All Outputs (5)

Leveraging the Cloud for Large-Scale Software Testing – A Case Study: Google Chrome on Amazon (2013)
Book Chapter
Pakhira, A., & Andras, P. (2013). Leveraging the Cloud for Large-Scale Software Testing – A Case Study: Google Chrome on Amazon. In S. Tilley, & T. Parveen (Eds.), Software Testing in the Cloud: Perspectives on an Emerging Discipline (252-279). IGI Global. https://doi.org/10.4018/978-1-4666-2536-5.ch012

Testing is a critical phase in the software life-cycle. While small-scale component-wise testing is done routinely as part of development and maintenance of large-scale software, the system level testing of the whole software is much more problematic... Read More about Leveraging the Cloud for Large-Scale Software Testing – A Case Study: Google Chrome on Amazon.

A measure to assess the behavior of method stereotypes in object-oriented software (2013)
Presentation / Conference Contribution
Andras, P., Pakhira, A., Moreno, L., & Marcus, A. (2013, May). A measure to assess the behavior of method stereotypes in object-oriented software. Presented at 2013 4th International Workshop on Emerging Trends in Software Metrics (WETSoM), San Francisco, CA, USA

The implementation of software systems should ideally follow the design intentions of the system. However, this is not always the case - the design and implementation of software systems may diverge during software evolution. In this paper we propose... Read More about A measure to assess the behavior of method stereotypes in object-oriented software.

On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution (2013)
Presentation / Conference Contribution
Hammerla, N. Y., Kirkham, R., Andras, P., & Ploetz, T. (2013, September). On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution. Presented at UbiComp '13: The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Zurich, Switzerland

The majority of activity recognition systems in wearable computing rely on a set of statistical measures, such as means and moments, extracted from short frames of continuous sensor measurements to perform recognition. These features implicitly quant... Read More about On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution.

Function approximation using combined unsupervised and supervised learning (2013)
Journal Article
Andras, P. (2014). Function approximation using combined unsupervised and supervised learning. IEEE Transactions on Neural Networks and Learning Systems, 25(3), 495-505. https://doi.org/10.1109/TNNLS.2013.2276044

Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data space, which usually requires exponentially increasi... Read More about Function approximation using combined unsupervised and supervised learning.

Towards reliable hybrid bio-silicon integration using novel adaptive control system (2013)
Presentation / Conference Contribution
Luo, J. W., Degenaar, P., Coapes, G., Yakovlev, A., Mak, T., & Andras, P. (2013, May). Towards reliable hybrid bio-silicon integration using novel adaptive control system. Presented at 2013 IEEE International Symposium on Circuits and Systems (ISCAS), Beijing, China

Hybrid bio-silicon networks are difficult to implement in practice due to variations of biological neuron bursting frequency. This causes the hybrid network to have inaccuracies and unreliability. The network may produce irregular bursts or incorrect... Read More about Towards reliable hybrid bio-silicon integration using novel adaptive control system.