Discrete Racah polynomials (DRPs) are considered essential for several applications such as approximation theory, quantum physics, and digital signal processing. However, the computation of high-order DRPs presents significant numerical and computational challenges. Even though the recent advancements in algorithms have improved numerical stability, the inherently sequential nature of these algorithms continues to be a bottleneck for large-scale implementations. This paper proposes a new multithreading-based algorithm for computing the DRP coefficients. The proposed algorithm is designed to accelerate the computation of high-order DRPs by considering the advantages of the independence of different tasks and the ability to process mu

The current study aimed to standardize the multi-position suicidal tendency scale MAST in the Saudi environment as well as to assess suicidal tendencies in adolescents. Moreover, the study aimed to test the psychometric characteristics of the scale among a sample of (490) high school and undergraduate students, in the adolescence who ranging in age from (16-21) years. The scale demonstrated satisfactory internal consistency in terms of validity and reliability tests. as the results showed of exploratory factor analysis to the four dimensions of suicidal tendencies loading on two factors that accommodate 74.60% of the overall variance of the scale (1) the attitude toward life,  and absorbs 43, 20% of the total variance of the scale,

Utilizing phase change materials in thermal energy storage systems is commonly considered as an alternative solution for the effective use of energy. This study presents numerical simulations of the charging process for a multitube latent heat thermal energy storage system. A thermal energy storage model, consisting of five tubes of heat transfer fluids, was investigated using Rubitherm phase change material (RT35) as the. The locations of the tubes were optimized by applying the Taguchi method. The thermal behavior of the unit was evaluated by considering the liquid fraction graphs, streamlines, and isotherm contours. The numerical model was first verified compared with existed experimental data from the literature. The outcomes re

Precise and interpretable classification of autism-related behaviors is important for initial diagnosis, personalized intervention, and support arrangements. This study proposes an interpretable machine learning (ML) model using Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) to classify behavioral patterns into four categories (normal, mild, moderate, and severe) associated with Autism Spectrum Disorder (ASD) based on a custom 377-instance survey dataset from Iraqi parents and teachers of children aged 6-12. The model observes 16 key features across communication and social interaction, repetitive behaviors, language, and adaptive skills, preprocessed via interquartile range (IQR) outlier removal, me

Focused research aims to provide a framework cognitive analytical nature of real estate investments and how they evaluated in the light of the assessment tools of modern theory of real options, and the possibility to rely on that theory in the detection of the true value of projects, real estate investments that would maximize the value of the investment decision taken, and the analysis of those projects that arise in the real estate markets and environments is the organization, which she was to make sure cases and high-risk, compared with entrances techniques, discounted cash flow (net present value). Based on the assumption lies in the possibility of the application of the implic

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