Traffic NOx Pollution Prediction and Health Cost Estimation Using Machine Learning: A Case Study of Toronto, Canada
Abstract
(ISSN 2690-1692)
Journal of Energy and Power Technology (JEPT) is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. This periodical is dedicated to providing a unique, peer-reviewed, multi-disciplinary platform for researchers, scientists and engineers in academia, research institutions, government agencies and industry. The journal is also of interest to technology developers, planners, policy makers and technical, economic and policy advisers to present their research results and findings.
Journal of Energy and Power Technology focuses on all aspects of energy and power. It publishes not only original research and review articles, but also various other types of articles from experts in these fields, such as Communication, Opinion, Comment, Conference Report, Technical Note, Book Review, and more, to promote intuitive understanding of the state-of-the-art and technology trends.
Main research areas include (but are not limited to):
Renewable energies (e.g. geothermal, solar, wind, hydro, tidal, wave, biomass) and grid connection impact
Energy harvesting devices
Energy storage
Hybrid/combined/integrated energy systems for multi-generation
Hydrogen energy
Fuel cells
Nuclear energy
Energy economics and finance
Energy policy
Energy and environment
Energy conversion, conservation and management
Smart energy system
Power generation - Conventional and renewable
Power system management
Power transmission and distribution
Smart grid technologies
Micro- and nano-energy systems and technologies
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High voltage and pulse power
Organic and inorganic photovoltaics
Batteries and supercapacitors
Publication Speed (median values for papers published in 2023): Submission to First Decision: 5.1 weeks; Submission to Acceptance: 11.6 weeks; Acceptance to Publication: 7 days (1-2 days of FREE language polishing included)
Special Issue
Energy Efficiency in Flexible and Reconfigurable Manufacturing: Emerging Trends, Models and Applications in the Industry 4.0 Era
Submission Deadline: May 15, 2021 (Closed) Submit Now
Guest Editor
Marco Bortolini, PhD
Senior Assistant Professor, Department of Industrial Engineering, Alma Mater Studiorum - Bologna University, Italy
Research Interests: energy efficiency, advanced production system, Industry 4.0, multi-attribute model, renewable energy for industry, sustainability
Co-Editor
Francesco Gabriele Galizia, PhD
Post-Doctoral Research Fellow, Department of Industrial Engineering, Alma Mater Studiorum - Bologna University, Italy
Research Interests: reconfigurable manufacturing system, collaborative assembly, optimization in production, Industry 4.0, smart manufacturing
Introduction
Industry 4.0 is the present of production. Starting from a theoretical concept to draw the future of industry, Industry 4.0 is, now, much more than a vision. This term comes from a project in the high-tech strategy of the German government in 2011 for promoting the computerization of manufacturing and, in the last few years, the Industry 4.0 emerged as the fourth industrial revolution. In this new era, digital manufacturing plays a crucial role and digital manufacturing technologies are key enabling technologies for the future manufacturing.
Nine enabling technologies, characterizing the upcoming industrial revolution, support the transition to the industrial practice:
Each of these technologies and, much more, the synergic coordination of these, allow disruptive changes and upgrades to almost all the industrial and advanced tertiary sectors with performance improvement, waste reduction, cost and time savings, etc. At the same time, all these technologies are fueled by energy, representing the power for their use.
Within this scenario, this Special Issue aims at investigating the synergies and conflicts between Industry 4.0 techs applied to flexible production and energy efficiency, introducing the energy saving dimension together with other, almost highly discussed, metrics, such as quality, cost and productivity.
Scientists and Experts from academy and industry are highly welcomed to contribute with methods, reviews and case histories from the field presenting innovative research and experiences.
Relevant topics include, but are not limited to:
Keywords
industry 4.0; flexible production; energy efficiency; advanced production; flexible assembly; reconfigurable manufacturing; sustainability; enabling technology; case histories; models, strategies and reviews.
Manuscript Submission Information
Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (jept@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.
Welcome your submission!
Publication
Traffic NOx Pollution Prediction and Health Cost Estimation Using Machine Learning: A Case Study of Toronto, Canadaby
Hamidreza Shamsi
,
Ehsan Haghi
,
Manh-Kien Tran
,
Sean Walker
,
Kaamran Raahemifar
and
Michael Fowler
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