Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

The best means and ways to develop an athlete's physical and skill capabilities, and among these means is the use of training aids that help develop some bio-kinetic abilities, and prepared exercises have had an important role in improving athletic performance in badminton, where the player must possess physical fitness, explosive power, and strength. Characterized by speed as well as accuracy, awareness, and focus while playing on the court, the badminton player must be physically fit through a continuous movement of small and large muscles to achieve good performance, which requires special physical abilities and skills, and the most important of these bio-kinetic abilities are agility, coordination, and measuring the coordination

Background: The use of electronic apex locators for working length determination eliminates many of the problems associated with the radiographic measurements (interference of anatomical structures, errors in projection such as elongation or shortening, and lack of three-dimensional representation). Its most important advantage over radiography is that it measures the length of the root canal to the apical constriction, not to the radiographic apex. The aim of this study was to assess the accuracy of a new fifth generation apex locator (Joypex 5) in recording the apical constriction and comparing it with a third generation apex locator (Root ZX) in vitro. Materials and method: Twenty four single-rooted sound human premolars, extracted for t

Background; Perforated duodenal ulcer (PDU) is a common surgical emergency that is associated with high mortality and morbidity. Early diagnosis and prompt surgical treatment is required to prevent grave complications.
Objective; The study was designed to evaluate the diagnostic accuracy of different radiological investigations in the diagnosis of perforated duodenal ulcer.
Methods; A prospective study of 185 pts with PDU at al kindy teaching hospital, Baghdad, Iraq from June 2008- august 2010. patients were examined clinically and investigated by blood test, chest x ray, plain X ray of the abdomen. Ultrasonography (U/S) and CT scanning done for those patients with negative X- ray finding. Resuscitation by intravenous fluid and ant

Sol-gel method was use to prepare Ag-SiO2 nanoparticles. Crystal structure of the nanocomposite was investigated by means of X-ray diffraction patterns while the color intensity was evaluated by spectrophotometry. The morphology analysis using atomic force microscopy showed that the average grain sizes were in range (68.96-75.81 nm) for all samples. The characterization of Ag-SiO2 nanoparticles were investigated by using Scanning Electron Microscopy (SEM). Ag-SiO2 NPs are highly stable and have significant effect on both Gram positive and negative bacteria. Antibacterial properties of the nanocomposite were tested with the use of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The results have shown antibacteri

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

Background: Bell's palsy was defined as facial weakness of lower motor neuron type caused by idiopathic facial nerve involvement outside the central nervous system without evidence of aural or more widespread neurologic disease. The cause is unclear, but the disorder occurs more commonly in diabetics.Objectives: to differentiate cases of idiopathic Bell's palsy from diabetic mononeuropathy presented with Facial nerve palsy by assessing the taste, because they differ in etiology, management & prognosis.Patients &Methods: One hundred and fifteen consecutive patients were referred for the treatment of facial palsy, from May the 5th 2012 to April 12th 2013 in Al-Kindy Teaching Hospital and The Neurosciences Hospital, in Baghdad / Ira

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Due to severe scouring, many bridges failed worldwide. Therefore, the safety of the existing bridge (after contrition) mainly depends on the continuous monitoring of local scour at the substructure. However, the bridge's safety before construction mainly depends on the consideration of local scour estimation at the bridge substructure. Estimating the local scour at the bridge piers is usually done using the available formulae. Almost all the formulae used in estimating local scour at the bridge piers were derived from laboratory data. It is essential to test the performance of proposed local scour formulae using field data. In this study, the performance of selected bridge scours estimation formulae was validated and sta