Combination Strategies for Semantic Role Labeling

This paper introduces and analyzes a battery of inference models for the problem of semantic role labeling: one based on constraint satisfaction, and several strategies that model the inference as a meta-learning problem using discriminative classifiers. These classifiers are developed with a rich set of novel features that encode proposition and sentence-level information. To our knowledge, this is the first work that: (a) performs a thorough analysis of learning-based inference models for semantic role labeling, and (b) compares several inference strategies in this context. We evaluate the proposed inference strategies in the framework of the CoNLL-2005 shared task using only automatically-generated syntactic information. The extensive experimental evaluation and analysis indicates that all the proposed inference strategies are successful -they all outperform the current best results reported in the CoNLL-2005 evaluation exercise- but each of the proposed approaches has its advantages and disadvantages. Several important traits of a state-of-the-art SRL combination strategy emerge from this analysis: (i) individual models should be combined at the granularity of candidate arguments rather than at the granularity of complete solutions; (ii) the best combination strategy uses an inference model based in learning; and (iii) the learning-based inference benefits from max-margin classifiers and global feedback

Autocontrol y comportamiento : efectividad de las tecnicas autoinstruccionales en el aprendizaje de las operaciones aritmeticas

This experiment was designed to research the efficacy of self-instructional variables to improve performance in solving easy arithmetic problems. Children, boys and girls, six and seven years old, studying first school year of E.G.B., were used. The results, as a whole, tell us that training in self-instructional techniques significantly affects the dependent variable, decreasing the number of mistakes pupils make in arithmetical operations. It is appropriate to underline the group verbalizing the addition, which got the most significant reduction. These results, which confirm the findings of other authors, show the possibility of applying Cognitive-conductual techniques in the school frame

Interband electron Raman scattering in a quantum wire in a transverse magnetic field

Electron Raman scattering (ERS) is investigated in a parabolic semiconductor quantum wire in a transverse magnetic field neglecting by phonon-assisted transitions. The ERS cross-section is calculated as a function of a frequency shift and magnetic field. The process involves an interband electronic transition and an intraband transition between quantized subbands. We analyze the differential cross-section for different scattering configurations. We study selection rules for the processes. Some singularities in the Raman spectra are found and interpreted. The scattering spectrum shows density-of-states peaks and interband matrix elements maximums and a strong resonance when scattered frequency equals to the "hybrid" frequency or confinement frequency depending on the light polarization. Numerical results are presented for a GaAs/AlGaAs quantum wire.Comment: 8 pages, 5 figure

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CoDaPack 2.0: a stand-alone, multi-platform compositional software

Historically CoDaPack 3D has intended to be a software of Compositional Data with an easy and intuitive way of use. For this reason from the beginning it has been associated to Excel, a software known and used for many people. However, over the years different versions of Excel and Windows have been appeared and CoDaPack has had to be adapted to these new versions due to some incompatibilities. For this reason, and also because of CoDaPack only works with Excel under windows, the Girona Compositional Data Group has decided to implement a new software with at least the same capabilities and the same profile of users but independent of any other software. The graphical user interface has three different areas: The variables area, the data area and the results area which has a textual output window and independent graphical output. Also, because the new CoDaPack is being developed under Java code, the final software is going to work in any platform having a Java Virtual Machine: Windows, Linux and other Unix based systems