Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variability. In the practical sphere it is however more realistic to capture the most significant parameters of the research design through the best fitted candidate model for this research. Simulation studies demonstrate that the mixed-effects conditional logistic regression is more accurate for pollution studies, with fixed-effects conditional logistic regression models potentially generating flawed conclusions. This is because mixed-effects conditional logistic regression provides detailed insights on clusters that were largely overlooked by fixed-effects conditional logistic regression.
The research seeks to identify the proposed scenarios to predict and ward off monetary credit risks that the bank is exposed to in the future, using the banking stress tests model, and showing their impact on capital adequacy and profitability ratio,To achieve this purpose, Sumer Commercial Bank was taken as a case study, and mathematical equations were used to extract the results. Low percentage of profits and returns, strictness in the process of granting credit and financing operations in order to reduce credit risks.
Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreAdsorption and ion exchange are examples of fixed-bed sorption processes that show transient behavior. This means that differential equations are needed to design them. As a result, numerical methods are commonly utilized to solve these equations. The solution frequently used in analytical methods is called the Thomas solution. Thomas gave a complete solution that adds a nonlinear equilibrium relationship that depends on second-order reaction kinetics. A computational approach was devised to solve the Thomas model. The Thomas model's validity was established by conducting three distinct sets of experiments. The first entails the adsorption of acetic acid from the air through the utilization of activated carbon. Following
... Show MoreThe research includes synthesis and identification of novel three amino acids ligands complexes of some heavy metal (II) ions by using the amino acids like glycine, L-alanine and L-valine. New metal mixed ligand complexes with amino acids are prepared the reaction by reacting the three amino acids with the metals(II) chloride by using 50% ethanolic solution and 50% distall water in the molar ratio [1:1:1:1] ( M:Gly:Ala:Val) except for Co(II) and Ni(II) complexes were found after diagnosis the coordination with both Lalanine and L-valine. The prepared complexes identified by using physical properties, flame atomic absorption and conductivity measurements, in addition, mass, FT.IR and UV.vis spectrum as well magnetic moment data. The general
... Show MoreIn this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .
Media, especially press plays an important role in fighting corruption and tackling this phenomenon, which has become widespread in our society, through its effective role in raising awareness of the seriousness of spreading of corruption of all its forms in society.
All international conventions and agreements stress the necessity of the role of media and its importance in the light of corruption. All countries also commit themselves to the necessity of guaranteeing the freedom of media and the circulation of information and preparing it as a prerequisite for activating the People’s Control Mechanism and supporting measures and means to prevent and combat financial and administrative corruption more actively and effectively.
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