Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Purpose: To use the balanced measurement approach as a strategic link for increasing the effectiveness of strategic planning in the direction of achieving satisfaction rates at Bisha University in Saudi Arabia

Design / methodology / approach –The questionnaire survey was used to collect the data of the study from the faculty members at University of Bisha.

Findings –Prove the assumption that the use of the balanced measurement approach - as a strategic planning tool - leads to maximize the satisfaction rates among faculty members at the University of Bisha.

Research limitations/implications-  adopt effective strategic planning in order to achieve

The basic concept of diversity; where two or more inputs at the receiver are used to get uncorrelated signals. The aim of this paper is an attempt to compare some possible combinations of diversity reception and MLSE detection techniques. Various diversity combining techniques can be distinguished: Equal Gain Combining (EGC), Maximal Ratio Combining (MRC), Selection Combining and Selection Switching Combining (SS).The simulation results shows that the MRC give better performance than the other types of combining (about 1 dB compare with EGC and 2.5~3 dB compare with selection and selection switching combining).

The process of identifying the region is not an easy process when compared with other operations within the attribute or similarity. It is also not difficult if the process of identifying the region is based on the standard and standard indicators in its calculation. The latter requires the availability of numerical and relative data for the data of each case Any indicator or measure is included in the legal process

Mutans streptococci (MS) are a group of oral bacteria considered as the main cariogenic organisms. MS consists of several species of genus Streptococcus which are sharing similar phenotypes and genotypes. The aim of this study is to determine the genetic diversity of the core species of clinical strains of Streptococcus mutans, Streptococcus sobrinus and Streptococcus downei by using repitative extragenic palindromic (REP) primer. The DNA of the clinical strains of S. mutans (n=10), S. sobrinus (n=05) and S. downei (n=04) have been employed in the present study, which have been previously isolated from caries active subjects. The DNA of the clinical and reference strains was