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    Wyświetlanie 1-2 z 2
    Tytuł:
    Change over Time in Learners’ Mindsets about Learning a Foreign Language
    Autorzy:
    Shirvan, Majid Elahi
    Taherian, Tahereh
    Yazdanmehr, Elham
    Robat, Esmaeel Saeedy
    Powiązania:
    https://bibliotekanauki.pl/articles/2121371.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    language mindsets
    language mindsets index
    initial level
    growth level
    curve of factors model
    Opis:
    Inspired by the recent avenues for longitudinal research in second language acquisition (SLA), in this study we aimed to trace changes in language mindsets over time via a curve of factors model. The data were collected from 437 adult English as a foreign language learners’ response to the Language Mindsets Index in four time points. The model fit was accepted and the invariance of the latent factor was attested over time. The findings indicated a negative covariance between the initial level language mindsets and the growth level of the construct. This finding implies that learners with a highly initial level of language mindsets experienced less change in the construct over time and those with a lower level of the construct changed their mindsets more over time. Pedagogical implications of the findings such as language teachers’ consideration of growth language mindsets interventions are discussed.
    Źródło:
    Polish Psychological Bulletin; 2022, 53, 2; 94-103
    0079-2993
    Pojawia się w:
    Polish Psychological Bulletin
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An Efficient Classification of Hyperspectral Remotely Sensed Data Using Support Vector Machine
    Autorzy:
    Mahendra, H. N.
    Mallikarjunaswamy, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/2134051.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    support vector machine
    SVM
    central processing unit
    CPU
    digital signal processor
    DSP
    field programmable gate array
    FPGA
    high level synthesis
    HLS
    hardware description language
    HDL
    Opis:
    This work present an efficient hardware architecture of Support Vector Machine (SVM) for the classification of Hyperspectral remotely sensed data using High Level Synthesis (HLS) method. The high classification time and power consumption in traditional classification of remotely sensed data is the main motivation for this work. Therefore presented work helps to classify the remotely sensed data in real-time and to take immediate action during the natural disaster. An embedded based SVM is designed and implemented on Zynq SoC for classification of hyperspectral images. The data set of remotely sensed data are tested on different platforms and the performance is compared with existing works. Novelty in our proposed work is extend the HLS based FPGA implantation to the onboard classification system in remote sensing. The experimental results for selected data set from different class shows that our architecture on Zynq 7000 implementation generates a delay of 11.26 μs and power consumption of 1.7 Watts, which is extremely better as compared to other Field Programmable Gate Array (FPGA) implementation using Hardware description Language (HDL) and Central Processing Unit (CPU) implementation.
    Źródło:
    International Journal of Electronics and Telecommunications; 2022, 68, 3; 609--617
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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