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.
Bimetallic Au –Pt catalysts supporting TiO2 were synthesised using two methods; sol immobilization and impregnation methods. The prepared catalyst underwent a thermal treatment process at 400◦ C, while the reduction reaction under the same condition was done and the obtained catalysts were identified with transmission electron microscopy (TEM) and energy-dispersive spectroscopy (EDS). It has been found that the prepared catalysts have a dimension around 2.5 nm and the particles have uniform orders leading to high dispersion of platinum molecules .The prepared catalysts have been examined as efficient photocatalysts to degrade the Crystal violet dye under UV-light. The optimum values of Bimetallic Au –
... Show MoreThe main work of this paper is devoted to a new technique of constructing approximated solutions for linear delay differential equations using the basis functions power series functions with the aid of Weighted residual methods (collocations method, Galerkin’s method and least square method).
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 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
... Show MoreThe main focus of research is on how to achieve the internal and external dimensions of corporate social responsibility through human resources management strategies, which is a major of research aimed. The main problem of this research was confirmed, which confirms that there is an unclear role for social responsibility, lack of human resources management strategies, and ambiguity of roles in the municipality under study. The diagnose of the problem and determining the gap between the internal and external dimensions of social responsibility and human resources management was identified, which attacked the researcher's attention to navigate in this subject, look for the reasons for the gaps and try to reduce them. The case study
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The multiple linear regression model of the important regression models used in the analysis for different fields of science Such as business, economics, medicine and social sciences high in data has undesirable effects on analysis results . The multicollinearity is a major problem in multiple linear regression. In its simplest state, it leads to the departure of the model parameter that is capable of its scientific properties, Also there is an important problem in regression analysis is the presence of high leverage points in the data have undesirable effects on the results of the analysis , In this research , we present some of
... Show MoreThe research study includes shedding light on the sas dance in Iraq, as it is one of the popular legacies that are rich in the Mesopotamian civilization and because of the different practices it has in the different occasions on which these dances are held. Which is one of the kinetic arts widespread among the classes of Iraqi society. The researcher explained its features and artistic content that characterizes Iraqi music. The (methodological framework) reviewed the justification, importance and purpose of the research, and the limits of the research that included the (National Troupe of Folk Art) as a human limit to discover the artistic methods of the Sas dance and then define the terms of the search. The "theoretical framework" cont
... Show MoreEnvironmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant
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