The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

Background: Pain, swelling and trismus are the main minor complications encountered after surgical extraction of impacted third molars, minimizing these postoperative complications is the center of many studies, one proposed method is the prophylactic administration of corticosteroids, the aim of this study is to evaluate the effect of prophylactic Dexamethasone administration on facial swelling and trismus after surgical extraction of impacted third molars. Materials and methods: 20 patients were included in this study, they were randomly divided into 2 groups of 10 patients each; a study group in which patients were given 8 mg. Dexamethasone 1 hour before surgical extraction of impacted third molar and 4 mg. 6 hours postoperatively, and a

Gypseous soil covers approximately 30% of Iraqi lands and is widely used in geotechnical and construction engineering as it is. The demand for residential complexes has increased, so one of the significant challenges in studying gypsum soil due to its unique behavior is understanding its interaction with foundations, such as strip and square footing. This is because there is a lack of experiments that provide total displacement diagrams or failure envelopes, which are well-considered for non-problematic soil. The aim is to address a comprehensive understanding of the micromechanical properties of dry, saturated, and treated gypseous sandy soils and to analyze the interaction of strip base with this type of soil using particle image

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

The experiment was carried out in the green house of botanical garden belong to Department of Biology/College of Education for Pure Science- Ibn–al- Haitham/University of Baghdad, for the growth season 2015 using plastic pots. The experiment aimed to study the effect of two concentrations of sodium chloride (50, 100) mM.L-1 in addition to the control and four concentrations of kinetin (25, 50, 75, 100) mg.L-1 in addition to the control and the influence of application and non application of fertilizlizer NPKZn in the level 160 kg.h1- and their interactions on some growth parameters (fresh weight for both root and vegetative part, dry weight for leaves , value of secondary productivity, biomass duration for vegetative part and dry weight f