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

Praise be to God, Lord of the worlds, and prayers and peace be upon our master Muhammad and upon his family and companions as a whole.
    The topic of attention was drawn to the attention of the speakers, as it made me ponder it carefully, and my goal in that is to know the reason for the interest of the speakers and their care for it, and to clarify from their books the purpose of making this topic one of the advanced investigations with them.

     The idea of ​​writing a paper on the subject of consideration was not absent from my thinking, because I saw the attention of speakers on this issue, as they made it one of the first issues that they deal with studying in their work

Background: presence of lingual vascular foramina and canals in the interforaminal region may increase the risk ofsurgical complications during implant placement or any surgical procedure in this area. Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended Al-Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canal

Background: The new concepts and technologies continue to change the dynamics of endodontic practices in the world. Rapid and significant changes in techniques, instrument design, and the type of metals used to manufacture endodontic instruments which have been made during the last few years in an attempt to overcome canal preparation errors. The purpose of this study is to measure and compare canal transportation and centering ability of Self Adjusting File with two rotary nickel-titanium (Ni-Ti) systems, ProTaper and BioRaCe at different levels. Material and Methods: Forty five distal roots of mandibular first molars with moderate curvature were selected using Schneider method. Roots were divided randomly into 3 groups of 15 each and were

Background: presence of lingual vascular foramina and canals in the interforaminal regionmay increase the risk ofsurgical complications during implant placement or any surgical procedure in this area.Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended AL- Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canals