The research topic is summarized in the importance of studying the measuring the extent of the university youth’s exposure in the Emirati Society to those series and the resulting achieved satisfaction. The most important results and recommendations of the study are as follows: a high rate of the respondents’, sample individuals, exposure to the dubbed Turkish series since it is evident that almost three-fourths of the study individuals watch the dubbed Turkish series,.”. The most significant positive aspects of the dubbed Turkish series are: “they focus on the most important tourist attractions in Turkey” and “ improving the audience›s knowledge and information on the traditions of the Turkish society”. The most apparent

Arid and semi-arid climates are critical for water security in sustainable river systems. The Euphrates River in western Iraq has been increasingly stressed by both geogenic and anthropogenic factors. This study analyzed hydro-geochemical processes, recharge dynamics, and groundwater flow modeling in western Iraq. Additionally, stable isotope tracing (δ¹⁸O, Cl⁻) integrated with hydro-chemical parameters was used to assess water quality and river-aquifer connectivity in both Syria and western Iraq. A total of 144 groundwater samples were collected annually across 12 stations in western Iraq. Surface water and groundwater data were collected from previous studies at 13 stations in Syria. Results revealed slightly alkaline freshwater con

The main objective of this study was to evaluate the adsorption efficiency of two adsorbent materials, Iraqi chicken eggshells (ESh) and activated carbon (AC) derived from ESh powder for the removal of a cationic dye (Janus green B; JGD) from aqueous solution. Activated carbon was synthesised from ESh using a simple chemical activation method using phosphoric acid as the activating agent. The physicochemical properties of the adsorbents were characterised by the Brunauer–Emmett–Teller (BET) method, FT-IR spectroscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), inductively coupled plasma optical emission spectroscopy (ICP-OES), and point of zero charge (pHpzc). The results of BET analysis confirmed th

Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info

Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is conclud

Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing