Background: Accurate measurement of a patient’s height and weight is an essential part of diagnosis and therapy, but there is some controversy as to how to calculate the height and weight of patients with disabilities. Objective: This study aims to use anthropometric measurements (arm span, length of leg, chest circumference, and waist circumference) to find a model (alternatives) that can allow the calculation of the height and the body weight of patients with disabilities. Additionally, a model for the prediction of weight and height measurements of patients with disabilities was established. Method: Four hander patients aged 20-80 years were enrolled in this study and divided into two groups, 210 (52.5%) male and 190 (47.5%) fe

The present study was designed to determine the predictive capacity of Coronavirus’s impact, as well as, the psychological adjustment among university students in Oman. A total of (566) male and female students were employed to form the swtudy sample. The descriptive method was used. The findings showed that there is a significantly university student affected by Coronavirus; the dimensions of scale were arranged as follows: the Academic requirements of pandemic came first, the social communication came second, and the academic future stress came in third. The results also showed that Psychological Adjustment among University Students was affected by the Coronavirus pandemic, the average was low. Also, the result showed that the Corona

Heavy metals especially lead (Pb), cadmium (Cd), chromium (Cr) and copper (Cu) are noxious pollutants with immense health hazards on living organisms, these pollutants enter aquatic environment in Iraq mainly Tigris and Euphrates rivers via waste water came from different anthropological activities, This study investigated capacity of dried and ground root of water hyacinth (Eichhornia crassipes) in removing the heavy metals from their aqueous solutions. Effects of initial concentrations of the heavy metals and pH of their aqueous solutions were studied. Results of this study revealed excellent biosorption capacity of water hyacinth root in general, removal of Pb was the highest and Cr was lowest. The results showed that the Pb, Cu and C

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

أن التطور العلمي الحاصل فيما يخص المجال الرياضي أرسى آفاق جديدة لمواكبة التطور الكبير في مجا ل الألعاب والفعاليات الرياضية المختلفة ,و أن تحقيق النتائج الجيدة في فعاليات العاب القوى بشكل عام والثلاثية بشكل خاص في التدريب الرياضي يتطلب إتباع الأساليب العلمية الدقيقة والموضوعية بشكل سليم ومخطط له،فضلا عنة تطبيق نظريات ومنحى جديد لمواكبة الاتجاهات الحديثة في تحقيق النتائج الجيدة للوصول إلى المستويات العالية

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

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 variab