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
In this study, the Earth's surface was studied in Razzaza Lake for 25 years, using remote sensing methods. Images of the satellites Landsat 5 (TM) and 8 (OLI) were used to study and determine the components of the land cover. The study covered the years 1995-2021 with an interval of 5 years, as this region is uninhabited, so the change in the land cover is slow. The land cover was divided into three main classes and seven subclasses and classified using the maximum likelihood classifier with the help of training sets collected to represent the classes that made up the land cover. The changes detected in the land cover were studied by considering 1995 as a reference year. It was found that there was a significant reduction in the water mass
... Show MoreThe outbreak of a current public health coronavirus 2019 disease is a causative agent of a serious acute respiratory syndrome and even death. COVID-19 has exposed to multi-suggested pharmaceutical agents to control this global disease. Baricitinib, a well-known antirheumatic agent, was one of them. This article reviews the likely pros and cons of baricitinib in attenuation of COVID-19 based on the mechanism of drug action as well as its pharmacokinetics. The inhibitory effect of baricitinib on receptor mediated endocytosis promoter, AKK1, and on JAK-STAT signaling pathway is benefacial in inhibition of both viral assembling and inflammation. Also, its pharmacokinetic has encouraged the physicians toward the drug
... Show MoreThis study is intended to examine the concept of transcultural identity in the travel book The Global Soul: Jet Lag, Shopping Malls, and the Search for Home by (Iyer, 2001). Jeffries’ model of critical stylistics (2010) (henceforth, CS) has been selected to analyze the book. To be more specific, Negation is selected to analyze the concept under study. As such, the study aims at finding out how Negation is used to portray ideological meanings representing the concept of transcultural identity in one non-fictional travel book; and finding out the ideologies related to the concept analyzed. The analysis of the data shows that Negation is a suitable analytical tool to reach the ideational meaning of the text towards the concept of tra
... Show MoreIn this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
... Show MoreA new series of Fe (III) , Co (II) , Ni (II) and Cu (II) complexes of the Schiff base, 5 (2-hydroxy benzylidine) -2-thio ether -1, 3, 4-thiadiazole were prepared and characterized .The imine behaves as a bidentate. The nature of bonding and the stereochemistry of the complexes were deduced from metal analyses, infrared, electronic spectra,magnetic susceptibility and conductivity measurements, an octahedral geometry was suggested for all complexes except the copper complex has a square planar geometry .preliminary in vitro tests for antimicrobial activity show that all the prepared compounds except iron complex display good activity to gram positive Staphelococcus aures and gram negative Escherchia coli.
Bulk AlxSb1-x samples were prepared with different x ratios (0.1, 0.3, 0.5, 0.7 and 0.9) by quenching technique. This was done throughout mixing the aluminum and antimony elements according to the proper atomic weight and put them in an evacuated quartz ampoule which then sealed and heated at 1273 K for five hours and left to cool in air. Thin films of AlxSb1-xwere prepared by using thermal evaporation under vacuum of 10-5 mbar on glass substrates at room temperature with deposition rate (10-15nm/min) at thickness of ∼ 500nm. The structures of AlxSb1-x bulk and thin films have been studied by X–ray diffraction technique. The results showed that all alloys have polycrystalline structures and the p
Pure cadmium oxide films (CdO) and doped with zinc were prepared at different atomic ratios using a pulsed laser deposition technique using an ND-YAG laser from the targets of the pressed powder capsules. X-ray diffraction measurements showed a cubic-shaped of CdO structure. Another phase appeared, especially in high percentages of zinc, corresponding to the hexagonal structure of zinc. The degree of crystallinity, as well as the crystal size, increased with the increase of the zinc ratio for the used targets. The atomic force microscopy measurements showed that increasing the dopant percentage leads to an increase in the size of the nanoparticles, the particle size distribution was irregular and wide, in addition, to increase the surfac
... Show MoreBackground: Cyclophosphamide (Cpd), a common immunosuppressive and chemotherapeutic drug, can cause hepatotoxicity by inducing inflammation and oxidative stress. Dapagliflozin (Dapa) and other sodium-glucose cotransporter-2 inhibitors (SGLT2i) have anti-inflammatory and antioxidant properties, and Silymarin is a natural compound extracted from the seeds of the milk thistle plant (Silybum marianum). It is best known for its antioxidant, anti-inflammatory, and hepatoprotective effects.Objective: By measuring oxidative stress, inflammation, and liver regeneration parameters, with an emphasis on the Nrf2/HO-1 pathway and hepatocyte nuclear factors (HNF4α and HNF6), Dapa's hepatoprotective effects in comparison to Sil on Cpd-induced liv
... Show MoreThe research aims to measure the extent of the impact of Earnings quality in the continuity of the company for a sample of private commercial banks listed on the Iraq Stock Exchange. The research sample included (15) of the listed commercial banks that continue to issue their financial statements for the period from (2009-2018).The research relied on three main models of measurement and on four steps. The first step is to measure the Persistence (Earnings Quality) by Depending the sustainability model. While the second step included measuring the Predictability of accounting profits by deriving the square root of the disparity of the estimation error from the first model Persistence (Earnings Quality), and the third step included
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