In this study, tin oxide (SnO2) and mixed with cadmium oxide (CdO) with concentration ratio of (5, 10, 15, 20)% films were deposited by spray pyrolysis technique onto glass substrates at 300ºC temperature. The structure of the SnO2:CdO mixed films have polycrystalline structure with (110) and (101) preferential orientations. Atomic force microscopy (AFM) show the films are displayed granular structure. It was found that the grain size increases with increasing of mixed concentration ratio. The transmittance in visible and NIR region was estimated for SnO2:CdO mixed films. Direct optical band gap was estimated for SnO2 and SnO2 mixed CdO and show a decrease in the energy gap with increasing mixing ratio. From Hall measurement, it was fou

Photonic Crystal Fiber (PCF) based on the Surface Plasmon Resonance (SPR) effect has been proposed to detect polluted water samples. The sensing characteristics are illustrated using the finite element method. The right hole of the right side of PCF core has been coated with chemically stable gold material to achieve the practical sensing approach. The performance parameter of the proposed sensor is investigated in terms of wavelength sensitivity, amplitude sensitivity, sensor resolution, and linearity of the resonant wavelength with the variation of refractive index of analyte. In the sensing range of 1.33 to 1.3624, maximum sensitivities of 1360.2 nm ∕ RIU and 184 RIU⁻¹ are achieved with the high sensor resolutions of 7

The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

Background: The Covid-19 pandemic changed the world; its most important achievement for education was changing the approach from traditional to virtual education. The present study aimed to investigate the role of virtual education networks on mental health of students including personality, beliefs, scientific, and cultural dimensions, in selected countries.Methods: This was an exploratory and applied study. According to the phenomenology strategy, theoretical saturation occurred after 24 semi-structured and targeted qualitative interviews with teachers from Iran, Iraq, Syria and Lebanon, in 2023. Quantitative data was collected through a researcher-made online questionnaire with 423 participants. Teachers with at least a Bachelor’s degr

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

The employment of cognitive radio (CR) is critical to the successful development of wireless communications. In this field, especially when using the multiple input multiple output (MIMO) antenna technology, energy consumption is critical. If the principal user (PU) is present, developers can utilize the energy detecting approach to tell. The researchers employed two distinct phases to conduct their research: the intense and accurate sensing stages. After the furious sensing step was completed, the PU user was identified as having a maximum or minimal energy channel. There are two situations in which the proposed algorithm's performance is tested: channels for fading AWGN and Rayleigh. When the proposed methods' simulation results a

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

Chemical compounds, characteristics, and molecular structures are inevitably connected. Topological indices are numerical values connected with chemical molecular graphs that contribute to understanding a chemical compounds physical qualities, chemical reactivity, and biological activity. In this study, we have obtained some topological properties of the first dominating David derived (DDD) networks and computed several K-Banhatti polynomials of the first type of DDD.