A total of sixty raw milk samples were collected from (street vendors and shops) from Baghdad city, Iraq. The samples were inoculated into peptone water and, then, subcultured onto MacConkey agar and Blood agar. Identification of isolates was confirmed by microscopic examination, cultural characteristic, biochemical tests, Vitek (VITEK®2 system), and Biolog GN substrate reactions followed by 16S rRNA and specific genes sequencing. Of 60 raw cow’s milk samples, Providencia spp. were identified only in 4 samples (6.67%) and P. rettgeri was the most common, 2/4 (50%), followed by P. stuartii and P. vermicola, 1/4 (25%). Antimicrobial susceptibility tests were conducted against ten antibiotics by the disc diffusion method. All Provid

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

KA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1

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

This study seeks to shed light on the aspects of visual pollution and its impact on the aesthetics of the town of Al-Eizariya known to suffer from the phenomenon. In order to identify the real causes of the problem which develops in various forms and patterns, threatening not only the aesthetic appearance of the towns, but also causes the emergence of new problems and phenomena that will have negative repercussions on the population. The researcher uses the analytical descriptive method to analyze the phenomenon of visual pollution in terms of reality, development, manifestations and spread and uses photos which document the visual pollution and its impact on the aesthetics of the known. The study concluded the existence of a strong rela