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 achieved lower computational complexity and number of layers, while being more reliable compared with other algorithms applied to recognize face masks. The findings reveal that the model's validation accuracy reaches 97.55% to 98.43% at different learning rates and different values of features vector in the dense layer, which represents a neural network layer that is connected deeply of the CNN proposed model training. Finally, the suggested model enhances recognition performance parameters such as precision, recall, and area under the curve (AUC).
A modified Leslie-Gower predator-prey model with a Beddington-DeAngelis functional response is proposed and studied. The purpose is to examine the effects of fear and quadratic fixed effort harvesting on the system's dynamic behavior. The model's qualitative properties, such as local equilibria stability, permanence, and global stability, are examined. The analysis of local bifurcation has been studied. It is discovered that the system experiences a saddle-node bifurcation at the survival equilibrium point whereas a transcritical bifurcation occurs at the boundary equilibrium point. Additionally established are the prerequisites for Hopf bifurcation existence. Finally, using MATLAB, a numerical investigation is conducted to verify t
... Show MoreThe importance of this research is due to its importance goals, Which are about the attempt of researchers to investigate the probability of depending on businesses, environments to transform organizations, performance in away that enhance the leading role of organizations in their environments , and through views of a number of the staff working in the foundation of technical institutes in Mosul. .
After deciding the methodology of the study that ,in one hand ,performs the goals of the study , and achieving a suitable theoretical framework to present the concepts of businesses, environments and the leadin
... Show MoreA set newly complexes with the general formula [M(L)Cl2] are resulting from the reaction of a new schiff base ligand [Ethyl (6R,7R)-7-((E)-2-((2-ethoxy-2- oxoethoxy)imino)-2-(2-(((E)-4-nitrobenzylidene) amino) thiazol -4- yl) acetamido) -8- oxo -3- vinyl -5- thia -1-aza bicyclo [4. 2.0] oct -2- ene -2- carboxylate] (L). This ligand was derived from the reaction of the two substances 4-nitrobenzaldehyde and precursor (P). Reaction the ligand with metal ions M= Mn(II), Co(II), Ni(II), Cu(II) and Cd(II) afforded new complexes which are characterized by FT-IR and Electronic Spectra. These measurements indicate that the complexes have a tetrahedral geometry. The Penicillin-Binding Protein 3 (PBP3) of Staphylococcus aureus and the target protein
... Show MoreNew chalcones of -{ - - - y - - hi di z e- -y he y - - e e- - e- - - substituted phenyl have been prepared from condensation of a new of 4-[5-(4`-tolyl)1,3,4-thiadiazole-2-yl] benzaldehyde (which is synthesized by the reaction of 2- amino-5- (4`-tolyl) -1,3,4-thiadiazole and benzaldehyde) with 3- or 4- substituted acetophenones in alkaline medium. The physical, CHNS analysis and spectral data of the synthesized compounds were determined. The biological activity evaluated of new compounds showed that many of these compounds possess antiba
... Show MoreFollowing model educational offenders in collection and Alasbaka of fifth grade students preparatory in history A. M. Dr Prepared by: Dr. Bashaer Mawloud Tawfeeq, The Center of Educational and Psychological Studies Baghdad University - There is no difference statistically significant at the 0.05 level of significance between the average scores of the following students studying using model and offenders and who are studying in the usual manner (traditional) in the collection - There is no difference statistically significant at the 0.05 level of significance between the mean scores for the following students studying using model and offenders and who are studying in the usual manner (traditional) in retention Find limits: Current search
... Show MoreIn this paper, a mathematical model for the oxidative desulfurization of kerosene had been developed. The mathematical model and simulation process is a very important process due to it provides a better understanding of a real process. The mathematical model in this study was based on experimental results which were taken from literature to calculate the optimal kinetic parameters where simulation and optimization were conducted using gPROMS software. The optimal kinetic parameters were Activation energy 18.63958 kJ/mol, Pre-exponential factor 2201.34 (wt)-0.76636. min-1 and the reaction order 1.76636. These optimal kinetic parameters were used to find the optimal reaction conditions which
... Show MorePurpose: The research aims to determine the relationship between E-Learning and Total Quality Management (TQM) in Educational institutions in Nineveh Governorates.
Methodology / Design: The researchers distributed (30) questionnaires to employees (teachers and administrators) of Nineveh Governorate education who represent the community of the research sample, as they were analyzed using the SPSS V.20
The importance of research: The importance of the research in the fact that it focuses on one of the educational methods represented in integrating the traditional method and relying on modern technologies using computers and the Internet in the field of education to improve the reali
... Show MoreThe growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
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