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Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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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.

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Publication Date
Sat Jun 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
A novel fusion-based approach for the classification of packets in wireless body area networks
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This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
The Impact of Black Marketing on Purchasing Decisions: An Exploratory Study Using AI-Driven Analytical Tools
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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Thu Dec 01 2016
Journal Name
2016 Ieee Symposium Series On Computational Intelligence (ssci)
A fusion of time-domain descriptors for improved myoelectric hand control
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Publication Date
Mon Jun 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Theoretical Study and calculation The cold Reaction Rate of Deuteron Fusion In Nickel Metal Using Bose–Einstein Condensate Theory
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In this paper, we focused on the investigated and studied the cold fusion reaction rate for D-D using the theory of Bose-Einstein condensation and depending on the quantum mechanics consideration. The quantum theory was based on the concept of single conventional of deuterons in Nickel-metal due to Bose-Einstein condensation, it has supplied a consistent description and explained of the experimental data. The analysis theory model has capable of explaining the physical behaviour of deuteron induced nuclear reactions in Nickel metals upon the five-star matter, it's the most expected for a quantitative predicted of the physical theory. Based on the Bose-Einstein condensation theorem formulation, we calculation the cold fusion reaction rate fo

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Publication Date
Mon May 27 2019
Journal Name
Al-academy
The Symbolic Construction of Scenes of Love in the Feature Film: محمد عبد الحميد ضيدان
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Scenes of love constitute a large space within the orbit of the movies, so that there is almost no film (no matter what kind) void of these scenes, as they are associated with many dimensions and they constitute a major attraction for viewers, and thus the direction solutions and their connection to the director's vision constitute a large part in the process of employing signs to highlight what should be highlighted or to refer to it symbolically on the grounds that the director does not have full freedom in the transfer of scenes of love at all levels as they are in reality. The research included three sections within the theoretical framework:The first section: the concept of image and its rhetorical importance. This section discussed

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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials &amp; Continua
A Technical Framework for Selection of Autonomous UAV Navigation Technologies and Sensors
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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Selection of variables Affecting Red Blood Cell by Firefly Algorithm
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Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.

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Publication Date
Tue Jan 01 2019
Journal Name
Proceedings Of The 5th International Conference On Information Systems Security And Privacy
Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion
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