Chromium oxide (Cr₂O₃) doped ZnO nanoparticles were prepared by pulsed laser deposition (PLD) technique at different concentration ratios (0, 3, 5, 7 and 9 wt %) of ZnO on glass substrate. The effects of ZnO dopant on the average crystallite size of the synthesized nanoparticles was examined By X-ray diffraction. The morphological features were detected using atomic force microscopy (AFM). The optical band gap value was observed to range between 2.78 to 2.50 eV by UV-Vis absorption spectroscopy, with longer wavelength shifted in comparison with that of the bulk Cr₂O₃ (~3eV). Gas sensitivity, response, and recovery times of the sensor in the presence of NH₃

Rapid breakdown anodization (RBA) process was used to fabricate TiO₂ sensor to measure pressure and humidity and sense gases at room temperature. This chemical process transformed Ti to its oxide (TiO₂) as a powder with amorphous phase as X ray diffraction (XRD) technique confirmed.  This oxide consisted from semi spherical nanoparticles and titania nanotubes (TNTs) as Scanning electron microscope (SEM) technique showed.  TiO₂ powder was deposited on Ti substrates by using electrophoretic deposition (EPD) method.   Average pressure sensitivity was 0.34 MΩ/bar and hysteresis area was 1.4 MΩ .bar. Resistance of TiO₂ decreased exponentially with the increasing of relative

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

      In education, exams are used to asses students’ acquired knowledge; however, the manual assessment of exams consumes a lot of teachers’ time and effort. In addition, educational institutions recently leaned toward distance education and e-learning due the Coronavirus pandemic. Thus, they needed to conduct exams electronically, which requires an automated assessment system. Although it is easy to develop an automated assessment system for objective questions. However, subjective questions require answers comprised of free text and are harder to automatically assess since grading them needs to semantically compare the students’ answers with the correct ones. In this paper, we present an automatic short answer grading metho

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

     The inefficient use of spectrum is the key subject to overcome the upcoming spectrum crunch issue. This paper presents a study of performance of cooperative cognitive network via hard combining of decision fusion schemes. Simulation results presented different cooperative hard decision fusion schemes for cognitive network. The hard-decision fusion schemes provided different discriminations for detection levels. They also produced small values of Miss-Detection Probability at different values of Probability of False Alarm and adaptive threshold levels. The sensing performance was investigated under the influence of channel condition for proper operating conditions. An increase in the detection performance was achi

Nowadays, it is quite usual to transmit data through the internet, making safe online communication essential and transmitting data over internet channels requires maintaining its confidentiality and ensuring the integrity of the transmitted data from unauthorized individuals. The two most common techniques for supplying security are cryptography and steganography. Data is converted from a readable format into an unreadable one using cryptography. Steganography is the technique of hiding sensitive information in digital media including image, audio, and video. In our proposed system, both encryption and hiding techniques will be utilized. This study presents encryption using the S-DES algorithm, which generates a new key in each cyc