Polytechnic University of Catalonia

About: Polytechnic University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Finite element method & Population. The organization has 16006 authors who have published 45325 publications receiving 949306 citations. The organization is also known as: UPC - BarcelonaTECH & Technical University of Catalonia.

Adaptive Learning from Evolving Data Streams

Abstract: We propose and illustrate a method for developing algorithms that can adaptively learn from data streams that drift over time. As an example, we take Hoeffding Tree, an incremental decision tree inducer for data streams, and use as a basis it to build two new methods that can deal with distribution and concept drift: a sliding window-based algorithm, Hoeffding Window Tree, and an adaptive method, Hoeffding Adaptive Tree. Our methods are based on using change detectors and estimator modules at the right places; we choose implementations with theoretical guarantees in order to extend such guarantees to the resulting adaptive learning algorithm. A main advantage of our methods is that they require no guess about how fast or how often the stream will drift; other methods typically have several user-defined parameters to this effect. In our experiments, the new methods never do worse, and in some cases do much better, than CVFDT, a well-known method for tree induction on data streams with drift.

A gene network model accounting for development and evolution of mammalian teeth.

Abstract: Generation of morphological diversity remains a challenge for evolutionary biologists because it is unclear how an ultimately finite number of genes involved in initial pattern formation integrates with morphogenesis. Ideally, models used to search for the simplest developmental principles on how genes produce form should account for both developmental process and evolutionary change. Here we present a model reproducing the morphology of mammalian teeth by integrating experimental data on gene interactions and growth into a morphodynamic mechanism in which developing morphology has a causal role in patterning. The model predicts the course of tooth-shape development in different mammalian species and also reproduces key transitions in evolution. Furthermore, we reproduce the known expression patterns of several genes involved in tooth development and their dynamics over developmental time. Large morphological effects frequently can be achieved by small changes, according to this model, and similar morphologies can be produced by different changes. This finding may be consistent with why predicting the morphological outcomes of molecular experiments is challenging. Nevertheless, models incorporating morphology and gene activity show promise for linking genotypes to phenotypes.

Effects of artificial micro- and nano-structured surfaces on cell behaviour.

Abstract: Substrate topography, independently of substrate chemistry, has been reported to have significant effects on cell behaviour. Based on the use of fabrication techniques developed by the silicon microtechnology industry, numerous studies can now be found in the literature analyzing cell behaviour as to various micro- and nano-features such as lines, wells, holes and more. Most of these works have been found to relate the micro- and nano-sized topographical features with cell orientation, migration, morphology and proliferation. In recent papers, even the influence of substrate nanotopography on cell gene expression and differentiation has been pointed out. However, despite the large number of papers published on this topic, significant general trends in cell behaviour are difficult to establish due to differences in cell type, substrate material, feature aspect-ratio, feature geometry and parameters measured. This paper intends to compile and review the relevant existing information on the behaviour of cells on micro- and nano-structured artificial substrates and analyze possible general behavioural trends.

SVMTool: A general POS Tagger Generator Based on Support Vector Machines

Abstract: This paper presents the SVMTool , a simple, flexible, effective and efficient part-of-speech tagger based on Support Vector Machines. The SVMTool offers a fairly good balance among these properties which make it really practical for current NLP applications. It is very easy to use and easily configurable so as to perfectly fit the needs of a number of different applications.

Grasp quality measures: review and performance

Abstract: The correct grasp of objects is a key aspect for the right fulfillment of a given task. Obtaining a good grasp requires algorithms to automatically determine proper contact points on the object as well as proper hand configurations, especially when dexterous manipulation is desired, and the quantification of a good grasp requires the definition of suitable grasp quality measures. This article reviews the quality measures proposed in the literature to evaluate grasp quality. The quality measures are classified into two groups according to the main aspect they evaluate: location of contact points on the object and hand configuration. The approaches that combine different measures from the two previous groups to obtain a global quality measure are also reviewed, as well as some measures related to human hand studies and grasp performance. Several examples are presented to illustrate and compare the performance of the reviewed measures.