Network convergence and QoS for future multimedia services in the VISION project

The emerging use of real-time 3D-based multimedia applications imposes strict quality of service (QoS) requirements on both access and core networks. These requirements and their impact to provide end-to-end 3D videoconferencing services have been studied within the Spanish-funded VISION project, where different scenarios were implemented showing an agile stereoscopic video call that might be offered to the general public in the near future. In view of the requirements, we designed an integrated access and core converged network architecture which provides the requested QoS to end-to-end IP sessions. Novel functional blocks are proposed to control core optical networks, the functionality of the standard ones is redefined, and the signaling improved to better meet the requirements of future multimedia services. An experimental test-bed to assess the feasibility of the solution was also deployed. In such test-bed, set-up and release of end-to-end sessions meeting specific QoS requirements are shown and the impact of QoS degradation in terms of the user perceived quality degradation is quantified. In addition, scalability results show that the proposed signaling architecture is able to cope with large number of requests introducing almost negligible delay.

Structure function and Multifractal spectrum applied to Digital Elevation Model

A Digital Elevation Model (DEM) provides the information basis used for many geographic applications such as topographic and geomorphologic studies, landscape through GIS (Geographic Information Systems) among others. The DEM capacity to represent Earth?s surface depends on the surface roughness and the resolution used. Each DEM pixel depends on the scale used characterized by two variables: resolution and extension of the area studied. DEMs can vary in resolution and accuracy by the production method, although there are statistical characteristics that keep constant or very similar in a wide range of scales. Based on this property, several techniques have been applied to characterize DEM through multiscale analysis directly related to fractal geometry: multifractal spectrum and the structure function. The comparison of the results by both methods is discussed. The study area is represented by a 1024 x 1024 data matrix obtained from a DEM with a resolution of 10 x 10 m each point, which correspond with a region known as ?Monte de El Pardo? a property of Spanish National Heritage (Patrimonio Nacional Español) of 15820 Ha located to a short distance from the center of Madrid. Manzanares River goes through this area from North to South. In the southern area a reservoir is found with a capacity of 43 hm3, with an altitude of 603.3 m till 632 m when it is at the highest capacity. In the middle of the reservoir the minimum altitude of this area is achieved.

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).

Techniques to accelerate convergence of stress-controlled molecular dynamics simulations of dislocation motion

Dislocation mobility —the relation between applied stress and dislocation velocity—is an important property to model the mechanical behavior of structural materials. These mobilities reflect the interaction between the dislocation core and the host lattice and, thus, atomistic resolution is required to capture its details. Because the mobility function is multiparametric, its computation is often highly demanding in terms of computational requirements. Optimizing how tractions are applied can be greatly advantageous in accelerating convergence and reducing the overall computational cost of the simulations. In this paper we perform molecular dynamics simulations of ½ 〈1 1 1〉 screw dislocation motion in tungsten using step and linear time functions for applying external stress. We find that linear functions over time scales of the order of 10–20 ps reduce fluctuations and speed up convergence to the steady-state velocity value by up to a factor of two.

Atomistic modeling of Ge damage accumulation, amorphization and solid phase epitaxial regrowth

En los últimos años, el Ge ha ganado de nuevo atención con la finalidad de ser integrado en el seno de las existentes tecnologías de microelectrónica. Aunque no se le considera como un canddato capaz de reemplazar completamente al Si en el futuro próximo, probalemente servirá como un excelente complemento para aumentar las propiedades eléctricas en dispositivos futuros, especialmente debido a su alta movilidad de portadores. Esta integración requiere de un avance significativo del estado del arte en los procesos de fabricado. Técnicas de simulación, como los algoritmos de Monte Carlo cinético (KMC), proporcionan un ambiente atractivo para llevar a cabo investigación y desarrollo en este campo, especialmente en términos de costes en tiempo y financiación. En este estudio se han usado, por primera vez, técnicas de KMC con el fin entender el procesado “front-end” de Ge en su fabricación, específicamente la acumulación de dañado y amorfización producidas por implantación iónica y el crecimiento epitaxial en fase sólida (SPER) de las capas amorfizadas. Primero, simulaciones de aproximación de clisiones binarias (BCA) son usadas para calcular el dañado causado por cada ión. La evolución de este dañado en el tiempo se simula usando KMC sin red, o de objetos (OKMC) en el que sólamente se consideran los defectos. El SPER se simula a través de una aproximación KMC de red (LKMC), siendo capaz de seguir la evolución de los átomos de la red que forman la intercara amorfo/cristalina. Con el modelo de amorfización desarrollado a lo largo de este trabajo, implementado en un simulador multi-material, se pueden simular todos estos procesos. Ha sido posible entender la acumulación de dañado, desde la generación de defectos puntuales hasta la formación completa de capas amorfas. Esta acumulación ocurre en tres regímenes bien diferenciados, empezando con un ritmo lento de formación de regiones de dañado, seguido por una rápida relajación local de ciertas áreas en la fase amorfa donde ambas fases, amorfa y cristalina, coexisten, para terminar en la amorfización completa de capas extensas, donde satura el ritmo de acumulación. Dicha transición ocurre cuando la concentración de dañado supera cierto valor límite, el cual es independiente de las condiciones de implantación. Cuando se implantan los iones a temperaturas relativamente altas, el recocido dinámico cura el dañado previamente introducido y se establece una competición entre la generación de dañado y su disolución. Estos efectos se vuelven especialmente importantes para iones ligeros, como el B, el cual crea dañado más diluido, pequeño y distribuido de manera diferente que el causado por la implantación de iones más pesados, como el Ge. Esta descripción reproduce satisfactoriamente la cantidad de dañado y la extensión de las capas amorfas causadas por implantación iónica reportadas en la bibliografía. La velocidad de recristalización de la muestra previamente amorfizada depende fuertemente de la orientación del sustrato. El modelo LKMC presentado ha sido capaz de explicar estas diferencias entre orientaciones a través de un simple modelo, dominado por una única energía de activación y diferentes prefactores en las frecuencias de SPER dependiendo de las configuraciones de vecinos de los átomos que recristalizan. La formación de maclas aparece como una consecuencia de esta descripción, y es predominante en sustratos crecidos en la orientación (111)Ge. Este modelo es capaz de reproducir resultados experimentales para diferentes orientaciones, temperaturas y tiempos de evolución de la intercara amorfo/cristalina reportados por diferentes autores. Las parametrizaciones preliminares realizadas de los tensores de activación de tensiones son también capaces de proveer una buena correlación entre las simulaciones y los resultados experimentales de velocidad de SPER a diferentes temperaturas bajo una presión hidrostática aplicada. Los estudios presentados en esta tesis han ayudado a alcanzar un mejor entendimiento de los mecanismos de producción de dañado, su evolución, amorfización y SPER para Ge, además de servir como una útil herramienta para continuar el trabajo en este campo. In the recent years, Ge has regained attention to be integrated into existing microelectronic technologies. Even though it is not thought to be a feasible full replacement to Si in the near future, it will likely serve as an excellent complement to enhance electrical properties in future devices, specially due to its high carrier mobilities. This integration requires a significant upgrade of the state-of-the-art of regular manufacturing processes. Simulation techniques, such as kinetic Monte Carlo (KMC) algorithms, provide an appealing environment to research and innovation in the field, specially in terms of time and funding costs. In the present study, KMC techniques are used, for the first time, to understand Ge front-end processing, specifically damage accumulation and amorphization produced by ion implantation and Solid Phase Epitaxial Regrowth (SPER) of the amorphized layers. First, Binary Collision Approximation (BCA) simulations are used to calculate the damage caused by every ion. The evolution of this damage over time is simulated using non-lattice, or Object, KMC (OKMC) in which only defects are considered. SPER is simulated through a Lattice KMC (LKMC) approach, being able to follow the evolution of the lattice atoms forming the amorphous/crystalline interface. With the amorphization model developed in this work, implemented into a multi-material process simulator, all these processes can be simulated. It has been possible to understand damage accumulation, from point defect generation up to full amorphous layers formation. This accumulation occurs in three differentiated regimes, starting at a slow formation rate of the damage regions, followed by a fast local relaxation of areas into the amorphous phase where both crystalline and amorphous phases coexist, ending in full amorphization of extended layers, where the accumulation rate saturates. This transition occurs when the damage concentration overcomes a certain threshold value, which is independent of the implantation conditions. When implanting ions at relatively high temperatures, dynamic annealing takes place, healing the previously induced damage and establishing a competition between damage generation and its dissolution. These effects become specially important for light ions, as B, for which the created damage is more diluted, smaller and differently distributed than that caused by implanting heavier ions, as Ge. This description successfully reproduces damage quantity and extension of amorphous layers caused by means of ion implantation reported in the literature. Recrystallization velocity of the previously amorphized sample strongly depends on the substrate orientation. The presented LKMC model has been able to explain these differences between orientations through a simple model, dominated by one only activation energy and different prefactors for the SPER rates depending on the neighboring configuration of the recrystallizing atoms. Twin defects formation appears as a consequence of this description, and are predominant for (111)Ge oriented grown substrates. This model is able to reproduce experimental results for different orientations, temperatures and times of evolution of the amorphous/crystalline interface reported by different authors. Preliminary parameterizations for the activation strain tensors are able to also provide a good match between simulations and reported experimental results for SPER velocities at different temperatures under the appliance of hydrostatic pressure. The studies presented in this thesis have helped to achieve a greater understanding of damage generation, evolution, amorphization and SPER mechanisms in Ge, and also provide a useful tool to continue research in this field.

Efficient Model-based 3D Tracking by Using Direct Image Registration

This thesis deals with the problem of efficiently tracking 3D objects in sequences of images. We tackle the efficient 3D tracking problem by using direct image registration. This problem is posed as an iterative optimization procedure that minimizes a brightness error norm. We review the most popular iterative methods for image registration in the literature, turning our attention to those algorithms that use efficient optimization techniques. Two forms of efficient registration algorithms are investigated. The first type comprises the additive registration algorithms: these algorithms incrementally compute the motion parameters by linearly approximating the brightness error function. We centre our attention on Hager and Belhumeur’s factorization-based algorithm for image registration. We propose a fundamental requirement that factorization-based algorithms must satisfy to guarantee good convergence, and introduce a systematic procedure that automatically computes the factorization. Finally, we also bring out two warp functions to register rigid and nonrigid 3D targets that satisfy the requirement. The second type comprises the compositional registration algorithms, where the brightness function error is written by using function composition. We study the current approaches to compositional image alignment, and we emphasize the importance of the Inverse Compositional method, which is known to be the most efficient image registration algorithm. We introduce a new algorithm, the Efficient Forward Compositional image registration: this algorithm avoids the necessity of inverting the warping function, and provides a new interpretation of the working mechanisms of the inverse compositional alignment. By using this information, we propose two fundamental requirements that guarantee the convergence of compositional image registration methods. Finally, we support our claims by using extensive experimental testing with synthetic and real-world data. We propose a distinction between image registration and tracking when using efficient algorithms. We show that, depending whether the fundamental requirements are hold, some efficient algorithms are eligible for image registration but not for tracking.

An approach of the European higher education framework to the management of higher education at university level in Perú

This communication research gives an insight to University Education in Peru and a brief review of the main European documents that deal with the European Higher Education Framework, highlighting the principles upon which it is based, as well as the strategic objectives that it sets forth and the tools to achieve them. The purpose of this process is to adapt our university education management in Peru to the EEES, seeking to identify the limitations and constraints faced with regard to the keys of European convergence and the means or instruments that we have in order to attain convergence in Peru.

An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used.

A Keyword-driven approach for generating OWL DL conformance test data

The conformance of semantic technologies has to be systematically evaluated to measure and verify the real adherence of these technologies to the Semantic Web standards. Currente valuations of semantic technology conformance are not exhaustive enough and do not directly cover user requirements and use scenarios, which raises the need for a simple, extensible and parameterizable method to generate test data for such evaluations. To address this need, this paper presents a keyword-driven approach for generating ontology language conformance test data that can be used to evaluate semantic technologies, details the definition of a test suite for evaluating OWL DL conformance using this approach,and describes the use and extension of this test suite during the evaluation of some tools.

Improving availability of mobile networks using a cluster routing protocol with redundant cluster head

We show a cluster based routing protocol in order to improve the convergence of the clusters and of the network it is proposed to use a backup cluster head. The use of a event discrete simulator is used for the implementation and the simulation of a hierarchical routing protocol called the Backup Cluster Head Protocol (BCHP). Finally it is shown that the BCHP protocol improves the convergence and availability of the network through a comparative analysis with the Ad Hoc On Demand Distance Vector (AODV)[1] routing protocol and Cluster Based Routing Protocol (CBRP)[2]

Consulta on-line basada en corpus de construcciones con preposición en el texto técnico en inglés y su traducción al español

Basándonos en la recopilación inicial de preposiciones, locuciones preposicionales, términos con preposición dependiente y phrasal verbs utilizados en el texto técnico realizada en otros proyectos anteriores del Departamento de Lingüística Aplicada a la Ciencia y a la Tecnología, el objetivo de este trabajo es completar, organizar, actualizar y dar visibilidad a esta información inicial. Tras realizar un proceso exhaustivo de verificación, unificación, clasificación y ampliación de la información existente, en caso necesario, el listado resultante se utiliza para elaborar un glosario de términos con preposición. El objetivo final de este proyecto es que este glosario esté a disposición de los usuarios, a través de una consulta on-line, en la página del ILLLab (http://illlab.euitt.upm.es/wordpress/), dependiente del Departamento de Lingüística Aplicada a la Ciencia y a la Tecnología. Para incluir en el glosario ejemplos actualizados de textos técnicos, se ha recopilado un corpus lingüístico de textos técnicos, tomando como base diferentes números de la revista IEEE Spectrum, en su edición digital, publicados entre los años 2009 y 2012. El objetivo de esta recopilación es la de ofrecer al consultante diferentes ejemplos de uso en el texto técnico de los distintos términos con preposición que componen el glosario, de manera que pueda acceder de manera rápida y sencilla a ejemplos de uso real de los términos que está buscando, con objeto de clarificar aspectos relacionados con su uso o, en su caso, facilitar su aprendizaje. Toda esta información, tanto el listado de términos con preposición como las frases pertenecientes al corpus recopilado, se incorpora a una base de datos, alojada dentro de la misma página web del ILLLab. A través de un formulario de consulta, a disposición del usuario en dicha página, se pueden obtener todos los términos recopilados que coincidan con los criterios de búsqueda introducidos. El usuario puede realizar dos tipos de búsqueda principales: por preposición o por término completo. Además, puede elegir una búsqueda global (entre todos los términos que integran el glosario) o parcial (en una sola de las categorías en las que se han dividido los diferentes términos, de acuerdo con su función gramatical). Por último, se presentan unas estadísticas de uso de los términos recopilados dentro de los diferentes textos que integran el corpus lingüístico, de manera que pueda establecerse una relación de los que aparecen con más frecuencia en el texto técnico. ABSTRACT. Based on the initial collection of prepositions, prepositional phrases, dependent prepositions and phrasal verbs used in technical texts collected on previous projects in the Department of Applied Linguistics to Science and Technology, the aim of this project is to improve, organize, update and provide visibility to this initial information. Following a process of verification, unification, classification and extension of existing information, if necessary, a glossary of terms with preposition is built. The ultimate objective of this project is to make this glossary available to users through an online consultation in the ILLLab webpage (http://illlab.euitt.upm.es/wordpress/). The administration of tis webpage depends of the Department of Applied Linguistics in Science and Technology. A linguistic corpus of technical texts has been compiled, based on different numbers of the IEEE Spectrum magazine, in its online edition, published between the years 2009 and 2012. The aim of this collection is to provide different examples of use in the technical text for the terms included in the glossary, so that examples of the actual use of the terms consulted can be easily and quickly accessed, in order to clarify doubts regarding their meaning or translation into Spanish and facilitate learning. All this information, both the list of terms with prepositional phrases as well as the corpus developed, is incorporated in a database. Through a searching form, the ILLLab's user may obtain all the terms matching the search criteria entered. The user can perform two types of main search: by preposition or by full term. Additionally, a global search can be selected (including all terms included in the glossary) or a partial one (including only one of the glossary's categories). Finally, some statistics of use are presented according to the various texts included in the corpus, so a relation of the most frequent prepositions in the technical text can be established.

Two design methods for radial line slot antennas with arbitrary or beam pattern

Two design procedures for Radial Line Slot Antennas (RLSAs) with circular polarization and either maximum gain or an arbitrary shaped pattern are proposed. Firstly, a method to design a RLSA with any desired pattern is presented. It is based on an optimization algorithm and some measures to ensure its fast convergence and stability need to be taken. Secondly, a fast technique to calculate the length and the position of every slot in a high gain RLSA with uniform field distribution is described. Both procedures are vali dated with the design of three antennas with different characteristics.

Urban agriculture in the new framework of green cities.

Urban Agriculture was a common practice in the old times. However after a period of low interest by urban population there is a movement of renaissance of urban agriculture especially in the new megalopolis. It is important to understand the role of UA in the new framework, and the interface of urban and rural agricultures, with their comparative advantages. Thus, we describe the impact of UA in several scenarios: political, socioeconomic and environmental. As a consequence several actions should be developed for improving the situation, with the stimulus to UA: urban planning, food value chain, appropriate technology, education and extension services, entertainment and leisure, selection of botanic varieties and agrochemical inputs, design and landscape and good farming practices. As a complement, there is an analysis of the Urban Greening Value Organization in our society. In the paper there is a description of the situation of urban agriculture in Spain (located mainly in roofs, walls, indoor and ground places) the existence of local regulations, barriers and opportunities in the new situation. Due to the social dimension of urban agriculture there are some comments about the role of the more significant stakeholders, and the goals and the structure of the neighbor communities.

El nuevo reto de relación con los clientes: Social CRM

La evolución de Internet al modelo Web 2.0, ha creado el nuevo sistema denominado Social Media, donde han proliferado un número ingente de redes sociales, que han cambiado las formas de relación y colaboración entre los usuarios, así como la relaciones de éstos y las empresas. En respuesta a estos dramáticos cambios sociales y tecnológicos, que actualmente están dando forma a las relaciones negocio-empresa, las empresas están descubriendo que es necesario modificar la estrategia de utilización del CRM (Customer Relationship Management) con sus clientes y desarrollar nuevas capacidades que permitan la creación de valor con los clientes. Y es aquí donde aparece el concepto de Social CRM, entendido como una estrategia centrada en entender, anticiparse y responder mejor a las necesidades de los clientes existentes o potenciales, aprovechando los datos sociales, para crear unas fuertes relaciones beneficiosas para ambas partes. En este trabajo se describe un modelo de adopción de Social CRM, aplicando un método de análisis “Top-Down”, y basado en el modelo de Gartner denominado “The Eight Building Blocks of CRM” [1]. El presente trabajo descompone el modelo de adopción descrito por Gartner, en los siguientes puntos. - Una decisión estratégica de la compañía - Asomarse a la realidad social - Analizar las redes sociales. - Metodología de adopción. - Despliegue y extensión en todos los departamentos de la compañía y la adaptación de los recursos humanos. - Selección e integración con las plataformas tradicionales de CRM - Análisis de herramientas de monitorización de Social CRM El modelo propuesto tiene dos objetivos, por un lado pretende proporcionar la visión de cómo CRM puede influir en los resultados empresariales en la era del cliente social, y por otro, proporcionar a los administradores cómo las inversiones y los recursos existentes de CRM puede ser integrados con las nuevas tecnologías y procesos para formar capacidades que pueden mejorar el rendimiento del negocio. ABSTRACT. “The Internet evolution to Web 2.0 model has created a new system called Social Media, where have proliferated a huge number of social networks which have changed the relationship and collaboration forms user-to-user and user-to-company. In response to these dramatic social and technological changes that are currently shaping the business-business relationships, companies are finding it necessary to modify the strategy for use of CRM (Customer Relationship Management) with customers and develop new capabilities to creating value with customers. And here is where the concept of Social CRM appears, understood as a focus on understanding, anticipating and responding to the needs of existing and potential customers strategy, leveraging social data to create a strong mutually beneficial relationships. In this paper describes an adoption model of Social CRM, using a "Top-Down" analysis method and based on the model of Gartner called "The Eight Building Blocks of CRM" [1]. This paper decomposes the adoption model described by Gartner in the following points. - A company strategic decision. - Look at social reality. - Analyze social networks. - Methodology adoption. - Deployment and extension in all departments of the company and the adaptation of human resources. - Selection and integration with traditional CRM platforms. - Analysis of monitoring tools for Social CRM. The proposed model has two objectives, firstly aims to provide insight into how CRM can influence business outcomes in the era of the social customer, and secondly, to provide administrators how investments and existing resources can be integrated CRM with new technologies and processes for developing capabilities that can increase business performance”.

An inverse optimization strategy to determine single crystal mechanical behavior from polycrystal tests: Application to AZ31 Mg alloy

An inverse optimization strategy was developed to determine the single crystal properties from experimental results of the mechanical behavior of polycrystals. The polycrystal behavior was obtained by means of the finite element simulation of a representative volume element of the microstructure in which the dominant slip and twinning systems were included in the constitutive equation of each grain. The inverse problem was solved by means of the Levenberg-Marquardt method, which provided an excellent fit to the experimental results. The iterative optimization process followed a hierarchical scheme in which simple representative volume elements were initially used, followed by more realistic ones to reach the final optimum solution, leading to important reductions in computer time. The new strategy was applied to identify the initial and saturation critical resolved shear stresses and the hardening modulus of the active slip systems and extension twinning in a textured AZ31 Mg alloy. The results were in general agreement with the data in the literature but also showed some differences. They were partially explained because of the higher accuracy of the new optimization strategy but it was also shown that the number of independent experimental stress-strain curves used as input is critical to reach an accurate solution to the inverse optimization problem. It was concluded that at least three independent stress-strain curves are necessary to determine the single crystal behavior from polycrystal tests in the case of highly textured Mg alloys.