Performance Evaluation of Aspect Dependent-Based Ghost Suppression Methods for Through-the-Wall Radar Imaging

There are many approaches which address multipath ghost challenges in Through-the-Wall Radar Imaging (TWRI) under Compressive Sensing (CS) framework. One of the approaches, which exploits ghosts’ locations in the images, termed as Aspect Dependent (AD), does not require prior knowledge of the reflecting geometry making it superior over multipath exploitation based approaches. However, which method is superior within the AD based category is still unknown. Therefore, their performance comparison becomes inevitable, and hence this paper presents their performance evaluation in view of target reconstruction. At first, the methods were grouped based on how the subarrays were applied: multiple subarray, hybrid subarray and sparse array. The methods were fairly evaluated on varying noise level, data volume and the number of targets in the scene. Simulation results show that, when applied in a noisy environment, the hybrid subarray-based approaches were robust than the multiple subarray and sparse array. At 15 dB signal-to-noise ratio, the hybrid subarray exhibited signal to clutter ratio of 3.9 dB and 4.5 dB above the multiple subarray and sparse array, respectively. When high data volumes or in the case of multiple targets, multiple subarrays with duo subarrays became the best candidates. Keywords: Aspect dependent; compressive sensing; point target; through-wall-radar imaging

Collaborative development of remote electronics laboratories in the ELVIS ilab

Remote laboratories represent a significant value to engineering curricula in a variety of cases. Whether it is a complement to a hands-on experience or a substitute when a traditional lab is not feasible, remote laboratories can be a valuable educational resource. Since 1998, the MIT iLab Project has worked to increase the quality and availability of remote laboratories. Using the iLab Shared Architecture, developers of new labs can leverage a set of generic support functions and then share those labs easily and with minimal administrative cost. More recently, the iLab Project, in partnership with Obafemi Awolowo University in Nigeria, Makerere University in Uganda and the University of Dar-es-Salaam in Tanzania and in coordination with the Maricopa Advanced Technology Education Center (MATEC), has focused on building iLabs around the National Instruments Educational Laboratory Virtual Instrumentation Suite (ELVIS) platform. The ELVIS is a low-cost, small-footprint unit that contains most of the common test instruments found in a typical electrical engineering lab. By coupling the ELVIS with iLabs, a variety of remote electronics laboratories can be built and shared around the world. Using this common hardware/software platform, participants in the iLab Project at different levels of the educational spectrum have developed experiments that meet their individual curricular needs and are able to host them for use by other peer institutions. Not only does this increase the variety of ELVISbased iLabs, but it also spurs the creation of teams that can then build other, more diverse iLabs and substantively participate in project-wide collaborative development efforts. Through such coordinated efforts, iLabs can provide rich practical experiences for studentsMaricopa County Community College District. Maricopa Advanced Technology Education CenterCarnegie Corporation of New YorkMicrosoft CorporationNational Science Foundation (U.S.) (award 0702735)Singapore-MIT Alliance for Research and Technology Cente

Performance Analysis of Grey Level Fitting Mechanism based Gompertz Function for Image Reconstruction Algorithms in Electrical Capacitance Tomography Measurement System

Research Article published by International Journal of Computer Applications Volume 109 – No. 15, January 2015This paper analyses the performance of grey level fitting mechanism based on Gompertz function used in Electrical Capacitance Tomography measurement system. In order to evaluate its performance, the data fitting mechanism has been applied to common image reconstruction algorithms which include; Linear Back Projection, Singular Value Decomposition, Tikhonov Regularization, Iterative Tikhonov Regularization, Landweber iteration and Projected Landweber iteration. Images were reconstructed using measured capacitance data for annular and stratified flows, and qualitative and quantitative evaluation were done on the reconstructed images in comparison with respective reference images. Results show that this grey level fitting mechanism is better in terms of improving image spatial resolution, minimizing relative image error and distribution error and maximizing correlation coefficient

A review of image reconstruction methods in electrical capacitance tomography

A research article was submitted to Journal of Mathematical and Computational Science volume 6 (2016)In this paper, we review image reconstruction methods and their suitability in electrical capacitance tomography measurement system. These methods can be grouped into direct and iterative methods. Direct meth- ods include Linear back projection, Singular value decomposition, and Tikhonov regularization. Iterative methods are further divided into algebraic and optimization methods. Algebraic reconstruction methods include itera- tive linear back projection, iterative Tikhonov, Landweber iteration, simultaneously algebraic reconstruction, and model−based reconstruction. Optimization methods include fuzzy mathematical modeling, genetic algorithms, artificial neural networks, generalized vector sampled pattern matching, total variation regularization, regularized total least squares, extended Tikhonov regularization, simulated annealing, compressed sensing principle, popu- lation entropy, adaptive differential evolution, least−squares support vector machine, and self-adaptive particle swarm optimization. Some of these methods have been examined through experiments and their comparative analysis have been given. Results show that iterative methods generate high quality images compared with non- iterative ones when evaluated over full component fraction range. However, iterative methods are computationally expensive, and hence used for research and off-line investigations rather than for on-line process monitorin

A Grey Level Fitting Mechanism based on Gompertz Function for Two Phase Flow Imaging using Electrical Capacitance Tomography Measurement Systems

Research Article published by International Journal of Computer Applications Volume 101– No.8, September 2014Electrical Capacitance Tomography (ECT) is an image generating system based on soft field sensory system. The preferred Linear Back Projection (LPB) reconstruction algorithm for multi-phase measurement has blurring effect on the image generated. These two inherent factors, among others, affect the quality of image generated from ECT systems. Introducing fitting in the image generation process is one the solutions to improving its quality. In this article an alternative fitting mechanism based on the Gompertz function has been developed and evaluated. Comparative analysis results shows improvement on the spatial quality of images generated, in terms of minimum relative image and distribution errors, maximum correlation coefficient, and at relatively no additional computational cost. The mechanism is more effective for annular than stratified flow data hence complimenting the weakness of Xie method for annular flow

Analysis and Performance Evaluation of Entropic Thresholding Image Processing Techniques for Electrical Capacitance Tomography Measurement System

To improve image quality generated from the electrical capacitance tomography measurement system, the use of entropic thresholding techniques is investigated in this article. Based on the analysis of the principle of Electrical Capacitance Tomography (ECT) image reconstruction and entropic thresholding, various algorithms have been proposed for easy extraction of quantitative information from tomograms generated from the ECT system. Experiments indicate that proposed algorithms can provide high-quality images at no or minimum computational cost. It is easier to implement and integrate with classical algorithms such as Linear Back Projection, Singular value decomposition, Tikhonov regularization, and Landweber. Entropic thresholding techniques present a feasible and effective way toward the industrial utilization of ECT measurement systems. Keywords: Electrical Capacitance Tomography; Inverse Problem; Image Reconstruction; Entropic Thresholdin

Developing Multimedia Enhanced Content to Upgrade Science and Mathematics Subject Content Knowledge of Secondary School Teachers in Tanzania

The failure rates and lack of interest amongst students in science and mathematics in secondary schools in Tanzania is a serious problem. The Ministry of Education and Vocational Training (MoEVT) implemented the project to enhance and upgrade the pedagogical knowledge and subject content knowledge of teachers in selected difficult topics in science and mathematics at secondary education. This article reports on the process involved in the development of multimedia enhanced content that involved teachers, facilitators, and technical staff. The developed content was evaluated for its satisfaction using a sample of 72 experts that included teachers and instructors after using the content for 10 days. Generally, respondents were satisfied with the quality of the developed multimedia enhanced content. However, accuracy had minimum percentage of users’ satisfaction with 37%. This shows that the majority of the content had spelling and grammatical errors that were supposed to be corrected before producing the final product. Although this is ongoing work, we believe that the lessons learned from our efforts can be useful to similar organizations planning to develop multimedia enhanced content for educational purposes.

Developing Multimedia Enhanced Content to Upgrade Science and Mathematics Subject Content Knowledge of Secondary School Teachers in Tanzania

The failure rates and lack of interest amongst students in science and mathematics in secondary schools in Tanzania is a serious problem. The Ministry of Education and Vocational Training (MoEVT) implemented the project to enhance and upgrade the pedagogical knowledge and subject content knowledge of teachers in selected difficult topics in science and mathematics at secondary education. This article reports on the process involved in the development of multimedia enhanced content that involved teachers, facilitators, and technical staff. The developed content was evaluated for its satisfaction using a sample of 72 experts that included teachers and instructors after using the content for 10 days. Generally, respondents were satisfied with the quality of the developed multimedia enhanced content. However, accuracy had minimum percentage of users’ satisfaction with 37%. This shows that the majority of the content had spelling and grammatical errors that were supposed to be corrected before producing the final product. Although this is ongoing work, we believe that the lessons learned from our efforts can be useful to similar organizations planning to develop multimedia enhanced content for educational purposes.