The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Background: Numerous epidemiological studies were conducted in Iraq, concerning dental caries and related etiological factors however; most of these studies were concerned with pre-and primary school children and/or those at index ages (12-15years old). At the time studies regarding older ages are very limited. This study was done to determine the prevalence and severity of dental caries and treatment need among high schools girls (16-18 years old) in Al-Mussayb city, Babylon Governorate. Thus, it can be considered as a base line data that allows studying dental caries among permanent dentition, also allows the comparison with other studies in other parts of the world. Material and Method: A total number of 900 high school girls were examin

In Baghdad city, Iraq, the traffic volumes have rapidly grown during the last 15 years. Road networks need to reevaluate and decide if they are operating properly or not regarding the increase in the number of vehicles. Al-Jadriyah intersection (a four-leg signalized intersection) and Kamal Junblat Square (a multi-lane roundabout), which are two important intersections in Baghdad city with high traffic volumes, were selected to be reevaluated by the SIDRA package in this research. Traffic volume and vehicle movement data were abstracted from videotapes by the Smart Traffic Analyzer (STA) Software. The performance measures include delay and LOS. The analysis results by SIDRA Intersection 8.0.1 show that the performance of the roundab

Collapsing building structures during recent earthquakes, especially in Northern and Eastern Kurdistan, including the 2003 earthquake in Cewlig; the 2011 earthquake in Van; and the 2017 earthquake near Halabja province, has raised several concerns about the safety of pre-seismic code buildings and emergency facilities in Erbil city. The seismic vulnerability assessment of the hospital buildings as emergency facilities is one of the necessities which have a critical role in the recovery period following earthquakes. This research aims to study in detail and to extend the present knowledge about the seismic vulnerability of the Rizgary public hospital building in Erbil city, which was constructed before releasing the seism

   The Agricultural Policy is one of the most important tools adopted by the state to guide its economic and social activities through the delivery of suitable agricultural commodities to the consumer and in return to deliver agricultural inputs to the agricultural producers at the lowest possible cost to contribute in achieving a profit that helps the agricultural product to continue in the production process with the same efficiency and ambition. So as to help increase the contribution of the agricultural sector to GDP and achieve the best picture of sustainable agricultural development.

The research aimed at identifying the reality of agricultural policies and their role in achieving sustaina

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining