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

Quantum dots (QDs) of zinc sulfide (ZnS) was prepared by chemical reaction with different potential of hydrogen (pH) and used to fabricate organic quantum dot hybrid junction device. The optical properties of QDs were characterized by ultraviolet-visible (UV-Vis.) and photoluminescence (PL) spectrometer. The results show that the prepared QDs were nanocrystalline with defects formation. The energy gap (E_g)calculated from PL were 3.64, 3.53 and 3.35 eV for pH=8, 10 and 12 respectively. This decreasing of energy gaps is results of the effect the pH solution increases, which in turn leads to the shifted of the PL spectrum toward red shifted, which makes the energy bands at surface states are shallow ban

The enhancement of ZnSe/Si Heterojunction by adding some elements (V, In and Cu) as impurities is the main goal because they contribute to the manufacturing of renewable energy equipment, such as solar cells. This paper describes the preparation of thin films ZnSe with V, In and Cu doped using thermal evaporation method with a vacuum of 10–5 Torr. The thin film was obtained from this work could be applied in heterojunction solar cell because of several advantages including high absorption coefficient value and direct band gap. The samples prepared on a glass and n-type Si wafer substrate. These films have been annealed for 1 h in 450 K. X-ray diffraction XRD results indicated that ZnSe thin film possesses poly-crystalline structure after

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

In this work, Pure and Cu: doped titanium dioxide nano-powder was prepared through a solid-state method. the dopant concentration [Cu/TiO₂ in atomic percentage (wt%)] is derived from 0 to 7 wt.%. structural properties of the samples performed with XRD revealed all nanopowders are of titanium dioxide having polycrystalline nature. Physical and Morphological studies were conducted using a scanning electronic microscope SEM test instrument to confirm the grain size and texture. The other properties of samples were examined using an optical microscope, Lee's Disc, Shore D hardness instrument, Fourier-transform infrared spectroscopy (FTIR), and Energy-dispersive X-ray spectroscopy (EDX). Results showed that the thermal conductivity

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