Access to large data, especially for text processing applications, results in more effec tive algorithms and therefore becomes transcendental to take advantage of these large amounts of data. Latent Semantic Analysis (LSA) ...

In recent years dynamic programming of networks has gained popularity, this is known as software defined networks. The communications protocol OpenFlow has become one of the most important amongst the software defined ...

Balancing algorithms challenge the state of the art on how data exchanges as messages between programs that execute in the kernel and the applications running on top in user space on a modern Operating System. There is ...

Cluster analysis is one of data mining most common tasks, used frequently in finance, biology, medicine and market analysis problems [12]. High dimensional data poses a challenge to traditional clustering algorithms, where ...

Continuous improvement, preventive maintenance and machine fault prediction are the main focus of engineers that develop such machines today. Through signal analysis, correlations and anomalies can be found which would ...

As HPC systems move towards extreme scale, soft errors leading to silent data corruptions become a major concern. In this thesis, we propose a set of three optimizations to the classical Redundant Multithreading (RMT) ...