Background: Salivary immunoglobulin IgA plays an essential role in the immune response against dental caries. This studywas conducted to compare the salivary IgA levels and flow rate of stimulated saliva in caries active and caries free children. Materials and methods: The present study included sixty healthy children age 7-10 yearswho were divided into two groups. They were caries free and caries active children (30 children in each group). Assessment and recording of caries – experience were through the application of Decayed, Missing and Filled Tooth Index (DMFT) and (dmft) index, for permanent and deciduous teeth respectively. After dental examination, stimulated saliva samples were collected from the subjects and performed und

Background: Salivary immunoglobulin IgA plays an essential role in the immune response against dental caries. This studywas conducted to compare the salivary IgA levels and flow rate of stimulated saliva in caries active and caries free children. Materials and methods: The present study included sixty healthy children age 7-10 yearswho were divided into two groups. They were caries free and caries active children (30 children in each group). Assessment and recording of caries – experience were through the application of Decayed, Missing and Filled Tooth Index (DMFT) and (dmft) index, for permanent and deciduous teeth respectively. After dental examination, stimulated saliva samples were collected from the subjects and performed und

Routing protocols are responsible for providing reliable communication between the source and destination nodes. The performance of these protocols in the ad hoc network family is influenced by several factors such as mobility model, traffic load, transmission range, and the number of mobile nodes which represents a great issue. Several simulation studies have explored routing protocol with performance parameters, but few relate to various protocols concerning routing and Quality of Service (QoS) metrics. This paper presents a simulation-based comparison of proactive, reactive, and multipath routing protocols in mobile ad hoc networks (MANETs). Specifically, the performance of AODV, DSDV, and AOMDV protocols are evaluated and analyz

The use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models                  

          In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear

Background: Chronic otitis media (COM) of mucosal or squamous type is a common problem in otolaryngology practice, the active form of COM is characterized by discharge of pus and is treated by antibiotics to start with, the appropriate antibiotic should be prescribed to avoid antibiotic abuse and guarantee good outcome. Objectives:The objective of this study is to identify the causative organisms of active chronic active otitis media both (mucosal, squamous) type and test their sensitivity to various anti- microbial agents &compare with abroad studies.Methods:A prospective study was done on eighty patients, different ages and sexes were taken and carful history and examination was done, examination under microscope was done with carf

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an