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.
Background: Enforcement of sustainable and green chemistry protocols has seen colossal surge in recent times, the development of an effective, eco-friendly, simple and novel methodologies towards the synthesis of valuable synthetic scaffolds and drug intermediates. Recent advances in technology have now a more efficient means of heating reactions that made microwave energy. Efforts to synthesize novel heterocyclic molecules of biological importance are in continuation. Microwave irradiation is well known to promote the synthesis of a variety of organic and inorganic compounds. The aim of current study was to conceivea mild base mediated preparation of novel Schiff base of 2-Acetylpheno with trimethoprim drug (H2TPBD) and its complexes w
... Show MoreThe recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli
... Show MoreIn this research, the X-ray diffraction pattern was used, which was obtained experimentally after preparation of barium oxide powder. A program was used to analyze the X-ray diffraction lines of barium oxide nanoparticles, and then the particle size was calculated by using the Williamson-Hall method, where it was found that the value of the particle size is 25.356 nm. Also, the dislocation density was calculated, which is equal to1.555 x1015 (lines/nm2), and the value of the unit cell number was also calculated, as it is equal to 23831.
This research aims to identify the reality of teaching political science research methods curriculum, to observe practices, and differences in teaching and learning between the Arab and Western universities. Moreover, it focuses on the difficulties that face students' acquisition of the course skills. The research uses the course model of some Western and Arab universities as case study.
This research shows that the curriculum do not reach yet the final form as other political science curriculums, and its upcoming changes will reflect the needs of stakeholders. The best method to teach this curriculum is to use applied learning in groups, learning by doing, and finally problem-based learning approach. Using optimal assessment deep
... Show MoreGlobal technological advancements drive daily energy consumption, generating additional carbon-induced climate challenges. Modifying process parameters, optimizing design, and employing high-performance working fluids are among the techniques offered by researchers for improving the thermal efficiency of heating and cooling systems. This study investigates the heat transfer enhancement of hybrid “Al2O3-Cu/water” nanofluids flowing in a two-dimensional channel with semicircle ribs. The novelty of this research is in employing semicircle ribs combined with hybrid nanofluids in turbulent flow regimes. A computer modeling approach using a finite volume approach with k-ω shear stress transport turbulence model was used in these simu
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