Journals

  • Machine Learning Applications in Engineering Education and Management

    Machine Learning Applications in Engineering Education and Management (ISSN: 2984-7834)

    Frequency: Bi-Annually (Two times a year)

    Article Processing Charges: None

    About MLAEEM Journal

    Machine Learning Applications in Engineering Education and Management (MLAEEM) is a peer reviewed, open access journal focused on research related to machine learning. The journal encompasses all aspects of research and development in ML, including but not limited to data mining, computer vision, natural language processing (NLP), intelligent systems, neural networks, AI-based software engineering, bioinformatics, and their applications in the areas of engineering, business, and social sciences. It covers a broad spectrum of applications in the community, from industry, government, and academia.

    The journal publishes research results in addition to new approaches to ML, with a focus on value and effectiveness. Application papers should demonstrate how ML can be used to solve important practical problems. Research methodology papers should demonstrate an improvement to the way in which existing ML research is conducted.

    Submissions must be novel, technically sound, and clearly presented. MLAEEM accepts both regular papers and technical notes (technical notes are limited to a maximum of 12 pages). In addition, survey articles and discussion papers on ML are welcome.

    Submissions meeting journal criteria will undergo a double-blind review process, utilizing a minimum of two (2) external referees. Our dedicated editorial team, together with active researchers from all areas of ML, ensure that papers move through the evaluation and review as fast as possible without compromising on the quality of the process.

    The journal audience comprises academia, industry, and practitioners. Authors are strongly encouraged to make their datasets publicly accessible via a repository of their choosing. Please see our Guide for Authors for information on article submission

  • Engineering and Technology Conference Proceedings

    Engineering and Technology Conference Proceedings (ISSN: 2984-7818)

    Engineering and Technology Conference Proceedings is a Bi-annual open access journal dedicated to publishing findings resulting from conferences, workshops, and similar events, in all areas of engineering. The journal operates two peer review processes: for conference volumes, the peer review process is handled by the conference committee, and the review method as well as reports number are decided by the conference organizers' requirements; for standalone papers, the process is handled by researchers and scholars, as a single-blind assessment with at least one independent reviewer, followed by a final acceptance/rejection decision by the journal’s Advisory Board Members.

    Engineering and Technology Conference Proceedings provides an advanced forum for studies on engineering that are presented at an academic conference. It publishes proceeding papers, abstracts, and conference reports on particular subjects.

    The aim of Engineering and Technology Conference Proceedings is to help the conference organizers to publish cutting-edge, original, and peer-reviewed outputs resulting from the conference. All kinds of materials that result from the conference, including but not limited to presentations, posters, and videos, can be published along with their paper in the journal if accepted by the academic editor after peer review.

    Scope

    • Chemical engineering
    • Civil engineering
    • Electric and electronic engineering
    • Mechanical engineering
    • Materials engineering
    • Bioengineering
    • Environmental engineering
    • Computer and software engineering
    • Biomedical engineering

  • Machine Learning Applications: Conference Proceedings

    Proceeding Name: Machine Learning Applications: Conference Proceedings

    ISSN: 2984-7826

    Frequency: Separate Volume for each submitted Proceeding (Irregular)

    The Machine Learning Applications: Conference Proceedings is a conference series that publishes machine learning research papers presented at symposuims and conferences. Each volume is separately titled and associated with a particular symposuim or conference and will be published online on the web site. Authors retain copyright.

    Machine Learning Applications: Conference Proceedings is a peer reviewed proceeding focused on research related to machine learning. This proceeding encompasses all aspects of research and development in ML, including but not limited to data mining, computer vision, natural language processing (NLP), intelligent systems, neural networks, AI-based software engineering, bioinformatics, and their applications in the areas of engineering, business, and social sciences. It covers a broad spectrum of applications in the community, from industry, government, and academia.

    The proceedings publishes research results in addition to new approaches to ML, with a focus on value and effectiveness. Application papers should demonstrate how ML can be used to solve important practical problems. Research methodology papers should demonstrate an improvement to the way in which existing ML research is conducted. The proceeding audience comprises academia, industry, and practitioners. Authors are strongly encouraged to make their datasets publicly accessible via a repository of their choosing.