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The research deals with the statement of the importance of unanimous in Islamic Sharia in terms of being the third source of Islamic legislation after the Holy Qur’an and the Sunnah of the Prophet, and the extent of interest of the scholars of interpretation in it, and those who took great interest in mentioning what was agreed upon in every site that necessitated mentioning its issues within, or mentioning an event that has encountered an unanimous, and in various sciences, to extract and extrapolate Sharia rules when these rules are lost in the texts, because it is based on them and derived from them. Among these distinguished scholars is Muhammad bin Jarir al-Tabari. Besides, the research discusses in

The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

Background: The integration of modern computer-aided design and manufacturing technologies in diagnosis, treatment planning, and appliance construction is changing the way in which orthodontic treatment is provided to patients. The aim of this study is to assess the validity of digital and rapid prototyped orthodontic study models as compared to their original stone models. Materials and methods: The sample of the study consisted of 30 study models with well-aligned, Angle Class I malocclusion. The models were digitized with desktop scanner to create digital models. Digital files were then converted to plastic physical casts using prototyping machine, which utilizes the fused deposition modeling technology. Polylactic acid polymer was chose

Is to obtain competitive advantage legitimate objective pursued by all organizations to achieve, because they live today in environments of rapid change and dynamic in order to meet the demands of the customer changing as well as intense competition between the organizations, which requires them to get the location of competitive markets in order to do this will remain to do the building and strengthening competitive advantage to be able to achieve, but that this feature is not easy and is not only through the identification and use of a successful strategy for a competitive standard and then manage it successfully. Hence the research problem of determining the sources of differentiation strategy and its impact on the dimensions of compe

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,