Department of Computer Science and Information Systems

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Author: search.filters.author.K., Pradheep KumarSubject: search.filters.subject.Fuzzy logic

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    Fuzzy Based Augmented Reality for 3D Image Modelling
    (TEST Engineering & Management, 2020) K., Pradheep Kumar
    In today’s world Augmented Reality and Virtual Reality is of prime importance. To create a scenario using Augmented Reality it is important to model objects in 3D space. Once the modelling is complete the Augmented Reality Map could be used in several applications like medicine where 3D bio printing should be done. It could also be used in education and teaching to illustrate complex working mechanisms. Here a fuzzy based algorithm has been proposed to create 3D models of objects for Augmented Reality maps. The Fuzzy rule method reduces RMSE, compared to AR Marker, Fingertips and Checkerboard by 35%, 45% and 21% respectively. The Fuzzy rule method also improves accuracy of resolution of images, compared to AR Marker, Fingertips and Checkerboard by 48%, 11% and 11% respectively.
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    Fuzzy-Based Querying Approach for Multidimensional Big Data Quality Assessment
    (2017) K., Pradheep Kumar
    This paper is intended to design a fuzzy based approach to assess standards and quality of big data. It also serves as a platform to organizations that intend to migrate their existing database environment to big data environment. Data is assessed using a multidimensional approach based on quality factors like accuracy, completeness, reliability, usability, etc. These factors are analysed by constructing decision trees to identify the quality aspects which need to be improved. In this work fuzzy queries have been designed. The queries are grouped as sets namely Excellent, Optimal, Fair and Hybrid. Based on the fuzzy data sets formed and the query compatibility index, a query set is chosen. A data set that has a very high degree of membership is assigned a fair query set. A data set with a medium degree of membership is assigned a optimal query set. A data set that has a lesser degree of membership is assigned a Excellent query set. A data set which needs a combination of queries of all the above is assigned a hybrid query set. The fuzzy query based approach reduces the query compatibility index by 36%, compared to a normal query set approach.