Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

Abstract:
Taghlib tribe had an important part in the history of the first century of
hijra. She managed to get the best social, economic and political basis in the
Arab- Islamic state. In this basis Taghlib was the best Dhimies in the Islamic
state. This tribe refused to be among the people of the book, and to be from
the people of dhima. That tribe refused to pay the Jizya and Khraj, but
accepted to pay double Sadaqa in stead of Jizya and Khraj, so in that case
many Muslims become angry.
Although their Christianity was naïve and simple, Taghlib hold it until the
end of the third century A.H. Taghlib did so because her people wanted to
keep their good relation with the Byzantine. Taghlib thought that the

            In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

This research aims to solve a problem in the field of accounting and financial knowledge in the world today, that is, the problem of creative accounting. Especially after the global financial crisis and the collapse of many large companies in the world, people find that they use creative accounting methods to distinguish them from reality, showing the results of their activities and their financial status. This research discusses the concept of creative accounting, the most important methods used in financial statements and its relationship with external auditing, and procedures to limit accounting creativity. This study uses descriptive analysis methods after confirming its theoretical aspects in practice. Using the statistical

Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t