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ABSTRACT Society depends now more strongly than ever on large-scale networks. Failures of great s... more ABSTRACT Society depends now more strongly than ever on large-scale networks. Failures of great significance have occurred in the last years. Thus, it has become of vital importance to define robustness metrics. Classical robustness analysis has been focused on the evaluation of topological characteristics. In this paper we extend this analysis introducing two new robustness metrics that include traffic service requirements: QuaNtitative Robustness Metric (QNRM) and QuaLitative Robustness Metric (QLRM). A review of some well known graph robustness metrics is provided. In order to compare these metrics with the proposals, a set of six topologies (random, small-world and scale-free) is evaluated. Finally, it is shown that our two new metrics are able to evaluate the performance of a network under a given kind of impairment.
... As a rule of thumb, about half of the participants in the futures markets are hedgers Page 3.... more ... As a rule of thumb, about half of the participants in the futures markets are hedgers Page 3. Easwaran and Ramasundaram : Commodity Futures Market in Agriculture 339 ... Page 5. Easwaran and Ramasundaram : Commodity Futures Market in Agriculture 341 ...
Many heuristics used for finding biclusters in microarray data use the mean squared residue as a ... more Many heuristics used for finding biclusters in microarray data use the mean squared residue as a way of evaluating the quality of biclusters. This has led to the discovery of interesting biclusters. Recently it has been proven that the mean squared residue may fail to identify some interesting biclusters. This motivates us to introduce a new measure, called Virtual Error, for assessing the quality of biclusters in microarray data. In order to test the validity of the proposed measure, we include it within an evolutionary algorithm. Experimental results show that the use of this novel measure is effective for finding interesting biclusters, which could not have been discovered with the use of the mean squared residue.
The use of Graphics Processing Units (GPUs) in general purpose computing has been shown to incur ... more The use of Graphics Processing Units (GPUs) in general purpose computing has been shown to incur significant performance benefits, for applications ranging from scientific computing to database sorting and search. The emergence of high-level APIs facilitates GPU programming to the point that general purpose computing with GPUs is now considered a viable system design and programming option. Nevertheless, the inclusion of a GPU in general purpose computing results in an associated increase in the system's power budget. This paper presents an experimental investigation into the power and energy cost of GPU operations and a cost/performance comparison versus a CPU-only system. Through real-time energy measurements obtained using a novel platform called LEAP-Server, we show that using a GPU results in energy savings if the performance gain is above a certain bound. We show this bound for an example experiment tested by LEAP-Server.
Abstract Biclustering is simultaneous clustering of both rows and columns of a data matrix. A me... more Abstract Biclustering is simultaneous clustering of both rows and columns of a data matrix. A measure called Mean Squared Residue (MSR) is used to simultaneously evaluate the coherence of rows and columns within a submatrix. In this paper a novel algorithm is developed for ...
ABSTRACT Society depends now more strongly than ever on large-scale networks. Failures of great s... more ABSTRACT Society depends now more strongly than ever on large-scale networks. Failures of great significance have occurred in the last years. Thus, it has become of vital importance to define robustness metrics. Classical robustness analysis has been focused on the evaluation of topological characteristics. In this paper we extend this analysis introducing two new robustness metrics that include traffic service requirements: QuaNtitative Robustness Metric (QNRM) and QuaLitative Robustness Metric (QLRM). A review of some well known graph robustness metrics is provided. In order to compare these metrics with the proposals, a set of six topologies (random, small-world and scale-free) is evaluated. Finally, it is shown that our two new metrics are able to evaluate the performance of a network under a given kind of impairment.
... As a rule of thumb, about half of the participants in the futures markets are hedgers Page 3.... more ... As a rule of thumb, about half of the participants in the futures markets are hedgers Page 3. Easwaran and Ramasundaram : Commodity Futures Market in Agriculture 339 ... Page 5. Easwaran and Ramasundaram : Commodity Futures Market in Agriculture 341 ...
Many heuristics used for finding biclusters in microarray data use the mean squared residue as a ... more Many heuristics used for finding biclusters in microarray data use the mean squared residue as a way of evaluating the quality of biclusters. This has led to the discovery of interesting biclusters. Recently it has been proven that the mean squared residue may fail to identify some interesting biclusters. This motivates us to introduce a new measure, called Virtual Error, for assessing the quality of biclusters in microarray data. In order to test the validity of the proposed measure, we include it within an evolutionary algorithm. Experimental results show that the use of this novel measure is effective for finding interesting biclusters, which could not have been discovered with the use of the mean squared residue.
The use of Graphics Processing Units (GPUs) in general purpose computing has been shown to incur ... more The use of Graphics Processing Units (GPUs) in general purpose computing has been shown to incur significant performance benefits, for applications ranging from scientific computing to database sorting and search. The emergence of high-level APIs facilitates GPU programming to the point that general purpose computing with GPUs is now considered a viable system design and programming option. Nevertheless, the inclusion of a GPU in general purpose computing results in an associated increase in the system's power budget. This paper presents an experimental investigation into the power and energy cost of GPU operations and a cost/performance comparison versus a CPU-only system. Through real-time energy measurements obtained using a novel platform called LEAP-Server, we show that using a GPU results in energy savings if the performance gain is above a certain bound. We show this bound for an example experiment tested by LEAP-Server.
Abstract Biclustering is simultaneous clustering of both rows and columns of a data matrix. A me... more Abstract Biclustering is simultaneous clustering of both rows and columns of a data matrix. A measure called Mean Squared Residue (MSR) is used to simultaneously evaluate the coherence of rows and columns within a submatrix. In this paper a novel algorithm is developed for ...