The historic cities in the Arab and Islamic world (including the cities of the holy shrines in Iraq) suffer from many and varied problems and most notably it is clear in its origin functional structure. It had been transformed from a basic place to live for a few thousand of the population to the center or part of the main center of large city populations of more than one million. Functional structure of the ancient city have been change with the beginning of the twentieth century and accelerated rate of change in the second half of the last century. The research aims to analyze the problems of the historic centers of holy cities and analyze the methods of dealing with these problems, leading to discrimination method could be the

                In the past years, the Algerian Economy has witnessed various monetary developments characterized by different monetary and banking reforms aimed by monetary authorities to achieve monetary stability and driving overall growth. It should be noted that there is evidence to initiate fundamental changes on the basis of which new monetary, financing and banking policy mechanisms must be formulated in Algeria by enhancing the pursuit of reforming the monetary system, in order to improve monetary and economic indicators.

                The study a

The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

natural and non-natural disasters, is an environmental challenges the society and the economy as well as a direct and indirect economic affect, and the units are part of the system overlapping among themselves and thus affected by external indicators, directly or indirectly, these direct effects appear in the destruction or damage inflicted by disasters in property , infrastructure , superstructure , accounting information systems and indirectly in the outcome of future business, comes research problem through access to accounting treatments issued by the Federal Office of financial supervision to address the damage caused by the disasters and prepare the missing financial accounts it turns out us that there is negligence of a nu

     In this paper, we study some cases of a common fixed point theorem for classes of firmly nonexpansive and generalized nonexpansive maps. In addition, we establish that the Picard-Mann iteration is faster than Noor iteration and we used Noor iteration to find the solution of delay differential equation.

Football has progressed from being a ritual and a celebration to become an amateur sport, a professional sport, and now, increasingly, a commercial sport. In the analysis of football business model, the systemic approach should be adopted. If sport is regarded as one of the business sectors, then the application of business system methodology can be fully justified. The interest to create strong football business system calls for the search of the ways of popularizing football business model and boosting the economic potential of its participants. In the research literature tend to ignore the business processes within the sports business. Besides, the systemic approach in football business is usually limited to p

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro