Design of a location-based augmented reality game for the development of key 21st century competences in primary education

The use of augmented reality games (ARGs) in education has gained increased attention from curriculum developers, teachers, and researchers in the past decade. Research findings show that ARGs can promote meaningful learning environments that foster key competences for the 21st century. This paper presents the design process of “EcoAegean”, an ARG for mobile devices, which was implemented in primary classroom environments to support the development of students’ key competences in the context of sustainability. The game was created using an open augmented reality software platform and its design was based on contemporary theoretical underpinnings regarding the use of such games in educational contexts. In the first section of the paper, we describe the design procedures of the learning scenario as well as the game itself. In the last section of the paper, we offer a set of critical insights on the design and implementation of mobile augmented reality games for the purpose of supporting students’ development of key 21st century competences.</p

Enhanced FEM-based DBIM approach for two-dimensional microwave imaging

© 2020 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The distorted Born iterative method (DBIM) is widely used in microwave imaging to solve the electromagnetic inverse scattering problem iteratively based on the distorted Born approximation. Various methods are used for the forward solver in the DBIM to simulate wave propagation and scattering. In this paper, a new matrix building technique exploiting the basis functions of the finite element method (FEM) is used as forward solver to create the inverse-problem matrix in a two-dimensional (2D) DBIM algorithm. The proposed approach provides great efficiency as the entries of this matrix are readily calculated from already pre-computed matrices in the FEM procedure without the need of interpolation to calculate the field. The FEM-based DBIM is validated with both simulated data and experimental data from a microwave tomography (MWT) system. Results confirm that the proposed FEM implementation can be an efficient and accurate forward solver for the MWT system.This work was funded in part by the Spanish Ministry of Science, Innovation and Universities, under grant number CAS18/00097 from the Jose Castillejo Research Mobility Programme, in part by Innovate UK grant number 103920, in part by the Engineering and Physical Sciences Research Council grant number EP/R013918/1, and in part by AEI/FEDER, UE, under project number TEC2016-76070-C3-1-R (ADDMATE

Tools for the efficient implementation of the DBIM algorithm in microwave imaging experiments

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksWe present two efficient tools to improve both the experimental data and the reconstruction results in microwave imaging. The time-gating technique can remove part of the unexpected reflections of the cables and tanks, thus improving the quality of the received signals obtained from the experiment system. We also apply the fast iterative shrinkage thresholding algorithm (FISTA) to the distorted Born iterative method (DBIM) as a linear inverse solver at each iteration of the DBIM, which shows better capabilities than the conventional conjugate gradient least squares (CGLS) method with experimental data. Results confirm that the two tools used in the DBIM can be efficient and accurate when employed in the microwave imaging systemThis work was funded in part by Innovate UK grant number 103920, in part by the Engineering and Physical Sciences Research Council grant number EP/R013918/1, in part by AEI/FEDER, UE, under project number TEC2016-76070-C3- 1-R (ADDMATE), and in part by the Spanish Ministry of Science, Innovation and Universities, under grant number CAS18/00097 from the Jose Castillejo Research Mobility Programm

Feasibility Study of Enhancing Microwave Brain Imaging Using Metamaterials

We present an approach to enhance microwave brain imaging with an innovative metamaterial (MM) planar design based on a cross-shaped split-ring resonator (SRR-CS). The proposed metasurface is incorporated in different setups, and its interaction with EM waves is studied both experimentally and by using CST Microwave Studio R and is compared to a “no MM” case scenario. We show that the MM can enhance the penetration of the transmitted signals into the human head when placed in contact with skin tissue, acting as an impedance-matching layer. In addition, we show that the MM can improve the transceivers’ ability to detect useful “weak” signals when incorporated in a headband scanner for brain imaging by increasing the signal difference from a blood-like dielectric target introduced into the brain volume. Our results suggest that the proposed MM film can be a powerful hardware advance towards the development of scanners for brain haemorrhage detection and monitoring

A Q-Slot Monopole for UWB Body-Centric Wireless Communications

This paper presents a novel and simple ultrawideband printed rectangular monopole antenna for body-centric wireless communications. The design is based on etching a Q-slot on a rectangular radiator and is optimized to produce the largest bandwidth in free space and close to the human body. We analyze the design of the proposed antenna and assess its performance in terms of bandwidth, gain, efficiency, and radiation patterns. We also characterize the antenna in the time-domain by calculating its fidelity factor. Our results show that the Q-slot antenna maintains its bandwidth when placed in close contact with the human body, or in contact with breast-mimicking tissue phantoms. The very good agreement between the calculated and measured antenna performances in free space and on body suggests that the antenna is immune to variations in the human tissue and is also robust to fabrication tolerances

Effect of Varying Prior Information in Axillary 2D Microwave Tomography

We numerically assess the potential of microwave tomography (MWT) for the detection and dielectric properties estimation of axillary lymph nodes (ALNs), and we study the robustness of our system using prior information with varying levels of accuracy. We adopt a 2-dimensional MWT system with 8 antennas (0.5-2.5 GHz) placed around the axillary region. The reconstruction algorithm implements the distorted Born iterative method. We show that: (i) when accurate prior knowledge of the axillary tissues (fat and muscle) is available, our system successfully detects an ALN; (ii) ±30% error in the prior estimation of fat and muscle dielectric properties does not affect image quality; (iii) ±7mm error in muscle position causes slight artifacts, while ± 14mm error in muscle position affects ALN detection. To the best of our knowledge, this is the first paper in the literature to study the impact of prior information accuracy on detecting an ALN using MWT.info:eu-repo/semantics/publishedVersio

Metamaterial designs to enhance microwave imaging applications

This paper presents an innovative metasurface design for emerging microwave brain imaging applications, such as stroke detection and monitoring. We have modelled different metamaterial designs in diverse setups, and have simulated their interactions with EM waves using CST Microwave Studio. Our results have shown an enhancement of penetration for the transmitted signals when the metamaterial film is placed in contact with the skin tissue. These results suggest that our design can be a significant hardware advance towards scanners for brain imaging

Experimental Validation of Microwave Tomographywith the DBIM-TwIST Algorithm for Brain StrokeDetection and Classification

We present an initial experimental validation of a microwave tomography (MWT) prototype for brain stroke detection and classification using the distorted Born iterative method, two-step iterative shrinkage thresholding (DBIM-TwIST) algorithm. The validation study consists of first preparing and characterizing gel phantoms which mimic the structure and the dielectric properties of a simplified brain model with a haemorrhagic or ischemic stroke target. Then, we measure the S-parameters of the phantoms in our experimental prototype and process the scattered signals from 0.5 to 2.5 GHz using the DBIM-TwIST algorithm to estimate the dielectric properties of the reconstruction domain. Ourresultsdemonstratethatweareabletodetectthestroketargetinscenarios where the initial guess of the inverse problem is only an approximation of the true experimental phantom. Moreover, the prototype can differentiate between haemorrhagic and ischemic strokes based on the estimation of their dielectric properties