The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

SUMMARY. The objectives of the present study were to assess the possible predictors of COVID-19 severity and duration of hospitalization and to identify the possible correlation between patient parameters, disease severity and duration of hospitalization. The study included retrospective medical record extraction of previous coron avirus COVID-19 patients in Basra hospitals, Iraq from March 1st and May 31st, 2020. The information of the participants was investigated anonymously. All the patients’ characteristics, treatments, vital signs and laboratory tests (hematological, renal and liver function tests) were collected. The analysis was conducted using the SPSS (version 22, USA). Spearman correlation was used to measure the relations

The oil and gas production industry is considered the most important industries in the modern world because of its large relative significance among the group of energy recourses required for the world, where the natural resources represent the oil and natural gas fields, phosphate, gold, coal, forests and others. The most important advantage of the natural resources is its need for huge financial investments for a relatively long period of time from the beginning of the work until the start of extracting natural resources. Also, there are numerous cases where the natural source is not feasible exploited economically and is not discovered until after the passage of a long period of time from the start of work and paying relatively high a

A simplified parallel key was presented in this work for the Taxa of Stackys L. wildly grown in Iraq. Three records within this genus were newly recorded to our country in the present work and they are S. kermanshahansis Rech S. setifera C.A. Mey. subsp setifera, S. setifera ssp iranica (Reck.) The characteristics of these new records were also given with some representative specimens.

In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

This study aims to design unified  electronic information system to manage students attendance in Lebanese French university/Erbil, as a system that simplifies the process of entering and counting the students absence, and generate absence reports to expel students who passed  the acceptable limit of being absent, and by that we can replace the traditional way of  using papers to count absence,  with  a complete electronically system for managing students attendance, in a way that makes the results accurate and unchangeable by the students.

            In order to achieve the study's objectives, we designed an information syst

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

A harvested prey-predator model with infectious disease in preyis investigated. It is assumed that the predator feeds on the infected prey only according to Holling type-II functional response. The existence, uniqueness and boundedness of the solution of the model are investigated. The local stability analysis of the harvested prey-predator model is carried out. The necessary and sufficient conditions for the persistence of the model are also obtained. Finally, the global dynamics of this model is investigated analytically as well as numerically. It is observed that, the model have different types of dynamical behaviors including chaos.