Zaid A. A. Yahya Alyasseri

Stroke is the second foremost cause of death worldwide and is one of the most common causes of disability. Several approaches have been proposed to manage stroke patient rehabilitation such as robotic devices and virtual reality systems, and researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. Therefore, the most challenging tasks with BCI applications involve identifying the best technique(s) that can reveal the neuron stimulus information from the patients’ brains and extracting the most effective features from these signals as well. Accordingly, the main novelty of this paper is twofold: propose a new feature fusion method for motor imagery (MI)-based BCI and develop an automatic MI framework to detect the changes pre- and post-rehabilitation. This study investigated the electroencephalography (EEG) dataset from post-stroke patients with upper extremity hemiparesis. All patients performed 25 MI-based BCI sessions with follow up assessment visits to examine the functional changes before and after EEG neurorehabilitation. In the first stage, conventional filters and automatic independent component analysis with wavelet transform (AICA-WT) denoising technique were used. Next, attributes from time, entropy and frequency domains were computed, and the effective features were combined into time–entropy–frequency (TEF) attributes. Consequently, the AICA-WT and the TEF fusion set were utilised to develop an AICA-WT-TEF framework. Then, support vector machine (SVM), k-nearest neighbours (kNN) and random forest (RF) classification technique were tested for MI-based BCI rehabilitation. The proposed AICA-WT-TEF framework with RF classifier achieves the best results compared with other classifiers. Finally, the proposed framework and feature fusion set achieve a significant performance in terms of accuracy measures compared to the state-of-the-art. Therefore, the proposed methods could be crucial for improving the process of automatic MI rehabilitation and are recommended for implementation in real-time applications.

Abstract For decades, image enhancement has been considered one of the most important aspects in computer science because of its in uence on a number of elds including but not limited to medical, security, banking and nancial sectors. In this paper, a new gray level image (edge preserving) en- hancement method called the harmony search algorithm (HSA) is proposed. HSA has been recently introduced stemmed by the musical improvisation pro- cess when a group of musicians play the pitches of their instruments seeking for pleasing harmony. Tremendous successful stories of HSA application to a wide variety of optimization problems have been passed on at a large scale. In order to evaluate the proposed HSA-based image enhancement method, 14 standard images from the literature have been used. For comparative evalu- ation, the results of the 14 enhanced image produced by HSA are compared with two classical image enhancement methods (i.e., Histogram Equalization algorithm and Image Adjacent algorithm) and two advanced methods (i.e., genetic algorithm and particle swarm optimization). These methods, it should be emphasized, used the same criteria ( number of edges in an gray scaled im- ages, summation intensity of edges detected using a Sobel lter and entropy measure) to evaluate HSA results. The HSA almost achieves the best results in comparison with the other classical and advanced image enhancement al- gorithms. Due to such achievements, we believe that the proposed method is very promising and has a potential to provide a substantial addition to the image enhancement domain.

Face recognition system compares the tested face with the various training faces reserved in the database with an efficient success rate. The best matching of the tested face with the training faces is an important task. In this article, how to recognize a face is presented; two different analysis algorithms are included in the evaluation system: Eigenface and ICA. The local dataset used in this article is pre-processed using statistical standard methods. Pre-processing software, which is provided by the Colorado State University (CSU) Face Identification Evaluation System Version 5.0 under Unix Shell scripts, was written using ANSII C code. Independent Component Analysis algorithm (ICA) is written using Matlab for face recognition implementation. This article explains how the faces, having some variations such as facial expressions and viewing conditions w.r.t the original faces reserved in the database, are detected with an improved accuracy and success rate. Finally, the result shows several graphs by Matlab.

Sorting or ordering is an arrangement of a set of items of a list in a certain order. Several sorting algorithms and methods are available. In this paper, we focus on the simplest but not highly efficient bubble sort algorithm. Rearranging parallel computing, i.e., message passing interface (MPI), it is explained why parallel architectures are now mainstream. Recently, parallel computing has become one of the most important aspects of computer science and it has showed dominance especially in the field of analyzing highperformance problems. One of the major results is the type of data structure obtained by using 3D array of char, which shows faster result, instead of using a vector of string with extra overhead. The threads (slaves) sort part of the list and return to the master thread, which merges all small lists in one final sorted list. This study shows an increase in speed and efficiency with the increase in number of threads, indicating an increase in the efficiency of bubble sort algorithm

Matlab is one of the most widely used mathematical computing environments in technical computing. It has an interactive environment which provides high performance computing (HPC) procedures and easy to use. Parallel computing with Matlab has been an interested area for scientists of parallel computing researches for a number of years. Where there are many attempts to parallel Matlab. In this book, we will present most of the past,present attempts of parallel Matlab such as MatlabMPI, bcMPI, pMatlab, Star-P and PCT. Also, we will expect the future attempts. Finally, This book is for readers which have a basic knowledge in Matlab. I expect after reading this book you will able to solve any problem using Parallel Matlab.

Population based metaheuristic algorithms have been providing efficient solutions to the problems posed by various domains including image processing. In this contribution we address the problem of image enhancement with a specific focus on preserving the edges inherent in images with the aid of a musically inspired harmony search based metaheuristic algorithm. We demonstrate the significance of our proposed intuitive approach which combines efficient techniques from the image processing domain as well as from the optimization domain. Pertaining to the problem under consideration, further we compare our results with the state-of-the-art histogram equalization approach

Dr. Zaid Al-Yasseri from the University of Kufa - faculty of Engineering was selected to be a member of the Scientific Committee of the Third International Conference on Information Technology

http://eng.uokufa.edu.iq/index.php/2013-09-04-10-32-55/927-2016-06-08-08-46-03

A group of professors from the Department of Electronic Engineering and Communications at the Faculty of Engineering, the UOK, successfully designed an electronic application by using the applications of (Google) for the purpose of evaluating the teaching staff for the academic year 2015-2016. For his part, the Dean of the Faculty of Engineering, Prof. Dr. Ali Hussein Otaiwi, stated that this method of evaluation is being conducted for the first time in the faculty and includes all the departments. While the head of the Department of Electronic Engineering and Communications, Dr. Raied Saleem Hashim, pointed out that this method saves both time and effort, as well as protects the confidentiality of the assessment.

Mr. Zaid Alyasseri published a book in Lambert publishing - Germany

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