Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete

This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

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

The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla

استهدف البحث المقارنة بين خميرتي Saccharomyces cerevisiae  و Saccharomyces carlesbergensis  لدراسة كفاءتهما في إنتاج الايثانول من أوساط الذرة المجروشة والمطحونة والنشا التجاري بطريقة تخمرات الحالة . بينت النتائج عدم وجود فروق معنوية بين خم

ليس جديداً القول بان هناك حاجة مستمرة ومتزايدة لاستخدام البيانات الاقتصادية المتسقة عن القطاعات المختلفة في الاقتصاد القومي لدعم وإسناد عملية التحليل الاقتصادي وتطوير النماذج الاقتصادية الكلية.

وتعرض مصفوفة الحسابات القومية Social Accounting Matrix  (SAM) اطاراً شاملاً من المعلومات الأساسية لهذا النوع من النماذج والتحليل. فهي تتضمن كلا من المستخدم- المنتج
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Carbon nanotubes (CNTs) were synthesized via liquefied petroleum gas (LPG) as precursor using flame fragments deposition (FFD) technique. In vitro, biological activates of carbon nanotubes (CNTs) synthesized by FFD technique were investigated. The physiochemical characterizations of synthesized CNTs are similar to other synthesized CNTs and to the standard sample. Pharmaceutical application of synthesized CNTs was studied via conjugation and adsorption with different types of medicines as promote groups. The conjugation of CNTs was performed by adsorption the drugs such as sulfamethoxazole (SMX) and trimethoprim (TMP) on CNTs depending on physical properties of both bonded parts. The synthesized CNTs almost have the same performance in a

In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

Through this research, We have tried to evaluate the health programs and their effectiveness in improving the health situation through a study of the health institutions reality in Baghdad to identify the main reasons that affect the increase in maternal mortality by using two regression models, "Poisson's Regression Model" and "Hierarchical Poisson's Regression Model". And the study of that indicator (deaths) was through a comparison between the estimation methods of the used models. The "Maximum Likelihood" method was used to estimate the "Poisson's Regression Model"; whereas the "Full Maximum Likelihood" method were used for the "Hierarchical Poisson's Regression Model