Young Researcher Paper Award 2023
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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 35, Number 4(3) (2023)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 1375-1384
S&M3253 Research Paper of Special Issue https://doi.org/10.18494/SAM4261 Published: April 27, 2023 Optimal Path Planner of Training Course Recommendation for Reskilling/Upskilling in New S-curve Industries [PDF] Nanta Sooraksa and Kritkorn Nawakitphaitoon (Received November 28, 2022; Accepted February 14, 2023) Keywords: graph-based planner, path planning, new S-curve industries, training, course recommendation
To meet the need for a more skilled and technology-oriented workforce, the new S-curve industrial revolution is restructuring the labor market worldwide. The Thai government is now focusing on upgrading the country’s human resource skills to meet new demands. This paper presents an application of the well-known A* path planner in the field of artificial intelligence (AI) for recommending reskilling/upskilling training courses. Data are obtained from the Career Discovery Analysis Platform (CDAP), which was designed and implemented by the authors. The results obtained from CDAP are then summarized, leading to training course recommendations for the government and individuals. By considering the mean score zone as the sensing node of a graph-based planner, an optimal path for upskilling training course recommendation can be identified.
Corresponding author: Nanta Sooraksa  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Nanta Sooraksa and Kritkorn Nawakitphaitoon, Optimal Path Planner of Training Course Recommendation for Reskilling/Upskilling in New S-curve Industries, Sens. Mater., Vol. 35, No. 4, 2023, p. 1375-1384. |
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