Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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

The specific activities of the natural radionuclides U-238 and Th-
232 and K-40 in 14 soil samples collected from different sites from
AL-Mustansiriyah university at two depths (topsoil "surface" and
20cm depth) were be investigated using gamma ray spectrometer
3"x3" NaI(Tl) scintillation detector.
The analysis of the energy spectra of the soil samples show that
these samples have specific activities ranging with (16.08-51.11)
Bq/kg for U-238, (14.79-52.29) Bq/kg for Th-232 and (191.08-
377.64) Bq/kg for K-40, with an average values of 29.37, 34.14 and
289.62 Bq/kg for U-238, Th-232, k-40 respectively. The radiation
hazard parameters of the natural radionuclides; radium equivalent
activity (Raeq), gamma a

The aim of the current research is to identify the impact of the SWOT strategy on developing systemic intelligence among students of the Ibn Rushd College of Education for Human Sciences University of Baghdad / College of Education Ibn Rushd for Human Sciences. The current research community consists of (8590) male and female students, divided into (7) departments. The current research relied on one of the partial control designs, which is the design of non-random groups: experimental group and a control group with a pre and post-test. As for the research tool, It was represented by Tourmanin’s Systemic Intelligence Scale (2012) of (50) items that measure the eight components of systemic intelligence. The results of the Mann Whitney te

Nano gamma alumina was prepared by double hydrolysis process using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, hydroxyle poly acid and CTAB (cetyltrimethylammonium bromide) as templates. Different crystallization temperatures (120, 140, 160, and 180) ⁰C and calcinations temperatures (500, 550, 600, and 650) ⁰C were applied. All the batches were prepared at PH equals to 9. XRD diffraction technique and infrared Fourier transform spectroscopy were used to investigate the phase formation and the optical properties of the nano gamma alumina. N₂ adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the particle size and the