The transportation problem (TP) is employed in many different situations, such as scheduling, performance, spending, plant placement, inventory control, and employee scheduling. When all variables, including supply, demand, and unit transportation costs (TC), are precisely known, effective solutions to the transportation problem can be provided. However, understanding how to investigate the transportation problem in an uncertain environment is essential. Additionally, businesses and organizations should seek the most economical and environmentally friendly forms of transportation, considering the significance of environmental issues and strict environmental legislation. This research employs a novel ranking function to solve the transpor

The research aims to apply the activities of the green value chain as one of the modern administrative techniques that economic units resort to develop solutions to the pollution problems that occur due to the activity of economic units and their products that may cause damage to the environment as well as the waste of natural resources and to identify the production of environmentally friendly products and reduce the costs of environmental failure of both types Internal and external that may be borne by economic units such as taxes, fines and compensation due to nonobservance of environmental requirements and the preservation of human health and protection of the environment. To achieve the goal of the research, the researchers rel

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

Abstract:

              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

In this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less

Economic units can benefit from the cleaner production strategy, which aims to reduce the environmental impact of economic activities while improving efficiency and profitability. Accordingly, the aim of the research was to clarify the knowledge foundations of cleaner production costs and to indicate their role in reducing the costs of poor quality (the costs of failure). A set of conclusions has been reached, the most important of which is that cleaner production has achieved a reduction in the costs of external failure, represented by the costs of guarantee, by an amount of 12,339,000 dinars. Contributes to reducing the costs of failure, and based on the conclusions, a set of recommendations were presented, the most important of w

In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best esti

Background: Chronic renal failure (CRF) is a clinical syndrome that occurs when there is gradual decline in renal operation overtime.

Objective: This study aims to investigate the prevalence of depression among medical students at university of Baghdad, college of medicine in Iraq and the association between some variables and depression.

Aim: This study aimed to identify the impact of tobacco use in the etiology of chronic renal failure among Sudanese patients in Omdurman Military Hospital and Omdurman Kidney Dialysis Center

Materials and methods: This descriptive community-based study was conducted in Khartoum State. A random sample of 100 cases with chronic renal failure and 100

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param