Raied Salman

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Calculating Euclidean distance matrix is a data intensive operation and becomes computationally prohibitive for large datasets. Recent development of Graphics Processing Units (GPUs) has produced superb performance on scientific computing problems using massive parallel processing cores. However, due to the limited size of device memory, many GPU based(More)
Support Vector Machine (SVM) is one of the most popular tools for solving general classification and regression problems because of its high predicting accuracy. However, the training phase of nonlinear kernel based SVM algorithm is a computationally expensive task, especially for large datasets. In this paper, we propose an intelligent system to solve(More)
k-means has recently been recognized as one of the best algorithms for clustering unsupervised data. Since k-means depends mainly on distance calculation between all data points and the centers, the time cost will be high when the size of the dataset is large (for example more than 500millions of points). We propose a two stage algorithm to reduce the time(More)
The Support Vector Machine (SVM) is an efficient tool in machine learning with high accuracy performance. However, in order to achieve the highest accuracy performance, n-fold cross validation is commonly used to identify the best hyperparameters for SVM. This becomes a weak point of SVM due to the extremely long training time for various hyperparameters of(More)
GPUSVM (Graphic Processing Unit Support Vector Machine) is a Computing Unified Device Architecture (CUDA) based Support Vector Machine (SVM) package. It is designed to offer an end-user a fully functional and user friendly SVM tool which utilizes the power of GPUs. The core package includes an efficient cross validation tool, a fast training tool and a(More)
Mobile devices are quickly becoming devices powerful enough to run personal computers with the advancement of wireless and mobile technology. Learning by means of mobile phones is becoming a new approach towards education, and it is unique in its own way and offers learning opportunities anywhere and anytime. Mobile Collaborative Learning (MCL) has been(More)
One neural network, (NN), is used for the adaptive inverse control of nonlinear systems. To adjust the identifier parameters, a method uses a compromised function to establish the performance of the identifier, is proposed. The main objective is to combine the performance error and the tracking errors. Also a reasonable control action is achieved for a(More)
In this paper an application of von Neumann correction technique to the output string of some chaotic rules of 1-D Cellular Automata that are unsuitable for cryptographic pseudo random number generation due to their non uniform distribution of the binary elements is presented. The one dimensional (1-D) Cellular Automata (CA) Rule space will be classified by(More)
It has been always observed that the effectiveness of MIS as a support tool for management decisions degenerate after time of implementation, despite the substantial investments being made. This is true for organizations at the initial stages of MIS implementations, manual or computerized. A survey of a sample of middle to top managers in business and(More)
When changes occur in complex images that involve minute details, it is usually a daunting task to track the changes that may have occurred between two time periods. We will be presenting a method for identifying these changes through digitizing; anchoring, reorienting and subtracting, successive images, and compiling an animated sequence of image(More)