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
An efficient modification and a novel technique combining the homotopy concept with Adomian decomposition method (ADM) to obtain an accurate analytical solution for Riccati matrix delay differential equation (RMDDE) is introduced in this paper . Both methods are very efficient and effective. The whole integral part of ADM is used instead of the integral part of homotopy technique. The major feature in current technique gives us a large convergence region of iterative approximate solutions .The results acquired by this technique give better approximations for a larger region as well as previously. Finally, the results conducted via suggesting an efficient and easy technique, and may be addressed to other non-linear problems.
A total number of 33 isolates of Pseudomoans aeruginosa were collected from different clinical samples, such as: burn, wound and urine from patients attending Al-Yarmouk teaching hospital and some private clinical laboratories in Baghdad city through the period from October to December 2016. On the other hand, 21 isolates of P. aeruginosa were collected from 38 different food samples; such as: vegetables and fruits, from different local markets in Baghdad city during the period from November to December 2016. All isolates were identified by using different bacteriological and biochemical assays and confirmed by Vitek-2 identification system. The antimicrobial susceptibility test for clinical and food isolates towards 17 antimicrobial a
... Show Moreكيف بنى الشاعر العربي القديم قصيدته موسيقيا ؟ ولماذا تقوم هذه القصيدة على معمار إيقاعي معين دون غيره ؟ ولماذا صار ذلك البناء سمة لتشكيل ذائقتنا الشعرية وترديد مسارها ـ الذي لا يكاد يشابهه ما لدى الأمم الأخرى ـ حتى عصرنا الراهن هذِا ؟ وما علاقة البناء الموسيقي بالانفعالات الشعورية والنفسية المشتجرة في ذات المبدع ؟
The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion
... Show MoreAbstract The Object of the study aims to identify the effectiveness of using the 7E’s learning cycle to learn movement chains on uneven bars, for this purpose, we used the method SPSS. On a sample composed (20) students on collage of physical education at the university of Baghdad Chosen as two groups experimental and control group (10) student for each group, and for data collection, we used SPSS After collecting the results and having treated them statistically, we conclude the use 7E’s learning cycle has achieved remarkable positive progress, but it has diverged between to methods, On this basis, the study recommended the necessity of applying 7E’s learning cycle strategy in learning the movement chain on uneven bar
... Show MoreWith the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative
... Show More