In this research, Argon gas was used to generate atmospheric plasma in the manufacture of platinum nanomaterials, to study the resultant plasma spectrum and to calculate the cellular toxicity of those manufactured nanomaterials. This research is keen on the generation of nonthermal atmospheric pressure plasma using aqueous platinum salts (H₂PtCl₆ 6H₂O) with different concentrations and exposure of cold plasma with a different time period used to produce platinum nanoparticles, to ensure typical preparation of nanoparticles. Visible UV and X-rays were performed for this purpose, and the diameter of the system probe was (1[Formula: see text]mm) with the Argon gas flow of

The aim of this paper, study the effect of carbon nanotubes on the electrical properties of polyvinylchloride. Samples of polyvinylchloride carbon nanotubes composite prepared by using hot press technique. The weight percentages of carbon nanotubes are 0,5,10 and 20wt.%. Results showed that the D.C electrical conductivity increases with increasing of the weight percentages of carbon nanotubes. Also, the D.C electrical conductivity changed with increase temperature for different concentrations of carbon nanotubes. The activation energy of D.C electrical conductivity is decreased with increasing of carbon nanotubes concentration.

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

     NS-2 is a tool to simulate networks and events that occur per packet sequentially based on time and are widely used in the research field. NS-2 comes with NAM (Network Animator) that produces a visual representation it also supports several simulation protocols. The network can be tested end-to-end. This test includes data transmission, delay, jitter, packet-loss ratio and throughput. The Performance Analysis simulates a virtual network and tests for transport layer protocols at the same time with variable data and analyzes simulation results based on the network simulator NS-2.

Hand gestures are currently considered one of the most accurate ways to communicate in many applications, such as sign language, controlling robots, the virtual world, smart homes, and the field of video games. Several techniques are used to detect and classify hand gestures, for instance using gloves that contain several sensors or depending on computer vision. In this work, computer vision is utilized instead of using gloves to control the robot's movement. That is because gloves need complicated electrical connections that limit user mobility, sensors may be costly to replace, and gloves can spread skin illnesses between users. Based on computer vision, the MediaPipe (MP) method is used. This method is a modern method that is discover

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.