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

An approach is depended in the recent years to distinguish any author or writer from other by analyzing his writings or essays. This is done by analyzing the syllables of writings of an author. The syllable is composed of two letters; therefore the words of the writing are fragmented to syllables and extract the most frequency syllables to become trait of that author. The research work depend on analyzed the frequency syllables in two cases, the first, when there is a space between the words, the second, when these spaces are ignored. The results is obtained from a program which scan the syllables in the text file, the performance is best in the first case since the sequence of the selected syllables is higher than the same syllables in

A new, simple, sensitive and fast developed method was used for the determination of methyldopa in pure and pharmaceutical formulations by using continuous flow injection analysis. This method is based on formation a burgundy color complex between methyldopa andammonium ceric (IV) nitrate in aqueous medium using long distance chasing photometer NAG-ADF-300-2. The linear range for calibration graph was 0.05-8.3 mmol/L for cell A and 0.1-8.5 mmol/L for cell B, and LOD 952.8000 ng /200 µL for cell A and 3.3348 µg /200 µL for cell B respectively with correlation coefficient (r) 0.9994 for cell A and 0.9991 for cell B, RSD % was lower than 1 % for n=8. The results were compared with classical method UV-Spectrophotometric at λ max=280 n

In this paper We introduce some new types of almost bi-periodic points in topological bitransfprmation groups and thier effects on some types of minimaliy in topological dynamics

        A newly developed analytical method was conducted for the determination of Ketotifen fumarate (KTF) in pharmaceuticals drugs via quenching of continuous fluorescence of 9(10H)-Acridone (ACD). The method was applied using flow injection system of a new homemade ISNAG fluorimeter with fluorescence measurements at ± 90◦ via 2×4 solar cell. The calibration graph was linear in the range of 1-45 mmol/L, with correlation coefficient r = 0.9762 and the limit of detection 29.785 µg/sample from the stepwise dilution for the minimum concentration in the linear dynamic ranged of the calibration graph. The method was successfully applied to the determination of Ketotifen fumarate in two different pharma

This study has applied the theoretical framework of conceptual metaphor theory to the analysis of the source and target domains of metaphors that are used in two English nineteenth century sonnets, both written by contemporaneous female poets. The quantitative and qualitative results of the textual analysis have clearly revealed that Elizabeth Barrett Browning’s sonnet 23 centres around the conceptual mapping of the journey of love and life with that of possession. In contrast, Christina Rossetti’s sonnet Remember tackles the central conceptual mapping of death as a journey in relation to its further experiential connections. In addition, the application of conceptual metaphor theory in identifying the frequencies and densities of metap