The digital dermatoglyphics were studied in 120 females derived from northern region of Iraq (60 Arabs and 60 Kurds). Two kinds of analyses were perfomed : Quantitative and Qualtative. The unilateral and bilateral analyses for dermal ridge counts in each digital and the overall did not reveal any significant difference when t-test was used. A high correlation coefficients were revealed in this study between homologous and adjacent digits, moreover, significant differences were revealed between Arabian and Kurdish samples in both analyses when Fisher Z transform test was used, but the significant differences in the bilateral analysis exceed the ones in the unilateral. This indicates the importance of the former analysis in detecting the vari

The communication inspiration formed an essential foundations for contribute the influence individuals and recipients, whether negatively or positively, through the messages that were published and presented in them with multiple themes and viewpoints that covered all parts of the world and all age groups; it is directed to children addressing the various stages of childhood, as it simulates many goals, including what is directed through the digital use of educational data in television production, as it is considered an intellectual and mental bag to deliver ideas and expressive and aesthetic connotations to children, where the songs and cartoons carrying data on education; within adjacent relations and in a mutual direction, both of th

Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse

Background: The integration of modern computer-aided design and manufacturing technologies in diagnosis, treatment planning, and appliance construction is changing the way in which orthodontic treatment is provided to patients. The aim of this study is to assess the validity of digital and rapid prototyped orthodontic study models as compared to their original stone models. Materials and methods: The sample of the study consisted of 30 study models with well-aligned, Angle Class I malocclusion. The models were digitized with desktop scanner to create digital models. Digital files were then converted to plastic physical casts using prototyping machine, which utilizes the fused deposition modeling technology. Polylactic acid polymer was chose

Digital literacy is crucial in the modern workforce, where technology plays an integral role in daily operations. This abstract explores the significance of digital literacy in enhancing productivity, efficiency, and competitiveness in the workplace. Digital literacy encompasses the ability to use and navigate digital tools and platforms effectively, including software, applications, and online communication tools. In today's digital age, employers increasingly value candidates with strong digital skills, as they are better equipped to adapt to rapidly evolving technologies. This abstract highlights the importance of digital literacy in empowering employees to perform tasks more efficiently, collaborate seamlessly, and innovate effecti

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

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Dylan Thomas (1914-1953) is a modern poet belongs to the apocalyptic movement of the 1940's.This movement is influenced by the doctrines and techniques of surrealism.

              Poetry for him should not be primarily concerned with man in society, but with the celebration of spiritual truth. It should bring to light the hidden causes, hence  his personal interest is to strip darkness and explore the inward motives. To do this he uses a cluster of images: a constant building up and breaking down of images. His poetry depends on the romantic spontaneity, suggestiveness of the Symbolists and the the surrealists' mysterious liberation of the unconsciousness and