Background. Najaf governorate was recorded as one of the most polluted Iraqi governorates with increased cancer, autoimmune, and abortion cases. Study Groups. A total of 88 adult volunteers from three test groups were divided based on their inhabitance in different geographical regions in Najaf governorate. Group 1 (G1; n, 29) inhabitants of Al‐Ansar, Al‐Abbaseyeh, and Al‐Manathera districts, Group 2 (G2; n, 27) inhabitants of 22 different scattered districts of the governorate, Group 3 (G3; n, 32) inhabitants of Kufa city and center districts in the old Najaf city. According to previous author

Background: One of the most predominant periodontal diseases is the plaque induced gingivitis. For the past 20 years, super-oxidized solutions have be..

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines