Civil environment in nursing education enhances achieving learning outcomes. Addressing incivility can be crucial to improve academic achievements. The purpose of this study was examining the psychometric properties of the Arabic version of the Incivility in Nursing Education-Revised scale regarding nursing faculty.

The aim of the current research is to recognizing the impact of mind and informational strategy on the achievement with the second intermediate students in the grammar of arabic language, the researcher used a partial-set experimental design and intentionally selected a sample out of the second intermediate class from (AL- Markazya Intermediate school) in the district of Hilla, affiliated which belongs to General Directorate of Babylon Education in the year (2020-2021) for applying the experiment. The sample was composed of (50) students, (25) ones for each group, the experimental group and normal one. The researcher balanced between the two groups in various changes including: (the chronological age counted by months, the academic achie

This study sought to understand how critical cultural awareness was in translating English idioms into Arabic, particularly in political news where clarity and precision are paramount. The challenges that arise from the linguistic and cultural disparities between the two languages include differences in metaphor, image, and cultural reference. The study demonstrates, through the lens of Skopos Theory, how efficient translation relies on the function and intent of the text taking precedence over word-for-word equivalence and cultural context. Overall, the study establishes the need to transform idioms so that they better align with what is appropriate given the expectations of the audience. The results highlight the importance of inn

Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,

Hand gestures are currently considered one of the most accurate ways to communicate in many applications, such as sign language, controlling robots, the virtual world, smart homes, and the field of video games. Several techniques are used to detect and classify hand gestures, for instance using gloves that contain several sensors or depending on computer vision. In this work, computer vision is utilized instead of using gloves to control the robot's movement. That is because gloves need complicated electrical connections that limit user mobility, sensors may be costly to replace, and gloves can spread skin illnesses between users. Based on computer vision, the MediaPipe (MP) method is used. This method is a modern method that is discover

Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

There has been a great deal of research into the considerable challenge of managing of traffic at road junctions; its application to vehicular ad hoc network (VANET) has proved to be of great interest in the developed world. Dynamic topology is one of the vital challenges facing VANET; as a result, routing of packets to their destination successfully and efficiently is a non-simplistic undertaking. This paper presents a MDORA, an efficient and uncomplicated algorithm enabling intelligent wireless vehicular communications. MDORA is a robust routing algorithm that facilitates reliable routing through communication between vehicles. As a position-based routing technique, the MDORA algorithm, vehicles' precise locations are used to establish th