Preparation of epoxy/ TiO2 and epoxy/ Al2O3 nanocomposites is studed and investigated in this paper. The nano composites are processed by different nano fillers concentrations (0, 0.01, 0.02 ,0.03, 0.04 ,0.05 ,0.07 and 0.1 wt%). The particles sized of TiO2,Al2O3 are about 20–50 nm.Epoxy resin and nano composites containing different shape nano fillers of (TiO2:Al2O3 composites),are shear mixing with ratio 1 to 1,with different nano hybrid fillers concentrations( 0.025 ,0.0 5 ,0.15 ,0.2, and 0.25 wt%) to Preparation of epoxy/ TiO2- Al2O3 hybrid composites. The mechanical properties of nanocomposites such as bending ,wearing, and fatigue are investigated as mechanical properties.

Electrochemical Machining is a term given to one of nontraditional machining that uses a chemical reaction associated with electric current to remove the material. The process is depending on the principle of anodic dissolution theory for evaluating material removal during electrochemical process. In this study, the electrochemical machining was used to remove 1 mm from the length of the a workpiece (stainless steel 316 H) by immersing it in to electrolyte (10, 20 and 30 g) of NaCl and Na₂SO₄ to every (1 litter of filtered water).  The tool used was made from copper. Gap size between the workpiece and electrode is (0.5) mm. This study focuses on the effect of the changing the type and concentration of electroly

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.