The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

This study was planned to evaluate the renal function tests and liver function tests and it carried out in Al-Yarmouk hospital,Baghdad –Iraqin patients withtype 1 and type 2 diabetes mellitus by measuring(uric acid,urea and creatinine) ,Aspartate aminotransferase (AST) and Alanine aminotransferase (ALT). Seventy five individuals of Iraqi adults (male) were divided into three groups, 25 patients with type1 diabetes mellitus ,25 patients with type 2 diabetes mellitus and 25 normal individuals were taken as control group. The mean value of uric acid, urea and creatinine was higher significantly in patients thanin control group (P< 0.05),while the correlation(p< 0.01) between age ,creatinine in type 1 and between age and (Urea, Uric acid ,cr

The artistic process operates whether in general in all arts or specifically in one type of arts or one of the genres of arts types on the preoccupations of the pressing artistic references as the founder of the artistic work in the material formulations on the one hand and on the other hand as a translator to understand the artistic achievement in general and plastic art in particular and for the importance The researcher chose the title of her research tagged (the preoccupations of the pressing reference and its impact on the formations of postmodern arts).
The first chapter of the methodological framework deals with the problem of research, importance, objective, limits, and then terminology and its definition, and then the secon

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

The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus

This study attempts to provide an approach analysis for the news, depending on the bases and principles which conceptuality semiotic researchers of this field first of them «A. J. Gremas» for the theory of «narrative discourse analysis», to more clarify we tried to apply it on a published press- news, to concludes the most important steps and methods that are necessary to follows gain more understanding of the press- news.