Forthcoming and Online First Articles

International Journal of Experimental Design and Process Optimisation

International Journal of Experimental Design and Process Optimisation (IJEDPO)

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 Articles will not be published until the final proofs are validated by their authors.

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International Journal of Experimental Design and Process Optimisation (2 papers in press)

Regular Issues

  • Data Analysis and Prediction Model Discovery through Decision Tree Learning   Order a copy of this article
    by Parham Porouhan 
    Abstract: Data mining and machine learning tools and approaches have been extensively used and practiced in bioinformatics with the purpose of analysing biomedical datasets. In this paper, we have chosen 'RapidMiner Studio' as a platform to create/generate 'decision tree models', which are obtained from a medical dataset. In research, 'decision trees' are considered as one of the most popular supervised (machine) learning techniques, which, as an instance can be effectively used for prediction of specific indicators/attributes affecting a disease. In general, this paper is divided into two main parts. In the first part of the study, an existing medical dataset with known label values (so-called, a training dataset) is used to identify and discover the hidden patterns. In the second part of the study, the generated/resulting patterns are used for making predictions. The results of the study provide groundwork for further and future studies.
    Keywords: data mining; rapidminer studio; decision trees; predictive analytics; model discovery; medical dataset.
    DOI: 10.1504/IJEDPO.2022.10051049
     
  • Characterization of Ionic Conductivity in Lithium-borate Glass: Experimental and Instructional Material on Impedance Spectroscopy   Order a copy of this article
    by Mbadiwe Samuel Benyeogor, Kosisochukwu Pal Nnoli, OLadayo Olufemi Olakanmi 
    Abstract: This paper discusses Impedance spectroscopy as a novel and effective method of characterising electrical materials and probing the dynamics of charge carriers at the interfacial layers of dielectrics. Here, an experiment is carried out to characterise the ionic conductivity (which infers resistivity) of two lithium-borate glass samples as a function of temperature, by means of impedance spectroscopy. The experiment compares or fits the impedance data to an equivalent circuit, which is a model of the underlying physical processes under investigation, and discusses the analogies between circuit elements and the processes. Analyses of the results show how the impedance of lithium-borate glass varies with temperature, between 240 and 320 degrees celsius. Moreover, this paper provides a conceptual foundation for introducing the experiment into school curricula.
    Keywords: electrical materials; impedance spectroscopy; ionic conductivity; instructional materials; lithium-borate glass; thin films.
    DOI: 10.1504/IJEDPO.2022.10052267
     

 

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