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

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Abstract: The article aimed to formulate an MLX binary ethosome hydrogel for topical delivery to escalate MLX solubility, facilitate dermal permeation, avoid systemic adverse events, and compare the permeation flux and efficacy with the classical type. MLX ethosomes were prepared using the hot method according to the Box–Behnken experimental design. The formulation was implemented according to 16 design formulas with four center points. Independent variables were (soya lecithin, ethanol, and propylene glycol concentrations) and dependent variables (vesicle size, dispersity index, encapsulation efficiency, and zeta potential). The design suggested the optimized formula (MLX−Ethos−OF) with the highest desirability to perform the

          The objective of the present investigation was to enhance the solubility of practically insoluble mirtazapine by preparing nanosuspension, prepared by using solvent anti solvent technology. Mirtazapine is practically insoluble in water which act as antidepressant .It was prepared as nano particles in order to improve its solubility and dissolution rate. Twenty formulas were prepared and different stabilizing agents were used with different concentrations such as poly vinyl pyrrolidone (PVPK-90), poly vinyl alcohol (PVA), poloxamer 188 and poloxamer 407. The ratios of drug to stabilizers used to prepare the nanoparticles were 1: 1 and 1:2. The prepared nanoparticles were evaluated for

Profit is a goal sought by all banks because it brings them income and guarantees them survival and continuity, and on the other hand, facing commitments without financial crisis. Hence the idea of research in his quest to build scientific tools and means that can help bank management in particular, investors, lenders and others to predict financial failure and to detect early financial failures. The research has produced a number of conclusions, the most important of which is that all Islamic banks sample a safe case of financial failure under the Altman model, while according to the Springate model all Islamic banks sample a search for a financial failure except the Islamic Bank of Noor Iraq for Investment and Finance )BINI(. A

Banks are considered the main basis of financial sector ,so they must be submitted to sound and strict regulatory system and so as to ensure their operations and according to instructions and regulations , in order to maintain the integrity of the banking sector and financial sector in general .One of the importance regulatory tools that are adopted by the Iraqi Central Bank to control over the banks an financial and periodic statements that are provided by the banks in accordance with planned schedules .The financial statements of the banks must reflect clearly and accurately financial situation and the result of their activities during the period in which they represent to achiveing its purposes.So it has the goal of Search is statemen

This research aims to identify the effective role of self-managed teams in the quality of service performance in the directorate of Ramadi municipality. The problematic nature of our research involves this main question of the effective role of self-managed teams in the Municipality of Ramadi in improving the services of performance quality to the beneficiaries from the Directorate service. The importance of this study lies in the role played by the work teams in the organizations that excel in their field, the attendant of the changes in the leadership, administrative roles of the institutions, and teams leaders, will be achieved by the self-managed teams in improving the quality of the service provided by the institution to whi

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the