Evaluation of complex temporal questions in CLEF-QA

This paper presents the evaluation of a QA system for the treatment of complex temporal questions. The system was implemented in a multilayered architecture where complex temporal questions are first decomposed into simple questions, according to the temporal relations expressed in the original question. These simple questions are then processed independently by our standard Question Answering engine and their respective answers are filtered to satisfy the temporal restrictions of each simple question. The answers to the simple decomposed questions are then combined, according to the temporal relations extracted from the original complex question, to give the final answer. This evaluation was performed as a pilot task in the Spanish QA Track of the Cross Language Evaluation Forum 2004.

Evaluating EmotiBlog robustness for sentiment analysis tasks

EmotiBlog is a corpus labelled with the homonymous annotation schema designed for detecting subjectivity in the new textual genres. Preliminary research demonstrated its relevance as a Machine Learning resource to detect opinionated data. In this paper we compare EmotiBlog with the JRC corpus in order to check the EmotiBlog robustness of annotation. For this research we concentrate on its coarse-grained labels. We carry out a deep ML experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC demonstrating the EmotiBlog validity as a resource for the SA task.

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

Extractive text summarization: can we use the same techniques for any text?

In this paper we address two issues. The first one analyzes whether the performance of a text summarization method depends on the topic of a document. The second one is concerned with how certain linguistic properties of a text may affect the performance of a number of automatic text summarization methods. For this we consider semantic analysis methods, such as textual entailment and anaphora resolution, and we study how they are related to proper noun, pronoun and noun ratios calculated over original documents that are grouped into related topics. Given the obtained results, we can conclude that although our first hypothesis is not supported, since it has been found no evident relationship between the topic of a document and the performance of the methods employed, adapting summarization systems to the linguistic properties of input documents benefits the process of summarization.

Towards a new proposal to evaluate the learning objects quality in learning strategies for education (QEES)

In Computer Science world several proposals have been developed for the assessment of the quality of the digital objects, based on the capabilities and facilities offered by current technologies and the available resources. Years ago researchers and specialists from both educational and technological areas have been committed to the development of strategies that improve the quality of education. At present, in the field of teaching-learning, another important aspect is the need to improve the manner of gaining knowledge and learning in education, which the use of learning strategies is a major advance in the teaching-learning process in institutions of higher education. This paper presents QEES, a proposal for evaluating the quality of the learning objects employed on learning strategies to support students during their education processes by using information extraction techniques and ontologies.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Experiences Using an Open Source Sofware Library to Teach Computer Vision Subjects

Machine vision is an important subject in computer science and engineering degrees. For laboratory experimentation, it is desirable to have a complete and easy-to-use tool. In this work we present a Java library, oriented to teaching computer vision. We have designed and built the library from the scratch with enfasis on readability and understanding rather than on efficiency. However, the library can also be used for research purposes. JavaVis is an open source Java library, oriented to the teaching of Computer Vision. It consists of a framework with several features that meet its demands. It has been designed to be easy to use: the user does not have to deal with internal structures or graphical interface, and should the student need to add a new algorithm it can be done simply enough. Once we sketch the library, we focus on the experience the student gets using this library in several computer vision courses. Our main goal is to find out whether the students understand what they are doing, that is, find out how much the library helps the student in grasping the basic concepts of computer vision. In the last four years we have conducted surveys to assess how much the students have improved their skills by using this library.

An Electronic Reconfigurable Neural Architecture for Intrusion Detection

The explosive growth of the traffic in computer systems has made it clear that traditional control techniques are not adequate to provide the system users fast access to network resources and prevent unfair uses. In this paper, we present a reconfigurable digital hardware implementation of a specific neural model for intrusion detection. It uses a specific vector of characterization of the network packages (intrusion vector) which is starting from information obtained during the access intent. This vector will be treated by the system. Our approach is adaptative and to detecting these intrusions by using a complex artificial intelligence method known as multilayer perceptron. The implementation have been developed and tested into a reconfigurable hardware (FPGA) for embedded systems. Finally, the Intrusion detection system was tested in a real-world simulation to gauge its effectiveness and real-time response.

Simulation of the secondary electrons energy deposition produced by proton beams in PMMA: influence of the target electronic excitation description

We have studied the radial dependence of the energy deposition of the secondary electron generated by swift proton beams incident with energies T = 50 keV–5 MeV on poly(methylmethacrylate) (PMMA). Two different approaches have been used to model the electronic excitation spectrum of PMMA through its energy loss function (ELF), namely the extended-Drude ELF and the Mermin ELF. The singly differential cross section and the total cross section for ionization, as well as the average energy of the generated secondary electrons, show sizeable differences at T ⩽ 0.1 MeV when evaluated with these two ELF models. In order to know the radial distribution around the proton track of the energy deposited by the cascade of secondary electrons, a simulation has been performed that follows the motion of the electrons through the target taking into account both the inelastic interactions (via electronic ionizations and excitations as well as electron-phonon and electron trapping by polaron creation) and the elastic interactions. The radial distribution of the energy deposited by the secondary electrons around the proton track shows notable differences between the simulations performed with the extended-Drude ELF or the Mermin ELF, being the former more spread out (and, therefore, less peaked) than the latter. The highest intensity and sharpness of the deposited energy distributions takes place for proton beams incident with T ~ 0.1–1 MeV. We have also studied the influence in the radial distribution of deposited energy of using a full energy distribution of secondary electrons generated by proton impact or using a single value (namely, the average value of the distribution); our results show that differences between both simulations become important for proton energies larger than ~0.1 MeV. The results presented in this work have potential applications in materials science, as well as hadron therapy (due to the use of PMMA as a tissue phantom) in order to properly consider the generation of electrons by proton beams and their subsequent transport and energy deposition through the target in nanometric scales.

Essays on Firm Heterogeneity with Empirical Applications in Economic History and Agricultural Economics

This thesis uses models of firm-heterogeneity to complete empirical analyses in economic history and agricultural economics. In Chapter 2, a theoretical model of firm heterogeneity is used to derive a statistic that summarizes the welfare gains from the introduction of a new technology. The empirical application considers the use of mechanical steam power in the Canadian manufacturing sector during the late nineteenth century. I exploit exogenous variation in geography to estimate several parameters of the model. My results indicate that the use of steam power resulted in a 15.1 percent increase in firm-level productivity and a 3.0-5.2 percent increase in aggregate welfare. Chapter 3 considers various policy alternatives to price ceiling legislation in the market for production quotas in the dairy farming sector in Quebec. I develop a dynamic model of the demand for quotas with farmers that are heterogeneous in their marginal cost of milk production. The econometric analysis uses farm-level data and estimates a parameter of the theoretical model that is required for the counterfactual experiments. The results indicate that the price of quotas could be reduced to the ceiling price through a 4.16 percent expansion of the aggregate supply of quotas, or through moderate trade liberalization of Canadian dairy products. In Chapter 4, I study the relationship between farm-level productivity and participation in the Commercial Export Milk (CEM) program. I use a difference-in-difference research design with inverse propensity weights to test for causality between participation in the CEM program and total factor productivity (TFP). I find a positive correlation between participation in the CEM program and TFP, however I find no statistically significant evidence that the CEM program affected TFP.