Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

the visual and aesthetic characteristics of the city depending on understanding several levels of visual and aesthetic characteristics to the city, starting with the study of the physical characteristics and morphology of the city in general, and urban style to it, and then study of visual composition of the city from the optical components that affect the composition of the image (visual composition) of the city represent by pathways, borders, regions and the specific features as classified by (Kevin Lynch), and then studying the details and the attention of all elements that would confer the beautiful appearance as necessary for the needs of society and the environment in general, for example, interest in the distribution and c

In this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for

Background: Depression in elderly aged (60 year and above )is a widespread mental health problem . The current primary healthcare systeminadequately recognize and treat elderly  patients with depression..

Objectives:To determine the prevalence of depression among elderly patientsin Mosul city, its correlation with some sociodemographic variablesand to assess severity of depression in relation to past history of depression.

Type of the study: This is a cross-sectional study.

Methods: This study assess the  prevalence of depression in a randomly selected sample 150 elderly patients aged 60 years and above (89 female &