3 research outputs found

    Comprehensive overview of education during three COVID-19 pandemic periods : impact on engineering students in Sri Lanka

    Get PDF
    The study provided an overview of changes in the educational system due to the COVID-19 pandemic among engineering undergraduates of Sri Lanka. Results show that students’ attendance in online classes improved over time compared to the initial pandemic period. Nearly 50% of students’ family income was impacted- either stopped or reduced due to the pandemic. Most students have issues regarding computing devices, internet connectivity, and the home environment, which are not conducive to learning at home. Under normal circumstances, engineering undergraduates in Sri Lanka have high exposure to modern technology and a diversity of instructional delivery, hence this student cohort was chosen for the study

    GAUSS: Guided Encoder-Decoder Architecture for Hyperspectral Unmixing with Spatial Smoothness

    Full text link
    In recent hyperspectral unmixing (HU) literature, the application of deep learning (DL) has become more prominent, especially with the autoencoder (AE) architecture. We propose a split architecture and use a pseudo-ground truth for abundances to guide the `unmixing network' (UN) optimization. Preceding the UN, an `approximation network' (AN) is proposed, which will improve the association between the centre pixel and its neighbourhood. Hence, it will accentuate spatial correlation in the abundances as its output is the input to the UN and the reference for the `mixing network' (MN). In the Guided Encoder-Decoder Architecture for Hyperspectral Unmixing with Spatial Smoothness (GAUSS), we proposed using one-hot encoded abundances as the pseudo-ground truth to guide the UN; computed using the k-means algorithm to exclude the use of prior HU methods. Furthermore, we release the single-layer constraint on MN by introducing the UN generated abundances in contrast to the standard AE for HU. Secondly, we experimented with two modifications on the pre-trained network using the GAUSS method. In GAUSSblind_\textit{blind}, we have concatenated the UN and the MN to back-propagate the reconstruction error gradients to the encoder. Then, in the GAUSSprime_\textit{prime}, abundance results of a signal processing (SP) method with reliable abundance results were used as the pseudo-ground truth with the GAUSS architecture. According to quantitative and graphical results for four experimental datasets, the three architectures either transcended or equated the performance of existing HU algorithms from both DL and SP domains.Comment: 16 pages, 6 figure

    A Comprehensive Overview of Education during Three COVID-19 Pandemic Periods: Impact on Engineering Students in Sri Lanka

    No full text
    The COVID-19 pandemic has impacted the education system in Sri Lanka, similar to many countries in the world. As a result, the mode of education shifted from conventional face-to-face classes to online mode. The main objective of this study is to provide a comprehensive overview of the changes to the educational system due to the COVID-19 pandemic among engineering undergraduates of Sri Lanka over three identified pandemic periods. Quantitative descriptive analysis was used together with chi-square statistics to answer the research questions using the data collected through a google survey from engineering undergraduates in Sri Lanka. According to the results, students’ attendance in online classes has improved over time compared to the initial pandemic period. Nearly 50% of students’ family income has been impacted, either stopped or reduced due to the pandemic. Most students have issues regarding computing devices, internet connectivity, and the home environment. According to the chi-square statistics results, few of these issues had a statistically significant relationship between the family income; lower the income, higher the negative impact on students. More than half of the students felt isolated when studying at home during the pandemic. Still, more than 50% of students agreed that lecturers were well prepared to guide and deliver lessons remotely. The overall recommendations of the study are implementing workshops, training on new technologies, awareness programs for educational stakeholders, providing incentives to purchase digital devices, and improving internet connectivity to improve the new standard education system of Sri Lanka
    corecore