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

  The relationship between the vision of the scenario and the director is represented in the second search for new mechanisms and possibilities that possess the direct effect and synonyms of the vision of the scenario, so he works on investing them in achieving his ideas and visions with more effectiveness and flexibility to achieve creative potentials, without resorting to the installations and expressive structures themselves that have exhausted their meaning, and lost their luster due to Its prevalence and familiarity on the one hand, and its activation on the other hand to achieve modernity at the level of aromas, after the director takes a method or approach that has privacy and exclusivity, and based on the foregoing, getting

The expanding use of multi-processor supercomputers has made a significant impact on the speed and size of many problems. The adaptation of standard Message Passing Interface protocol (MPI) has enabled programmers to write portable and efficient codes across a wide variety of parallel architectures. Sorting is one of the most common operations performed by a computer. Because sorted data are easier to manipulate than randomly ordered data, many algorithms require sorted data. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. In this paper, sequential sorting algorithms, the parallel implementation of man

In the recent years, remote sensing applications have a great interest because it's offers many advantages, benefits and possibilities for the applications that using this concept, satellite it's one must important applications for remote sensing, it's provide us with multispectral images allow as study many problems like changing in ecological cover or biodiversity for earth surfers, and illustrated biological diversity of the studied areas by the presentation of the different areas of the scene taken depending on the length of the characteristic wave, Thresholding it's a common used operation for image segmentation, it's seek to extract a monochrome image from gray image by segment this image to two region (for

The aim of this research is to identify the role of strategic agility achieving organizational excellence in one of the formations of the Ministry of Municipalities (Dhi Qar Sewage Directorate), as important service organizations that have a key role in serving and developing the society which faced many administrative challenges and issues and as a result of the changes in the environment is continuing and accelerating, so the adoption of modern administrative concepts such as strategic Agility and knowledge of their role in achieving organizational excellence can help them in facing these changes and achieve what they aspire to. In order to achieve research objectives, two main hypotheses have been formulated. The first hypothe

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec