The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the

This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF)

Introduction/Aim. Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in pediatric population and adolescents. Limited data is available on the characteristics of RMS in Iraqi pediatric patients. The aim of the study was to examine the clinical and histological aspects of RMS in Iraqi children, with a focus on their response to treatment, prognosis, and survival. Methods. A retrospective cohort study was conducted at the Oncology Unit of Children's Welfare Teaching Hospital, Medical City, Baghdad, Iraq and included patients who were newly diagnosed with RMS and received treatment during the period between January 1, 2015, and December 31, 2019. The patients were followed up from the time of diagnosis until October 1, 2020.

This research will cover different aspects of estimating process of construction work in a desert area. The inherent difficulties which accompany the cost estimating of the construction works in desert environment in a developing country, will stem from the limited information available, resources scarcity, low level of skilled workers, the prevailing severe weather conditions and many others, which definitely don't provide a fair, reliable and accurate estimation. This study tries to present unit price to estimate the cost in preliminary phase of a project.  Estimations are supported by developing mathematical equations based on the historical data of maintenance, new construction of managerial and school projects.

The Research aims to investigate into reality in terms of planning and scheduling management process for sake the implementation and maintenance of irrigation and drainage projects in the Republic of Iraq, with an indication of the most important obstacles that impede the planning and scheduling management process for these projects and ways of addressing them and minimizing their effects.                                                  For the purpose of achieving the goal of the research, a sci

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

     A new colorimetric-flow injection method has been developed and validated for the detection of Cefotaxime sodium in pharmaceutical formulations. This method stands out for its rapid and sensitive nature. The formation of a brown-colored complex between Cefotaxime sodium and the Biuret reagent in a highly alkaline environment serves as the basis for the detection. The intensity of this colored complex is measured using a custom-built Continuous Flow Injection Analyzer, enabling accurate quantification of Cefotaxime sodium. Optimization studies of the chemical and physical parameters such as dilution of Biuret reagent, effect of the medium basicity, flow rate, sample loop and others have been investigated. The calibration gra