Browsing by Author "Erabadda, B"

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    item: Article-Abstract
    Cloud To Cloud: Enabling Content Transfer among Personal Cloud Instances
    Erabadda, B; Baddegama, V; Dias, G
    With increasing globalization, it has become essential to share digital content with various parties. Meanwhile, it is important to preserve confidentiality and have control over how a particular party’s personal content is maintained. Although public clouds enable users to share files with anyone, privacy and confidentiality of client data is highly questionable with public cloud vendors as client data lies with external parties. As a result, personal cloud solutions are being introduced so that people can maintain their own clouds and have control over their data. But with personal clouds, it is not possible to share content among cloud instances as they operate individually and separately from each other. Cloud To Cloud is a solution which enables content transfer among two or more personal cloud instances. For the purpose of explaining the feasibility of the solution, we have implemented the solution using ownCloud, the best existing personal cloud solution with many features. The solution can be extended to interconnect any number of ownCloud instances. The same methodology can be adapted to any preferred personal cloud solution.
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    item: Conference-Abstract
    Computer Aided Evaluation of Multi-Step Answers to Algebra Questions
    Erabadda, B; Ranathunga, S; Dias, G
    This paper presents a system that automatically assesses multi-step answers to algebra questions. The system requires teacher involvement only during the question set-up stage. Two types of algebra questions are currently supported: questions with linear equations containing fractions, and questions with quadratic equations. The system evaluates each step of a student's answer and awards full/partial marks according to a marking scheme. The system was evaluated for its performance using a set of student answer scripts from a government school in Sri Lanka and also by undergraduate students. The system accuracy was over 95.4%, and over 97.5%, respectively for the aforementioned data sets.