Clasificación visual estructural de la madera de pino radiata procedente de Cataluña

Se han clasificado visualmente, según la norma española UNE 56544; 150 piezas de madera aserrada de pino radiata procedentes de Cataluña (España) con una sección de 80x150 mm y una longitud de 2.500 mm. Esta norma establece dos calidades visuales (ME-1 y ME-2) para piezas con grueso menor o igual que 70 mm y una única calidad visual (MEG) para gruesos mayores de 70 mm. Con el fin de conocer el efecto frontera entre la pequeña y la gran escuadría se clasificaron las piezas según ambas categorías. Se determinó la tensión de rotura en flexión, el módulo de elasticidad en flexión y la densidad de cada pieza mediante el ensayo de acuerdo con la norma UNE-EN 408 siguiendo los ajustes definidos en la norma UNE-EN 384. Un 53 % de las piezas se clasificaron como MEG con una resistencia característica a flexión de 28 N/mm2 y un valor medio del módulo de elasticidad de 9.900 N/mm2. Por otra, un 42 % de las piezas se clasificaron como ME-2 y sólo un 3 % como ME-1; en este caso las propiedades mecánicas de la calidad ME-2 no se alejan mucho de las de la calidad MEG. El elevado porcentaje de piezas rechazadas (47 % frente a la MEG) se debe principalmente al defecto de alabeo responsable de un 39 % de rechazo. Si no se considera el alabeo en la clasificación el porcentaje de rechazo desciende al 17 % y las propiedades mecánicas de la calidad MEG presentan un valor característico de resistencia a flexión de 21 N/mm2 y un módulo de elasticidad de 9.100 N/mm2. A sample of 150 pieces of radiata pine sawn timber with 180x120 mm in cross-section and 2.500 mm in length sourcing from Catalonia (Spain) were visually graded according to Spanish standard UNE 56544. This standard establish two visual grades (ME-1 and ME-2) for timber pieces with thickness equal or less than 70 mm, and one grade (MEG) for thickness bigger than 70 mm. In order to know the border effect between small and larger cross-section the pieces were graded in both categories. The modulus of rupture, modulus of elasticity and density were obtained by test according to EN 408 standard and the adjustments of EN 384. A 53 % of pieces were classified as MEG with a characteristic bending strength of 28 N/mm2 and a mean value of MOE of 9.900 N/mm2. On the other hand, a 42 % of pieces were classified as ME-2 and only a 3 % as ME-1; in this case the mechanical properties of ME-2 are not far from MEG properties. The high percentage of rejected pieces (47 % vs MEG) is mainly due to the twist defect with a 39 % of rejected pieces. If twist is not considered in the grading process the reject percentage decreases to 17 % and the mechanical properties of MEG grade present a characteristic value of bending strength of 21 N/mm2 and a MOE of 9.100 N/mm2.

A method for Kinematic Calibration of a Parallel Robot by using one camera in hand and a spherical object

The main purpose of robot calibration is the correction of the possible errors in the robot parameters. This paper presents a method for a kinematic calibration of a parallel robot that is equipped with one camera in hand. In order to preserve the mechanical configuration of the robot, the camera is utilized to acquire incremental positions of the end effector from a spherical object that is fixed in the word reference frame. The positions of the end effector are related to incremental positions of resolvers of the motors of the robot, and a kinematic model of the robot is used to find a new group of parameters which minimizes errors in the kinematic equations. Additionally, properties of the spherical object and intrinsic camera parameters are utilized to model the projection of the object in the image and improving spatial measurements. Finally, the robotic system is designed to carry out tracking tasks and the calibration of the robot is validated by means of integrating the errors of the visual controller.

Analyzing Query Success and User Context

This paper describes the participation of DAEDALUS at the LogCLEF lab in CLEF 2011. This year, the objectives of our participation are twofold. The first topic is to analyze if there is any measurable effect on the success of the search queries if the native language and the interface language chosen by the user are different. The idea is to determine if this difference may condition the way in which the user interacts with the search application. The second topic is to analyze the user context and his/her interaction with the system in the case of successful queries, to discover out any relation among the user native language, the language of the resource involved and the interaction strategy adopted by the user to find out such resource. Only 6.89% of queries are successful out of the 628,607 queries in the 320,001 sessions with at least one search query in the log. The main conclusion that can be drawn is that, in general for all languages, whether the native language matches the interface language or not does not seem to affect the success rate of the search queries. On the other hand, the analysis of the strategy adopted by users when looking for a particular resource shows that people tend to use the simple search tool, frequently first running short queries build up of just one specific term and then browsing through the results to locate the expected resource

Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications

Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure 88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performance

A comparative study on unconstrained hand biometrics

Biometrics applied to mobile devices are of great interest for security applications. Daily scenarios can benefit of a combination of both the most secure systems and most simple and extended devices. This document presents a hand biometric system oriented to mobile devices, proposing a non-intrusive, contact-less acquisition process where final users should take a picture of their hand in free-space with a mobile device without removals of rings, bracelets or watches. The main contribution of this paper is threefold: firstly, a feature extraction method is proposed, providing invariant hand measurements to previous changes; second contribution consists of providing a template creation based on hand geometric distances, requiring information from only one individual, without considering data from the rest of individuals within the database; finally, a proposal for template matching is proposed, minimizing the intra-class similarity and maximizing the inter-class likeliness. The proposed method is evaluated using three publicly available contact-less, platform-free databases. In addition, the results obtained with these databases will be compared to the results provided by two competitive pattern recognition techniques, namely Support Vector Machines (SVM) and k-Nearest Neighbour, often employed within the literature. Therefore, this approach provides an appropriate solution to adapt hand biometrics to mobile devices, with an accurate results and a non-intrusive acquisition procedure which increases the overall acceptance from the final user.

Unconstrained and Contactless Hand Geometry Biometrics

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM) and k-Nearest Neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices

OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web

OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).

Propuesta de actividades de autoaprendizaje para el nivel A2 de lengua inglesa en la plataforma Moodle

Los objetivos de este proyecto son proporcionar la teoría, los ejercicios y otros recursos necesarios para que los alumnos de la EUIT de Telecomunicación con un nivel A1 en el Marco Común Europeo de Referencia para las Lenguas (MCERL) puedan obtener el nivel A2 en inglés sin necesidad de asistir a clases ni matricularse en cursos presenciales. La plataforma utilizada para conseguir este fin es Moodle, siendo utilizada en la página web de ILLLab. Este curso online sirve para alcanzar los conocimientos requeridos en la asignatura optativa Introduction to English for Professional and Academic Communication I que parte del nivel B1. Se realiza una propuesta de la gramática con sus correspondientes ejemplos y ejercicios basados todos ellos en adaptaciones de actividades publicadas en un corpus de libros de texto. Se añaden recursos (pequeñas lecturas, videos, enlaces) que se consideran apropiados para el tema tratado. Por otro lado, también se persigue solucionar el problema de los cursos de idiomas basados en e-learning ya que no proporcionan las herramientas necesarias para poner en práctica la expresión oral. Para ello, se aporta una aplicación basada en técnicas de reconocimiento de voz, con tres actividades en las que los resultados han de darse de forma hablada y con la correcta pronunciación. Así, se busca dar una base de conocimientos y experiencias prácticas para futuros proyectos basados en herramientas de síntesis y reconocimiento de voz, además de buscar un nuevo enfoque en el estudio de idiomas. Abstract: The objectives of this project are to provide the theory, exercises and other resources for students at the EUIT Telecommunications with A1 level in the Common European Framework of Reference for Languages (MCERL) in order to get A2 level in English without attending face-to-face courses. The platform used to achieve this aim is Moodle, which is currently being used in ILLLab website. This online course is due to attain the knowledge required in the optional subject Introduction to English for Professional and Academic Communication I which is based on the B1 level. It is a proposal of grammar with corresponding examples and exercises all based on adaptations of activities posted on a corpus of textbooks. It also adds resources (short readings, videos or links) that are appropriate for the subject. On the other hand, this project aims to solve the problem of language courses based on e-learning because these do not usually provide the student with the necessary tools to practice speaking. For this, we develop an application based on speech recognition techniques and propose three activities to practice speaking, and pronunciation. The proposal seeks to provide knowledge and practical experience for future projects based on synthesis tools and voice recognition, and means a new approach to e-learning courses for the study of languages.

Las presentaciones de trabajo en lengua inglesa: una propuesta de curso on-line.

Desde la explosión de crecimiento de internet que comenzó en los años 90, se han ido creando y poniendo a disposición de los usuarios diversas herramientas para compartir información y servicios de diversas formas, desde el nacimiento del primer navegador hasta nuestros días, donde hay infinidad de lenguajes aplicables al ámbito web. En esta fase de crecimiento, en primer lugar, de cara a usuarios individuales, saldrían herramientas que permitirían a cada cual hacer su web personal, con sus contenidos expuestos. Más adelante se fue generando el fenómeno “comunidad”, con, por ejemplo, foros, o webs en las que había múltiples usuarios que disfrutaban de contenidos o servicios que la web ofreciese. Este crecimiento del mundo web en lo comunitario ha avanzado en muchas ramas,entre ellas, por supuesto, la educacional, surgiendo plataformas como la que es base del proyecto que a continuación se presenta, y herramienta básica y prácticamente ya imprescindible en la enseñanza universitaria: Moodle. Moodle es una herramienta diseñada para compatir recursos y diseñar actividades para el usuario potencial, complementando su aprendizaje en aula, o incluso siendo una vía autónoma de aprendizaje en sí misma. Se ha realizado un estudio sobre el estado de saludo de los contenidos que se exponen en Moodle, y se ha encontrado que una gran mayoría de los cursos que se pueden visitar tienen un gran número de carencias. Por un lado, hay pocos con material original explotado exclusivamente para el curso, y, si tienen material original, no se ha observado una especial atención por la maquetación. Por otro lado, hay muchos otros sin material original, y, en ambos casos, no se ha encontrado ningún curso que ofrezca material audiovisual exclusivo para el curso, presentando algunos en su lugar material audiovisual encontrado en la red (Youtube, etc). A la vista de estos hechos, se ha realizado un proyecto que intenta aportar soluciones ante estas carencias, y se presenta un curso procedente de diversas referencias bibliográficas, para la parte textual, y material audiovisual original e inédito que también se ha explotado específicamente para este curso. Este material ha sido por un lado vídeo, que se ha visionado, editado y subtitulado con software de libre distribución, y por otro lado, audio, que complementa un completo glosario que se ha añadido como extra al curso y cuyo planteamiento no se ha encontrado en ningún curso online de los revisados. Todo esto se ha envuelto en una maquetación cuidada que ha sido fruto del estudio de los lenguajes web html y CSS, de forma que, por un lado, el curso sea un lugar agradable en el que aprender dentro de internet, y por otro, se pudiesen realizar ciertas operaciones que sin estos conocimientos habrían sido imposibles, como la realización del glosario o la incrustación de imágenes y vídeos. A su vez, se ha tratado de dar un enfoque didáctico a toda la memoria del proyecto, de forma que pueda ser de utilidad a un usuario futuro que quisiese profundizar en los usos de Moodle, introducirse en el lenguaje web, o introducirse en el mundo de la edición de vídeo. ABSTRACT: Since the explosion of Internet growth beginning in the 90s, many tools have been created and made available for users to share information and services in various ways, from the birth of the first browser until today, where there are plenty of web programming languages. This growth stage would give individual users tools that would allow everyone to make an own personal website, with their contents exposed. Later, the "community" phenomenon appeared with, for example, forums, or websites where multiple users enjoyed the content or web services that those websites offered. Also, this growth in the web community world has progressed in many fields, including education, with the emerge of platforms such as the one that this project uses as its basis, and which is the basic and imperative tool in college education: Moodle. Moodle is a tool designed to share resources and design activities for the potential user, completing class learning, or even letting this user learn in an autonomous way. In this project a study on the current situation of the content present in Moodle courses around the net has been carried out, and it has been found that most of them lack of original material exploited exclusively for the courses, and if they have original material, there has been not observed concern on the layout where that material lies. On the other hand, there are many other with non original material, and in both cases, there has not been found any course that offers audio- visual material made specifically for the course, instead of presenting some audiovisual material found on the net (Youtube, etc). In view of these facts, the project presented here seeks to provide solutions to these shortcomings, presenting a course with original material exploited from various references, and unpublished audioevisual material which also has been exploited specifically for this course. This material is, on one hand, video, which has been viewed, edited and subtitled with free software, and on the other, audio, which complements a comprehensive glossary that has been added as an extra feature to the course and whose approach was not found in any of the online courses reviewed. All of this has been packaged in a neat layout that has been the result of the study of web languages HTML and CSS, so that first, the course was a pleasant place to learn on the internet, and second, certain operations could be performed which without this knowledge would have been impossible, as the glossary design or embedding images and videos. Furthermore, a didactic approach has been adopted to the entire project memory, so it can be useful to a future user who wanted to go deeper on the uses of Moodle, containing an intro into the web language, or in the world video editing.

An automatic translation scheme from prolog to the andorra kernel language

The Andorra family of languages (which includes the Andorra Kernel Language -AKL) is aimed, in principie, at simultaneously supporting the programming styles of Prolog and committed choice languages. On the other hand, AKL requires a somewhat detailed specification of control by the user. This could be avoided by programming in Prolog to run on AKL. However, Prolog programs cannot be executed directly on AKL. This is due to a number of factors, from more or less trivial syntactic differences to more involved issues such as the treatment of cut and making the exploitation of certain types of parallelism possible. This paper provides basic guidelines for constructing an automatic compiler of Prolog programs into AKL, which can bridge those differences. In addition to supporting Prolog, our style of translation achieves independent and-parallel execution where possible, which is relevant since this type of parallel execution preserves, through the translation, the user-perceived "complexity" of the original Prolog program.

Generación y Gestión Optimizadas de la Base de Datos de un Visual para su Implementación en un Simulador de Formación

Los Sistemas de Información Geográfica están desarrollados para gestionar grandes volúmenes de datos, y disponen de numerosas funcionalidades orientadas a la captura, almacenamiento, edición, organización, procesado, análisis, o a la representación de información geográficamente referenciada. Por otro lado, los simuladores industriales para entrenamiento en tareas de conducción son aplicaciones en tiempo real que necesitan de un entorno virtual, ya sea geoespecífico, geogenérico, o combinación de ambos tipos, sobre el cual se ejecutarán los programas propios de la simulación. Este entorno, en última instancia, constituye un lugar geográfico, con sus características específicas geométricas, de aspecto, funcionales, topológicas, etc. Al conjunto de elementos que permiten la creación del entorno virtual de simulación dentro del cual se puede mover el usuario del simulador se denomina habitualmente Base de Datos del Visual (BDV). La idea principal del trabajo que se desarrolla aborda un tema del máximo interés en el campo de los simuladores industriales de formación, como es el problema que presenta el análisis, la estructuración, y la descripción de los entornos virtuales a emplear en los grandes simuladores de conducción. En este artículo se propone una metodología de trabajo en la que se aprovechan las capacidades y ventajas de los Sistemas de Información Geográfica para organizar, optimizar y gestionar la base de datos visual del simulador, y para mejorar la calidad y el rendimiento del simulador en general. ABSTRACT Geographic Information Systems are developed to handle enormous volumes of data and are equipped with numerous functionalities intended to capture, store, edit, organise, process and analyse or represent the geographically referenced information. On the other hand, industrial simulators for driver training are real-time applications that require a virtual environment, either geospecific, geogeneric or a combination of the two, over which the simulation programs will be run. In the final instance, this environment constitutes a geographic location with its specific characteristics of geometry, appearance, functionality, topography, etc. The set of elements that enables the virtual simulation environment to be created and in which the simulator user can move, is usually called the Visual Database (VDB). The main idea behind the work being developed approaches a topic that is of major interest in the field of industrial training simulators, which is the problem of analysing, structuring and describing the virtual environments to be used in large driving simulators. This paper sets out a methodology that uses the capabilities and benefits of Geographic Information Systems for organising, optimising and managing the visual Database of the simulator and for generally enhancing the quality and performance of the simulator.

A Satisfaction-based Model for Affect Recognition from Conversational Features in Spoken Dialog Systems

Detecting user affect automatically during real-time conversation is the main challenge towards our greater aim of infusing social intelligence into a natural-language mixed-initiative High-Fidelity (Hi-Fi) audio control spoken dialog agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. This paper attempts to address part of this challenge by considering the role of user satisfaction ratings and also conversational/dialog features in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. However, given the laboratory constraints, users might be positively biased when rating the system, indirectly making the reliability of the satisfaction data questionable. Machine learning experiments were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. Our results indicated that standard classifiers were significantly more successful in discriminating the abovementioned emotions and their intensities (reflected by user satisfaction ratings) from annotator data than from user data. These results corroborated that: first, satisfaction data could be used directly as an alternative target variable to model affect, and that they could be predicted exclusively by dialog features. Second, these were only true when trying to predict the abovementioned emotions using annotator?s data, suggesting that user bias does exist in a laboratory-led evaluation.

User-independent accelerometer-based gesture recognition for mobile devices

Many mobile devices embed nowadays inertial sensors. This enables new forms of human-computer interaction through the use of gestures (movements performed with the mobile device) as a way of communication. This paper presents an accelerometer-based gesture recognition system for mobile devices which is able to recognize a collection of 10 different hand gestures. The system was conceived to be light and to operate in a user -independent manner in real time. The recognition system was implemented in a smart phone and evaluated through a collection of user tests, which showed a recognition accuracy similar to other state-of-the art techniques and a lower computational complexity. The system was also used to build a human -robot interface that enables controlling a wheeled robot with the gestures made with the mobile phone.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Posibilidades del motor 3D de la Nintendo DS

La consola portátil Nintendo DS es una plataforma de desarrollo muy presente entre la comunidad de desarrolladores independientes, con una extensa y nutrida escena homebrew. Si bien las capacidades 2D de la consola están muy aprovechadas, dado que la mayor parte de los esfuerzos de los creadores amateur están enfocados en este aspecto, el motor 3D de ésta (el que se encarga de representar en pantalla modelos tridimensionales) no lo está de igual manera. Por lo tanto, en este proyecto se tiene en vista determinar las capacidades gráficas de la Nintendo DS. Para ello se ha realizado una biblioteca de funciones en C que permite aprovechar las posibilidades que ofrece la consola en el terreno 3D y que sirve como herramienta para la comunidad homebrew para crear aplicaciones 3D de forma sencilla, dado que se ha diseñado como un sistema modular y accesible. En cuanto al proceso de renderizado se han sacado varias conclusiones. En primer lugar se ha determinado la posibilidad de asignar varias componentes de color a un mismo vértice (color material reactivo a la iluminación, color por vértice directo y color de textura), tanto de forma independiente como simultáneamente, pudiéndose utilizar para aplicar diversos efectos al modelo, como iluminación pre-calculada o simulación de una textura mediante color por vértice, ahorrando en memoria de video. Por otro lado se ha implementado un sistema de renderizado multi-capa, que permite realizar varias pasadas de render, pudiendo, de esta forma, aplicar al modelo una segunda textura mezclada con la principal o realizar un efecto de reflexión esférica. Uno de los principales avances de esta herramienta con respecto a otras existentes se encuentra en el apartado de animación. El renderizador desarrollado permite por un lado animación por transformación, consistente en la animación de mallas o grupos de vértices del modelo mediante el movimiento de una articulación asociada que determina su posición y rotación en cada frame de animación. Por otro lado se ha implementado un sistema de animación por muestreo de vértices mediante el cual se determina la posición de éstos en cada instante de la animación, generando frame a frame las poses que componen el movimiento (siendo este último método necesario cuando no se puede animar una malla por transformación). Un mismo modelo puede contener diferentes esqueletos, animados independientemente entre sí, y cada uno de ellos tener definidas varias costumbres de animación que correspondan a movimientos contextuales diferentes (andar, correr, saltar, etc). Además, el sistema permite extraer cualquier articulación para asociar su transformación a un objeto estático externo y que éste siga el movimiento de la animación, pudiendo así, por ejemplo, equipar un objeto en la mano de un personaje. Finalmente se han implementado varios efectos útiles en la creación de escenas tridimensionales, como el billboarding (tanto esférico como cilíndrico), que restringe la rotación de un modelo para que éste siempre mire a cámara y así poder emular la apariencia de un objeto tridimensional mediante una imagen plana, ahorrando geometría, o emplearlo para realizar efectos de partículas. Por otra parte se ha implementado un sistema de animación de texturas por subimágenes que permite generar efectos de movimiento mediante imágenes, sin necesidad de transformar geometría. ABSTRACT. The Nintendo DS portable console has received great interest within the independent developers’ community, with a huge homebrew scene. The 2D capabilities of this console are well known and used since most efforts of the amateur creators has been focused on this point. However its 3D engine (which handles with the representation of three-dimensional models) is not equally used. Therefore, in this project the main objective is to assess the Nintendo DS graphic capabilities. For this purpose, a library of functions in C programming language has been coded. This library allows the programmer to take advantage of the possibilities that the 3D area brings. This way the library can be used by the homebrew community as a tool to create 3D applications in an easy way, since it has been designed as a modular and accessible system. Regarding the render process, some conclusions have been drawn. First, it is possible to assign several colour components to the same vertex (material colour, reactive to the illumination, colour per vertex and texture colour), independently and simultaneously. This feature can be useful to apply certain effects on the model, such as pre-calculated illumination or the simulation of a texture using colour per vertex, providing video memory saving. Moreover, a multi-layer render system has been implemented. This system allows the programmer to issue several render passes on the same model. This new feature brings the possibility to apply to the model a second texture blended with the main one or simulate a spherical reflection effect. One of the main advances of this tool over existing ones consists of its animation system. The developed renderer includes, on the one hand, transform animation, which consists on animating a mesh or groups of vertices of the model by the movement of an associated joint. This joint determines position and rotation of the mesh at each frame of the animation. On the other hand, this tool also implements an animation system by vertex sampling, where the position of vertices is determined at every instant of the animation, generating the poses that build up the movement (the latter method is mandatory when a mesh cannot be animated by transform). A model can contain multiple skeletons, animated independently, each of them being defined with several animation customs, corresponding to different contextual movements (walk, run, jump, etc). Besides, the system allows extraction of information from any joint in order to associate its transform to a static external object, which will follow the movement of the animation. This way, any object could be equipped, for example, on the hand of a character. Finally, some useful effects for the creation of three-dimensional scenes have been implemented. These effects include billboarding (both spherical and cylindrical), which constraints the rotation of a model so it always looks on the camera's direction. This feature can provide the ability to emulate the appearance of a three-dimensional model through a flat image (saving geometry). It can also be helpful in the implementation of particle effects. Moreover, a texture animation system using sub-images has also been implemented. This system allows the generation of movement by using images as textures, without having to transform geometry.