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
These factors, as well as disasters and wars that the Arab homeland exposed to and still under this exposure, in addition to the severe stress upon.
Iraqi Academics have been subjected to direct consequences of 2003 war. Exact figures are not known. It was mentioned. Many people were killed, sacked from their academics jobs, threatened to leave directly or indirectly their jobs, houses, and Iraq. Others have been imprisoned, tortured, or kidnapped / threatened to be kidnapped etc. Their families have been subjected to similar traumatic experiences or threats. All theses stressors may have lead to Post Traumatic (PTSD) Experiences. These Traumatic experiences have lead to Dislocation, relocation and Immigration etc. All sectors of
... Show MoreToday’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin
... Show MoreAll major organs may be impacted by the connective disease systemic lupus erythematosus, a separate risk factor for coronary artery disease (CAD). Adhesion molecules like intercellular adhesion molecules (ICAM) and vascular cell adhesion molecules (VCAM) can detect endothelial damage and dysfunction, which appear to play a crucial role. This study investigated whether people with SLE had elevated subclinical and clinical atherosclerosis risk factors. Traditional CAD risk factors such as smoking, hypertension, and hyperlipidemia cannot entirely explain this elevation. It is thought that immunological dysfunction also increases CAD risk in SLE patients. The study aimed to assess early endothelial changes in SLE Iraqi female patients w
... Show MoreMagnetic Resonance Imaging (MRI) uses magnetization and radio waves, rather than x-rays to make very detailed, cross- sectional pictures of the brain. In this work we are going to explain some procedures belongs contrast and brightness improvement which is very important in the improvement the image quality such as the manipulation with the image histogram. Its has been explained in this worked the histogram shrink i.e. reducing the size of the gray level gives a dim low contrast picture is produced, where, the histogram stretching of the gray level was distributed on a wide scale but there is no increase in the number of pixels in the bright region. The histogram equalization has also been discuss together with its effects of the improveme
... Show MoreSurveillance cameras are video cameras used for the purpose of observing an area. They are often connected to a recording device or IP network, and may be watched by a security guard or law enforcement officer. In case of location have less percentage of movement (like home courtyard during night); then we need to check whole recorded video to show where and when that motion occur which are wasting in time. So this paper aims at processing the real time video captured by a Webcam to detect motion in the Scene using MATLAB 2012a, with keeping in mind that camera still recorded which means real time detection. The results show accuracy and efficiency in detecting motion
Among the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe
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