Search Results - (( developing pervasive computing algorithm ) OR ( java implementation towards algorithm ))
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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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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Network game (Literati) / Chung Mei Kuen
Published 2003“…This thesis steps towards developing a networked game, Literati game system that supporting two players at one time. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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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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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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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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Article -
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…The system is capable in operating an off-line programming method, starting from its programming sequences until robotic implementation of the program. During early stages, the research is emphasis more towards designing a robotic system using RoboLab software and C++ programming language. …”
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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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Network monopoly / Tan Kean Yeap
Published 2002“…The main aspect of this thesis is to produce a network monopoly system, which process multiple game sessions concurrently, enabling users to play the graphical game with people within the network. The algorithm design and implementation method mustnot only be workable, but also highly efficient in terms of execution speed and respond time. …”
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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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