Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

     In this study,  has been discussed the issue of non-interest income and its impact on the Iraqi banking sector profit for the period between (2008-2017) as it was the main objective of the study is to find the relationship between the non-interest income and the profits of the banking sector in order to know  the size of the sector's dependence on non-interest income As well as an analysis of its profitability compared to selected countries, And to test hypotheses, the financial ratios and some statistical tests to determine the stability of the time series such as the test (Correlegram , Dickey -Fuller (depending on the statistical program (E-Views V8) and a simple linear regression method by (Minitab

E-learning is a lifeline for the educational process, which contributed to the sustainability of working educational organizations and prevented them from stopping, so the study came to measure the compatibility between E-learning quality dimensions (information technology, educational curricula, teaching methods, and intellectual capital of educational institution) as an independent variable, and educational services quality dimensions represented by (safety, tangibility, reliability and Confidence) as a dependent variable. The sample was 150 teachers was drawn from the College of Administration and Economics community of 293 teachers through the use of several statistical methods to measure the degree of correlation and impact between the

The bank risks has greaten and changed in its nature under the developments of financial liberalization, banking innovation and increasing use for new financial instruments which created by the huge technological advancement happened in the banking  industry. So that, banks in large choose to base the profitability measures adjusted for risks; that is we introduced this research. The most important reason led us to do this is the restriction to use the modern statistical methods by trade bank in Arab countries equally with world banks which were the antecedent to base those models. Therefore, the research problem is embedded in the banks need to use measures that link between profitability and risks and this is what achieved by RARC

Representing banking supervision An important function performed by the Iraqi Central Bank, in order to achieve stability in the financial and banking system, and safeguard the rights of depositors, investors and other targets, and to realize the Iraqi Central Bank banking supervision actors on banks, there must be an awareness of regulatory bank's existing control and subject them, as well as the role of banking oversight interested in spreading this awareness.
So sought search to find out the role played by the Iraqi Central Bank in raising awareness of the regulatory banking between the parties to the regulatory process, through the presentation and analysis of the legal framework for banking supervision and awareness supervisory