Virtual laboratory for educational environments

In this paper a new simulation environment for a virtual laboratory to educational proposes is presented. The Logisim platform was adopted as the base digital simulation tool, since it has a modular implementation in Java. All the hardware devices used in the laboratory course was designed as components accessible by the simulation tool, and integrated as a library. Moreover, this new library allows the user to access an external interface. This work was motivated by the needed to achieve better learning times on co-design projects, based on hardware and software implementations, and to reduce the laboratory time, decreasing the operational costs of engineer teaching. Furthermore, the use of virtual laboratories in educational environments allows the students to perform functional tests, before they went to a real laboratory. Moreover, these functional tests allow to speed-up the learning when a problem based approach methodology is considered. © 2014 IEEE.

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

System-on-chip field-programmable gate array design for onboard real-time hyperspectral unmixing

Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.

FPGA-based architecture for hyperspectral endmember extraction

Hyperspectral instruments have been incorporated in satellite missions, providing data of high spectral resolution of the Earth. This data can be used in remote sensing applications, such as, target detection, hazard prevention, and monitoring oil spills, among others. In most of these applications, one of the requirements of paramount importance is the ability to give real-time or near real-time response. Recently, onboard processing systems have emerged, in order to overcome the huge amount of data to transfer from the satellite to the ground station, and thus, avoiding delays between hyperspectral image acquisition and its interpretation. For this purpose, compact reconfigurable hardware modules, such as field programmable gate arrays (FPGAs) are widely used. This paper proposes a parallel FPGA-based architecture for endmember’s signature extraction. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data sets collected by the NASA’s Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems, opening new perspectives for onboard hyperspectral image processing.

An exploratory study of orthoptic student satisfaction in a blended learning environment

Purpose: To describe orthoptic student satisfaction in a blended learning environment. Methods: Blended learning and teaching approaches that include a mix of sessions with elearning are being used since 2011/2012 involving final year (4th year) students from an orthoptic program. This approach is used in the module of research in orthoptics during the 1 semester. Students experienced different teaching approaches, which include seminars, tutorial group discussions and e-learning activities using the moodle platform. The Constructivist OnLine Learning Environment Survey (COLLES ) was applied at the end of the semester with 24 questions grouped in 6 dimensions with 4 items each: Relevance to professional practice, Reflection, Interactivity, Tutor support, Peer support and Interpretation. A 5-point Likert scale was used to score each individual item of the questionnaire (1 - almost never to 5 – almost always). The sum of items in each dimension ranged between 4 (negative perception) and 20 (positive perception). Results: Twenty-four students replied to the questionnaire. Positive points were related with Relevance (16.13±2.63), Reflection (16.46±2.45), Tutor support (16.29±2.10) and Interpretation (15.38±2.16). The majority of the students (n=18; 75%) think that the on-line learning is relevant to students’ professional practice. Critical reflections about learning contents were frequent (n=19; 79.17%). The tutor was able to stimulate critical thinking (n=21; 87.50%), encouraged students to participate (n=18; 75%) and understood well the student’s contributions (n=15; 62.50%). Less positive points were related with Interactivity (14.13±2.77) and Peer support (13.29±2.60). Response from the colleagues to ideas (n=11; 45.83%) and valorization of individual contributions (n=10; 41.67%) scored lower than other items. Conclusions: The flow back and forth between face-to-face and online learning situations helps the students to make critical reflections. The majority of the students are satisfied with a blended e-learning system environment. However, more work needs to be done to improve interactivity and peer support.