In modern years, internet and computers were used by many nations all overhead the world in different domains. So the number of Intruders is growing day-by-day posing a critical problem in recognizing among normal and abnormal manner of users in the network. Researchers have discussed the security concerns from different perspectives. Network Intrusion detection system which essentially analyzes, predicts the network traffic and the actions of users, then these behaviors will be examined either anomaly or normal manner. This paper suggested Deep analyzing system of NIDS to construct network intrusion detection system and detecting the type of intrusions in traditional network. The performance of the proposed system was evaluated by using Kdd cup 99 dataset. The experimental results displayed that the proposed module are best suited due to their high detection rate with false alarm rate.
Single crystals of pure and Cu+2,Fe+2 doped potassium sulfate were grown from aqueous solutions by the slow evaporation technique at room temperature. with dimension of (11x9 x4)mm3 and ( 10x 8x 5)mm3 for crystal doping with Cu &Fe respectively. The influence of doping on crystal growth and its structure revealed a change in their lattice parameters(a=7.479 Ã… ,b=10.079 Ã… ,c=5.772 Ã…)for pure and doping (a=9.687 Ã…, b=14.926 Ã… ,c= 9.125 Ã…) & (a=9.638 Ã… , b= 8.045 Ã… ,c=3.271 Ã…) for Cu & Fe respectively. Structure analysis of the grown crystals were obtained by X-Ray powder diffraction measurements. The diffraction patterns were analyzed by the Rietveld refinement method. Rietveld refinement plo
... Show MoreIn this paper, the Normality set will be investigated. Then, the study highlights some concepts properties and important results. In addition, it will prove that every operator with normality set has non trivial invariant subspace of .
(3)
(1)
In this paper we introduce the definition of Lie ideal on inverse semiring and we generalize some results of Herstein about Lie structure of an associative rings to inverse semirings.
(2)
(1)
An algebra has been constructed from a (D, A)-stacked algebra A, under the conditions that , A 1 and . It is shown that when the construction of algebra B is built from a (D, A)-stacked monomial algebra A then B is a d-Koszul monomial algebra.
Let S be a prime inverse semiring with center Z(S). The aim of this research is to prove some results on the prime inverse semiring with (α, β) – derivation that acts as a homomorphism or as an anti- homomorphism, where α, β are automorphisms on S.
(1)
This paper deal with the estimation of the shape parameter (a) of Generalized Exponential (GE) distribution when the scale parameter (l) is known via preliminary test single stage shrinkage estimator (SSSE) when a prior knowledge (a0) a vailable about the shape parameter as initial value due past experiences as well as suitable region (R) for testing this prior knowledge.
The Expression for the Bias, Mean squared error [MSE] and Relative Efficiency [R.Eff(×)] for the proposed estimator are derived. Numerical results about beha
... Show More
Background: There is a recognized association between prolongation of the heart rate corrected QT interval (QTc) and antipsychotic drugs. QTc prolongation may increase the risk of ventricular tachyarrhythmias, especially torsade de pointes, and therefore, sudden cardiac death.
Objective: This study assess the effect of antipsychotics and prolongation of the heart rate corrected QT interval (QTC), and QTC prolongation may increase the risk of ventricular tachyarrhythmias, especially torsade de pointes and sudden cardiac death.
Results: Abnormal QTc was defined as an interval of more than 440 ms (0.44 second) and was present in 21.7% (43 patients of 198). Benzhexol (-0.333
... Show More
In this paper we introduced a new class of - called - and study their basic properties in nano topological spaces. We also introduce -closure and -interior and study some of their fundamental properties.
In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.