigate how undergraduate Computer Science (CS) students can learn media literacy as a by-product of collaborative video tutorial production. The paper presents a study of 34 third-year CS undergraduates who, as part of their learning, were each asked to produce three video tutorials on Raspberry Pi programming, using a collaborative video production tool for mobile phones (Bootlegger). We provide results of both quantitative and qualitative analysis of the production process and resulting video tutorials,

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

Abstract

The research aims to demonstrate the commitment of the Federal Financial Supervisory Bureau to meet the requirements of the International Organization of Supreme Audit Institutions (INTOSAI) 3000, the general and private supervision of performance as the highest supervisory authority in Iraq, which is the only authorized to carry out the process of monitoring the performance of government work and activities. To analyze and present the results of the survey questionnaire prepared for the compliance of the Bureau with the requirements of the general and specific criteria related to the performance control process. The researcher reached a number of conclusions, the most important of which is the commitment of the

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

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