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Autor:
Lee, Siaw Li1 (AUTHOR), Liew, Chin Ying1 (AUTHOR), Chen, Chee Khium1 (AUTHOR), Voon, Li Li1 (AUTHOR)
Publikováno v:
International Journal of Mathematics & Mathematical Sciences. 10/12/2022, p1-10. 10p.
Publikováno v:
International Journal of Academic Research in Business and Social Sciences. 13
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7deec58da9f1eecb03ea5da66df15369
https://doi.org/10.6007/ijarbss/v13-i5/16907
https://doi.org/10.6007/ijarbss/v13-i5/16907
Publikováno v:
Applied Network Science; 1/17/2023, Vol. 8 Issue 1, p1-34, 34p
Publikováno v:
International Journal of Service Management and Sustainability. 4
The purpose of this paper is to examine the confidence level and selfefficacy beliefs of Mathematics teachers, particularly in Kuching and Samarahan, using the instrument adapted from two reliable questionnaires: Trend in International Mathematics an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cc85b736df3219ce0b571550e6c07fb
https://doi.org/10.24191/ijsms.v4i2.8145
https://doi.org/10.24191/ijsms.v4i2.8145
Publikováno v:
Asian Journal of University Education. 16:121
Sketching the graph of mathematical functions using derivatives is a challenging task for undergraduate students who enrol for the first level of calculus course. Before graph plotting, students are required to perform a thorough function analysis us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b607f0bcd28a8232980544f3c0aaf578
https://doi.org/10.24191/ajue.v16i4.11962
https://doi.org/10.24191/ajue.v16i4.11962
Publikováno v:
KES
Current study intends to formulate a habitat suitability model of a newly surveyed marine mammal species where the research scenario is characterized by real-world data that is scarce with no detail demographic value available. It is extremely challe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f53c7047496dd59cff2a7024b92bfadc
https://doi.org/10.1016/j.procs.2015.08.126
https://doi.org/10.1016/j.procs.2015.08.126
Publikováno v:
AIP Conference Proceedings.
Support vector machines (SVMs) is a powerful machine learning algorithm for classification particularly in medical, image processing and text analysis related studies. Nonetheless, its application in ecology is scarce. This study aims to demonstrate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1e27fd1d284869dfd002f9b3cbc6521
https://doi.org/10.1063/1.4915644
https://doi.org/10.1063/1.4915644
Publikováno v:
Pertanika Journal of Social Sciences & Humanities; 3/ 1/2014, Vol. 22 Issue 1, p345-363, 19p