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
The aim of this study is to evaluate oxidative stress in diabetes mellitus (DM) Type1 by the measurement of Glucose-6-phosphate Dehydrogenase (G-6-PD), an enzyme expressed in human RBCs, is important in the generation of reduced glutathione which is the key product in oxidative stress controls. The Study was carried on 80 samples of blood and serum of National Diabetes Center (NDC). The study groups under fasting conditions and they divided as:20 samples of diabetes mellitus patients without complications and 20 samples of diabetes mellitus with cardiovascular (CV) complications and 20 samples of diabetes mellitus with Nephropathy (Neph) complications compared with 20 control group with average age (13-67) years.. The results sh
... Show Morethe Current research aims to identify the psychological stressors coping strategies and their relationship to the cognitive motivation among Al-Anbar University students through the following hypotheses: 1) no statistically significant differences at a level (0.05) among the sample according to the instrumental support strategy depending on the variable type and specialization, 2) No statistically significant differences at a level (0.05) among the sample in regard of coping avoiding strategy depending on the variable type and specialization, 3) There is no statistically significant difference at a level (0.05) in cognitive motivation level among Al-Anbar University students, 4) No statistically significant differences at a level (0.05)
... Show MoreSuccess in selecting the best among the sources of supply is one of the most important factors in the efficiency of the procurement activity in the company, because the proper selection of the source of the supply significantly affect the achievement of what is desired by the factors of quality, quantity, price and service, and the ability of the competent supplier to meet everything associated with this Factors of commitments, hereby supporting the procurement function's efforts to fully discharge its responsibilities, and in view of adopting of Al-Furat company quality management system by applying the standards of ISO (9001: 2015) and purpose of getting the on-demand benefits from the application of international standards reg
... Show MoreImage compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreThe aim of the current research is to know the degree to which middle school teachers and female teachers in the southern border schools use electronic educational alternatives in the field of education from their point of view and its relationship to some variables, and to achieve this goal, a random sample of (200) teachers was selected in southern border schools, and a questionnaire was prepared to collect The data, as well as the descriptive approach was used to achieve this goal. T-test and analysis of variance were used for the statistical treatment. The results concluded that the educational courses provided to male and female teachers are not sufficient. It has also been concluded that the use of electronic educational alternativ
... Show MoreThe purpose of this study is to illuminate the role of CBCT in forensic dentistry through variations of mandibular measurements of Bonwill’s triangles in gender determination among the Iraqi population.
In this retrospective study 70 CBCT scans were analyzed to measure the Bonwill’s triangle, 35 for males and 35 for females aged between 20 and 50 years, all data were collected at the oral and maxillofacial radiology department in Ghazi AL-Hariri hospital for 3 months, and the data were obtained using a Kavo CBCT device (3D On De
Laser scanning has become a popular technique for the acquisition of digital models in the field of cultural heritage conservation and restoration nowadays. Many archaeological sites were lost, damaged, or faded, rather than being passed on to future generations due to many natural or human risks. It is still a challenge to accurately produce the digital and physical model of the missing regions or parts of our cultural heritage objects and restore damaged artefacts. The typical manual restoration can become a tedious and error-prone process; also can cause secondary damage to the relics. Therefore, in this paper, the automatic digital application process of 3D laser modelling of arte