The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

Background: Celiac disease is an autoimmune chronic disease that affects the human’s intestine and subsequently reflects its effect on the entire body health by retardation the absorption and immune mediated complications cause the involvement of oral health. The present study intended to evaluate the impact of the histopathological disease activity upon dental enamel defects and dental caries.

Subjects and methods: Forty celiac-diseased patients aged 7-11 years were collected from 3 different teaching hospitals in Baghdad classified by means of the histopathological activity of the intestinal disease according to modified Marsh-Ros

    The main goal of this research is to determine the impact of some variables that we believe that they are important to cause renal failuredisease by using logistic regression approach.The study includes eight explanatory variables and the response variable represented by (Infected,uninfected).The statistical program SPSS is used to proform the required calculations

An eco-epidemiological system incorporating a vertically transmitted infectious disease is proposed and investigated. Micheal-Mentence type of harvesting is utilized to study the harvesting effort imposed on the predator. All the properties of the solution of the system are discussed. The dynamical behaviour of the system, involving local stability, global stability, and local bifurcation, is investigated. The work is finalized with the numerical simulation to observe the global behaviour of the solution.

In the current study, remote sensing techniques and geographic information systems were used to detect changes in land use / land cover (LULC) in the city of Al Hillah, central Iraq for the period from 1990 - 2022. Landsat 5 TM and Landsat 8 OLI visualizations, correction and georeferencing of satellite visuals were used. And then make the necessary classifications to show the changes in LULC in the city of Al Hillah. Through the study, the results showed that there is a clear expansion in the urban area from 20.5 km2 in 1990 to about 57 km2 in 2022. On the other hand, the results showed that there is a slight increase in agricultural areas and water. While the arid (empty) area decreased from 168.7 km 2 to 122 km 2 in 2022. Long-term ur

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Delays and disruption are a common issue in both community and personal building programs The problem exists all throughout the world, but it is particularly prevalent in Iraq, where millions of dollars are squandered each time as a outcome. Delays and interruptions may have serious consequences not just for Iraq's construction plans, but also for the country's economic and social status. While numerous studies have been conducted to investigate the factors driving delays and disruption in Iraqi construction projects, slight consideration has been given to by what means project management implements and approaches have affected the occurrence of project delays and disruption. After analyzing the crucial reasons for delays and instability in

     The aim of the study is the measuring of changes in the spectral reflectivity water quality, analyzing the seasonal difference of Tigris River within Mosul City in the north of Iraq using Geographic Information Systems (GIS) and remote sensing techniques during the period (2014-2018). For this paper, Satellite images of the 8 Landsat in 2018 for four seasons have been selected in order to study the seasonal changes on the river they took place during 2018.  A total of ten sample datasets were taken at the upstream, midstream and downstream along the Tigris River. This research focuses on analyzing the locational variance of reflectance, analyzing seasonal difference, and finding modeling algal amount change.

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS