Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorder
Background: Coronary artery disease (CAD) is one of the leading causes of death worldwide. Clopidogrel, antiplatelet drug, has been widely used for management of CAD. Arylesterase, the activity of Paraoxonase-1 (PON-1), is mainly contributed in the biotransformation of clopidogrel to its active thiol form. The purpose of this study was to investigate the effect of receiving clopidogrel drug on the arylesterase activities in CAD patients. The effect of receiving clopidogrel drug on the antioxidant activity of arylesterase was also monitored by determination of malondialdehyde (MDA) level. Methods: One hundred CAD patients, who were followed-up for 5 days after reciving clopidogrel, and 50 healthy volunteers were included in our study
... Show MoreSupply Chain Management (SCM) attempts to a create a synchronization of the firm’s processes and those of the supplier to match the flow of materials, services, and information with the customer demand. Due to its importance, the SCM has become inevitable to modern companies. Therefore this research work has been conducted to set a theoretical and applied basis to assist the 1 AYAR factory in adopting the Electronic Supply Chain (e-SC). To accomplish that the searchers applied many tools such as: quantitative and qualitative analysis, process analysis, Visual Basic software, Monte Carlo Simulation to simulation the designed supply chain to compare its performance against the actual performance of the current supply chain
... Show MoreAbnormalities in the Lipid and lipoprotein levels are common in the general population and are considered as very important risk- factors for cardiovascular disease .In this context the effect of cholesterol, which is one of the most clinically relevant lipids is very important. Aim of the present study was to determine the levels of GLP-1 and GPCR in non- diabetic dyslipidaemic patients and compare the results with the control group, which may be used as a novel biomarker to predict heart disease in these patients. The study was also aimed to find the relationship between GLP-1 and GPCR with lipid profile and glucagon in the patient group. The study involved 90 non-diabetic dyslipidaemia patients, with 90 healthy controls. The subjects wer
... Show MoreBackground: This study aimed to determine the cephalometric values of tetragon analysis on a sample of Iraqi adults with normal occlusion. Material and methods: Forty digital true lateral cephalometric radiographs belong to 20 males and 20 females having normal dental relation were analyzed using AutoCAD program 2009. Descriptive statistics and sample comparison with Fastlicht norms were obtained. Results: The results showed that maxillary and mandibular incisors were more proclined and the maxillary/mandibular planes angle was lower in Iraqi sample than Caucasian sample. Conclusion: It's recommended to use result from this study when using tetragon analysis for Iraqis to get more accurate result.
A water resources management for earthen canal/stream is introduced through creating a combination procedure between a field study and the scientific analytical concepts that distinguish the hydraulic problems on this type of stream with using the facilities that are available in HECRAS software; aiming to point the solutions of these problems. Al Mahawil stream is an earthen canal which is subjected to periodic changes in cross sections due to scour, deposition, and incorrect periodic dredging processes due to growth of the Ceratophyllum plants and weeds on the bed and banks of the stream; which affect the characteristics of the flow. This research aims to present a strategy of water resources management through a field study that conducte
... Show MoreThe research aims to evaluate the radioactivity in elected samples of cereals and legume which are wide human consumption in Iraq using Nuclear Track Detectors (NTDs) model CN-85.
The samples were prepared scientifically according to references in this field. After 150 days of exposure, the detector were collected and chemically treated according to scientific sources (etching chemical), nuclear effects have been calculated using the optical microscope.
Radon (222Rn) concentration and uranium (238U) were calculated in unit Bq/m3 and (ppm), the results indicate that the highest concentration of radon and uranium was in yellow corn where the concentration of radon was 137.17×102 Bq/m3 and uranium concentration 2.63 (ppm). The lowest
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe purpose of this research is to identify heritage and highlight its value by drawing on its decorative vocabulary and integrating it with the Arabic calligraphy to revive the heritage in a contemporary style, and to create decorative design units inspired by Sadou and Arabic calligraphy and to employ them in the modern fashion designs. The applied descriptive approach has been used in this research, and the research community is made of women in Riyadh area. The tools used in this research were the questionnaire and the observation. The most important results of the research are: the design of decorative units from the integration of Arabic calligraphy and the decorations of the Saduo, and the use of these units in the design of the o
... Show MorePower switches require snubbing networks for driving single – phase industrial heaters. Designing these networks, for controlling the maximum allowable rate of rise of anode current (di/dt) and excessive anode – cathode voltage rise (dv/dt) of power switching devices as thyristors and Triacs, is usually achieved using conventional methods like Time Constant Method (TCM), resonance Method (RM), and Runge-Kutta Method (RKM). In this paper an alternative design methodology using Fuzzy Logic Method (FLM) is proposed for designing the snubber network to control the voltage and current changes. Results of FLM, with fewer rules requirements, show the close similarity with those of conventional design methods in such a network of a Triac drivin
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