31,959 research outputs found
A diagrammatic representation for entities and mereotopological relations in ontologies
In the graphical representation of ontologies, it is customary to use graph theory as the representational background. We claim here that the standard graph-based approach has a number of limitations. We focus here on a problem in the graph-based representation of ontologies in complex domains such as biomedical, engineering and manufacturing: lack of mereotopological representation. Based on such limitation, we proposed a diagrammatic way to represent an entity’s structure and various forms of mereotopological relationships between the entities
Neural Networks Architecture Evaluation in a Quantum Computer
In this work, we propose a quantum algorithm to evaluate neural networks
architectures named Quantum Neural Network Architecture Evaluation (QNNAE). The
proposed algorithm is based on a quantum associative memory and the learning
algorithm for artificial neural networks. Unlike conventional algorithms for
evaluating neural network architectures, QNNAE does not depend on
initialization of weights. The proposed algorithm has a binary output and
results in 0 with probability proportional to the performance of the network.
And its computational cost is equal to the computational cost to train a neural
network
On bicluster aggregation and its benefits for enumerative solutions
Biclustering involves the simultaneous clustering of objects and their
attributes, thus defining local two-way clustering models. Recently, efficient
algorithms were conceived to enumerate all biclusters in real-valued datasets.
In this case, the solution composes a complete set of maximal and non-redundant
biclusters. However, the ability to enumerate biclusters revealed a challenging
scenario: in noisy datasets, each true bicluster may become highly fragmented
and with a high degree of overlapping. It prevents a direct analysis of the
obtained results. To revert the fragmentation, we propose here two approaches
for properly aggregating the whole set of enumerated biclusters: one based on
single linkage and the other directly exploring the rate of overlapping. Both
proposals were compared with each other and with the actual state-of-the-art in
several experiments, and they not only significantly reduced the number of
biclusters but also consistently increased the quality of the solution.Comment: 15 pages, will be published by Springer Verlag in the LNAI Series in
the book Advances in Data Minin
Broad Histogram Method for Continuous Systems: the XY-Model
We propose a way of implementing the Broad Histogram Monte Carlo method to
systems with continuous degrees of freedom, and we apply these ideas to
investigate the three-dimensional XY-model with periodic boundary conditions.
We have found an excellent agreement between our method and traditional
Metropolis results for the energy, the magnetization, the specific heat and the
magnetic susceptibility on a very large temperature range. For the calculation
of these quantities in the temperature range 0.7<T<4.7 our method took less CPU
time than the Metropolis simulations for 16 temperature points in that
temperature range. Furthermore, it calculates the whole temperature range
1.2<T<4.7 using only 2.2 times more computer effort than the Histogram Monte
Carlo method for the range 2.1<T<2.2. Our way of treatment is general, it can
also be applied to other systems with continuous degrees of freedom.Comment: 23 pages, 10 Postscript figures, to be published in Int. J. Mod.
Phys.
Visualizing test diversity to support test optimisation
Diversity has been used as an effective criteria to optimise test suites for
cost-effective testing. Particularly, diversity-based (alternatively referred
to as similarity-based) techniques have the benefit of being generic and
applicable across different Systems Under Test (SUT), and have been used to
automatically select or prioritise large sets of test cases. However, it is a
challenge to feedback diversity information to developers and testers since
results are typically many-dimensional. Furthermore, the generality of
diversity-based approaches makes it harder to choose when and where to apply
them. In this paper we address these challenges by investigating: i) what are
the trade-off in using different sources of diversity (e.g., diversity of test
requirements or test scripts) to optimise large test suites, and ii) how
visualisation of test diversity data can assist testers for test optimisation
and improvement. We perform a case study on three industrial projects and
present quantitative results on the fault detection capabilities and redundancy
levels of different sets of test cases. Our key result is that test similarity
maps, based on pair-wise diversity calculations, helped industrial
practitioners identify issues with their test repositories and decide on
actions to improve. We conclude that the visualisation of diversity information
can assist testers in their maintenance and optimisation activities
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