Abstract
Praise be to Allah, The Lord of the worlds, and peace be upon
Muhammad the master of former and latter people, and peace be upon His
relatives, companions and those who followed Him to Judgment day.
After recognizing the prescription which is called (Al- Fadhaly's Thesis in
parsing of "There is no god but God") as it is related with the word of the
investigation of this issue attracted me, as being related with the idea of the
only one God that is mentioned in the prophetic speech, which is said by
Anas- God satisfies him- Who said, Said the Messenger Muhammad peace
be upon him " Goes out of the Hell who said: there is no god but God, and in
his heart a hair weight of charity, and goes out of the He

The commercial job is one of the most important businesses in the cities as there is no city can exist without commercial markets to offer service to its inhabitants. This study aims to distribute the commercial function in Abu Tayara Street located in the municipality of Al-Dora by highlighting the size of such businesses in this street. It focuses on analyzing the change that has occurred due to the usages of the commercial land not only in the residential areas, but also in various aspects associated with the growth of the population in the city. Both expansion and development of the economic and social aspects in the area have increased the demand for commercial services. So, the research focuses on the aspects of functional speciali

The research presents the "theory of happiness according to Junaid al-Baghdadi" and the theory's most significant characteristics.

The reasons for happiness, include knowledge, love, and providence, and happiness itself is the return of man or spirit to the source from which it originated.

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

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar