The study aims to identify the degree of implementation of the coronavirus prevention standards (covid-19) in the kingdom of Saudi Arabia and compare it with the families of intellectual disabilities. The study population consisted of all families residing in the Kingdom of Saudi Arabia. To achieve the objectives of the research, the analytical descriptive approach was employed. The study sample consisted of (372) families, among them (84) families with intellectual disabilities, and (288) families without intellectual disabilities. They were chosen from the Saudi community according to what is available for collection in a simple random way, using the standard criteria for the prevention of coronavirus (Covid- 19) Prepared by the researcher, consisted of (23) items distributed on one axis. The results found that mean for the Coronavirus Prevention standards (Covid-19) for the families of those without intellectual disabilities reported a high response average, as for the average, it was (4,139) and a standard deviation was (0,592). The results also found that the means of the Coronavirus Prevention standards (Covid-19) among families with intellectual disabilities was very high with a mean (4,214) and a standard deviation of (0.558). The results showed there were statistically significant differences at the level of statistical significance (0.05) between the average response to the application of the standards for the prevention of coronavirus (Covid-19) by families of the intellectually disabled and those who have a chronic disease and who do not have a chronic disease. These differences were in favor of the families of the intellectually disabled and those who have chronic disease in terms of applying prevention standards. Finally, the results showed there are no statistically significant differences at the level of statistical significance (0.05) between the average responses of the families of the intellectually disabled and the ordinary families on the scale of the standards prevention of coronavirus (COVID-19). These differences were in favor of the families of the intellectually disabled. The study came out with a set of recommendations, the most important of which was the follow-up of parents to educate their children through educational seminars through the Internet during periods of home quarantine. The need to set up solid communication bridges between the families and the competent authorities to combat Coronavirus (Covid-19). The need to maintain a distance of one and a half meters with others during Leaving the house, with an emphasis on the necessity of sterilization and hygiene, and the application of preventive measures.
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This study was carried out from February to October 2012 in six semi salty ponds in Gwer sub-district which is the first work in the area. A total of 32 species and 2 genera of algae where reported as the new records. Mostly the non diatoms are belonging to Cyanophyta, Chlorophyta, Euglenophyta, Cryptophyta, Chrysophyceae, while diatoms or Bacilariophyceae are belong to pennals- order.
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
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Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.
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