Millions of pilgrims and visitors from numerous parts of the world flock to Karbala (one of the most prominent ideological and religious places in central Iraq) each year to visit the holy shrines in Karbala due to their sanctity. Many improvements have been made to the Two Holy Shrines (THS), the Shrines of Imam Husayn and Imam Abbas, and the area between them (ATHS), due to the high temperatures in this region and to improve pedestrian thermal comfort. Studies on improving outdoor thermal comfort in Karbala are scarce. Hence, this research aims to look into historical and current architectural changes and how they affect thermal comfort. On the hottest summer day, the ENVI-met software program was used to simulate the building des

Millions of pilgrims and visitors from numerous parts of the world flock to Karbala (one of the most prominent ideological and religious places in central Iraq) each year to visit the holy shrines in Karbala due to their sanctity. Many improvements have been made to the Two Holy Shrines (THS), the Shrines of Imam Husayn and Imam Abbas, and the area between them (ATHS), due to the high temperatures in this region and to improve pedestrian thermal comfort. Studies on improving outdoor thermal comfort in Karbala are scarce. Hence, this research aims to look into historical and current architectural changes and how they affect thermal comfort. On the hottest summer day, the ENVI-met software program was used to simulate the building des

This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional b

This paper focuses on the most important element of scientific research: the research problem which is confined to the concept of concern or concern surrounding the researcher about any event or phenomenon or issue paper and need to be studied and addressed in order to find solutions for them, to influence the most scientific research steps from asking questions and formulating hypotheses, to employ suitable methods and tools to choose the research and sample community, to employ measurement and analysis tools. This problem calls for a great effort by the researcher intellectually or materially to develop solutions.

     The process of stocks evaluating considered as a one of challenges for the financial analysis, since the evaluating focuses on define the current value for the cash flows which the shareholders expected to have. Due to the importance of this subject, the current research aims to choose Fama & French five factors Model to evaluate the common stocks to define the Model accuracy in Fama& French for 2014. It has been used factors of volume, book value to market value, Profitability and investment, in addition to Beta coefficient which used in capital assets pricing Model as a scale for Fama & French five factors Model. The research sample included 11 banks listed in Iraq stock market which have me

In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.

The method of estimating the distribution parameters for each device was the OLS method.

The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and acc

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings