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

The relationship between respiratory diseases and natural geographical variables relative to temperature, relative humidity, wind and solar radiation is a strong one.
The environmental factors have impact on increasing the proportion of people with respiratory diseases in the province of Najaf, especially industrial pollution and working conditions as well as the economic level.
Ah-Mishkhab was in the first rank in terms of the number of people infected with respiratory diseases reached 135177 and 41%, followed by Najaf governorate which reached its numbers to 77801 and 23%. The district of Kufa ranked third with 42051 and 13%, and the other administrative units at fourth and fifth rank respectively.
When comparing diseases and

The study conducted to investigate the association between Helicobacter pylori infection and eye diseases (Glaucoma, Cataract, CSR and Uveitis). One hundred and four patients with multiple eye disorders (10-80) years were observed from 10/9 to 18/11/2020 and compared to thirty-one healthy people (19 female and 12 male). Both participants were tested for anti-H. pylori IgA, and IgG antibodies using ELISA. There were non –significant differences (P≥0.05) in the concentration of anti-H. pylori IgA Abs in sera of patients with Glaucoma, CSR, and Uveitis compared to the control group, but there was a significant difference (P≤0.05) in the concentration of H. pylori IgA Abs in sera of patients with Cataract compared to the control group and

This study presents an updated checklist of the dipteran-borne diseases in Iraq, together with their original name combinations and synonyms. According to this checklist, 152 species, 40 genera within 14 families. Furthermore, minor corrections were applied to some authors’ names and years of publication.

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

The aim of this study to identity using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students. The researchers used the experimental method to design equivalent groups with a preand post-test, and the research community was identified with the students of the third stage in the college for the academic year 2020-2021 .The subject was, (3) class were randomly selected, so (30) students distributed into (3) groups). has been conducted pretesting after implementation of the curriculum for (4) weeks and used the statistical bag of social sciences(SPSS)to process the results of the research and a set of conclusions was reached, the most important of which is t

Image processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of it

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re