This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

The increasing use of polymeric materials in the daily life, leads to challenges in the processing industry to deliver high performance materials with affordable terms. However, new processing techniques lead to high costs. In order to reduce processing costs it is necessary to understand the non-Newtonian behavior of the polymers in their molten state to be able to simulate the processes before the construction of the plants starts. Here the shear thinning behavior of the viscosity of polymeric melts is essential. Thus, this paper deals with the experimental investigation of the thermo-rheological behavior of the viscosity of one of the most used polymers (Polypropylene) over a wide range of temperatures and shear rates.  Furthermo

This research aims to test the causal relationship long-and short-run between the price of gold the global crude oil price and the exchange rate of the dollar and how you can take advantage of the nature of this relationship, particularly in the Arab oil states that achieve huge surpluses, including Iraq and how to keep on the purchasing power of these surpluses or reduce the levels of risk.

The problem is that the Arab oil countries, adversely affected, as a result of that relationship, due to the fact that its role confined to the sale of crude oil only. They do not have control in the dollar, then they are not able to take advantage of its impact on the price of gold the fact that gold is effective pr

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

Abstract

Objective of this research focused on testing the impact of internal corporate governance instruments in the management of working capital and the reflection of each of them on the Firm performance. For this purpose, four main hypotheses was formulated, the first, pointed out its results to a significant effect for each of corporate major shareholders ownership and Board of Directors size on the net working capital and their association with a positive relation.  The second, explained a significant effect of net working capital on the economic value added, and their link inverse relationship, while the third, explored a significant effect for each of the corporate major shareholders ownershi

In this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro