Forthcoming Articles

International Journal of Forensic Engineering

International Journal of Forensic Engineering (IJFE)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are also listed here. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

International Journal of Forensic Engineering (2 papers in press)

Regular Issues

  • Image averaging and shape recognition in forensic analysis of video evidence   Order a copy of this article
    by Geoffrey T. Desmoulin, Mark Nolette, Theodore E. Milner 
    Abstract: Averaging of raw images obtained from single frames of a body worn camera was used to illustrate the ability of averaging to significantly reduce the noise present in a single video frame. The outline the subject in the averaged image was then compared to outlines of a different subject adopting four similar postures, which included one posture that mimicked the posture of the first subject (reference posture). Using Hausdorff distance as a measure of shape similarity, it was possible to demonstrate that the outline of the second subject was most similar to the outline of the reference posture when the second subject mimicked the reference posture. Despite the similarity of the four postures, the Hausdorff distance was at least 50% less when the second subject mimicked the reference posture than for any of the other postures.
    Keywords: image averaging; image shape recognition; video analysis; shape difference measure; posture analysis.
    DOI: 10.1504/IJFE.2023.10059452
     
  • The role of artificial intelligence in engineering forensics: a meta-analysis study   Order a copy of this article
    by Moataz M. Sherif 
    Abstract: Artificial Intelligence (AI) presents a transformative potential for engineering forensics, yet a consolidated, quantitative assessment of its crossdomain performance and implementation pathways is lacking. This study conducts the first integrative cross-domain meta-analysis, 144 quantitative studies (from 156 eligible full-text studies) published between 2018 and 2024, supplemented by 25 case studies and 15 expert interviews. Random-effects models were used to synthesise effect sizes, with heterogeneity and publication bias assessed. AI integration significantly improves investigation accuracy (+30-87%, varying by domain), reduces investigation time (50-60%), cuts costs (40-42%), and enhances inter-analyst agreement (+-29.4%). Machine learning achieves 87% accuracy in failure prediction, while computer vision reaches 92% in defect detection. However, successful implementation requires addressing data quality, model interpretability, and ethical challenges. The research proposes and validates a five-phase adoption framework, providing evidence-based strategies for advancing forensic engineering toward a predictive and preventive paradigm. Performance benchmarks should be interpreted cautiously given evidence of publication bias.
    Keywords: artificial intelligence; engineering forensics; meta-analysis; machine learning; computer vision; failure analysis; explainable AI; structural health monitoring; implementation framework; predictive modelling.
    DOI: 10.1504/IJFE.2026.10078064
     

 

Return to top