Author: Mohammad Taye, Published Year: 2016
Computer Applications: An International Journal (CAIJ), Vol.3, No.1
Faculty: Information Technology

Abstract: People who have problems with talking, in general, are facing difficulty in communication with others, these disabilities may cause embarrassment to them. Therefore, we have developed a new tool that could help speechless people to share their ideas and conversations with others. This tool will overcome these problems by turning sign language into spoken words, allowing easier communication with others. This project based on hardware device that convert Sign Language to voice. So, the person who cannot speck could be able to use it to transfer his sign to voice. The tool can be used by wearing the special hardware which consists of the smart gloves, a speaker and the interpreter box. Indeed, the sign language only used by speechless people so it’s not clear to anyone , so this tool convert the sign language to voice throw smart gloves that will understand the sign, and generate voice throw speaker .

Keywords: sign language, smart gloves, speaker, interpreter

Research Title: Wavelet-Based Feature Extraction for the Analysis of EEG Signals Associated with Imagined Fists and Feet Movements
Author: Emad A. Awada, Published Year: 2014
Faculty: Engineering and Technology

Abstract: Electroencephalography (EEG) signals were analyzed in many research applications as a channel of communication between humans and computers. EEG signals associated with imagined fists and feet movements were filtered and processed using wavelet transform analysis for feature extraction. The proposed work used Neural Networks (NNs) as a classifier that enables the classification of imagined movements into either fists or feet. Wavelet families such as Daubechies, Symlets, and Coiflets wavelets were used to analyze the extracted events and then different feature extraction measures were calculated for three detail levels of the wavelet coefficients. Intensive NN training and testing experiments were carried out and different network configurations were compared. The optimum classification performance of 89.11% was achieved with a NN classifier of 20 hidden layers while using the Mean Absolute Value (MAV) of the Coiflets wavelet coefficients as inputs to NN. The proposed system showed a good performance that enables controlling computer applications via imagined fists and feet movements.

Keywords: Discrete Wavelet Transform (DWT), Electroencephalography (EEG), Brain-Computer Interface (BCI), machine learning, Neural Networks (NN), feature extraction, data mining

Research Title: Transparent Computing: A Primer
Author: Emad A. Awada, Published Year: 2020
Faculty: Engineering and Technology

Abstract: Transparent computing is an emerging technology that allows users to enjoy user-controlled services by extending the stored program concept in the von Neumann architecture spatio-temporally into networking environments. It is considered a form of persuasive computing and is a characteristic of pervasive computing. It aims to provide a cross-platform user experience in a hassle-free way, and make computer systems more secure, more reliable, and more flexible. It may be regarded as the latest realization of ubiquitous computing. This paper provides a brief introduction to transparent computing

Keywords: transparent computing, ubiquitous computing, pervasive computing

Research Title: Stochastic Computing: An Introduction
Author: Emad A. Awada, Published Year: 2019
Faculty: Engineering and Technology

Abstract: Abstract—Stochastic Computing (SC) essentially represents numbers as streams of random bits and reconstructs numbers by calculating frequencies. It employs random bits to calculate via simpler circuits and with greater tolerance for errors. As a computing paradigm, SC is currently undergoing a revival. Since stochastic circuits have a small size, SC has regained interest recently due to its potential usage in some emerging nanotechnologies. In this paper, we briefly present stochastic computing and discuss its applications, benefits, and challenges.

Keywords: Stochastic computing, unconventional computing, probabilistic computing

Research Title: Modified phase locked loop for grid connected single phase inverter
Author: Emad A. Awada, Published Year: 2019
Faculty: Engineering and Technology

Abstract: Connecting a single-phase or three-phase inverter to the grid in distributed generation applications requires synchronization with the grid. Synchronization of an inverter-connected distributed generation units in its basic form necessitates accurate information about the frequency and phase angle of the utility grid. Phase Locked Loop (PLL) circuit is usually used for the purpose of synchronization. However, deviation in the grid frequency from nominal value will cause errors in the PLL estimated outputs, and that’s a major drawback. Moreover, if the grid is heavily distorted with low order harmonics the estimation of the grid phase angle deteriorates resulting in higher oscillations (errors) appearing in the synchronization voltage signals. This paper proposes a modified time delay PLL (MTDPLL) technique that continuously updates a variable time delay unit to keep track of the variation in the grid frequency. The MTDPLL is implemented along a Multi-Harmonic Decoupling Cell (MHDC) to overcome the effects of distortion caused by gird lower order harmonics. The performance of the proposed MTDPLL is verified by simulation and compared in terms of performance and accuracy with recent PLL techniques.

Keywords: Multi-harmonic decoupling Phase locked loop Variable timedelay adjustment

Research Title: The Algorithm of Testing ADC Effective Number of Bits Based on Hilbert and Wavelet Transform
Author: Emad A. Awada, Published Year: 2019
3rd International Conference on Information System and Data Mining, Houston, Texas, USA
Faculty: Engineering and Technology

Abstract: In today advanced digital signal processing, many parameters must be tested to evaluate the accuracy performance of system output. Therefore, focusing down into an essential part of signal converts (Analog to Digital Converts) is a must prior to any system evaluations. As a result, this work will emphasize on the testing enhancement of Analog to Digital Converts parameters, such as Effected Number of Bits, to determine the accuracy of waveform regeneration and device performance with a newly implemented algorithm. That is, a new algorithm based on structuring Discrete Wavelet transform decomposition on prior interleave Hilbert transform, of Analog to Digital Converts output waveform, to measure Converts ability to reproduce a waveform in their full capacity. With such arrangement, the new algorithm intends to improve previous work for the testing process, higher testing accuracy, fewer computation data samples, and provide a platform of modulation process for other parameters measurement at the same time.

Keywords: Analog-to-Digital Converters (ADCs), Effective Number of Bits (ENOB), Discrete Wavelet Transforms (DWT), Hilbert Transform.

Research Title: Hilbert Based Testing of ADC Differential Non-linearity Using Wavelet Transform Algorithms
Author: Emad A. Awada, Published Year: 2017
International Journal of Electrical and Computer Engineering (IJECE), 8
Faculty: Engineering and Technology

Abstract: In testing Mixed Signal Devices such as Analog to Digital and Digital to Analog Converters, some dynamic parameters, such as Differential NonLinearity and Integral Non-linearity, are very critical to evaluating devises performance. However, such analysis has been notorious for complexity and massive compiling process. Therefore, this research will focus on testing dynamic parameters such as Differential Non-Linearity by simulating numerous numbers of bits Analog to Digital Converters and test the output signals base on new testing algorithms of Wavelet transform based on Hilbert process. Such a new testing algorithm should enhance the testing process by using less compiling data samples and prompt testing results. In addition, new testing results will be compared with the conventional testing process of Histogram algorithms for accuracy and enactment.

Keywords: Differential Non-Linearity Digital-to-Analog Converters Discrete Wavelet Transform Hilbert Transform

Research Title: Fuzzy Logic Control for Low-Voltage Ride-Through Single-Phase Grid-Connected PV Inverter
Author: Emad A. Awada, Published Year: 2019
Faculty: Engineering and Technology

Abstract: : This paper presents a control scheme for a photovoltaic (PV) system that uses a single-phase grid-connected inverter with low-voltage ride-through (LVRT) capability. In this scheme, two PI regulators are used to adjust the power angle and voltage modulation index of the inverter; therefore, controlling the inverter’s active and reactive output power, respectively. A fuzzy logic controller (FLC) is also implemented to manage the inverter’s operation during the LVRT operation. The FLC adjusts (or de-rates) the inverter’s reference active and reactive power commands based on the grid voltage sag and the power available from the PV system. Therefore, the inverter operation has been divided into two modes: (i) Maximum power point tracking (MPPT) during the normal operating conditions of the grid, and (ii) LVRT support when the grid is operating under faulty conditions. In the LVRT mode, the de-rating of the inverter active output power allows for injection of some reactive power, hence providing voltage support to the grid and enhancing the utilization factor of the inverter’s capacity. The proposed system was modelled and simulated using MATLAB Simulink. The simulation results showed good system performance in response to changes in reference power command, and in adjusting the amount of active and reactive power injected into the grid

Keywords: grid-connected inverter; fuzzy logic control; low-voltage ride-through; photovoltaic system

Research Title: Exascale Computing (Supercomputers): An Overview of Challenges and Benefits
Author: Emad A. Awada, Published Year: 2020
Faculty: Engineering and Technology

Abstract: Exascale computing is the term given to the next 50-100 fold increase in speed over the fastest supercomputers in use today. This super powerful machine is poised to transform modeling and simulation in science and engineering. It is hoped that the exascale machines will solve some or all of the major problems that are facing us today. This paper provides a brief introduction to exasclae computing where implementation and applications of such a system will be discussed to point out the venture challenges and tremendous benefits of function execution precision, fast data compiling and many other improving system qualities

Keywords: Exascale computing, supercomputers, transform, engineering

Research Title: Analysis of SFDR Using Power Spectrum Based on Wavelet Extraction
Author: Emad A. Awada, Published Year: 2017
International Journal of Applied Engineering Research, 11
Faculty: Engineering and Technology

Abstract: The high frequency of advanced digital signal processing and data analysis in wide range of everyday data computing applications has propagated the uses of Analog to Digital Converters. However, such a converter can be very crucial and critical for some applications. Especially with the use of sensitive equipment's, errors or deviations from original signal could lead to catastrophic results. Therefore, testing output signal for dynamic parameters can always define the performance of the converters. In this research, the dynamic range parameters of Spurious-Free Dynamic Range will be tested using FFT testing application process based on Wavelet decomposition algorithms. This new proposes testing technique will utilize Wavelet special characteristic of decomposition feature, reduce compiling sample data, and expedite testing process. The new propose testing technique will be compared with conventional method of FFT application in term of accuracy, variance, and number of collect and computed samples.

Keywords: Spurious-Free Dynamic Range, Analog to Digital Converters, Wavelet Transform