The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

The aim of this study is for testing the applicability of Ramamoorthy and Murphy method for identification of predominant pore fluid type, in Middle Eastern carbonate reservoir, by analyzing the dynamic elastic properties derived from the sonic log. and involving the results of Souder, for testing the same method in chalk reservoir in the North Sea region. Mishrif formation in Garraf oilfield in southern Iraq was handled in this study, utilizing a slightly-deviated well data, these data include open-hole full-set logs, where, the sonic log composed of shear and compression modes, and geologic description to check the results. The Geolog software is used to make the conventional interpretation of porosity, lithology, and saturation. Also,

Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.

In order for the process of removing pollutants, including dyes, from the aquatic environment to be effective, plant wastes such as banana peels were used as adsorbent surfaces by thermally activating them (ABP) and modifying them with iron oxide nanoparticles (MABP), which were characterized using Fourier transform infrared (FT-IR) and X-ray diffraction (XRD) techniques. They were applied in the field of Janus green (JG) dye adsorption for the batch system and studied the effect of several factors (adsorbent weight, contact time, initial concentration, and temperature). Their data were analyzed kinetically using first- and second-order kinetic models and they were found to follow the second order. Their data were also analyzed thro

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai

The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t

Time series is an important statistical method adopted in the analysis of phenomena, practices, and events in all areas during specific time periods and predict future values ​​contribute to give a rough estimate of the status of the study, so the study aimed to adopt the ARIMA models to forecast the volume of cargo handled and achieved in four ports (Umm Qasr Port, Khor Al Zubair Port, Abu Flus Port, and Maqal Port(, Monthly data on the volume of cargo handled for the years (2006-2018) were collected (156) observations. The study found that the most efficient model is ARIMA (1,1,1).

The volume of go

Background: Lack of durability of the bond of the dental adhesive systems to tooth structure is one of the most important problems in tooth colored restorative work. This in vitro study was performed to evaluate the effect of 2% chlorhexidine gluconate(CHX) on dentin bond strength by using total etch adhesive system at twenty-four hours and three months of water storage. Material and methods:A flat dentin surface was prepared for forty sound human maxillary premolar teeth which were acid etched with 36% phosphoric acid gel after being divided randomly into four groups of ten teeth each according to storage time and CHX application, theCHX was applied for 60 seconds before adhesive application for groups I and III which were tested after twe