Acoustic records of the underwater soundscape at PALAOA with links to audio stream files, 2005-2011

Scientific background: Marine mammals use sound for communication, navigation and prey detection. Acoustic sensors therefore allow the detection of marine mammals, even during polar winter months, when restricted visibility prohibits visual sightings. The animals are surrounded by a permanent natural soundscape, which, in polar waters, is mainly dominated by the movement of ice. In addition to the detection of marine mammals, acoustic long-term recordings provide information on intensity and temporal variability of characteristic natural and anthropogenic background sounds, as well as their influence on the vocalization of marine mammals Scientific objectives: The PerenniAL Acoustic Observatory in the Antarctic Ocean (PALAOA, Hawaiian "whale") near Neumayer Station is intended to record the underwater soundscape in the vicinity of the shelf ice edge over the duration of several years. These long-term recordings will allow studying the acoustic repertoire of whales and seals continuously in an environment almost undisturbed by humans. The data will be analyzed to (1) register species specific vocalizations, (2) infer the approximate number of animals inside the measuring range, (3) calculate their movements relative to the observatory, and (4) examine possible effects of the sporadic shipping traffic on the acoustic and locomotive behaviour of marine mammals. The data, which are largely free of anthropogenic noise, provide also a base to set up passive acoustic mitigation systems used on research vessels. Noise-free bioacoustic data thereby represent the foundation for the development of automatic pattern recognition procedures in the presence of interfering sounds, e.g. propeller noise.

From regression estimates to document tables: output formatting using -estout-

Postestimation processing and formatting of regression estimates for input into document tables are tasks that many of us have to do. However, processing results by hand can be laborious, and is vulnerable to error. There are therefore many benefits to automation of these tasks while at the same time retaining user flexibility in terms of output format. The estout package meets these needs. estout assembles a table of coefficients, "significance stars", summary statistics, standard errors, t/z statistics, p-values, confidence intervals, and other statistics calculated for up to twenty models previously fitted and stored by estimates store. It then writes the table to the Stata log and/or to a text file. The estimates are formatted optionally in several styles: html, LaTeX, or tab-delimited (for input into MS Excel or Word). There are a large number of options regarding which output is formatted and how. This talk will take users through a range of examples, from relatively basic simple applications to complex ones.

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).

datos.bne.es: A library linked dataset

We describe the datos.bne.es library dataset. The dataset makes available the authority and bibliography catalogue from the Biblioteca Nacional de España (BNE, National Library of Spain) as Linked Data. The catalogue contains around 7 million authority and bibliographic records. The records in MARC 21 format were transformed to RDF and modelled using IFLA (International Federation of Library Associations) ontologies and other well-established vocabularies such as RDA (Resource Description and Access) or the Dublin Core Metadata Element Set. A tool named MARiMbA automatized the RDF generation process and the data linkage to DBpedia and other library linked data resources such as VIAF (Virtual International Authority File) or GND (Gemeinsame Normdatei, the authority dataset from the German National Library).

An automatic documentation generator for (C)LP - Reference manual

Lpdoc is an automatic program documentation generator for (C)LP systems. Lpdoc generates a reference manual automatically from one or more source files for a logic program (including ISO-Prolog, Ciao, many CLP systems, ...). It is particularly useful for documenting library modules, for which it automatically generates a description of the module interface. However, lpdoc can also be used quite successfully to document full applications and to generate nicely formatted plain ascii "readme" files. A fundamental advantage of using lpdoc to document programs is that it is much easier to maintain a true correspondence between the program and its documentation, and to identify precisely to what version of the program a given printed manual corresponds. The quality of the documentation generated can be greatly enhanced by including within the program text: • assertions (types, modes, etc. ...) for the predicates in the program, and • machine-readable comments (in the "literate programming" style). The assertions and comments included in the source file need to be written using the Ciao system assertion language. A simple compatibility library is available to make traditional (constraint) logic programming systems ignore these assertions and comments allowing normal treatment of programs documented in this way. The documentation is currently generated in HTML or texinf o format. From the texinf o output, printed and on-line manuals in several formats (dvi, ps, info, etc.) can be easily generated automatically, using publicly available tools, lpdoc can also generate 'man' pages (Unix man page format) as well as brief descriptions in html or emacs info formats suitable for inclusion in an on-line index of applications. In particular, lpdoc can create and maintain fully automatically WWW and info sites containing on-line versions of the documents it produces. The lpdoc manual (and the Ciao system manuals) are generated by lpdoc. Lpdoc is distributed under the GNU general public license. Note: lpdoc is fully supported on Linux, Mac OS X, and other Un*x-like systems. Due to the use of several Un*x-related utilities, some documentation back-ends may require Cygwin under Win32. This documentation corresponds to version 3.0 (2011/7/7, 16:33:15 CEST).

Scalable Raid Storage Based on the Structure of Multimedia File.

In professional video production, users have to access to huge multimedia files simultaneously in an error-free environment, this restriction force the use of expensive disk architectures for video servers. Previous researches proposed different RAID systems for each specific task (ingest, editing, file, play-out, etc.). Video production companies have to acquire different servers with different RAIDs systems in order to support each task in the production workflow. The solution has multiples disadvantages, duplicated material in several RAIDs, duplicated material for different qualities, transfer and transcoding processes, etc. In this work, an architecture for video servers based on the spreading of JPEG200 data in different RAIDs is presented, each individual part of the data structure goes to a specific RAID type depending on the effect that produces the data on the overall image quality, the method provide a redundancy correlated with the data rank. The global storage can be used in all the different tasks of the production workflow saving disk space, redundant files and transfers procedures.

Hybrid Contribution of JPEG200 Video Files for Professional Production Centers Reliability and Non-Reliability Transmission File Based in Image Quality Needed

ATM, SDH or satellite have been used in the last century as the contribution network of Broadcasters. However the attractive price of IP networks is changing the infrastructure of these networks in the last decade. Nowadays, IP networks are widely used, but their characteristics do not offer the level of performance required to carry high quality video under certain circumstances. Data transmission is always subject to errors on line. In the case of streaming, correction is attempted at destination, while on transfer of files, retransmissions of information are conducted and a reliable copy of the file is obtained. In the latter case, reception time is penalized because of the low priority this type of traffic on the networks usually has. While in streaming, image quality is adapted to line speed, and line errors result in a decrease of quality at destination, in the file copy the difference between coding speed vs line speed and errors in transmission are reflected in an increase of transmission time. The way news or audiovisual programs are transferred from a remote office to the production centre depends on the time window and the type of line available; in many cases, it must be done in real time (streaming), with the resulting image degradation. The main purpose of this work is the workflow optimization and the image quality maximization, for that reason a transmission model for multimedia files adapted to JPEG2000, is described based on the combination of advantages of file transmission and those of streaming transmission, putting aside the disadvantages that these models have. The method is based on two patents and consists of the safe transfer of the headers and data considered to be vital for reproduction. Aside, the rest of the data is sent by streaming, being able to carry out recuperation operations and error concealment. Using this model, image quality is maximized according to the time window. In this paper, we will first give a briefest overview of the broadcasters requirements and the solutions with IP networks. We will then focus on a different solution for video file transfer. We will take the example of a broadcast center with mobile units (unidirectional video link) and regional headends (bidirectional link), and we will also present a video file transfer file method that satisfies the broadcaster requirements.

Herramienta para la gestión de diarios de entretenimientos configurables

El Trabajo Fin de Grado ha consistido en el diseño e implementación de una herramienta para la gestión y administración de los entrenamientos de atletas de deportes individuales. Hasta ahora los deportistas debían gestionar sus entrenamientos a través de hojas de cálculo, teniendo que dedicar tiempo al aprendizaje de herramientas como Microsoft Excel u OpenOffice Excel para personalizar las plantillas y guardar los datos, utilizar otras herramientas como Google Calendar para obtener una visión de un calendario con los entrenamientos realizados o bien utilizar programas hechos a medida para un deporte e incluso para un deportista. El objetivo principal consistía en desarrollar una herramienta que unificara todas las tareas para ofrecer al deportista las funciones de configuración de plantillas, registro y generación de gráficas de los datos registrados y visionado del calendario de entrenamientos de una forma ágil, sencilla e intuitiva, adaptándose a las necesidades de cualquier deporte o deportista. Para alcanzar el objetivo principal realizamos encuestas a atletas de una gran diversidad de deportes individuales, detectando las particularidades de cada deporte y analizando los datos que nos ofrecían para alcanzar el objetivo de diseñar una herramienta versátil que permitiera su uso independientemente de los parámetros que se quisiera registrar de cada entrenamiento. La herramienta generada es una herramienta programada en Java, que ofrece portabilidad a cualquier sistema operativo que lo soporte, sin ser necesario realizar una instalación previa. Es una aplicación plug and play en la que solo se necesita del fichero ejecutable para su funcionamiento; de esta forma facilitamos que el deportista guarde toda la información en muy poco espacio, 6 megabytes aproximadamente, y pueda llevarla a cualquier lado en un pen drive o en sistemas de almacenamiento en la nube. Además, los ficheros en los que se registran los datos son ficheros CSV (valores separados por comas) con un formato estandarizado que permite la exportación a otras herramientas. Como conclusión el atleta ahorra tiempo y esfuerzo en tareas ajenas a la práctica del deporte y disfruta de una herramienta que le permite analizar de diferentes maneras cada uno de los parámetros registrados para ver su evolución y ayudarle a mejorar aquellos aspectos que sean deficientes. ---ABSTRACT---The Final Project consists in the design and implementation of a tool for the management and administration of training logs for individual athletes. Until now athletes had to manage their workouts through spreadsheets, having to spend time in learning tools such as Microsoft Excel or OpenOffice in order to save the data, others tools like Google Calendar to check their training plan or buy specifics programs designed for a specific sport or even for an athlete. The main purpose of this project is to develop an intuitive and straightforward tool that unifies all tasks offering setup functions, data recording, graph generation and training schedule to the athletes. Whit this in mind, we have interviewed athletes from a wide range of individual sports, identifying their specifications and analyzing the data provided to design a flexible tool that registers multitude of training parameters. This tool has been coded in Java, providing portability to any operating system that supports it, without installation being required. It is a plug and play application, that only requires the executable file to start working. Accordingly, athletes can keep all the information in a relative reduced space (aprox 6 megabytes) and save it in a pen drive or in the cloud. In addition, the files whit the stored data are CSV (comma separated value) files whit a standardized format that allows exporting to other tools. Consequently athletes will save time and effort on tasks unrelated to the practice of sports. The new tool will enable them to analyze in detail all the existing data and improve in those areas with development opportunities.

Desarrollo e implementación de un sistema robótico aéreo con programación tridimensional orientado al recorrido de rutas

En la actualidad se estudia en numerosos campos cómo automatizar distintas tareas ejecutadas por aeronaves con tripulación humana. Estas tareas son en todos los casos muy costosos, debido al gran consumo de combustible, gran coste de adquisición y mantenimiento de la propia aeronave, todo ello sin contar el riesgo para los mismos tripulantes. Como ejemplo de estas tareas se puede incluir la vigilancia policial y fronteriza, revisiones de tendidos de alta tensión, la alerta temprana de incendios forestales y la medición de parámetros contaminantes. El objetivo de este proyecto es el diseño y la construcción de un prototipo electrónico empotrado basado en microcontrolador con núcleo C8051 de Silicon labs, que sea capaz de gobernar una aeronave de radiocontrol de forma transparente, de manera que en un futuro se pueda sustituir el propio aeromodelo, con la modificación de algunos parámetros, para poder incorporar sistemas de video o distintos medios de detección de variables. El prototipo seguirá una ruta confeccionada y transferida como un archivo de texto con un formato determinado que contendrá los datos necesarios para poder navegar mediante GPS. El trabajo con los modelos de motorización térmica (motores de combustión interna tipo glow, en este caso) resulta peligroso debido a la gran energía que son capaces de alcanzar. A fin de mantener la máxima seguridad durante la evolución del proyecto, se ha diseñado un proceso de tres partes independientes que permitan la correcta familiarización de los distintos componentes que se emplearán. Las fases son las siguientes: 1. Test y modelado de todos los componentes mediante pequeños montajes con protoboard de inserción y programas individuales. Se realizará mediante una tarjeta multipropósito que contendrá un microcontrolador similar en características, aunque de menor complejidad, al del prototipo final. 2. Integración de todos los componentes mediante una tarjeta especialmente diseñada que servirá de interfaz entre la tarjeta multipropósito y todo el hardware necesario para el control de un vehículo terrestre de iguales características (actuadores y motorización) al aeromodelo. 3. Diseño de un sistema embebido que concentre todos los subsistemas desarrollados en las fases anteriores y que integre todos los componentes necesarios para el gobierno de una aeronave de ala fija. ABSTRACT. Nowadays, the way of automating different tasks done by manned vehicles is studied. These tasks are any case very expensive, due to large fuel consumption, costs of aircraft buying, without taking into account the risk for human crew. As an example of these tasks, we can include policing or border surveillance, maintenance of high voltage lines, early warning of forest fire and measuring of pollution parameters. The target of this project is the design and construction of an embedded electronic prototype, based on a microcontroller with C8051 core from Silicon labs, and it will be able to controlling an aircraft transparently, in order that in the future the flying model could be changed with the modification of some parameters, and video or any variables detection systems could be added. The prototype will follow a designed and transferred path as an plain text file with a given format, that will contain all the necessary data for GPS navigation. Working with heat engine models (internal combustion engine, glow type, in this case) becomes dangerous due to the large energy that can be able to acquire. In order to keep the maximum safety level during the project evolution a three independent stages process have been designed, this allows familiarizing properly with the parts that will be used. The stages are as follows: 1. Test and modeling of all of the parts by little assemblies with through-hole protoboard and stand alone programs. It will be done with a multipurpose card which contains a microcontroller of similar characteristics, although less complex, of the final prototype. 2. Integrating of all of parts through a dedicated design card that will serve as interface between multipurpose card and all the necessary hardware for controlling a ground vehicle with the same characteristics (actuators and engine) of the flying model. 3. Embedded system designing that contains all the developed subsystems in the previous stages and integrates all the necessary parts for controlling a fixed-wing aircraft.

Generador de exámenes de test aleatorio

En este documento se detalla, la planificación y elaboración de un paquete que respeta el estándar S4 de programación en lenguaje R. El paquete consiste en una serie de métodos y clases para la generación de exámenes tipos test y soluciones a partir de un archivo xls, que hace las funciones de una base de datos. El diseño propuesto está orientado a objetos y desarrolla un conjunto de clases que representan los contenidos de una prueba de evaluación tipo test: enunciados, peguntas y respuestas. Se ha realizado una implementación sencilla de un prototipo con las funciones básicas necesarias para generar los tests. Además se ha generado la documentación necesaria para crear el paquete, esto significa que cada método tiene una página de ayuda, que se podrá consultar desde un terminal con R, dicha documentación incluye ejemplos de ejecución de cada método.---ABSTRACT---In this document is detailed the elaboration and development of a package that meets the standard S4 of programming language R. This package consists of a group of methods and classes used for the generation of test exams and their solutions starting from a xls format file wich plays the role of a data base at the same time. These classes have been grouped in a way that the user could have a complete and easy vision of them. This division has been done by using data storage and functions whose tasks are more or less the same. Furthermore, the necessary documentation to create this package has also been generated, that means that every method has a help page wich can be called from a R terminal if necessary. This documentation has examples of the execution of every method.

Efficient RDF Interchange (ERI) format for RDF data streams

RDF streams are sequences of timestamped RDF statements or graphs, which can be generated by several types of data sources (sensors, social networks, etc.). They may provide data at high volumes and rates, and be consumed by applications that require real-time responses. Hence it is important to publish and interchange them efficiently. In this paper, we exploit a key feature of RDF data streams, which is the regularity of their structure and data values, proposing a compressed, efficient RDF interchange (ERI) format, which can reduce the amount of data transmitted when processing RDF streams. Our experimental evaluation shows that our format produces state-of-the-art streaming compression, remaining efficient in performance.