Most of the Internet of Things (IoT), cell phones, and Radio Frequency Identification (RFID) applications need high speed in the execution and processing of data. this is done by reducing, system energy consumption, latency, throughput, and processing time. Thus, it will affect against security of such devices and may be attacked by malicious programs. Lightweight cryptographic algorithms are one of the most ideal methods Securing these IoT applications. Cryptography obfuscates and removes the ability to capture all key information patterns ensures that all data transfers occur Safe, accurate, verified, legal and undeniable.  Fortunately, various lightweight encryption algorithms could be used to increase defense against various at

For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

This research deals with the design and simulation of a solar power system consisting of a KC200GT solar panel, a closed loop boost converter and a three phase inverter by using Matlab / Simulink. The mathematical equations of the solar panel design are presented. The electrical characteristics of the panel are tested at the values ​​of 1000  for light radiation and 25 °C for temperature environment. The Proportional Integral (PI) controller is connected   as feedback with the Boost converter to obtain a stable output voltage by reducing the oscillations in the voltage to charge a battery connected to the output of the converter. Two methods (Particle Swarm Optimization (PSO) and Zeigler- Nichols) are used for tuning

Low grade crude palm oil (LGCPO) presents as an attractive option as feedstock for biodiesel production due to its low cost and non-competition with food resources. Typically, LGCPO contains high contents of free fatty acids (FFA), rendering it impossible in direct trans-esterification processes due to the saponification reaction. Esterification is the typical pre-treatment process to reduce the FFA content and to produce fatty acid methyl ester (FAME). The pre-treatment of LGCPO using two different acid catalysts, such as titanium oxysulphate sulphuric acid complex hydrate (TiOSH) and 5-sulfosalicylic acid dihydrate (5-SOCAH) was investigated for the first time in this study. The optimum conditions for the homogenous catalyst (5-SOCAH) wer

In this paper, a new class of nonconvex sets and functions called strongly -convex sets and strongly -convex functions are introduced. This class is considered as a natural extension of strongly -convex sets and functions introduced in the literature. Some basic and differentiability properties related to strongly -convex functions are discussed. As an application to optimization problems, some optimality properties of constrained optimization problems are proved. In these optimization problems, either the objective function or the inequality constraints functions are strongly -convex. 

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

An experimental study is conducted on the utilization of the inlet ethanol injection technique in order to evaluate its impact on the performance of a two-shaft T200D mini-gas turbine engine. The maximum degradation recorded in power output was 32.8% at the climate temperature of 45^oC. Nevertheless, at that temperature, adding ethanol with Eth/LPG ratio of 20% by volume brought an enhancement in power output of 19.2% compared to normal LPG run. SFC of the dual-fuel engine ranked a level of 22% higher than that with pure LPG consumption. The overall efficiency suffered a maximum reduction of 14.4% with Eth/LPG fuel ratio of 20%, but when the loading was raised beyond 70% of the engine full load; the efficiency of dual-fuel engi