Forthcoming and Online First Articles

International Journal of Intelligent Defence Support Systems

International Journal of Intelligent Defence Support Systems (IJIDSS)

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 Articles will not be published until the final proofs are validated by their authors.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 Intelligent Defence Support Systems (2 papers in press)

Regular Issues

  • IoT Services and Deep Learning Techniques for an On-site Facial Recognition Security System   Order a copy of this article
    by Amlan Mohanty, Rakesh Kumar Lenka 
    Abstract: Security is a primary concern today for any organization. With the advancement in technology, newer and more effective security systems and solutions are being put to use, making it tougher to breach and easier to manage. The Internet of Things (IoT) is a bridge between machines and the hub of all data the Internet. A potent security model is a real-time Face Recognition system. This research tries to put forth a model of an effective and smart security structure using IoT services and face recognition technology. IoT devices have been used along with the Intel Neural Compute Stick2. Deep Learning and DNN concepts are implemented for the face recognition algorithm for their effectiveness over other algorithms. The Caffe detector is used for localizing faces, followed by creating face embedding by implementing Deep Metric Learning and Triplet Loss concepts. Finally, we have used the Support Vector Machine Classifier for recognizing the faces.
    Keywords: Internet of Things; Face Recognition; Deep Learning; Deep Neural Network; Face Identification and Security.
    DOI: 10.1504/IJIDSS.2022.10050575
     
  • A Delphi-Analytical Hierarchy Process (AHP) Approach for Important Factors and Indicators Selection for Big Data Model in E-Governance   Order a copy of this article
    by Charu Verma, P.K. Suri 
    Abstract: This study explores the key factors and indicators of a big data model for e-governance performance by using a six-step modified Delphi followed by analytical hierarchy process (AHP). The study aims to develop this model through consensus among selected experts for the factors that define e-governance performance and the factors (big data related) that impact it. The experts included e-governance practitioners, consultants and academicians. Analysis of experts’ inputs after two rounds of Delphi led to a shortlist of nine factors and 40 indicators (initially 46 indicators were identified from the literature review). The importance of each factor and indicator was calculated using AHP weights. Out of nine factors, four factors were of greater importance,
    Keywords: analytical hierarchy process; AHP; analytics; big data; Delphi; e-governance; electronic governance; e-government; electronic government; performance.
    DOI: 10.1504/IJIDSS.2022.10052082
     

 

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