The fetal electrocardiogram (FECG) signal reflects the electrical activity of the fetal heart as it contains information on the health status of the fetus. Therefore, an early diagnosis of any cardiac defects before delivery increases the effectiveness of the appropriate treatment. In this project we devised a novel technique for non-invasively extracting the FECG form abdominal and thoracic ECG recordings form the mother. The novel technique uses advanced pattern recognition and signal processing algorithms. The devised technique has been proven to yield superior results when compared with the existing state-of-theart fetal ECG extraction methods. The technique has been patented in the USA and was published in leading journals and conferences.

Manufacturing and Materials Processing

This group focuses on machinability of difficult to cut materials like titanium alloys, achine tools dynamics, tool wear, process optimization , process automation, and development of sustainability metrics for machining processes.

Arabic Sign Language Recognition

 In this project we developed a set of solutions for automatic Arabic Sign Language (ArSL) recognition.These solutions are divided into two categories: sensor-based solutions, and computer vision based solutions. The sensor based solutions use advanced mechatronics and signal processing techniques, while the computer vision based solutions use  advanced video and image processing algorithms with pattern recognition systems. We have published several articles on our ArSL recognition results in leading journals and conferences.

Transformer Health Monitoring Using Signal Processing and Intelligent Systems

The proposed transformer health monitoring will provide assessment of the transformer health condition which will be useful for maintenance, ensuring optimum transformer performance, increased efficiency and also increased expected life time. Several parameters can be monitored to assess the transformer health like partial discharge activities, oil and paper insulation quality.

Automatic Inspection of Outdoor Insulators using Digital Image Processing and Artificial Intelligence

Outdoor insulators are very important to the integrity of the power system grid. Recently, polymer insulators have been used in many countries including the United Arab Emirates. One of the major problems that face utility engineers is to evaluate the aging performance of those insulators. The proposed system automate the surface condition assessment system of polymer insulators developed by the Swedish Transmission Research Institute (STRI).

A Clean Biofuel from Solid Waste

This research project proposes a technique for converting solid waste into a biofuel that can be utilized as a clean source of energy in many industrial and domestic applications. . As such, this project has an advantage of managing the waste and producing a good source of alternative energy in order to minimize the pollution.

Microbiological Fuel Cells and Water Sesalination

This project studies and explores the electricity, desalination capacity and performance of Microbial desalination cell (MDC) combined with Microbial Fuel Cell (MFC). The aim of the project is to maximize fresh water from sea water by using  electricity generated from (MFC). The study covers waste water treatment as well.

Biofilter Project

This project proposes a process technology for biofilter development and testing for removal of air pollutants for industry and wastewater treatment stations. A mobile biofilter system was constructed and set up to treat H2S and waste gas. The H2S concentration in the exhaust from the stack was treated and reduced from 130ppm to 3ppm.

A Comprehensive Study of the Damage Behavior and Failure Modes of Structural Steel Column Subjected to Transverse Impact

This research presents a comprehensive study and consistent methodology for the assessment of the nonlinear damage behavior of structural steel columns subjected to transverse impact. The intellectual merit for this proposal is to enhance the understanding of the ductile failure mechanism due to accumulation of plastic deformation that is needed to enable proper structural design and hence provide better serviceability.

Reliable Latching RF MEMS Switches and Switch Matrices

The proposed RF MEMS switches in this research project are measured in micrometer scale and use a novel latching mechanism that exhibits high displacement to obtain superior RF performance in  comparison with other RF MEMS switches. The switch will be designed such that it works under vacuum and withstand low temperature conditions, such conditions do exist in space environment. It also can stand high power signals and temperature generated through them due to the high power up to 85 deg Celsius. Those circuits can be utilized in phase array system and triple stage switch matrices for satellite applications

Nutrient Recovery from Wastewater

The project is aimed in determining the feasibility of recovering nutrients (nitrogen and phosphorus) from domestic wastewater in UAE in the form of a slowrelease fertilizer. This study is a precursor to developing a sustainable process where we can consider wastewater as a resource rather than a waste/problem.

Tensile Material Properties of Different Types of Fiber-Reinforced Polymer Sheets at Elevated Temperatures

The aim of this proposal is to investigate experimentally the tensile mechanical properties of FRP sheets under elevated temperatures. The experimental matrix will be composed of CFRP, GFRP, Basalt (BFRP), and hybrid combination of (GFRP/CFRP) and (BFRP/CFRP) sheets. The specimens will be mechanically tested in tension at temperatures ranging from 25 to 250 ˚C. The parameters that will be considered to investigate the effectiveness of the sheets in elevated temperatures compared to room temperature include the modulus of elasticity, ultimate tensile strength, and strain at break, along with the corresponding stress-strain curves.

Detecting Sleep Apnea Using Mobile Phones

The paper discusses the design and implementation of a mobile application that uses the smart phone's sensors, e.g. microphone and built-in accelerometer, to record the snoring, breathing and movement patterns of users and get a sense of whether or not the user is likely to suffer from sleep apnea before continuing with more expensive and advanced sleep tests.