With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusion Detection System (IDS). Success is measured by a variety of metrics, including accuracy, precision, recall, F1-Score, and execution time. Applying feature selection approaches such as Analysis of Variance (ANOVA), Mutual Information (MI), and Chi-Square (Ch-2) reduced execution time, increased detection efficiency and accuracy, and boosted overall performance. All classifiers achieve the greatest performance with 99.99% accuracy and the shortest computation time of 0.0089 seconds while using ANOVA with 10% of features.
Scientists were interested in the statement of the concept of companions and the definition of the companion in terms of his status or his novel or inherent to the Prophet of Allah (peace be upon him) and was for those who did not walk in the translations and the abundant share in this work, and among these scientists Hafiz Shams al-Din al-Dhahabi, which was translated to the companions His books, indicating their status and effort, and who had a novel of them - what we will see in the folds of the research, God willing -
The research was titled: Approval of the Imam of the Nuclear of Iraqis through the curriculum of the students.
The research revolves around the study of the weight of the imam nuclear jurisprudence in which the views of the Iraqi jurists of the Imam Shafi'i agreed through the book of students' approach to the nuclear imam, the research included a brief translation of the nuclear imam, and the definition of his place in the Shafi'i school, and then the definition of Iraqi jurists and then study the jurisprudence The course of research is only three issues, and compared with the views of imams, and the statement of the most correct opinion, and God and the conciliator.
researcher
This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.
This paper deals with the thirteenth order differential equations linear and nonlinear in boundary value problems by using the Modified Adomian Decomposition Method (MADM), the analytical results of the equations have been obtained in terms of convergent series with easily computable components. Two numerical examples results show that this method is a promising and powerful tool for solving this problems.
Economic intelligence represents a modern field of knowledge that has been and is still the focus of many studies and research, including this research that deals with economic intelligence and its role in strengthening Iraqi national security - an analytical study. Economic development and economic development without security, and in a situation such as that of Iraq, which is still suffering from conflicts, conflicts and the effects of wars, as well as the unstable conditions in its regional environment, the directions of that relationship cannot be determined except through the availability of accurate information, indicators, full knowledge of reality and the pos
... Show MoreThis paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi
... Show MoreA flight simulation programme has been developed on a personal computer using Microsoft
FORTRAN to simulate flight trajectories of a light aircraft by using Six-Degree-of-Freedom
equation of motion. The simulation has been made realistic through pre-programmed the input to
the control surfaces, atmospheric gust during the flight mode. The programme plays an important
role in the evaluation and validation of the aircraft design process. A light aircraft (Cessna 182T)
has been tested through free flight, gliding flight, flight with gust. The results show good trend and
show that the programme could be dependent as a realistic flight test programme.
Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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