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Making location-aware computing working accurately in smart spaces
Published 2011“…In smart environment, making a location-aware personal computing working accurately is a way of getting close to the pervasive computing vision. …”
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Book Chapter -
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Graph processing hardware accelerator for shortest path algorithms in nanometer very large-scale integration interconnect routing
Published 2007“…Graphs are pervasive data structures in computer science, and algorithms working with them are fundamental to the field. …”
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A hardware implementation of Rivest-Shamir-Adleman co-processor for resource constrained embedded systems
Published 2006“…The concern with security problems has been rapidly increasing as computers and Internet services become a more pervasive part of our daily life. …”
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LINGUISTIC FUZZY MODELING IN LASER MACHINING QUALITY EVALUATION
Published 2007“…The aim of this scientific research is to design knowledge based linguistic rules, algorithm, architecture & learning ability and further develop fuzzy model for laser machining kerf edge quality prediction. …”
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Conference or Workshop Item -
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Fuzzy expert system modeling of laser processing
Published 2009“…This paper discusses a specific approach of surface roughness predictive modelling by Fuzzy Logic - a unique way of computational solution. The objective of the paper is: to design knowledge based rules, algorithm, architecture & learning ability to develop fuzzy surface roughness predictive model for laser machining; to develop fuzzy predictive model using design parameters which were critically analyzed; to make a comparative study of the observed and modelled surface roughness output of 5mm Mn-Mo pressure vessel plate. …”
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RSSI Fingerprinting Approach for Location-Based Services
Published 2006“…Therefore, based on my knowledge and developed tools in localization, I can further develop a locationbased service system. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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Portfolio optimization with percentage error-based fuzzy random data for industrial production
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Portfolio optimization with percentage error-based fuzzy random data for industrial production
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