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

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

CR-39 is a solid state nuclear track detector (SSNTD) that has been used in many research areas. In spite of the assumption that the CR-39 detectors are insensitive to beta and gamma rays, irradiation with these rays can have significant effects on the detector properties. In this study, beta and gamma rays mass attenuation coefficients μ/ρ (cm2 g-1) for the CR-39 detector have been measured using NaI(Tl) scintillation spectrometer along with a standard geometrical arrangement in the energy region of (0.546-2.274) MeV beta rays and standard gamma sources having energy 0.356, 0.5697, 0.6617 and 1.063 MeV. The total atomic cross-section (σtot), total electronic cross-section (σT E) and the effective atomic number (Zeff) of gamma rays a

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

Lorraine Hansberry’s A Raisin in the Sun (1959) appeared at the beginning of renewed political activity on the part of the blacks; it is a pamphlet about the dream of recognition of black people and the confusion of purposes and means to reach such recognition. It embodies ideas that have been uncommon on the Broadway stage in any period. Situations such as a black family moving into an all-white neighborhood were not familiar before this time; they were just beginning to emerge. In depicting this so realistically, Hansberry depends more on her personal experience as an African American embittered by social prejudices and discrimination. 

This study deals with the grammatical processing ability of English Subordinate Clauses which can account for variance in word recognition and production skills. The study aims at: A) Assessing whether the students can recognize correct usage and comprehension of different types of Subordinate Clauses English grammar sentences by using appropriate word. B) Showing if the students can produce the correct type of Subordinate Clauses that should be used in English grammar sentences. To achieve these aims, a test has been conducted and distributed on 50 students at third stage at the College of Education (Ibn-Rushd) for the academic year 2012-2013. A test is exposed to a jury of experts for the purpose of ascertaining their validity. The spli

Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M