Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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

Classical cryptography systems exhibit major vulnerabilities because of the rapid development of quan tum computing algorithms and devices. These vulnerabilities were mitigated utilizing quantum key distribution (QKD), which is based on a quantum no-cloning algorithm that assures the safe generation and transmission of the encryption keys. A quantum computing platform, named Qiskit, was utilized by many recent researchers to analyze the security of several QKD protocols, such as BB84 and B92. In this paper, we demonstrate the simulation and implementation of a modified multistage QKD protocol by Qiskit. The simulation and implementation studies were based on the “local_qasm” simulator and the “FakeVigo” backend, respectively. T

Background: Oil refinery workers are continuously exposed to numerous hazardous materials. Petroleum contains the heavy metals as a natural constituent or as additives. These metals induce the production of ROS which associated with an oxidative damage to DNA, proteins, and lipids. This study was conducted to assess the salivary levels of heavy metals, salivary oxidative status, oral immunological activity (salivary sIgA) and assessment of the oral findings among the workers of Al-Daura oil refinery in Baghdad city. Subjects, Materials and Methods: This study was done in Al-Daura oil refinery; samples consist of 60 workers involved in refinery processes (study group) and 20 non-workers (control group). Oral examination and saliva collection

Abstract                                                         

The issue of the protection of the environment is a shared responsibility between several destinations and sectors, and constitutes a main subject in which they can achieve sustainable development. In the sectors of government programs can be set up towards the establishment of the government sector to the green environment, so to be the implementati

The present paper focuses on the nature of the different interactions between cometary nucleus and tail with solar wind. The dynamics of the comet will impose many features that provide unique behavior of the comet when entering the solar system. These features are reviewed in this paper and few investigations are made. The calculations made in this work represent the analysis and interpretation of the different features of the comet, such as perihelion and eccentricity dependence on the gas production rate, and the dependence of the latter on the composition of the comet nucleus. The dependences of the heliocentric, bow shock, contact surface, and stand-off distances with gas production rate for many types of comets that cover linear and n

The chronic renal disease is a principle common medical dilemma in Iraq. Peripheral arterial disease (PAD) is a prevalent infirmity in the hemodialysis people. The aim of present study was to estimate the prevalence of PAD in subjects with end-stage renal disease (ESRD). This cross-sectional study was done between January 2016 and May 2017 on ESRD subjects regularly attending renal dialysis unit in Al-Kindy teaching hospital in Baghdad, Iraq. PAD was diagnosed on the base of the ankle-brachial index (ABI) measured by using a hand-held Doppler ultrasound. Subjects with ABI ≤0.9 were supposed positive for PAD. A total of 150 ESRD cases were analyzed. The mean age of the subject was 49.52±15 years. Majority of them were males 87(58%). Most

The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut