Diyala Governorate has many unique and diverse geomorphological features that the region enjoys, which are among the attractions for natural tourism, as the natural environment is considered a maker of tourism. The importance of geomorphological aspects as components of natural tourism is due to their association with tourism and entertainment, as a result of the enjoyment of many geomorphological aspects of the beauty of its natural landscape on the one hand, and on the other hand, the association of these manifestations with different types of tourism activity. Any tourist area as it is the main factor for tourist attractions, such as the presence of the Hamrin hills, and sand dunes. Planning for the development of tourism activity in the

The aesthetic dimension in popular subjects is one of the important topics in the history and culture of peoples, as it is the vessel from which their faith, traditions, original values, language, ideas, practices and way of life are derived, which expresses their culture and national identity, and it is the bridge of communication between generations throughout the ages.

It is one of the main pillars in the process of development and development, and popular subjects have special images related to real daily life, and they are the best source for man to narrate through him in his portrayal of daily life in general, and for the artist in particular, who is part of this daily life and its vocabulary, as he interacts with it so that

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

In this study, the modified size-strain plot (SSP) method was used to analyze the x-ray diffraction lines pattern of diffraction lines (1 0 1), (1 2 1), (2 0 2), (0 4 2), (2 4 2) for the calcium titanate(CaTiO3) nanoparticles, and to calculate lattice strain, crystallite size, stress, and energy density, using three models: uniform (USDM). With a lattice strain of (2.147201889), a stress of (0.267452615X10), and an energy density of (2.900651X10-3 KJ/m3), the crystallite was 32.29477611 nm in size, and to calculate lattice strain of Scherrer (4.1644598X10−3), and (1.509066023X10−6 KJ/m3), a stress of(6.403949183X10−4MPa) and (26.019894 nm).

Background: The association between diabetes and inflammatory dental diseases had been studied extensively for more than 50 years. A large evidence base suggests that diabetes is associated with an increased prevalence, extent and severity of gingivitis and periodontitis and loss of teeth. Many patients do not aware that they are diabetic.Objectives:The aim of the current study was to assess a fast, non-invasive, safe procedure to screen for diabetes and its severity in dental clinics and to assess the change in blood glucose level before and after tooth extraction during periodontalResults: there were no significant differences between the blood samples collected before tooth extraction from finger puncture method (FPB) and the gingival

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an