Computer Science Research: Recent submissions

Now showing items 36-40 of 108

    • Reading small scalar data fields: color scales vs. Detail on Demand vs. FatFonts 

      Manteau, Constant; Nacenta, Miguel; Mauderer, Michael (Canadian Human-Computer Communications Society, 2017-05-16) - Conference item
      We empirically investigate the advantages and disadvantages of color- and digit-based methods to represent small scalar fields. We compare two types of color scales (one brightness-based and one that varies in hue, saturation ...

    • Opportunistic visualization with iVoLVER 

      Méndez, Gonzalo Gabriel; Nacenta, Miguel A. (IEEE Computer Society, 2016-11-08) - Conference item
      Proposed as 'data analysis anywhere, anytime, from anything', Opportunistic Information Visualization (Opportu-Vis) [1] seeks to provide analytical support in scenarios where the data of interest is not explicitly available ...

    • Algorithms for optimising heterogeneous Cloud virtual machine clusters 

      Thai, Long Thanh; Varghese, Blesson; Barker, Adam David (IEEE, 2016-12-12) - Conference item
      It is challenging to execute an application in a heterogeneous cloud cluster, which consists of multiple types of virtual machines with different performance capabilities and prices. This paper aims to mitigate this challenge ...

    • Timing properties and correctness for structured parallel programs on x86-64 multicores 

      Hammond, Kevin; Brown, Christopher Mark; Sarkar, Susmit (Springer, 2016) - Conference item
      This paper determines correctness and timing properties for structured parallel programs on x86-64 multicores. Multicore architectures are increasingly common, but real architectures have unpredictable timing properties, ...

    • Achieving stable subspace clustering by post-processing generic clustering results 

      Pham, Duc-Son; Arandjelovic, Ognjen; Venkatesh, Svetha (IEEE, 2016-10-31) - Conference item
      We propose an effective subspace selection scheme as a post-processing step to improve results obtained by sparse subspace clustering (SSC). Our method starts by the computation of stable subspaces using a novel random ...