Multiplicative inverse in GF (2 m ) is a complex step in some important application such as Elliptic Curve Cryptography (ECC) and other applications. It operates by multiplying and squaring operation depending on the number of bits (m) in the field GF (2 m ). In this paper, a fast method is suggested to find inversion in GF (2 m ) using FPGA by reducing the number of multiplication operations in the Fermat's Theorem and transferring the squaring into a fast method to find exponentiation to (2 k ). In the proposed algorithm, the multiplicative inverse in GF(2 m ) is achieved by number of multiplications depending on log 2 (m) and each exponentiation is operates in a single clock cycle by generating a reduction matrix for high power of two ex

An efficient combination of Adomian Decomposition iterative technique coupled with Laplace transformation to solve non-linear Random Integro differential equation (NRIDE) is introduced in a novel way to get an accurate analytical solution. This technique is an elegant combination of theLaplace transform, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has also been established that (LT

Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

      Manganese-zinc ferrite Mn_xZn_1-xFe₂O₄ (MnZnF) powder was prepared using the sol-gel method. The morphological, structural, and magnetic properties of MnZnF powder were studied using X-ray diffraction (XRD), atomic force microscopy (AFM), energy dispersive X-ray (EDX), field emission-scanning electron microscopes (FE-SEM), and vibrating sample magnetometers (VSM). The XRD results showed that the MnxZn1-xFe2O4 that was formed had a trigonal crystalline structure. AFM results showed that the average diameter of Manganese-Zinc Ferrite is 55.35 nm, indicating that the sample has a nanostructure dimension. The EDX spectrum revealed the presence of transition metals (Mn, Fe, Zn, and O) in Mang

Alumina thin films have significant applications in the areas of optoelectronics, optics, electrical insulators, sensors and tribology. The novel aspect of this work is that the homogeneous alumina thin films were prepared in several stages to generate a plasma jet. In this paper, aluminium nanoparticles suspended in vinyl alcohol were prepared using exploding wire plasma. TEM analysis was used to determine the size and shape of particles in aluminium and vinyl alcohol suspensions; the TEM images showed that the particle size is 17.2 nm. Aluminium/poly vinyl alcohol (Al/PVA) thin films were prepared using this suspension on quartz substrate by plasma jet technique at room temperature with an argon gas flow rate of 1 L/min. The Al/PV

Electrochemical method was used to prepare carbon quantum dots (CQDs). Size of matter was nature when evaluate via X-ray diffraction (XRD). A distinct peak at 2θ equal to 31.6° and three other small peaks at 38.28°, 56.41° and 66.12° were observed. The measures of Fourier Transform Infrared Spectroscopy (FTIR) showed the bonds in the transmittance spectrum are manufactured with carbon nanostructures in view. The first peaks are the O–H stretching vibration bands at (3417 and 2922) cm−1, (C–O–H at 1400, and 1317) cm−1, (C–H), (C=C), (C–O–H), (C=O), and (C–O) bonds at 2850, 1668, 1101, and 1026 cm−1 sequentially. The transmission electron microscopy (TEM) results presented that the spherical CQDs are in shape and on a

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the