Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Samples (4th) reviewed are deposited and stored in the Iraqi Natural History Museum (INHM), and there are 4th of them. Sciurus anomalous (Güldenstädt, 1785) species are preserved and mummified. It is a Caucasian squirrel (S. anomalus) that was medium in size, with a grayish-to-chestnut color, a golden gray back, and a golden tail. It is found in the forests of East and Southeast Asia. The variety possessed for the study was previously registered in the vertebrate literature by several authors and was stored by scientific methods in the museum. As a result of the multiplication and growth of these species, and to know the environmental changes that occurred in them, they were compared with models and samples found throughout Iraq

ZSM-5 zeolite was synthesis under hydrothermal conditions at 175^oC. The synthesis parameters have been investigated to find optimum synthesis method. Firstly, the crystallization time has been investigated to find the optimum crystallization time. Also, the ageing time was studied. The morphology, structure, and composition of the synthesized ZSM-5 zeolite were characterized using scanning electron microscopy (SEM), pH meter, viscometer, and X-ray powder diffraction (XRD). The bulk Si/Al ratio of ZSM-5 zeolite was in the range of 9.5—11.7. The synthesized ZSM-5 zeolite with appropriate ageing time could adjust crystal size and degree of the crystallinity. The crystal size of ZSM-5 zeolite obtained at an agei

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

The issue of the research lies in the non-representation of the models developed for the communication process in the interaction and networking processes through social media, as the research sought to build a network model of communication according to the specific data and features of social media platforms in order to reach a special generalization to understand how the process of networking operates in cyberspace.

The researcher followed the analytical survey approach as she described the communication models outwardly in order to be able to build a networked communication model that represents the flow of post-reactive communication. Therefore, it has been named "Nebula - Sadeem" after the concept of post-space and cosmic g