The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

NA Nasir, SHM Ali, HQMA AL-Ess, WA Hussein, MKW Al-Janabi, KIA Mohammed, JM Mosa, Euromediterranean Biomedical Journal, 2020

A field study was conducted in Al-Khalis district, Diyala Governorate in 2019 to test the sensitivity of three varieties of pepper to the population density of the whitefly B. tabaci, Anaheim pepper, Aleppo and local variety, and the results showed that the Anaheim variety was the most infested with the whitefly density 4.08 whitefly/ leaf and then the local variety 2.7 whitefly/ leaf. The lowest population density was 1.25 whitefly/ leaf of Aleppo variety. Variety Aleppo also recorded the lowest percentage of whitefly infection B. tabaci of 39.22%, but not have significant differences in the percentage of whitefly infestation, as it reached 53.64% and 54.85% for the Anaheim and local varieties, respectively. The resistance of variety Alepp

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r

Two locally isolated microalgae (Chlorella vulgaris Bejerinck and Nitzschia palea (Kützing) W. Smith) were used in the current study to test their ability to production biodiesel through stimulated in different nitrogen concentration treatments (0, 2, 4, 8 gl ), and effect of nitrogen concentration on the quantity of primary product (carbohydrate, protein ), also the quantity and quality of lipid. The results revealed that starvation of nitrogen led to high lipid yielding, in C. vulgaris and N. palea the lipid content increased from 6.6% to 40% and 40% to 60% of dry weight (DW) respectively.Also in C. vulgaris, the highest carbohydrate was 23% of DW from zero nitrate medium and the highest protein was 50% of DW in the treatment 8gl. Whil

AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3

Objective: Pregnancy-induced hypertension (PIH) is a major pregnancy complication that leads to maternal mortality. Here, we have scrutinized the correlation between serum levels of hydrogen peroxide (H2O2) and superoxide dismutase (SOD) in PIH.Methods: Serum samples were collected from 80 Iraqi women (40 women with PIH as patients group, 20 normotensive pregnant women as a positive control, and 20 normotensive non-pregnant women as a negative control) all groups were diagnosed clinically.Results: Serum of H2O2 and SOD levels was measured for all studied groups. Results showed that there were no significant variances in age and gestational age distribution between all studied groups. Furthermore, result showed that the serum level o

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe