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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English 日本語
Instructions for manuscript preparation
English 日本語
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English
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MYU K.K.
Sensors and Materials
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The Art of Writing Scientific Papers
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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 32, Number 10(1) (2020)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 3235-3242
S&M2335 Research Paper of Special Issue https://doi.org/10.18494/SAM.2020.2862 Published: October 9, 2020 System for Recommending Facial Skincare Products [PDF] Chih-Hsien Hsia, Ting-Yu Lin, Jhe-Li Lin, Heri Prasetyo, Shih-Lun Chen, and Hsien-Wei Tseng (Received March 15, 2020; Accepted June 30, 2020) Keywords: acne, skincare, care product recommendation system, support vector machine
Acne is a skin problem that plagues many young people and adults. Even if it is cured, it leaves acne spots or acne scars and many individuals must use skincare products or undertake medical treatment. However, the use of inappropriate skincare products can exacerbate skin conditions. We propose the use of multifeature processing and classification of skin quality and acne status by machine learning to make recommendations for facial skincare products. The results for 15 subjects show that the proposed system achieves a consumer satisfaction index of 80%.
Corresponding author: Hsien-Wei Tseng  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Chih-Hsien Hsia, Ting-Yu Lin, Jhe-Li Lin, Heri Prasetyo, Shih-Lun Chen, and Hsien-Wei Tseng, System for Recommending Facial Skincare Products, Sens. Mater., Vol. 32, No. 10, 2020, p. 3235-3242. |
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- Deep Learning Prediction Model of Mortality Including Brain-type Natriuretic Peptide in Patients with Acute Decompensated Heart Failure
Hirotaka Takizawa, Masatoshi Minamisawa, Hirohiko Motoki, Koichiro Kuwahara, and Masaki Yamaguchi
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