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 current research aims to shed light on the Global Reporting Initiative (GRI), which helps to report financial and non-financial information by economic units in general and listed on the Iraq Stock Exchange in particular. The research was based on a main premise that apply the criteria of the Global Reporting Initiative (GRI) would provide useful information to users to help them make appropriate decisions. To achieve the goal of the research, the descriptive analysis method was used, and quantitative analysis was used. At the level of the descriptive analysis method, a desk survey was conducted. As for the quantitative analysis, it relied on applied data through a questionnaire form (Questioners) as a research tool, and the
... Show MoreHydro cracking of heavy oil is used in refinery to produce invaluable products. In this research, a model of hydro cracking reactor has been used to study the behavior of heavy oil in hydro cracking under the conditions recommended by literature in terms lumping of feed and products. The lumping scheme is based on five lumps include: heavy oil, vacuum oil, distillates, naphtha and gases. The first order kinetics was assumed for the conversion in the model and the system is modeled as an isothermal tubular reactor. MATLAB 6.1 was used to solve the model for a five lump scheme for different values of feed velocity, and temperature.
Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor
... Show MoreOptimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni
... Show MoreThe recurrent somatic variations in
The aim of the study was to detect the frequency of R132 mutations in the
Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq
... Show MoreThe syntheses, characterization and experimental solid state X-ray structures of five low-spin paramagnetic 2-pyridyl-(1,2,3)-triazole-copper compounds, [Cu(Ln)2Cl2], are presented in this study, for the following five Ln ligands: L1 = 2-(1-(p-tolyl)-1H-(1,2,3-triazol-4-yl)pyridine), L2 = 2-(1-(4- chlorophenyl)-1H-(1,2,3-triazol-4-yl)pyridine), L3 = 4-(4-(pyridin-2-yl)-1H-(1,2,3-triazol-4-yl)benzonitril), L4 = 2-(1-phenyl-1H-(1,2,3-triazol-4-yl)pyridine) and L5 = 2-(1-(4-(trifluoromethyl)phenyl)-1H-(1,2,3- triazol-4-yl)pyridine). These five [Cu(Ln)2Cl2] complexes each contain two bidentate 2-pyridyl-(1,2,3)- triazole (Ln) and two chloride ions as ligands, with the Cu–N(pyridine) bonds, Cu–N(triazole) and Cu–Cl bonds trans to each othe
... Show Moreتعتبر إزالة الكبريت بالأكسدة العميقة موضوعًا مهمًا لأبحاث التحفيز البيئي لإنتاج الديزل منخفض الكبريت.أحد العوامل المساعدة التي تم استخدامها مؤخرًا لإزالة مركبات الكبريت المقاوم من نموذج الديزل بالاكسدة هو بولي أوكسوميتالات من نوع كيجن. في هذا العمل, تم اختبار العامل المساعد من نوع كيجن TBAPW11O39 , نموذج الديزل, بيروكسيد الهيدروجين(H2O2) وسائل ايوني من نوع OMIM(PF6)) تحت ظروف تفاعل مختلفة. تم التقاط مركب الكبريت ث
... Show MoreThis paper critically looks at the studies that investigated the Social Network Sites in the Arab region asking whether they made a practical addition to the field of information and communication sciences or not. The study tried to lift the ambiguity of the variety of names, as well as the most important theoretical and methodological approaches used by these studies highlighting its scientific limitations. The research discussed the most important concepts used by these studies such as Interactivity, Citizen Journalism, Public Sphere, and Social Capital and showed the problems of using them because each concept comes out of a specific view to these websites. The importation of these concepts from a cultural and social context to an Ara
... Show More