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

Abstract

Lack of safe available non-resistant treatment for visceral leishmaniasis (Kala-azar) keeps limiting the complete cure of this disease ,drugs that have  toxic side effects or lack of effectiveness  have led to disease relapse ,all these factors have lightened  the way to the search for imperative drugs from natural resources that have been shown to have antileishmanial activity through literature survey

. In the present study, the comparative in vitro anti-leishmania activity of various fractions of Osteospermum ecklonis aerial parts fractions have been evaluated. Extracts were prepared through maceration and Soxhlet apparatus using 85% meth

AgInSe2 (AIS) thin films solar cell involving of n-type AgInSe2 and Si of p-type substrate by using thermal evaporation method. The influence of annealing of the preparation AgInSe2 were considered to find the best properties of solar device. Thin film AIS have been deposited under the vacuum of 1.5*10-6 Torr with (400) nm thickness at R.T and annealing temperatures (473,573) K. Polycrystalline tetragonal structure for AIS thin films from XRD and increasing of surface roughness from AFM, energy gap values decreasing with increasing annealing temperatures, all films were negative type, I-V characteristics show increasing of efficiency with increasing of annealing temperatures.

The research aims to measure the impact of the empowerment strategy on the performance of employees by mediating organizational trust in the organization. The problem of research was the weak ability of most business organizations to employ the strategy of empowerment in maximizing the performance of employees, and the importance of research in practice lies in the results of a guide to managers in how to use the strategy of empowerment in maximizing the performance of employees by mediating organizational trust dimensions of ability, benevolence, integrity. In order to achieve the objectives of the research and to answer the questions of the problem, the researcher has adopted the descriptive analytical approach as the questionnaire was

Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.