Background: Computerized tomography scan can show the detailed anatomy of the nose and paranasal sinuses. The sphenoid sinus is a very important corridor for the skull base because of its central position. This sinus has a great range of variation and can put structures around at risk during surgery. This study aims to examine the variation of the sphenoid sinus, and its relation to other structures around it, in this sample of Iraqi patients. Materials and Methods: CT scans of 122 patients, were obtained, and submitted for examination and measurements, during the period between September 2020 and September 2021. Observation of The sphenoid sinus pneumatization pattern, clival extension, Onodi cell, and lateral pneumatization of SS.

Background: Tooth wear is one of the most concerning problems of the current dental practice especially among older subjects. The aim of this study is to determine the severity of tooth wear and its relation with selected salivary variables (salivary pH and vitamin C level) among a group of older adults in Mosul city/Iraq. Materials and methods: All subjects (30 subjects) of both gender tookpart in the current study; sixteen of them were older adults (55-65 years) and compared with fourteen middle-aged adults (30-40 years) at Textile factory in Mosul city/Iraq. Unstimulated salivary samples were collected and salivary pH was immediately measured. Salivary vitamin C level was determined colormetrically. Severity of tooth wear was determined

Utilizing phase change materials in thermal energy storage systems is commonly considered as an alternative solution for the effective use of energy. This study presents numerical simulations of the charging process for a multitube latent heat thermal energy storage system. A thermal energy storage model, consisting of five tubes of heat transfer fluids, was investigated using Rubitherm phase change material (RT35) as the. The locations of the tubes were optimized by applying the Taguchi method. The thermal behavior of the unit was evaluated by considering the liquid fraction graphs, streamlines, and isotherm contours. The numerical model was first verified compared with existed experimental data from the literature. The outcomes re

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

Simulation of free convection heat transfer in a square enclosure induced by heated thin plate is represented numerically. All  the enclosure walls have constant temperature lower than the plate’s temperature. The flow is assumed to be two-dimensional. The discretized equations were solved stream function, vorticity, and energy equations by finite difference method using explicit technique and Successive Over- Relaxation method. The study was performed for different values of Rayleigh number ranging from 10³ to 10⁵ for different angle position of heated thin plate(0°, 45°, 90°). Air was chosen as a working fluid (Pr = 0.71). Aspect ratio of center of plate to the parallel left wall A₂

Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

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%.