A novel hybrid simulation-optimization approach for the optimal design of multicomponent distillation columns

Póster presentado en Escape 22, European Symposium on Computer Aided Process Engineering, University College London, UK, 17-20 June 2012.

GRO J1008−57: an (almost) predictable transient X-ray binary

A study of archival RXTE, Swift, and Suzaku pointed observations of the transient high-mass X-ray binary GRO J1008−57 is presented. A new orbital ephemeris based on pulse arrival-timing shows the times of maximum luminosities during outbursts of GRO J1008−57 to be close to periastron at orbital phase − 0.03. This makes the source one of a few for which outburst dates can be predicted with very high precision. Spectra of the source in 2005, 2007, and 2011 can be well described by a simple power law with high-energy cutoff and an additional black body at lower energies. The photon index of the power law and the black-body flux only depend on the 15–50 keV source flux. No apparent hysteresis effects are seen. These correlations allow us to predict the evolution of the pulsar’s X-ray spectral shape over all outbursts as a function of just one parameter, the source’s flux. If modified by an additional soft component, this prediction even holds during GRO J1008−57’s 2012 type II outburst.

Local convergence of quasi-Newton methods under metric regularity

We consider quasi-Newton methods for generalized equations in Banach spaces under metric regularity and give a sufficient condition for q-linear convergence. Then we show that the well-known Broyden update satisfies this sufficient condition in Hilbert spaces. We also establish various modes of q-superlinear convergence of the Broyden update under strong metric subregularity, metric regularity and strong metric regularity. In particular, we show that the Broyden update applied to a generalized equation in Hilbert spaces satisfies the Dennis–Moré condition for q-superlinear convergence. Simple numerical examples illustrate the results.

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.

Corpus Use and Learning to Translate, almost 20 years on

It is almost 20 years since a series of conferences known as CULT (Corpus Use and Learning to Translate) started. The first and second took place in Bertinoro, Italy, back in 1997 and 2000, respectively. The third was held in 2004 in Barcelona, and the fourth in 2015 in Alicante. Each was organized by a few enthusiastic lecturers and scholars who also happened to be corpus lovers. Guy Aston, Silvia Bernardini, Dominic Stewart and Federico Zanettin, from the Universitá di Bologna; Allison Beeby, Patricia Rodríguez-Inés and Pilar Sánchez-Gijón, from the Universitat Autònoma de Barcelona; and Daniel Gallego-Hernández, from the Universidad de Alicante, organized CULT conferences in the belief that spreading the word about the usefulness of corpora for teaching and professional translation purposes would have positive results.