Forthcoming and Online First Articles

International Journal of Space-Based and Situated Computing

International Journal of Space-Based and Situated Computing (IJSSC)

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 Articles will not be published until the final proofs are validated by their authors.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 Space-Based and Situated Computing (2 papers in press)

Regular Issues

  • Data Privacy and Anonymization of Simulated Health-Care Dataset using the ARX Open-Source Tool   Order a copy of this article
    by Yogesh Beeharry, N.Y. Fakeeroodeen, T.P. Fowdur 
    Abstract: Internet of Things (IoT) and Big Data Analytics fields have been adopted in many practical applications geared towards the concept of smart cities and smart world. One critical aspect of these concepts is that of Smart-Health where private health information has to be transmitted over networks. The main concern arising in this scenario is that of data privacy and anonymity. Various open source tools and algorithms have been developed along this line. In this work, an analysis of the K-anonymity and differential privacy alongside t-closeness for sensitive attributes, algorithms have been performed on a simulated health-care dataset using the ARX open-source tool. The results demonstrate that the two models with t-closeness provided similar output results in relation to risk analysis, utility statistics and output data indicating equal appropriateness for both models. However, their property of transformation differed from each other.
    Keywords: Data Anonymization; privacy; K-Anonymity; Differential Privacy; ARX open-source tool.

  • Traffic Intersection Crossing Method for Intelligent Vehicles Based on Game Theory   Order a copy of this article
    by Yikai Wang, Zhuming Nie, Xi He 
    Abstract: Game theory is a tool for decision-making in the face of uncertain factors. In this paper, by analyzing the defects of the existing traffic light timing strategy, combined with the existing traffic conditions, a dynamic traffic crossing strategy based on game theory is proposed. This paper attempts to use game theory to determine the traffic relationship between intersections, adjust the timing of traffic lights in real time, and compare it with the existing timing methods through software simulation. The experimental results show that the dynamic traffic strategy proposed in this paper can improve the traffic efficiency, effectively reduce the maximum queue length, and has a strong adaptability to emergencies.
    Keywords: Game Theory; Traffic Strategy; Intelligent Vehicles; Vehicle-road Collaboration; Real-time Adjustment.

 

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