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

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

The finite element method has been used in this paper to investigate the behavior of precast reinforced concrete dapped-ends beams (DEBs) numerically. A parametric investigation was performed on an experimental specimen tested by a previous researcher to show the effect of numerous parameters on the strength and behavior of RC dapped-end beams. Reinforcement details and steel arrangement, the influence of concrete compressive strength, the effect of inclined load, and the effect of support settlement on the strength of dapped-ends beams are examples of such parameters. The results revealed that the dapped-end reinforcement arrangement greatly affects the behavior of dapped end beam. The failure load decreases by 25% when

To evaluate impact the difference in stages ofage and related incidence of hemodialysis patients.Two hundred and fifty patients undergoing hemodialysis were collected from general hospital in Baghdad city /Iraq. The samples with renal failure before hemodialysis were divided into (138) male,( 112)female. The sera were separated from samples to physiological investigation. We found that renal failure was more predominant among the patients ages group ranging from (51-70) years old. The results shows A significant increase in the levels of urea, creatinine, in younger patients (≤ 30 years) when compared with older patients (>70 years). Furthermore a significant decrease in serum levels of total protein in patients in older patients (>7

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

This study was designed to investigate the effect of the Clenbuterol drug in some physiological parameters of Liver, Kidney function and lipidprofie concentration. Fourty adult male rabbits were used in this study. The animals were randomly divided into four groups,the first group was given distilled water (control) ,while the other third groups were given (2,4,6 µg/kg) of Clenbuterol drug for 30 days. Blood samples were collected after 14 and 30 days of the treatment for biochemical study. Drug caused non significant increase(P<0.05)in the AST and ALT enzymeactivity in second and third groups during treatment period ,while we note a significant increase(P<0.05) in both AST,ALT enzyme level in fourth group compared with control group , as

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

Current research included preparation, characterization of some new chitosan- hydroxy benzaldehyde-Schiff bases with maleic anhydride. The present study aimed to the synthesis and characterization of novel chitosan Schiff base compounds using para- hydroxy benzaldeh and maleic anhydride. The  derivative of the  schiff-chitosan base, which is associated with different drugs, has been replaced with   different  amino  and  hydroxy  drugs.  The derivative is characterized by different analytical techniques. The results of FT-IR studies clearly indicate construction of the chief amine group in chitosan and the emergence of new bands that correspond to the association of maleic anhydride with the chitosan base. TGA, ¹