Forthcoming and Online First Articles

International Journal of Intelligence and Sustainable Computing

International Journal of Intelligence and Sustainable Computing (IJISC)

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 Articles will not be published until the final proofs are validated by their authors.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 Intelligence and Sustainable Computing (3 papers in press)

Regular Issues

  • Emotional intelligence and Performance of Faculty in Knowledge Engineering Education   Order a copy of this article
    by Tenreiro Machado 
    Abstract: Faculty are instrumental in moulding and nurturing global citizens of future. Knowledge engineering looks very fascinating in terms of a rewarding career ahead and management education institutions are striving to not only to compete with each other but also to survive in current times of a dull employment scenario. There has been a drastic fall at the input level in most institutions that are affiliated to Universities and consequently the level of placements has suffered drastically with only a bright few getting decent salaries. The current scenario in education system requires herculean efforts on the part of the Management and especially the main facilitators, namely the faculty, to provide all resources and training to mould the students and transform them to be accepted by Corporate. Research was undertaken to analyse the levels of intelligence for the faculty alongside its effects on the performance given the fact that faculty are the core resource of such higher education institutions.
    Keywords: Knowledge engineering; post-graduation; institutions; emotional intelligence; faculty performance.
    DOI: 10.1504/IJISC.2020.10030890
     
  • A Variable Block Range Fractal Method for Image Compression   Order a copy of this article
    by Ghousia Anjum Shaik, T.Bhaskara Reddy, MOHAMMED ISMAIL, Mansoor Alam 
    Abstract: This paper presents and implements a variable block range fractal (VBRF) method for image compression on RGB images of different categories. The proposed technique shows improvement in compression ratio (CR), peak signal noise ratio (PSNR), similarity index (SI) and compression time (CT) on applying to digital images. Mean square error (MSE), entropy and coding redundancy issues are addressed for improvements. Standard test sample images are divided into varying blocks of three categories of maximum and minimum range (Ra) block of 16 x 4, 16 x 8 and 8 x 4 for implementation. Relative fractal affine transforms are used to form iterative ranges with varying blocks reconstructing corresponding eight inverse transforms. The proposed VBRF method is applied to set of test images like Lena, satellite urban and rural, MRI, rose, bird, Zelda, pepper, God hills, etc. and improvement in compression parameters is obtained with a rate of 8% to 10%. The results obtained on CR, PSNR, SI and CT shows the effectiveness of method in improving compression rate and noise mitigation in the compressed images. Proposed method implementation parameters are compared and validated with the other popular methods of fractal compression showing a considerable improvement in performance.
    Keywords: image compression; block ranges; compression ratio; peak signal noise ratio; PSNR; entropy; fractal compression and affine transforms.
    DOI: 10.1504/IJISC.2020.10036957
     
  • An Artificial Bee Colony based Reliable Cross Layer Design for Internet of Multimedia Things   Order a copy of this article
    by J. Shreyas, Dharamendra Chouhan, A.R. Akshatha, P.K. Udayprasad, S.M. Dilip Kumar 
    Abstract: The futuristic demands of multimedia applications requires extensive exchange of complex data attributes in the context of internet of multimedia things (IoMT). The exploration of the current research gap in this field shows that there is a need to develop an optimised routing technique for IoMT, which can cope-up with different network attributes, physical objects and fulfill communication requirements with cost-effective services and delivery modules. This paper proposes a cross-layer design optimisation for multimedia applications in IoMT where the prime focus has been laid towards communication performance aspects such as reducing the delay, energy constraints and maximising the low-cost energy utilisation. The proposed work models and integrates a swarm intelligence paradigm which involve intelligent computing of artificial bee colony (ABC) to ensure reliable link formation and selects optimal route between source and destination IoT nodes. The proposed work achieves the best routing utility for the communication of multimedia data over IoT. To ensure this, an extensive simulation outcome validates the performance of the proposed system. the results validated using MATLAB simulation tool shows 8% increase in energy utilisation, 10% increase in throughput, 8% decrease in end-to-end delay and 10% increase in packet delivery ratio.
    Keywords: internet of multimedia things; IoMT; cross layer design; artificial bee colony optimisation; swarm intelligence; quality of service.
    DOI: 10.1504/IJISC.2020.10037549
     

 

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