In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Some children are suffering from introversion in kindergartens , so it must be confront and obviated by specialists because it will inevitably lead to unsatisfactory results reflect negatively on the individual and the community together . And the introvert child is a miserable child incapable of social interaction or give - and - take with colleagues , lack of integration of the child to life leads to the obstruction of  participation with his peers in various activities.     Introversion  causes a real emotional deficit to the children of kindergartens which limits of possibility of their intellectual development and mental growth and that because of their isolation and poor focus in education

The practice of self medication is continuously increasing worldwide due to its important roles in curing minor conditions or symptoms. This study was conducted to evaluate the factors associated with self medication practice of Iraqi respondents residing in Baghdad City. This study was designed as cross sectional study in which data was collected via direct interviews with respondents using a previously prepared questionnaire. This study investigated 348 respondents from different age groups. The majority of respondents were male aged between 30-60 years, married with secondary or academic level of education and employed with accepted monthly income. The main reason for practicing self medication was previous experience with the same condi

Sports management is a fundamental pillar that supports sports institutions and plays a pivotal role in achieving advanced levels of success in talent development. The Talent Development Project is one of the key strategic initiatives of the Ministry of Youth and Sports. This study compares department heads with effective managerial competence to those with ineffective competence to highlight differences in performance quality. Through this comparison, the urgent need to assess the administrative performance skills of the heads of sports talent departments becomes evident, particularly their ability to lead and manage the Sports Talent Development Project. The objective is to identify strengths and weaknesses, establish a clear framework fo

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog