Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

The problem of internal sulfate attack in concrete is widespread in Iraq and neighboring countries.This is because of the high sulfate content usually present in sand and gravel used in it. In the present study the total effective sulfate in concrete was used to calculate the optimum SO3 content. Regression models were developed based on linear regression analysis to predict the optimum SO3 content usually referred as (O.G.C) in concrete. The data is separated to 155 for the development of the models and 37 for checking the models. Eight models were built for 28-days age. Then a late age (greater than 28-days) model was developed based on the predicted optimum SO3 content of 28-days and late age. Eight developed models were built for all

This work explores the designing a system of an automated unmanned aerial vehicles (UAV( for objects detection, labelling, and localization using deep learning. This system takes pictures with a low-cost camera and uses a GPS unit to specify the positions. The data is sent to the base station via Wi-Fi connection.

The proposed system consists of four main parts. First, the drone, which was assembled and installed, while a Raspberry Pi4 was added and the flight path was controlled. Second, various programs that were installed and downloaded to define the parts of the drone and its preparation for flight. In addition, this part included programs for both Raspberry Pi4 and servo, along with protocols for communication, video transmi

     The present research design examines the relationship between SCARB1 gene expression and the progression of chronic myeloid leukemia (CML) in Iraqi patients. The variations in gene expression between patients with CML and healthy controls were investigated. The gender and age correlations with CML patients were included, as was the association of gene expression folding of the SCARB1 gene with clinical data (WBC, RBC, hemoglobin, platelets, and BCR-ABL gene). The results displayed a significant difference in the mean gene expression level (∆Ct) of the CML group when compared to the matching ∆Ct values in the healthy control group. The gene expression folding of the SCARB1 gene indicates considerable changes in expression, wh

The study was aimed to investigate the morbidity of enteritis in goate from 2007 to 2011 by using 149 records contained veterinarian and breeding records from birth to yearling age to study factors refer to animals and that in relationship with enteritis morbidity included: breed, year, birth type, sex, birth weight, weaning weight, mother weight, season and age. General mean for enteritis incident rate was 0.94% and this not affected by birth type, sex, weaning weight, maternal weight, while significantly (p<0.05) affected by breed and birth weight and highly significant affect by year, season and age. This study indicated that local goats and shami have incidence rate received to 1.30% and 1.36% while for cross goats (local x Shami)

     The paper shows how to estimate the three parameters of the generalized exponential Rayleigh distribution by utilizing the three estimation methods, namely, the moment employing estimation method (MEM), ordinary least squares estimation method (OLSEM),  and maximum entropy estimation method (MEEM). The simulation technique is used for all these estimation methods to find the parameters for the generalized exponential Rayleigh distribution. In order to find the best method, we use the mean squares error criterion. Finally, in order to extract the experimental results, one of object oriented programming languages visual basic. net was used

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

This work presents the UC@MOOC project as a pedagogical innovation to face the effects of massification that are making Moroccan universities endure many constraints for the past ten years, as well as other African universities. It aims, among its objectives, to cope with the massification factor and to overcome the language difficulties encountered by students. In this project, our top priority is to reduce academic failure then we will get to the point of responding to the training' needs. Courses are scripted and posted online which did not require many resources, so their production cost is relatively low. Audiovisual digital content also helps us to save time, and go to a hybrid teaching or even flipped classrooms in some cases. The

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system