The phenomenon of financial failure is one of the phenomena that requires special attention and in-depth study due to its significant impact on various parties, whether they are internal or external and those who benefit from financial performance reports. With the increase in cases of bankruptcy and default facing companies and banks, interest has increased in understanding the reasons that led to this financial failure. This growing interest should be a reason to develop models and analytical methods that help in the early detection of this increasing phenomenon in recent year . The research examines the use of Sherrod's model in predicting financial failure in Iraqi private banks. The researchers relied on this mathematical model to analyze financial data and estimate the probability of financial failure occurring in these banks. Financial data was collected for a sample of private banks in Iraq over several years, and these data were used to apply the Sherrod model .As for the sample, a sample was chosen from the research consisting of two banks (the Commercial Bank of Iraq and the Iraqi Islamic Bank) for the research and a time series that extended for five years (2017 – 2021) , The results showed that the Sherrod model has a good ability to predict financial failure in Iraqi private banks. The researchers used a variety of financial and accounting variables in the model, which contributed to improving the accuracy of predicting financial failure .This study represents an important contribution to understanding how mathematical models such as Sherrod's model can be used to estimate the risk of financial failure in banks. These tools help guide strategies and make sound financial decisions. This research is considered an important step towards improving the sustainability and performance of private banks in Iraq and enhancing confidence in the financial system.
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Este estudio muestra una relación comparativa entre literatura y arte, concretamente entre las artes visuales (pintura y cine) y la literatura. Dicho estudio se puede clasificar dentro de los estudios actuales de literatura comparada. El interés por la cuestión viene por la problemática relación entre las dos artes, que tiene una larga tradición que se extiende desde el Ars poetica de Aristóteles hasta la aparición del vanguardismo en el siglo XX. La relación se presenta a través de los colores de las pinturas y los sonidos de las palabras. A los pintores de iconos se les conocía como iconógrafos porque se les consideraba más escritores que pintores. El icono era en realida
... Show MoreRecently Tobit Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique and Bayesian hierarchical model with adaptive ridge regression technique .
in double adaptive elastic net technique we assume different penalization parameters for penalization different regression coefficients in both parameters λ1and λ2 , also in adaptive ridge regression technique we assume different penalization parameters for penalization different regression coefficients i
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To achieve this objective, the research was based on the indicators of disclosure of the business model of the International Accounting Standards Board to measure the disclosure of the business model.
The research reached a number of conclusions, the most important of which were as follows:
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Problem of water scarcity is becoming common in many parts of the world. Thus to overcome this problem proper management of water and an efficient irrigation systems are needed. Irrigation with buried vertical ceramic pipe is known as a very effective in management of irrigation water. The two- dimensional transient flow of water from a buried vertical ceramic pipe through homogenous porous media is simulated numerically using the software HYDRUS/2D to predict empirical formulas that describe the predicted results accurately. Different values of pipe lengths and hydraulic conductivity were selected. In addition, different values of initial volumetric soil water content were assumed in this simulation a
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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