Special Issue "Computing Techniques for Environmental Research and Public Health"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".

Deadline for manuscript submissions: 31 July 2020.

Special Issue Editors

Prof. Dr. Gwanggil Jeon
E-Mail Website
Guest Editor
Department of Embedded Systems Engineering, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon, 22012, Korea
Tel. +82-32-835-8946
Interests: image/signal processing; entropy coding; artificial intelligence; color image processing; machine learning; remote sensing; hyperspectral imaging; data fusion Learning; Remote Sensing; Hyperspectral Imaging; Data Fusion
Special Issues and Collections in MDPI journals
Prof. Dr. Abdellah Chehri
E-Mail Website
Guest Editor
Department of Applied Sciences, University of Québec in Chicoutimi, Chicoutimi G7H 2B1, Canada
Interests: entropy coding; remote sensing; biomedical analysis of signals; pattern recognition; image processing; signal processing
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Human bodies are continuously generating information about our health. This information can be assessed by physiological tools that gauge bio-signals such as blood pressure, heart rate, and blood glucose. Computer scientists are obtaining knowledge on new technologies to manage these bio-signals using a range of equations and approaches. Currently, real-time monitoring, cloud computing, edge computing, and the Internet of Things are key technologies that can be applied in the Environmental Research and Public Health field. This Special Issue calls for recent studies on computing approaches for use in the Environmental Research and Public Health field. Papers of both theoretical and applicative nature are welcome, as well as contributions regarding new computing techniques for the Environmental Research and Public Health research community. Potential topics of interest include, but are not limited to:

  • public health;
  • bio-signal processing;
  • the Internet of Things;
  • real-time monitoring;
  • cloud computing.

Prof. Dr. Gwanggil Jeon
Prof. Dr. Abdellah Chehri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • public health
  • bio-signal processing
  • internet of things
  • real-time monitoring
  • cloud computing

Published Papers (1 paper)

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Research

Open AccessArticle
Predicting Factors Affecting Adolescent Obesity Using General Bayesian Network and What-If Analysis
Int. J. Environ. Res. Public Health 2019, 16(23), 4684; https://doi.org/10.3390/ijerph16234684 - 25 Nov 2019
Abstract
With the remarkable improvement in people’s socioeconomic living standards around the world, adolescent obesity has increasingly become an important public health issue that cannot be ignored. Thus, we have implemented its use in an attempt to explore the viability of scenario-based simulations through [...] Read more.
With the remarkable improvement in people’s socioeconomic living standards around the world, adolescent obesity has increasingly become an important public health issue that cannot be ignored. Thus, we have implemented its use in an attempt to explore the viability of scenario-based simulations through the use of a data mining approach. In doing so, we wanted to explore the merits of using a General Bayesian Network (GBN) with What-If analysis while exploring how it can be utilized in other areas of public health. We analyzed data from the 2017 Korean Youth Health Behavior Survey conducted directly by the Korea Centers for Disease Control & Prevention, including 19 attributes and 11,206 individual data points. Our simulations found that by manipulating the amount of pocket money-between $60 and $80-coupled with a low-income background, it has a high potential to increase obesity compared with other simulated factors. Additionally, when we manipulated an increase in studying time with a mediocre academic performance, it was found to potentially increase pressure on adolescents, which subsequently led to an increased obesity outcome. Lastly, we found that when we manipulated an increase in a father’s education level while manipulating a decrease in mother’s education level, this had a large effect on the potential adolescent obesity level. Although obesity was the chosen case, this paper acts more as a proof of concept in analyzing public health through GBN and What-If analysis. Therefore, it aims to guide health professionals into potentially expanding their ability to simulate certain outcomes based on predicted changes in certain factors concerning future public health issues. Full article
(This article belongs to the Special Issue Computing Techniques for Environmental Research and Public Health)
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