During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

    Water contamination is a pressing global concern, especially regarding the presence of nitrate ions. This research focuses on addressing this issue by developing an effective adsorbent for removing nitrate ions from aqueous solutions. two adsorbents Chitosan-Zeolite-Zirconium (Cs-Ze-Zr composite beads and Chitosan-Bentonite-Zirconium Cs-Bn-Zr composite beads were prepared. The study involved continuous experimentation using a fixed bed column with varying bed heights (1.5 and 3 cm) and inlet flow rates (1 and 3 ml/min). The results showed that the breakthrough time increased with higher bed heights for both Cs-Ze-Zr and Cs-Bn-Zr composite beads. Conversely, an increase in flow rate led to a decrease in breakthrough time. Notab

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

In order to improve the effectiveness, increase the life cycle, and avoid the blade structural failure of wind turbines, the blades need to be perfectly designed. Knowing the flow angle and the geometric characteristics of the blade is necessary to calculate the values of the induction factors (axial and tangential), which are the basis of the Blade Element Momentum theory (BEM). The aforementioned equations form an implicit and nonlinear system. Consequently, a straightforward iterative solution process can be used to solve this problem. A theoretical study of the aerodynamic performance of a horizontal-axis wind turbine blade was introduced using the BEM. The main objective of the current work is to examine the wind turbine blade’s perf

The first aim of this paper was to evaluate the push-out bond strength of the gutta-percha coating of Thermafil and GuttaCore and compare it with that of gutta-percha used to coat an experimental hydroxyapatite/polyethylene (HA/PE) obturator. The second aim was to assess the thickness of gutta-percha around the carriers of GuttaCore and HA/PE obturators using microcomputed tomography (μCT). Ten (size 30) 1 mm thick samples of each group (Thermafil, GuttaCore, and HA/PE) were prepared. An orthodontic wire with a diameter of 0.5 mm was attached to the plunger of an Instron machine in order to allow the push-out testing of the gutta-percha coating. Five samples of (GuttaCore and HA/PE) were scanned using

The research aims to identify the academic problems of family counseling diploma students at Saudi Universities. In addition, to identify the differences in these problems according to gender, marital status, place of study, academic specialization, and GPA. The sample consisted of (491) students. The researcher has used one questionnaire for academic problems prepared by the researcher.  The research revealed the following results: There were academic problems among family counseling diploma students at Saudi Universities, the most problems were related to the systems and administrations of the university, then the field training, the buildings, classrooms and campus facilities, then the academic courses, after that the exams, then

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve