Journal of Engineering Research and Reports <p style="text-align: justify;"><strong>Journal of Engineering Research and Reports</strong>&nbsp;<strong>(ISSN: 2582-2926)</strong> aims to publish high-quality papers in all areas&nbsp;of engineering.&nbsp;The journal also encourages the submission of useful reports of negative results. This is a quality controlled,&nbsp;OPEN&nbsp;peer-reviewed, open access INTERNATIONAL journal.</p> en-US (Journal of Engineering Research and Reports) (Journal of Engineering Research and Reports) Mon, 03 Aug 2020 14:11:21 +0000 OJS 60 Determination of Transmission Coefficients and Energy Density of an Overlay Microstrip Patch Antenna for Microwave Filters and Feeds Designs Using Microwave Methods <p>In designing filters and antenna feeds at microwave frequency, the energy density and stop bands are of vital importance. To this development, this work is set out to determine the transmission coefficients behavior of substrates along with their energy density for a microstrip structure using finite element method (FEM) and Vector network analyzer (VNA). In this work, a 15, 30 and 50 mm PTFE samples were used as an overlay substrate material on a patch microstrip antenna. Simulations and measurement were then carried using FEM and VNA, respectively. Transmission coefficient obtained via FEM and VNA were compared and the behavior of the substrates at 10 GHz were noted which is the area of broad stop band. Results from simulation and measurement showed that the energy density of the 50 mm thick substrates was 1.67 x 10<sup>-5</sup> J/m<sup>3</sup> while the attenuated power for the 15, 30 and 50 mm thick substrates at 10 GHz were 6.8, 8.0 and 14.6 dB, respectively. Based on these findings, it is concluded that the 50 mm thick PTFE substrates has the deepest stopband at 10 GHz and more suitable for filter designs and antenna feeds.</p> Abubakar Yakubu, Zulkifly Abbas, Suleiman Sahabi ##submission.copyrightStatement## Mon, 03 Aug 2020 00:00:00 +0000 Online Detection and Extraction of FECG Signals Using ICA: A Comparative Study <p>In this paper a new study to detect fetal heart rate (F H R) online from abdominal electrocardiogram (ECG) signal, which are extracted by three different algorithms of independent component analysis ICA (AMUSE, EVD2 and SOBI) is presented. Four stages for fetal electrocardiogram (FECG) extraction and detection is proposed. After preprocessing and (FECG) extraction by ICA, maternal QRS complex removal window is used to remove or scale down the maternal remaining peaks, and smoothed by II notch filter. 25 data sets are used to validate this method of study for fetal peak detection online from signals extracted by ICA. Two ways are used to test 25 signals firstly off line and secondly online.</p> <p>The average sensitivity of the ICA (AMUSE, EVD2 and SOBI) based method are 72.3%, 66.2% and 75.1% off line respectively, and 55%, 53% and 059% online respectively, while average positive predictivity are 61.4%, 61.3% and 69.7% off line respectively, while 43%, 41% and 46% online respectively. These show that the ICA based method is more successful in detecting the FHR off line than online, which is more complicated, where the automatic selection of the output signals is not a trivial task.</p> Mohammed Sheikh, Majdi Marai, Roiss Alhutaish ##submission.copyrightStatement## Tue, 04 Aug 2020 00:00:00 +0000 Vehicle Detection, Tracking and Counting Using Gaussian Mixture Model and Optical Flow <p>Vehicle detection, tracking, and counting play a significant role in traffic surveillance and are principle applications of the Intelligent Transport System (ITS). Traffic congestion and accidents can be prevented with an adequate solution to problems. In this paper, we implemented different image processing techniques to detect and track the moving vehicle from the videos captured by a stationary camera and count the total number of vehicles passed by. The proposed approach consists of an optical flow method with a Gaussian mixture model (GMM) to obtain an absolute shape of particular moving objects which improves the detection performance of moving targets.</p> Muhammad Moin Akhtar, Yong Li, Lei Zhong, Ayesha Ansari ##submission.copyrightStatement## Tue, 04 Aug 2020 00:00:00 +0000