In-field assessment of batteries and PV modules in a large photovoltaic rural electrification programme

Assuring the sustainability of quality in photovoltaic rural electrification programmes involves enhancing the reliability of the components of solar home systems as well as the characterization of the overall programme cost structure. Batteries and photovoltaic modules have a great impact on both the reliability and the cost assessment, the battery being the weakest component of the solar home system and consequently the most expensive element of the programme. The photovoltaic module, despite being the most reliable component, has a significant impact cost-wise on the initial investment, even at current market prices. This paper focuses on the in-field testing of both batteries and photovoltaic modules working under real operating conditions within a sample of 41 solar home systems belonging to a large photovoltaic rural electrification programme with more than 13,000 installed photovoltaic systems. Different reliability parameters such as lifetime have been evaluated, taking into account different factors, for example energy consumption rates, or the manufacturing quality of batteries. A degradation model has been proposed relating both loss of capacity and time of operation. The user e solar home system binomial is also analysed in order to understand the meaning of battery lifetime in rural electrification.

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).

Localization and activity detection Based on the fusion of environment And inertial sensors = Localización y detección de actividad Basadas en integración de sensores y dispositivos inerciales

Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

Using modular neural networks to model self-consciousness and self-representation for artificial entities

Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this paper, a cognitive architecture for self-consciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals'representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons’ cognitive architecture that enables dynamic self-representation. We analyse the effect of holon interaction, focusing on the evolution of the holon’s abstract self-representation. Finally, the results are explained and analysed and conclusions drawn.

Operational costs and reliability in a large rural electrification programme based on solar home systems

Experiences in decentralized rural electrification programmes using solar home systems have suffered difficulties during the operation and maintenance phase, due in many cases, to the underestimation of the maintenance cost, because of the decentralized character of the activity, and also because the reliability of the solar home system components is frequently unknown. This paper reports on the reliability study and cost characterization achieved in a large photovoltaic rural electrification programme carried out in Morocco. The paper aims to determinate the reliability features of the solar systems, focusing in the in-field testing for batteries and photovoltaic modules. The degradation rates for batteries and PV modules have been extracted from the in-field experiments. On the other hand, the main costs related to the operation and maintenance activity have been identified with the aim of establishing the main factors that lead to the failure of the quality sustainability in many rural electrification programmes.

Caracterización de colectores para sistemas de concentración fotovoltaica

Este proyecto, titulado “Caracterización de colectores para concentración fotovoltaica”, consiste en una aplicación en Labview para obtener las características de los elementos ópticos utilizados en sistemas de concentración fotovoltaica , atendiendo a la distribución espacial del foco de luz concentrado que generan. Un sistema de concentración fotovoltaica utiliza un sistema óptico para transmitir la radiación luminosa a la célula solar aumentando la densidad de potencia luminosa. Estos sistemas ópticos están formados por espejos o lentes para recoger la radiación incidente en ellos y concentrar el haz de luz en una superficie mucho menor. De esta manera se puede reducir el área de material semiconductor necesario, lo que conlleva una importante reducción del coste del sistema. Se pueden distinguir diferentes sistemas de concentración dependiendo de la óptica que emplee, la estructura del receptor o el rango de concentración. Sin embargo, ya que el objetivo es analizar la distribución espacial, diferenciaremos dos tipos de concentradores dependiendo de la geometría que presenta el foco de luz. El concentrador lineal o cilíndrico que enfoca sobre una línea, y el concentrador de foco puntual o circular que enfoca la luz sobre un punto. Debido a esta diferencia el análisis en ambos casos se realizará de forma distinta. El análisis se realiza procesando una imagen del foco tomada en el lugar del receptor, este método se llama LS-CCD (Difusión de luz y captura con CCD). Puede utilizarse en varios montajes dependiendo si se capta la imagen por reflexión o por transmisión en el receptor. En algunos montajes no es posible captar la imagen perpendicular al receptor por lo que la aplicación realizará un ajuste de perspectiva para obtener el foco con su forma original. La imagen del foco ofrece información detallada acerca de la uniformidad del foco mediante el mapa de superficie, que es una representación en 3D de la imagen pero que resulta poco manejable. Una representación más sencilla y útil es la que ofrecen los llamados “perfiles de intensidad”. El perfil de intensidad o distribución de la irradiancia que representa la distribución de la luz para cada distancia al centro, y el perfil acumulado o irradiancia acumulada que representa la luz contenida en relación también al centro. Las representaciones de estos perfiles en el caso de un concentrador lineal y otro circular son distintas debido a su diferente geometría. Mientras que para un foco lineal se expresa el perfil en función de la semi-anchura del receptor, para uno circular se expresa en función del radio. En cualquiera de los casos ofrecen información sobre la uniformidad y el tamaño del foco de luz necesarios para diseñar el receptor. El objetivo de este proyecto es la creación de una aplicación software que realice el procesado y análisis de las imágenes obtenidas del foco de luz de los sistemas ópticos a caracterizar. La aplicación tiene una interfaz sencilla e intuitiva para que pueda ser empleada por cualquier usuario. Los recursos necesarios para realizar el proyecto son: un PC con sistema operativo Windows, el software Labview 8.6 Professional Edition y los módulos NI Vision Development Module (para trabajar con imágenes) y NI Report Generation Toolkit (para realizar reportes y guardar datos de la aplicación). ABSTRACT This project, called “Characterization of collectors for concentration photovoltaic systems”, consists in a Labview application to obtain the characteristics of the optical elements used in photovoltaic concentrator, taking into account the spatial distribution of concentrated light source generated. A concentrator photovoltaic system uses an optical system to transmit light radiation to the solar cell by increasing the light power density. This optical system are formed by mirrors or lenses to collect the radiation incident on them and focus the beam of light in a much smaller surface area. In this way you can reduce the area of semiconductor material needed, which implies a significant reduction in system cost. There are different concentration systems depending on the optics used, receptor structure or concentration range. However, as the aim is to analyze the spatial distribution, distinguish between two types of concentrators depending on the geometry that has the light focus. The linear or cylindrical concentrator that focused on a line, and the circular concentrator that focused light onto a point. Because this difference in both cases the analysis will be carried out differently. The analysis is performed by processing a focus image taken at the receiver site, this method is called “LS-CCD” (Light Scattering and CCD recording). Can be used in several mountings depending on whether the image is captured by reflection or transmission on the receiver. In some mountings it is not possible to capture the image perpendicular to the receivers so that the application makes an adjustment of perspective to get the focus to its original shape. The focus image provides detail information about the uniformity of focus through the surface map, which is a 3D image representation but it is unwieldy. A simple and useful representation is provided by so called “intensity profiles”. The intensity profile or irradiance distribution which represents the distribution of light to each distance to the center. The accumulated profile or accumulated irradiance that represents the cumulative light contained in relation also to the center. The representation of these profiles in the case of a linear and a circular concentrator are different due to their distinct geometry. While for a line focus profile is expressed in terms of semi-width of the receiver, for a circular concentrator is expressed in terms of radius. In either case provides information about the uniformity and size of focus needed to design the receiver. The objective of this project is the creation of a software application to perform processing and analysis of images obtained from light source of optical systems to characterize.The application has a simple and a intuitive interface so it can be used for any users. The resources required for the project are: a PC with Windows operating system, LabVIEW 8.6 Professional Edition and the modules NI Vision Development Module (for working with images) and NI Report Generation Toolkit (for reports and store application data .)

Implementing distributed concurrent constraint execution in the CIAO system

This paper describes the current prototype of the distributed CIAO system. It introduces the concepts of "teams" and "active modules" (or active objects), which conveniently encapsulate different types of functionalities desirable from a distributed system, from parallelism for achieving speedup to client-server applications. The user primitives available are presented and their implementation described. This implementation uses attributed variables and, as an example of a communication abstraction, a blackboard that follows the Linda model. Finally, the CIAO WWW interface is also briefly described. The unctionalities of the system are illustrated through examples, using the implemented primitives.

Distributed concurrent constraint execution in the CIAO system

This paper describes the current prototype of the distributed CIAO system. It introduces the concepts of "teams" and "active modules" (or active objects), which conveniently encapsulate different types of functionalities desirable from a distributed system, from parallelism for achieving speedup to client-server applications. It presents the user primitives available and describes their implementation. This implementation uses attributed variables and, as an example of a communication abstraction, a blackboard that follows the Linda model. The functionalities of the system are illustrated through examples, using the implemented primitives. The implementation of most of the primitives is also described in detail.

Cognitive wireless sensor network platform for cooperative communications

Nowadays, Wireless Ad Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing RF spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage. This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the only cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application. Significant features such as radio interface (RI) agility or energy consumption have been proven throughout different performance tests.

Selecting crop models for decision making in wheat insurance

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES- Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems.

Estudio, ensamblaje, caracterización y ensayos de dos modelos reales de RPA

Un dron o un RPA (del inglés, Remote Piloted Aircraft) es un vehículo aéreo no tripulado capaz de despegar, volar y aterrizar de forma autónoma, semiautónoma o manual, siempre con control remoto. Además, toda aeronave de estas características debe ser capaz de mantener un nivel de vuelo controlado y sostenido. A lo largo de los años, estos aparatos han ido evolución tanto en aplicaciones como en su estética y características físicas, siempre impulsado por los requerimientos militares en cada momento. Gracias a este desarrollo, hoy en día los drones son uno más en la sociedad y desempeñan tareas que para cualquier ser humano serían peligrosas o difíciles de llevar a cabo. Debido a la reciente proliferación de los RPA, los gobiernos de los distintos países se han visto obligados a redactar nuevas leyes y/o modificar las ya existentes en relación a los diferentes usos del espacio aéreo para promover la convivencia de estas aeronaves con el resto de vehículos aéreos. El objeto principal de este proyecto es ensamblar, caracterizar y configurar dos modelos reales de dron: el DJI F450 y el TAROT t810. Para conseguir un montaje apropiado a las aplicaciones posteriores que se les va a dar, antes de su construcción se ha realizado un estudio individualizado en detalle de cada una de las partes y módulos que componen estos vehículos. Adicionalmente, se ha investigado acerca de los distintos tipos de sistemas de transmisión de control remoto, vídeo y telemetría, sin dejar de lado las baterías que impulsarán al aparato durante sus vuelos. De este modo, es sabido que los RPA están compuestos por distintos módulos operativos: los principales, todo aquel módulo para que el aparato pueda volar, y los complementarios, que son aquellos que dotan a cada aeronave de características adicionales y personalizadas que lo hacen apto para diferentes usos. A lo largo de este proyecto se han instalado y probado diferentes módulos adicionales en cada uno de los drones, además de estar ambos constituidos por distintos bloques principales, incluyendo el controlador principal: NAZA-M Lite instalado en el dron DJI F450 y NAZA-M V2 incorporado en el TAROT t810. De esta forma se ha podido establecer una comparativa real acerca del comportamiento de éstos, tanto de forma conjunta como de ambos controladores individualmente. Tras la evaluación experimental obtenida tras diversas pruebas de vuelo, se puede concluir que ambos modelos de controladores se ajustan a las necesidades demandadas por el proyecto y sus futuras aplicaciones, siendo más apropiada la elección del modelo M Lite por motivos estrictamente económicos, ya que su comportamiento en entornos recreativos es similar al modelo M V2. ABSTRACT. A drone or RPA (Remote Piloted Aircraft) is an unmanned aerial vehicle that is able to take off, to fly and to land autonomously, semi-autonomously or manually, always connected via remote control. In addition, these aircrafts must be able to keep a controlled and sustained flight level. Over the years, the applications for these devices have evolved as much as their aesthetics and physical features both boosted by the military needs along time. Thanks to this development, nowadays drones are part of our society, executing tasks potentially dangerous or difficult to complete by humans. Due to the recent proliferation of RPA, governments worldwide have been forced to draft legislation and/or modify the existing ones about the different uses of the aerial space to promote the cohabitation of these aircrafts with the rest of the aerial vehicles. The main objective of this project is to assemble, to characterize and to set-up two real drone models: DJI F450 and TAROT t810. Before constructing the vehicles, a detailed study of each part and module that composes them has been carried out, in order to get an appropriate structure for their expected uses. Additionally, the different kinds of remote control, video and telemetry transmission systems have been investigated, including the batteries that will power the aircrafts during their flights. RPA are made of several operative modules: main modules, i.e. those which make the aircraft fly, and complementary modules, that customize each aircraft and equip them with additional features, making them suitable for a particular use. Along this project, several complementary modules for each drone have been installed and tested. Furthermore, both are built from different main units, including the main controller: NAZA-M Lite installed on DJI F450 and NAZA-M V2 on board of TAROT t810. This way, it has been possible to establish an accurate comparison, related to the performance of both models, not only jointly but individually as well. After several flight tests and an experimental evaluation, it can be concluded that both main controller models are suitable for the requirements fixed for the project and the future applications, being more appropriate to choose the M Lite model strictly due to economic reasons, as its performance in recreational environment is similar to the M V2.

Characterization of thin film PV modules under standard test conditions: Results of indoor and outdoor measurements and the effects of sunlight exposure

Photovoltaic modules based on thin film technology are gaining importance in the photovoltaic market, and module installers and plant owners have increasingly begun to request methods of performing module quality control. These modules pose additional problems for measuring power under standard test conditions (STC), beyond problems caused by the temperature of the module and the ambient variables. The main difficulty is that the modules’ power rates may vary depending both on the amount of time they have been exposed to the sun during recent hours and on their history of sunlight exposure. In order to assess the current state of the module, it is necessary to know its sunlight exposure history. Thus, an easily accomplishable testing method that ensures the repeatability of the measurements of the power generated is needed. This paper examines different tests performed on commercial thin film PV modules of CIS, a-Si and CdTe technologies in order to find the best way to obtain measurements. A method for obtaining indoor measurements of these technologies that takes into account periods of sunlight exposure is proposed. Special attention is paid to CdTe as a fast growing technology in the market.

NGCPV: A new generation of concentrator photovoltaic cells, modules and systems

This work introduces the lines of research that the NGCPV project is pursuing and some of the first results obtained. Sponsored by the European Commission under the 7th Framework Program and NEDO (Japan) within the first collaborative call launched by both Bodies in the field of energy, NGCPV project aims at approaching the cost of the photovoltaic kWh to competitive prices in the framework of high concentration photovoltaics (CPV) by exploring the development and assessment of concentrator photovoltaic solar cells and modules, novel materials and new solar cell structures as well as methods and procedures to standardize measurement technology for concentrator photovoltaic cells and modules. More specific objectives we are facing are: (1) to manufacture a cell prototype with an efficiency of at least 45% and to undertake an experimental activity, (2) to manufacture a 35% module prototype and elaborate the roadmap towards the achievement of 40%, (3) to develop reliable characterization techniques for III-V materials and quantum structures, (4) to achieve and agreement within 5% in the characterization of CPV cells and modules in a round robin scheme, and (5) to evaluate the potential of new materials, devices technologies and quantum nanostructures to improve the efficiency of solar cells for CPV.

NGCPV: a new generation of concentrator photovoltaic cells, modules and systems

Starting on June 2011, NGCPV is the first project funded jointly between the European Commission (EC) and the New Energy and Industrial Technology Development Organization (NEDO) of Japan to research on new generation concentration photovoltaics (CPV). The Project, through a collaborative research between seven European and nine Japanese leading research centers in the field of CPV, aims at lowering the cost of the CPVproduced photovoltaic kWh down to 5 ?cents. The main objective of the project is to improve the present concentrator cell, module and system efficiency, as well as developing advanced characterization tools for CPV components and systems. As particular targets, the project aims at achieving a cell efficiency of at least 45% and a CPV module with an efficiency greater than 35%. This paper describes the R&D activities that are being carried out within the NGCPV project and summarizes some of the most relevant results that have already been attained, for instance: the manufacturing of a 44.4% world record efficiency triple junction solar cell (by Sharp Corp.) and the installation of a 50 kWp experimental CPV plant in Spain, which will be used to obtain accurate forecasts of the energy produced at system level.

Design of a twin capacitive load and its application to the outdoor rating of photovoltaic modules

This paper describes the design of an original twin capacitive load that is able of tracing simultaneously the I?V characteristics of two photovoltaic modules. Besides, an example of the application of this dual system to the outdoor rating of photovoltaic modules is presented, whose results have shown a good degree of repeatability.