Background: The use of the cone beam computed tomography for analysing the position of the greater palatine foramen in relation to various anatomical landmarks is crucial in dentistry. The aims of the current study, firstly is to determine the greater palatine foramen position in relation to various anatomical landmarks by using cone beam computed tomography and secondly is to make a comparison of the measurements according to side, gender, and age. Materials and methods: This prospective study included 60 Iraqi patients (28males and 32 females) who selected according to availability of Inclusion criteria, which include age range (21 - 60 years), with no dentofacial deformities or pathological lesion at the maxilla. All patients had inform

     The game theory has been applied to all situations where agents’ (people or companies) actions are utility-maximizing, and the collaborative offshoot of game theory has proven to be a robust tool for creating effective collaboration strategies in a broad range of applications. In this paper first, we employ the Banzhaf values to show the potential cost to waste producers in the case of a cooperation and to reduce the overall costs of processing non-recyclable waste during cooperation between producers. Secondly, we propose an application of the methodology to study a case for five waste producers' waste management in the Al-Mahmudiya factory with the aim of displaying the potential cost to waste producers in case of cooperatio

Despite scholars’ attention on the typology of modality as a linguistic phenomenon, yet the use of modality across varieties of English is not well visible in communication-based researches that take semantics, pragmatics and discourse issues as the objects for their investigation. The paper generates its data from six M. A. dissertations from Nigerian University and equal number of the M. A. dissertations from Iraqi University to qualitatively and quantitatively investigate the contextual use of modality within the pragmatic perspective. The data analysis reveals that modality such as usuality, potentiality, necessity, probability and obligation in the dissertations encapsulates interpersonal and authorial voice in which the mean

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Objectives: The study aims to assess the school refusal behavior of first class pupils at primary schools and identifying the relationship between the school refusal behavior and some of socio-demographic characteristics for the pupils.

Methodology:  A descriptive-analytic study was initiated from November 1^st, 2012 to April 1^st, 2013. A random sample of 411 students is selected from a probability stratified sample of 17 primary schools for both sexes in 4 sectors in Baghdad Al-Rasafa and Al-Karkh districts which are selected randomly from first class of primary school. A Self administrative questionnaire (Parents' Version) which constructed by the rese

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k