The aim of this research work is to study the effect of stabilizing gypseous soil, which covers
vast areas in the middle, west and south parts of Iraq, using liquid asphalt on its strength properties
to be used as a base course layer replacing the traditional materials of coarse aggregate and broken
stones which are scarce at economical prices and hauling distances.
Gypseous soil brought from Al-Ramadi City, west of Iraq, with gypsum content of 66.65%,
medium curing cutback asphalt (MC-30), and hydrated lime are used in this study.
The conducted tests on untreated and treated gypseous soil with different percentages of medium
curing cutback asphalt (MC-30), water, and lime were: unconfined compression strength, and o

FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

This paper was aimed to study the efficiency of forward osmosis (FO) process as a new application for the treatment of wastewater from textile effluent and the factors affecting the performance of forward osmosis process.
The draw solutions used were magnesium chloride (MgCl2), and aluminum sulphate (Al2 ( SO4)3 .18 H2O), and the feed solutions used were reactive red, and disperse blue dyes.
Experimental work were includes operating the forward osmosis process using thin film composite (TFC) membrane as flat sheet for different draw solutions and feed solutions. The operating parameters studied were : draw solutions concentration (10 – 90 g/l), feed solutions concentration (5 – 30 mg/l), draw solutions flow rate (10 – 50 l/hr

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable

Background: This study was conducted to evaluate the hard palate bone density and thickness during 3rd and 4th decades and their relationships with body mass index (BMI) and compositions, to allow more accurate mini-implant placement. Materials and method: Computed tomographic (CT) images were obtained for 60 patients (30 males and 30 females) with age range 20-39 years. The hard palate bone density and thickness were measured at 20 sites at the intersection of five anterioposterior and four mediolateral reference lines with 6 and 3 mm intervals from incisive foramen and mid-palatal suture respectively. Diagnostic scale operates according to the bioelectric impedance analysis principle was used to measure body weight; percentages of body fa