Sabah M. Ahmed

Bio: Sabah M. Ahmed is an academic researcher from Egypt-Japan University of Science and Technology. The author has contributed to research in topics: Wavelet & Wavelet packet decomposition. The author has an hindex of 19, co-authored 73 publications receiving 1435 citations. Previous affiliations of Sabah M. Ahmed include Jordan University of Science and Technology & Assiut University.

A new biometric modality for human authentication using eye blinking

Abstract: This paper proposes a new biometric identifier for humans based on eye blinking waveform extracted from brain waves. Brain waves were recorded using Neurosky Mindwave headset from 25 volunteers. Two approaches are adopted for the pre-processing stage; the first approach uses empirical mode decomposition to isolate electro-oculogram signal from brain waves, then, extracts eye blinking signal. The second approach extracts eye blinking signal directly from brain waves. Features are extracted based on time delineation of the eye blinking waveform and classified using linear discriminant analysis. The best correct identification and equal error rates achieved are 98.51% and 2.5% for identification and verification modes respectively. The obtained results in this paper confirm that eye blinking waveform carries discriminant information and is therefore appropriate as a basis for human recognition task.

Autonomous Flight Take-off in Flapping Wing Aerial Vehicles

Abstract: This paper presents the design and dynamic simulation of a jumping mechanism for flight initiation in flapping wing aerial vehicles to enhance their autonomous mobility. It is inspired by avian flyers that start flight by jumping using their hind limbs. A 4-bar linkage that performs the prescribed take-off maneuvers has been geometrically designed using dimensional synthesis by motion generation. The kinematic dimensions obtained thereof have been ascertained analytically. A magnetic latching solenoid actuator and its corresponding transmission mechanism has been proposed for jumping actuation due to its compact structure, and low power consumption with no heat nor electrical noise generation. After take-off, the necessity to sustain the aerial vehicle airborne by providing adequate supportive forces at low air speeds has been demonstrated by the prospect of unsteady aerodynamics. Fluid-structure interaction has been analyzed by co-simulation between ADAMSⓇ and MATLABⓇ/Simulink. The designed legs give an inclined take-off of about 64° and an initial speed of almost 2m/s with an angular deflection of 110° between the leg segments. Flight performance indicates an increase in lift/drag ratios with in both flapping rate and forward velocity up to some limit. The results also compared favorably with those from wind tunnel tests and previous analysis of related work. They all exhibited an increase in wing efficiency with decreasing mean angles of attack as the air vehicle approaches stable flight.

Design of FIR filters with arbitrary amplitude and phase specifications using genetic algorithm

Abstract: In this paper we present efficient design algorithm for FIR filters with arbitrary amplitude and phase specifications using genetic algorithm. This algorithm provides flexibility in control the genetic algorithms parameters such as population size, number of generations, crossover probability and so on. Filters with binary, integer or real coefficients can be easily handled by the proposed method. This includes the multiplierless coefficients case. It has been tested for the design of filters with different amplitude and phase specifications. The fitness function was defined as the simple reciprocal of sum squared of the error.

Wavelet Threshold-Based ECG Data Compression Technique Using Immune Optimization Algorithm

Abstract: In this paper, a new ECG compression method called Wavelet Threshold Based Immune Algorithm (WTBIA) is proposed. This method based on finding the best threshold level for each wavelet subband using Immune Algorithm (IA). The WTBIA algorithm consists of three main steps: 1) Applying 1-D Discrete Wavelet Transform (DWT) on ECG signal; 2) Thresholding of wavelet coefficients in each subband; and 3) Minimization of the Percent Root mean square Difference (PRD) and maximization of the Compression Ratio (CR) using IA. The main advantage of this method is finding the best threshold level for each subband based on the required CR and PRD. The compression algorithm was implemented and tested upon records selected from the MIT-BIH arrhythmia database [6] using different wavelets such as Haar, Daubechies, Coiflet, Symlet and Biorthogonal. Simulation results show that the proposed algorithm leads to high CR associated with low distortion level relative to previously reported compression algorithms.

Bio-inspired jumping maneuver for launching flapping wing micro air vehicles

Abstract: This paper presents the design and simulation of a jumping mechanism as a means of flight initiation in Flapping Wing Micro Air Vehicles (FWMAV) inspired by birds. Most flying birds take off for flight from standing or perching position at low air speed. A lightweight 4-bar leg mechanism has been designed using dimensional synthesis by motion generation. Graphical and analytical methods are established to determine the kinematic dimensions that fulfill some prescribed take-off maneuvers. Link cross sections have been optimized to reduce weight. The jumping leg has been tested with an efficient aerodynamic model that accurately predicts unsteady flapping wing aerodynamic characteristics just after launching. Transition of forces from leg to wings has been analyzed. For a jumping angle of about 50 degrees at 10m/s the 33.3 g ornithopter model gains momentum and reaches steady state flight at a velocity close to the initial value.

The Self-Organizing Map

Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

Wavelet transforms and the ECG: a review.

Abstract: The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn.

A smart home energy management system using IoT and big data analytics approach

Abstract: Increasing cost and demand of energy has led many organizations to find smart ways for monitoring, controlling and saving energy. A smart Energy Management System (EMS) can contribute towards cutting the costs while still meeting energy demand. The emerging technologies of Internet of Things (IoT) and Big Data can be utilized to better manage energy consumption in residential, commercial, and industrial sectors. This paper presents an Energy Management System (EMS) for smart homes. In this system, each home device is interfaced with a data acquisition module that is an IoT object with a unique IP address resulting in a large mesh wireless network of devices. The data acquisition System on Chip (SoC) module collects energy consumption data from each device of each smart home and transmits the data to a centralized server for further processing and analysis. This information from all residential areas accumulates in the utility’s server as Big Data. The proposed EMS utilizes off-the-shelf Business Intelligence (BI) and Big Data analytics software packages to better manage energy consumption and to meet consumer demand. Since air conditioning contributes to 60% of electricity consumption in Arab Gulf countries, HVAC (Heating, Ventilation and Air Conditioning) Units have been taken as a case study to validate the proposed system. A prototype was built and tested in the lab to mimic small residential area HVAC systems1.