The current research was aimed at the following:
1. Measurement of Personality Type Observer of the University students.
2. Identify the differences in Personality Type Observer among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary)
3. Measurement of Withdrawal of the University students.
4. Identify the differences in Withdrawal among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary).
5. Identify the relationship between Personality Type Observer and Withdrawal.
To achieve this aims of the research, the researchers set up the instrument is scale

BACKGROUND: Preeclampsia (PE) is a possible etiology of obstetrical and neonatal complications which are increased in resource-limited settings and developing countries. AIM: We aimed to find out the prevalence of PE in Iraqi ladies and specific outcomes, including gestational weight gain (GWG), cesarean section (CS), preterm delivery (PD), and low birth weight (LBW). METHODS: All singleton pregnant women visiting our tertiary center for delivery were involved over 3 years. PE women were compared with non-PE ladies. Complete history and examination were done during pregnancy and after delivery by the attending obstetrician and neonatologist with full documentation in medical records. RESULTS: PE prevalence was 4.79

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Recent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and p

The research problem is represented in the weakness of reliance on the role of some motor abilities (flexibility, balance and compatibility) in biomechanical indicators and the performance of a large number of gymnastics skills, including the skill of the human wheel, in addition to the lack of reliance on the use of video imaging of the skill in order to analyze its path and identify its weaknesses. The research aimed to identify the relationship between motor abilities, biomechanical indicators and the degree of performance of the skill of the human wheel, and the descriptive method was used on its own, chosen in an intentional method, consisting of (10) students from the third stage in the Department of Physical Education and Sp