The Frequency-hopping Spread Spectrum (FHSS) systems and techniques are using in military and civilianradar recently and in the communication system for securing the information on wireless communications link channels, for example in the Wi-Fi 8.02.X IEEE using multiple number bandwidth and frequencies in the wireless channel in order to hopping on them for increasing the security level during the broadcast, but nowadays FHSS problem, which is, any Smart Software Defined Radio (S-SDR) can easily detect a wireless signal at the transmitter and the receiver for the hopping sequence in both of these, then duplicate this sequence in order to hack the signal on both transmitter and receiver messages using the order of the se

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

KA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1

Double-layer micro-perforated panels (MPPs) have been studied extensively as sound absorption systems to increase the absorption performance of single-layer MPPs. However, existing proposed models indicate that there is still room for improvement regarding the frequency bands of absorption for the double-layer MPP. This study presents a double-layer MPP formed with two single MPPs with inhomogeneous perforation backed by multiple cavities of varying depths. The theoretical formulation is developed using the electrical equivalent circuit method to calculate the absorption coefficient under a normal incident sound. The simulation results show that the proposed model can produce absorption coefficient with wider absorption bandwidth compared w

Global technological advancements drive daily energy consumption, generating additional carbon-induced climate challenges. Modifying process parameters, optimizing design, and employing high-performance working fluids are among the techniques offered by researchers for improving the thermal efficiency of heating and cooling systems. This study investigates the heat transfer enhancement of hybrid “Al2O3-Cu/water” nanofluids flowing in a two-dimensional channel with semicircle ribs. The novelty of this research is in employing semicircle ribs combined with hybrid nanofluids in turbulent flow regimes. A computer modeling approach using a finite volume approach with k-ω shear stress transport turbulence model was used in these simu

The research involved attempt to inhibit the corrosion of Al-Si-Cu alloy in 2.5x10-3 mol.dm-3 NaOH solution (pH=11.4) by addition of six different inhibitors with three concentrations (1x10-3, 1x10-2, and 0.1 mol.dm-3). These inhibitors include three organic materials (sodium acetate, sodium benzoate, and sodium oxalate) and three inorganic materials (sodium chromate, disodium phosphate, and sodium sulphate). The data that concerning polarization behaviour are calculates which include the corrosion potential (Ecorr) and current density (icorr), cathodic and anodic Tafel slopes (bc & ba), and polarization resistance (Rp). Protection efficiency (P%) and activation energy (Ea) values were calculated for inhibition by the six inhibitors. The

Formation of Au–Ag–Cu ternary alloy nanoparticles (NPs) is of particular interest because this trimetallic system have miscible (Au–Ag and Au–Cu) and immiscible (Ag– Cu) system. So there is a possibility of phase segregation in this ternary system. At this challenge it was present attempts synthetic technique to generate such trimetallic alloy nanoparticles by exploding wire technique. The importance of preparing nanoparticles alloys in distilled water and in this technique makes the possibility of obtaining nanoparticles free of any additional chemical substance and makes it possible to be used in the treatment of cancer or diseases resulting from bacterial or virus with least toxic. In this work, three metals alloys Au-Ag-Cu

Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t