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

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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

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), Decision Tre

Some new norms need to be adapted due to COVID-19 pandemic period where people need to wear masks, wash their hands frequently, maintain social distancing, and avoid going out unless necessary. Therefore, educational institutions were closed to minimize the spread of COVID-19. As a result of this, online education was adapted to substitute face-to-face learning. Therefore, this study aimed to assess the Malaysian university students’ adaptation to the new norms, knowledge and practices toward COVID-19, besides, their attitudes toward online learning. A convenient sampling technique was used to recruit 500 Malaysian university students from January to February 2021 through social media. For data collection, all students

The purpose of this paper is to identify environmental awareness under the Corona pandemic among students of the Faculty of Physical Education and Sports Sciences at the University of Kufa. and comparison of environmental awareness under the Corona pandemic between students of the Faculty of Physical Education and Sports Sciences at the University of Kufa. The two researchers used the descriptive approach in the style of the survey and comparisons to identify the research community in the students of the College of Physical Education and Sports Sciences at the University of Kufa for the academic year 2020-2021, who numbered (210) students, then a sample of (80) students was chosen randomly, with a percentage of (38.09%) from the research co

Symptoms of posttraumatic stress disorder are associated with various variables such as the exposure to traumatic events, sex and age. Such events could lead to negative cognitions towards self and the world. These cognitions, in turn, may lead to traumatic related disorders.

The present study aims to identify the percentage of traumatised individuals according to sex and age category variables. It also aims to assess the average of spreading symptoms of posttraumatic stress disorder of traumatised individuals according to sex and age category variables. Likewise, it aims to test variables significance in cognitions towards the world and the self according to the level of the spread of posttraumatic stre

The aim of this research is to demonstrate the nature of the interactive relationship between the dimensions of the requirements of economic intelligence Represented by(Administrative and regulatory requirements, human requirements, and technical requirements) The strategic success of banks is represented by (Customer satisfaction, customer confidence, quality of service, growth) In three of the Iraqi banks own bank(Middle East Iraqi Investment, Al Ahli Iraqi, Gulf Commercial), The questionnaire was adopted as a tool for collecting data and information Of the sample (85) Who are they(Director of the Commissioner, M. Director Plenipotentiary, Director of Department, Director of Section, M. Section Manager, Division Officer, Unit Officer),