A novel FPGA-based evolvable hardware system based on multiple processing arrays

In this paper, an architecture based on a scalable and flexible set of Evolvable Processing arrays is presented. FPGA-native Dynamic Partial Reconfiguration (DPR) is used for evolution, which is done intrinsically, letting the system to adapt autonomously to variable run-time conditions, including the presence of transient and permanent faults. The architecture supports different modes of operation, namely: independent, parallel, cascaded or bypass mode. These modes of operation can be used during evolution time or during normal operation. The evolvability of the architecture is combined with fault-tolerance techniques, to enhance the platform with self-healing features, making it suitable for applications which require both high adaptability and reliability. Experimental results show that such a system may benefit from accelerated evolution times, increased performance and improved dependability, mainly by increasing fault tolerance for transient and permanent faults, as well as providing some fault identification possibilities. The evolvable HW array shown is tailored for window-based image processing applications.

Fluoro-sensing applied to detection and identification of hydrocarbons in inland waters. Study of the impact of different UV light sources

This paper presents the detection and identification of hydrocarbons through flu oro-sensing by developing a simple and inexpensive detector for inland water, in contrast to current systems, designed to be used for marine waters at large distances and being extremely costly. To validate the proposed system, three test-benches have been mounted, with various UV-Iight sources. Main application of this system would be detect hydrocarbons pollution in rivers, lakes or dams, which in fact, is of growing interest by administrations.

New method for analytical photovoltaic parameters identification: meeting manufacturer’s datasheet for different ambient conditions

At present, photovoltaic energy is one of the most important renewable energy sources. The demand for solar panels has been continuously growing, both in the industrial electric sector and in the private sector. In both cases the analysis of the solar panel efficiency is extremely important in order to maximize the energy production. In order to have a more efficient photovoltaic system, the most accurate understanding of this system is required. However, in most of the cases the only information available in this matter is reduced, the experimental testing of the photovoltaic device being out of consideration, normally for budget reasons. Several methods, normally based on an equivalent circuit model, have been developed to extract the I-V curve of a photovoltaic device from the small amount of data provided by the manufacturer. The aim of this paper is to present a fast, easy, and accurate analytical method, developed to calculate the equivalent circuit parameters of a solar panel from the only data that manufacturers usually provide. The calculated circuit accurately reproduces the solar panel behavior, that is, the I-V curve. This fact being extremely important for practical reasons such as selecting the best solar panel in the market for a particular purpose, or maximize the energy extraction with MPPT (Maximum Peak Power Tracking) methods.

Signal analysis and feature generation for pattern identification of partial discharges in high-voltage equipment

This paper proposes a method for the identification of different partial discharges (PDs) sources through the analysis of a collection of PD signals acquired with a PD measurement system. This method, robust and sensitive enough to cope with noisy data and external interferences, combines the characterization of each signal from the collection, with a clustering procedure, the CLARA algorithm. Several features are proposed for the characterization of the signals, being the wavelet variances, the frequency estimated with the Prony method, and the energy, the most relevant for the performance of the clustering procedure. The result of the unsupervised classification is a set of clusters each containing those signals which are more similar to each other than to those in other clusters. The analysis of the classification results permits both the identification of different PD sources and the discrimination between original PD signals, reflections, noise and external interferences. The methods and graphical tools detailed in this paper have been coded and published as a contributed package of the R environment under a GNU/GPL license.

Automatic expert system based on images for accuracy crop row detection in maize fields

This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.

El análogo natural de almacenamiento y escape de Co2 de la cuenca de Gañuelas-Mazarrón : implicaciones para el comportamiento y la seguridad de un almacenamiento de Co2 en estaso supercrítico

El aumento de la temperatura media de la Tierra durante el pasado siglo en casi 1 ºC; la subida del nivel medio del mar; la disminución del volumen de hielo y nieve terrestres; la fuerte variabilidad del clima y los episodios climáticos extremos que se vienen sucediendo durante las ultimas décadas; y el aumento de las epidemias y enfermedades infecciosas son solo algunas de las evidencias del cambio climático actual, causado, principalmente, por la acumulación de gases de efecto invernadero en la atmósfera por actividades antropogénicas. La problemática y preocupación creciente surgida a raíz de estos fenómenos, motivo que, en 1997, se adoptara el denominado “Protocolo de Kyoto” (Japón), por el que los países firmantes adoptaron diferentes medidas destinadas a controlar y reducir las emisiones de los citados gases. Entre estas medidas cabe destacar las tecnologías CAC, enfocadas a la captura, transporte y almacenamiento de CO2. En este contexto se aprobó, en octubre de 2008, el Proyecto Singular Estratégico “Tecnologías avanzadas de generación, captura y almacenamiento de CO2” (PSE-120000-2008-6), cofinanciado por el Ministerio de Ciencia e Innovación y el FEDER, el cual abordaba, en su Subproyecto “Almacenamiento Geológico de CO2” (PSS-120000-2008-31), el estudio detallado, entre otros, del Análogo Natural de Almacenamiento y Escape de CO2 de la cuenca de Ganuelas-Mazarrón (Murcia). Es precisamente en el marco de dicho Proyecto en el que se ha realizado este trabajo, cuyo objetivo final ha sido el de predecir el comportamiento y evaluar la seguridad, a corto, medio y largo plazo, de un Almacenamiento Geológico Profundo de CO2 (AGP-CO2), mediante el estudio integral del citado análogo natural. Este estudio ha comprendido: i) la contextualización geológica e hidrogeológica de la cuenca, así como la investigación geofísica de la misma; ii) la toma de muestras de aguas de algunos acuíferos seleccionados con el fin de realizar su estudio hidrogeoquímico e isotópico; iii) la caracterización mineralógica, petrográfica, geoquímica e isotópica de los travertinos precipitados a partir de las aguas de algunos de los sondeos de la cuenca; y iv) la medida y caracterización química e isotópica de los gases libres y disueltos detectados en la cuenca, con especial atención al CO2 y 222Rn. Esta información, desarrollada en capítulos independientes, ha permitido realizar un modelo conceptual de funcionamiento del sistema natural que constituye la cuenca de Ganuelas-Mazarrón, así como establecer las analogías entre este y un AGP-CO2, con posibles escapes naturales y/o antropogénicos. La aplicación de toda esta información ha servido, por un lado, para predecir el comportamiento y evaluar la seguridad, a corto, medio y largo plazo, de un AGP-CO2 y, por otro, proponer una metodología general aplicable al estudio de posibles emplazamientos de AGP-CO2 desde la perspectiva de los reservorios naturales de CO2. Los resultados más importantes indican que la cuenca de Ganuelas-Mazarrón se trata de una cubeta o fosa tectónica delimitada por fallas normales, con importantes saltos verticales, que hunden al substrato rocoso (Complejo Nevado-Filabride), y rellenas, generalmente, por materiales volcánicos-subvolcánicos ácidos. Además, esta cuenca se encuentra rellena por formaciones menos resistivas que son, de muro a techo, las margas miocenas, predominantes y casi exclusivas de la cuenca, y los conglomerados y gravas pliocuaternarias. El acuífero salino profundo y enriquecido en CO2, puesto de manifiesto por la xx exploración geotérmica realizada en dicha cuenca durante la década de los 80 y objeto principal de este estudio, se encuentra a techo de los materiales del Complejo Nevado-Filabride, a una profundidad que podría superar los 800 m, según los datos de la investigación mediante sondeos y geofísica. Por ello, no se descarta la posibilidad de que el CO2 se encuentre en estado supe critico, por lo que la citada cuenca reuniría las características principales de un almacenamiento geológico natural y profundo de CO2, o análogo natural de un AGP-CO2 en un acuífero salino profundo. La sobreexplotación de los acuíferos mas someros de la cuenca, con fines agrícolas, origino, por el descenso de sus niveles piezométricos y de la presión hidrostática, el ascenso de las aguas profundas, salinas y enriquecidas en CO2, las cuales son las responsables de la contaminación de dichos acuíferos. El estudio hidrogeoquímico de las aguas de los acuíferos investigados muestra una gran variedad de hidrofacies, incluso en aquellos de litología similar. La alta salinidad de estas aguas las hace inservibles tanto para el consumo humano como para fines agrícolas. Además, el carácter ligeramente ácido de la mayoría de estas aguas determina que tengan gran capacidad para disolver y transportar, hacia la superficie, elementos pesados y/o tóxicos, entre los que destaca el U, elemento abundante en las rocas volcánicas ácidas de la cuenca, con contenidos de hasta 14 ppm, y en forma de uraninita submicroscópica. El estudio isotópico ha permitido discernir el origen, entre otros, del C del DIC de las aguas (δ13C-DIC), explicándose como una mezcla de dos componentes principales: uno, procedente de la descomposición térmica de las calizas y mármoles del substrato y, otro, de origen edáfico, sin descartar una aportación menor de C de origen mantélico. El estudio de los travertinos que se están formando a la salida de las aguas de algunos sondeos, por la desgasificación rápida de CO2 y el consiguiente aumento de pH, ha permitido destacar este fenómeno, por analogía, como alerta de escapes de CO2 desde un AGP-CO2. El análisis de los gases disueltos y libres, con especial atención al CO2 y al 222Rn asociado, indican que el C del CO2, tanto disuelto como en fase libre, tiene un origen similar al del DIC, confirmándose la menor contribución de CO2 de origen mantélico, dada la relación R/Ra del He existente en estos gases. El 222Rn sería el generado por el decaimiento radiactivo del U, particularmente abundante en las rocas volcánicas de la cuenca, y/o por el 226Ra procedente del U o del existente en los yesos mesinienses de la cuenca. Además, el CO2 actúa como carrier del 222Rn, hecho evidenciado en las anomalías positivas de ambos gases a ~ 1 m de profundidad y relacionadas principalmente con perturbaciones naturales (fallas y contactos) y antropogénicas (sondeos). La signatura isotópica del C a partir del DIC, de los carbonatos (travertinos), y del CO2 disuelto y libre, sugiere que esta señal puede usarse como un excelente trazador de los escapes de CO2 desde un AGPCO2, en el cual se inyectara un CO2 procedente, generalmente, de la combustión de combustibles fósiles, con un δ13C(V-PDB) de ~ -30 ‰. Estos resultados han permitido construir un modelo conceptual de funcionamiento del sistema natural de la cuenca de Ganuelas-Mazarrón como análogo natural de un AGP-CO2, y establecer las relaciones entre ambos. Así, las analogías mas importantes, en cuanto a los elementos del sistema, serian la existencia de: i) un acuífero salino profundo enriquecido en CO2, que seria análoga a la formación almacén de un AGPxxi CO2; ii) una formación sedimentaria margosa que, con una potencia superior a 500 m, se correspondería con la formación sello de un AGP-CO2; y iii) acuíferos mas someros con aguas dulces y aptas para el consumo humano, rocas volcánicas ricas en U y fallas que se encuentran selladas por yesos y/o margas; elementos que también podrían concurrir en un emplazamiento de un AGP-CO2. Por otro lado, los procesos análogos mas importantes identificados serian: i) la inyección ascendente del CO2, que seria análoga a la inyección de CO2 de origen antropogénico, pero este con una signatura isotópica δ13C(V-PDB) de ~ -30 ‰; ii) la disolución de CO2 y 222Rn en las aguas del acuífero profundo, lo que seria análogo a la disolución de dichos gases en la formación almacén de un AGP-CO2; iii) la contaminación de los acuíferos mas someros por el ascenso de las aguas sobresaturadas en CO2, proceso que seria análogo a la contaminación que se produciría en los acuíferos existentes por encima de un AGP-CO2, siempre que este se perturbara natural (reactivación de fallas) o artificialmente (sondeos); iv) la desgasificación (CO2 y gases asociados, entre los que destaca el 222Rn) del acuífero salino profundo a través de sondeos, proceso análogo al que pudiera ocurrir en un AGP-CO2 perturbado; y v) la formación rápida de travertinos, proceso análogo indicativo de que el AGP-CO2 ha perdido su estanqueidad. La identificación de las analogías más importantes ha permitido, además, analizar y evaluar, de manera aproximada, el comportamiento y la seguridad, a corto, medio y largo plazo, de un AGP-CO2 emplazado en un contexto geológico similar al sistema natural estudiado. Para ello se ha seguido la metodología basada en el análisis e identificación de los FEPs (Features, Events and Processes), los cuales se han combinado entre sí para generar y analizar diferentes escenarios de evolución del sistema (scenario analysis). Estos escenarios de evolución identificados en el sistema natural perturbado, relacionados con la perforación de sondeos, sobreexplotación de acuíferos, precipitación rápida de travertinos, etc., serian análogos a los que podrían ocurrir en un AGP-CO2 que también fuera perturbado antropogénicamente, por lo que resulta totalmente necesario evitar la perturbación artificial de la formación sello del AGPCO2. Por último, con toda la información obtenida se ha propuesto una metodología de estudio que pueda aplicarse al estudio de posibles emplazamientos de un AGP-CO2 desde la perspectiva de los reservorios naturales de CO2, sean estancos o no. Esta metodología comprende varias fases de estudio, que comprendería la caracterización geológico-estructural del sitio y de sus componentes (agua, roca y gases), la identificación de las analogías entre un sistema natural de almacenamiento de CO2 y un modelo conceptual de un AGP-CO2, y el establecimiento de las implicaciones para el comportamiento y la seguridad de un AGP-CO2. ABSTRACT The accumulation of the anthropogenic greenhouse gases in the atmosphere is the main responsible for: i) the increase in the average temperature of the Earth over the past century by almost 1 °C; ii) the rise in the mean sea level; iii) the drop of the ice volume and terrestrial snow; iv) the strong climate variability and extreme weather events that have been happening over the last decades; and v) the spread of epidemics and infectious diseases. All of these events are just some of the evidence of current climate change. The problems and growing concern related to these phenomena, prompted the adoption of the so-called "Kyoto Protocol" (Japan) in 1997, in which the signatory countries established different measurements to control and reduce the emissions of the greenhouse gases. These measurements include the CCS technologies, focused on the capture, transport and storage of CO2. Within this context, it was approved, in October 2008, the Strategic Singular Project "Tecnologías avanzadas de generación, captura y almacenamiento de CO2" (PSE-120000-2008-6), supported by the Ministry of Science and Innovation and the FEDER funds. This Project, by means of the Subproject "Geological Storage of CO2" (PSS- 120000-2008-31), was focused on the detailed study of the Natural Analogue of CO2 Storage and Leakage located in the Ganuelas-Mazarron Tertiary basin (Murcia), among other Spanish Natural Analogues. This research work has been performed in the framework of this Subproject, being its final objective to predict the behaviour and evaluate the safety, at short, medium and long-term, of a CO2 Deep Geological Storage (CO2-DGS) by means of a comprehensive study of the abovementioned Natural Analogue. This study comprises: i) the geological and hydrogeological context of the basin and its geophysical research; ii) the water sampling of the selected aquifers to establish their hydrogeochemical and isotopic features; iii) the mineralogical, petrographic, geochemical and isotopic characterisation of the travertines formed from upwelling groundwater of several hydrogeological and geothermal wells; and iv) the measurement of the free and dissolved gases detected in the basin, as well as their chemical and isotopic characterisation, mainly regarding CO2 and 222Rn. This information, summarised in separate chapters in the text, has enabled to build a conceptual model of the studied natural system and to establish the analogies between both the studied natural system and a CO2-DGS, with possible natural and/or anthropogenic escapes. All this information has served, firstly, to predict the behaviour and to evaluate the safety, at short, medium and long-term, of a CO2-DGS and, secondly, to propose a general methodology to study suitable sites for a CO2-DGS, taking into account the lessons learned from this CO2 natural reservoir. The main results indicate that the Ganuelas-Mazarron basin is a graben bounded by normal faults with significant vertical movements, which move down the metamorphic substrate (Nevado-Filabride Complex), and filled with acid volcanic-subvolcanic rocks. Furthermore, this basin is filled with two sedimentary formations: i) the Miocene marls, which are predominant and almost exclusive in the basin; xxiv and ii) the Plio-Quaternary conglomerates and gravels. A deep saline CO2-rich aquifer was evidenced in this basin as a result of the geothermal exploration wells performed during the 80s, located just at the top of the Nevado-Filabride Complex and at a depth that could exceed 800 m, according to the geophysical exploration performed. This saline CO2-rich aquifer is precisely the main object of this study. Therefore, it is not discarded the possibility that the CO2 in this aquifer be in supercritical state. Consequently, the aforementioned basin gathers the main characteristics of a natural and deep CO2 geological storage, or natural analogue of a CO2-DGS in a deep saline aquifer. The overexploitation of the shallow aquifers in this basin for agriculture purposes caused the drop of the groundwater levels and hydrostatic pressures, and, as a result, the ascent of the deep saline and CO2-rich groundwater, which is the responsible for the contamination of the shallow and fresh aquifers. The hydrogeochemical features of groundwater from the investigated aquifers show the presence of very different hydrofacies, even in those with similar lithology. The high salinity of this groundwater prevents the human and agricultural uses. In addition, the slightly acidic character of most of these waters determines their capacity to dissolve and transport towards the surface heavy and/or toxic elements, among which U is highlighted. This element is abundant in the acidic volcanic rocks of the basin, with concentrations up to 14 ppm, mainly as sub-microscopic uraninite crystals. The isotopic study of this groundwater, particularly the isotopic signature of C from DIC (δ13C-DIC), suggests that dissolved C can be explained considering a mixture of C from two main different sources: i) from the thermal decomposition of limestones and marbles forming the substrate; and ii) from edaphic origin. However, a minor contribution of C from mantle degassing cannot be discarded. The study of travertines being formed from upwelling groundwater of several hydrogeological and geothermal wells, as a result of the fast CO2 degassing and the pH increase, has allowed highlighting this phenomenon, by analogy, as an alert for the CO2 leakages from a CO2-DGS. The analysis of the dissolved and free gases, with special attention to CO2 and 222Rn, indicates that the C from the dissolved and free CO2 has a similar origin to that of the DIC. The R/Ra ratio of He corroborates the minor contribution of CO2 from the mantle degassing. Furthermore, 222Rn is generated by the radioactive decay of U, particularly abundant in the volcanic rocks of the basin, and/or by 226Ra from the U or from the Messinian gypsum in the basin. Moreover, CO2 acts as a carrier of the 222Rn, a fact evidenced by the positive anomalies of both gases at ~ 1 m depth and mainly related to natural (faults and contacts) and anthropogenic (wells) perturbations. The isotopic signature of C from DIC, carbonates (travertines), and dissolved and free CO2, suggests that this parameter can be used as an excellent tracer of CO2 escapes from a CO2-DGS, in which CO2 usually from the combustion of fossil fuels, with δ13C(V-PDB) of ~ -30 ‰, will be injected. All of these results have allowed to build a conceptual model of the behaviour of the natural system studied as a natural analogue of a CO2-DGS, as well as to establish the relationships between both natural xxv and artificial systems. Thus, the most important analogies, regarding the elements of the system, would be the presence of: i) a deep saline CO2-rich aquifer, which would be analogous to the storage formation of a CO2-DGS; ii) a marly sedimentary formation with a thickness greater than 500 m, which would correspond to the sealing formation of a CO2-DGS; and iii) shallow aquifers with fresh waters suitable for human consumption, U-rich volcanic rocks, and faults that are sealed by gypsums and/or marls; geological elements that could also be present in a CO2-DGS. On the other hand, the most important analogous processes identified are: i) the upward injection of CO2, which would be analogous to the downward injection of the anthropogenic CO2, this last with a δ13C(V-PDB) of ~ -30 ‰; ii) the dissolution of CO2 and 222Rn in groundwater of the deep aquifer, which would be analogous to the dissolution of these gases in the storage formation of a CO2-DGS; iii) the contamination of the shallow aquifers by the uprising of CO2-oversaturated groundwater, an analogous process to the contamination that would occur in shallow aquifers located above a CO2-DGS, whenever it was naturally (reactivation of faults) or artificially (wells) perturbed; iv) the degassing (CO2 and associated gases, among which 222Rn is remarkable) of the deep saline aquifer through wells, process which could be similar in a perturbed CO2- DGS; v) the rapid formation of travertines, indicating that the CO2-DGS has lost its seal capacity. The identification of the most important analogies has also allowed analysing and evaluating, approximately, the behaviour and safety in the short, medium and long term, of a CO2-DGS hosted in a similar geological context of the natural system studied. For that, it has been followed the methodology based on the analysis and identification of FEPs (Features, Events and Processes) that have been combined together in order to generate and analyse different scenarios of the system evolution (scenario analysis). These identified scenarios in the perturbed natural system, related to boreholes, overexploitation of aquifers, rapid precipitation of travertines, etc., would be similar to those that might occur in a CO2-DGS anthropogenically perturbed, so that it is absolutely necessary to avoid the artificial perturbation of the seal formation of a CO2-DGS. Finally, a useful methodology for the study of possible sites for a CO2-DGS is suggested based on the information obtained from this investigation, taking into account the lessons learned from this CO2 natural reservoir. This methodology comprises several phases of study, including the geological and structural characterisation of the site and its components (water, rock and gases), the identification of the analogies between a CO2 storage natural system and a conceptual model of a CO2-DGS, and the implications regarding the behaviour and safety of a CO2-DGS.

A supervised cooperative learning system for early detection of language disorders

The Quality of Life of a person may depend on early attention to his neurodevel-opment disorders in childhood. Identification of language disorders under the age of six years old can speed up required diagnosis and/or treatment processes. This paper details the enhancement of a Clinical Decision Support System (CDSS) aimed to assist pediatricians and language therapists at early identification and re-ferral of language disorders. The system helps to fine tune the Knowledge Base of Language Delays (KBLD) that was already developed and validated in clinical routine with 146 children. Medical experts supported the construction of Gades CDSS by getting scientific consensus from literature and fifteen years of regis-tered use cases of children with language disorders. The current research focuses on an innovative cooperative model that allows the evolution of the KBLD of Gades through the supervised evaluation of the CDSS learnings with experts¿ feedback. The deployment of the resulting system is being assessed under a mul-tidisciplinary team of seven experts from the fields of speech therapist, neonatol-ogy, pediatrics, and neurology.

Evaluating a web-based clinical decision support system for language disorders screening in a nursery school

Background: Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. Objective: This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of early diagnosis of language disorders led us to deploy an easy-to-use CDSS in order to evaluate its accuracy in early detection of language pathologies. This CDSS can be used by pediatricians to support the screening of language disorders in primary care. Methods: This paper details the evaluation results of the ?Gades? CDSS at a nursery school with 146 children, 12 educators, and 1 language therapist. The methodology embraces two consecutive phases. The first stage involves the observation of each child?s language abilities, carried out by the educators, to facilitate the evaluation of language acquisition level performed by a language therapist. Next, the same language therapist evaluates the reliability of the observed results. Results: The Gades CDSS was integrated to provide the language therapist with the required clinical information. The validation process showed a global 83.6% (122/146) success rate in language evaluation and a 7% (7/94) rate of non-accepted system decisions within the range of children from 0 to 3 years old. The system helped language therapists to identify new children with potential disorders who required further evaluation. This process will revalidate the CDSS output and allow the enhancement of early detection of language disorders in children. The system does need minor refinement, since the therapists disagreed with some questions from the CDSS knowledge base (KB) and suggested adding a few questions about speech production and pragmatic abilities. The refinement of the KB will address these issues and include the requested improvements, with the support of the experts who took part in the original KB development. Conclusions: This research demonstrated the benefit of a Web-based CDSS to monitor children?s neurodevelopment via the early detection of language delays at a nursery school. Current next steps focus on the design of a model that includes pseudo auto-learning capacity, supervised by experts.

A proposal for an Internet of Things-based monitoring system composed by low capability, open source and open hardware devices

The Internet of Things makes use of a huge disparity of technologies at very different levels that help one to the other to accomplish goals that were previously regarded as unthinkable in terms of ubiquity or scalability. If the Internet of Things is expected to interconnect every day devices or appliances and enable communications between them, a broad range of new services, applications and products can be foreseen. For example, monitoring is a process where sensors have widespread use for measuring environmental parameters (temperature, light, chemical agents, etc.) but obtaining readings at the exact physical point they want to be obtained from, or about the exact wanted parameter can be a clumsy, time-consuming task that is not easily adaptable to new requirements. In order to tackle this challenge, a proposal on a system used to monitor any conceivable environment, which additionally is able to monitor the status of its own components and heal some of the most usual issues of a Wireless Sensor Network, is presented here in detail, covering all the layers that give it shape in terms of devices, communications or services.

Development of a genre-dependent TTS system with cross-speaker speaking-style transplantation

One of the biggest challenges in speech synthesis is the production of contextually-appropriate naturally sounding synthetic voices. This means that a Text-To-Speech system must be able to analyze a text beyond the sentence limits in order to select, or even modulate, the speaking style according to a broader context. Our current architecture is based on a two-step approach: text genre identification and speaking style synthesis according to the detected discourse genre. For the final implementation, a set of four genres and their corresponding speaking styles were considered: broadcast news, live sport commentaries, interviews and political speeches. In the final TTS evaluation, the four speaking styles were transplanted to the neutral voices of other speakers not included in the training database. When the transplanted styles were compared to the neutral voices, transplantation was significantly preferred and the similarity to the target speaker was as high as 78%.

Contributions to Speech Analytics based on Speech Recognition and Topic Identification

La última década ha sido testigo de importantes avances en el campo de la tecnología de reconocimiento de voz. Los sistemas comerciales existentes actualmente poseen la capacidad de reconocer habla continua de múltiples locutores, consiguiendo valores aceptables de error, y sin la necesidad de realizar procedimientos explícitos de adaptación. A pesar del buen momento que vive esta tecnología, el reconocimiento de voz dista de ser un problema resuelto. La mayoría de estos sistemas de reconocimiento se ajustan a dominios particulares y su eficacia depende de manera significativa, entre otros muchos aspectos, de la similitud que exista entre el modelo de lenguaje utilizado y la tarea específica para la cual se está empleando. Esta dependencia cobra aún más importancia en aquellos escenarios en los cuales las propiedades estadísticas del lenguaje varían a lo largo del tiempo, como por ejemplo, en dominios de aplicación que involucren habla espontánea y múltiples temáticas. En los últimos años se ha evidenciado un constante esfuerzo por mejorar los sistemas de reconocimiento para tales dominios. Esto se ha hecho, entre otros muchos enfoques, a través de técnicas automáticas de adaptación. Estas técnicas son aplicadas a sistemas ya existentes, dado que exportar el sistema a una nueva tarea o dominio puede requerir tiempo a la vez que resultar costoso. Las técnicas de adaptación requieren fuentes adicionales de información, y en este sentido, el lenguaje hablado puede aportar algunas de ellas. El habla no sólo transmite un mensaje, también transmite información acerca del contexto en el cual se desarrolla la comunicación hablada (e.g. acerca del tema sobre el cual se está hablando). Por tanto, cuando nos comunicamos a través del habla, es posible identificar los elementos del lenguaje que caracterizan el contexto, y al mismo tiempo, rastrear los cambios que ocurren en estos elementos a lo largo del tiempo. Esta información podría ser capturada y aprovechada por medio de técnicas de recuperación de información (information retrieval) y de aprendizaje de máquina (machine learning). Esto podría permitirnos, dentro del desarrollo de mejores sistemas automáticos de reconocimiento de voz, mejorar la adaptación de modelos del lenguaje a las condiciones del contexto, y por tanto, robustecer al sistema de reconocimiento en dominios con condiciones variables (tales como variaciones potenciales en el vocabulario, el estilo y la temática). En este sentido, la principal contribución de esta Tesis es la propuesta y evaluación de un marco de contextualización motivado por el análisis temático y basado en la adaptación dinámica y no supervisada de modelos de lenguaje para el robustecimiento de un sistema automático de reconocimiento de voz. Esta adaptación toma como base distintos enfoque de los sistemas mencionados (de recuperación de información y aprendizaje de máquina) mediante los cuales buscamos identificar las temáticas sobre las cuales se está hablando en una grabación de audio. Dicha identificación, por lo tanto, permite realizar una adaptación del modelo de lenguaje de acuerdo a las condiciones del contexto. El marco de contextualización propuesto se puede dividir en dos sistemas principales: un sistema de identificación de temática y un sistema de adaptación dinámica de modelos de lenguaje. Esta Tesis puede describirse en detalle desde la perspectiva de las contribuciones particulares realizadas en cada uno de los campos que componen el marco propuesto: _ En lo referente al sistema de identificación de temática, nos hemos enfocado en aportar mejoras a las técnicas de pre-procesamiento de documentos, asimismo en contribuir a la definición de criterios más robustos para la selección de index-terms. – La eficiencia de los sistemas basados tanto en técnicas de recuperación de información como en técnicas de aprendizaje de máquina, y específicamente de aquellos sistemas que particularizan en la tarea de identificación de temática, depende, en gran medida, de los mecanismos de preprocesamiento que se aplican a los documentos. Entre las múltiples operaciones que hacen parte de un esquema de preprocesamiento, la selección adecuada de los términos de indexado (index-terms) es crucial para establecer relaciones semánticas y conceptuales entre los términos y los documentos. Este proceso también puede verse afectado, o bien por una mala elección de stopwords, o bien por la falta de precisión en la definición de reglas de lematización. En este sentido, en este trabajo comparamos y evaluamos diferentes criterios para el preprocesamiento de los documentos, así como también distintas estrategias para la selección de los index-terms. Esto nos permite no sólo reducir el tamaño de la estructura de indexación, sino también mejorar el proceso de identificación de temática. – Uno de los aspectos más importantes en cuanto al rendimiento de los sistemas de identificación de temática es la asignación de diferentes pesos a los términos de acuerdo a su contribución al contenido del documento. En este trabajo evaluamos y proponemos enfoques alternativos a los esquemas tradicionales de ponderado de términos (tales como tf-idf ) que nos permitan mejorar la especificidad de los términos, así como también discriminar mejor las temáticas de los documentos. _ Respecto a la adaptación dinámica de modelos de lenguaje, hemos dividimos el proceso de contextualización en varios pasos. – Para la generación de modelos de lenguaje basados en temática, proponemos dos tipos de enfoques: un enfoque supervisado y un enfoque no supervisado. En el primero de ellos nos basamos en las etiquetas de temática que originalmente acompañan a los documentos del corpus que empleamos. A partir de estas, agrupamos los documentos que forman parte de la misma temática y generamos modelos de lenguaje a partir de dichos grupos. Sin embargo, uno de los objetivos que se persigue en esta Tesis es evaluar si el uso de estas etiquetas para la generación de modelos es óptimo en términos del rendimiento del reconocedor. Por esta razón, nosotros proponemos un segundo enfoque, un enfoque no supervisado, en el cual el objetivo es agrupar, automáticamente, los documentos en clusters temáticos, basándonos en la similaridad semántica existente entre los documentos. Por medio de enfoques de agrupamiento conseguimos mejorar la cohesión conceptual y semántica en cada uno de los clusters, lo que a su vez nos permitió refinar los modelos de lenguaje basados en temática y mejorar el rendimiento del sistema de reconocimiento. – Desarrollamos diversas estrategias para generar un modelo de lenguaje dependiente del contexto. Nuestro objetivo es que este modelo refleje el contexto semántico del habla, i.e. las temáticas más relevantes que se están discutiendo. Este modelo es generado por medio de la interpolación lineal entre aquellos modelos de lenguaje basados en temática que estén relacionados con las temáticas más relevantes. La estimación de los pesos de interpolación está basada principalmente en el resultado del proceso de identificación de temática. – Finalmente, proponemos una metodología para la adaptación dinámica de un modelo de lenguaje general. El proceso de adaptación tiene en cuenta no sólo al modelo dependiente del contexto sino también a la información entregada por el proceso de identificación de temática. El esquema usado para la adaptación es una interpolación lineal entre el modelo general y el modelo dependiente de contexto. Estudiamos también diferentes enfoques para determinar los pesos de interpolación entre ambos modelos. Una vez definida la base teórica de nuestro marco de contextualización, proponemos su aplicación dentro de un sistema automático de reconocimiento de voz. Para esto, nos enfocamos en dos aspectos: la contextualización de los modelos de lenguaje empleados por el sistema y la incorporación de información semántica en el proceso de adaptación basado en temática. En esta Tesis proponemos un marco experimental basado en una arquitectura de reconocimiento en ‘dos etapas’. En la primera etapa, empleamos sistemas basados en técnicas de recuperación de información y aprendizaje de máquina para identificar las temáticas sobre las cuales se habla en una transcripción de un segmento de audio. Esta transcripción es generada por el sistema de reconocimiento empleando un modelo de lenguaje general. De acuerdo con la relevancia de las temáticas que han sido identificadas, se lleva a cabo la adaptación dinámica del modelo de lenguaje. En la segunda etapa de la arquitectura de reconocimiento, usamos este modelo adaptado para realizar de nuevo el reconocimiento del segmento de audio. Para determinar los beneficios del marco de trabajo propuesto, llevamos a cabo la evaluación de cada uno de los sistemas principales previamente mencionados. Esta evaluación es realizada sobre discursos en el dominio de la política usando la base de datos EPPS (European Parliamentary Plenary Sessions - Sesiones Plenarias del Parlamento Europeo) del proyecto europeo TC-STAR. Analizamos distintas métricas acerca del rendimiento de los sistemas y evaluamos las mejoras propuestas con respecto a los sistemas de referencia. ABSTRACT The last decade has witnessed major advances in speech recognition technology. Today’s commercial systems are able to recognize continuous speech from numerous speakers, with acceptable levels of error and without the need for an explicit adaptation procedure. Despite this progress, speech recognition is far from being a solved problem. Most of these systems are adjusted to a particular domain and their efficacy depends significantly, among many other aspects, on the similarity between the language model used and the task that is being addressed. This dependence is even more important in scenarios where the statistical properties of the language fluctuates throughout the time, for example, in application domains involving spontaneous and multitopic speech. Over the last years there has been an increasing effort in enhancing the speech recognition systems for such domains. This has been done, among other approaches, by means of techniques of automatic adaptation. These techniques are applied to the existing systems, specially since exporting the system to a new task or domain may be both time-consuming and expensive. Adaptation techniques require additional sources of information, and the spoken language could provide some of them. It must be considered that speech not only conveys a message, it also provides information on the context in which the spoken communication takes place (e.g. on the subject on which it is being talked about). Therefore, when we communicate through speech, it could be feasible to identify the elements of the language that characterize the context, and at the same time, to track the changes that occur in those elements over time. This information can be extracted and exploited through techniques of information retrieval and machine learning. This allows us, within the development of more robust speech recognition systems, to enhance the adaptation of language models to the conditions of the context, thus strengthening the recognition system for domains under changing conditions (such as potential variations in vocabulary, style and topic). In this sense, the main contribution of this Thesis is the proposal and evaluation of a framework of topic-motivated contextualization based on the dynamic and non-supervised adaptation of language models for the enhancement of an automatic speech recognition system. This adaptation is based on an combined approach (from the perspective of both information retrieval and machine learning fields) whereby we identify the topics that are being discussed in an audio recording. The topic identification, therefore, enables the system to perform an adaptation of the language model according to the contextual conditions. The proposed framework can be divided in two major systems: a topic identification system and a dynamic language model adaptation system. This Thesis can be outlined from the perspective of the particular contributions made in each of the fields that composes the proposed framework: _ Regarding the topic identification system, we have focused on the enhancement of the document preprocessing techniques in addition to contributing in the definition of more robust criteria for the selection of index-terms. – Within both information retrieval and machine learning based approaches, the efficiency of topic identification systems, depends, to a large extent, on the mechanisms of preprocessing applied to the documents. Among the many operations that encloses the preprocessing procedures, an adequate selection of index-terms is critical to establish conceptual and semantic relationships between terms and documents. This process might also be weakened by a poor choice of stopwords or lack of precision in defining stemming rules. In this regard we compare and evaluate different criteria for preprocessing the documents, as well as for improving the selection of the index-terms. This allows us to not only reduce the size of the indexing structure but also to strengthen the topic identification process. – One of the most crucial aspects, in relation to the performance of topic identification systems, is to assign different weights to different terms depending on their contribution to the content of the document. In this sense we evaluate and propose alternative approaches to traditional weighting schemes (such as tf-idf ) that allow us to improve the specificity of terms, and to better identify the topics that are related to documents. _ Regarding the dynamic language model adaptation, we divide the contextualization process into different steps. – We propose supervised and unsupervised approaches for the generation of topic-based language models. The first of them is intended to generate topic-based language models by grouping the documents, in the training set, according to the original topic labels of the corpus. Nevertheless, a goal of this Thesis is to evaluate whether or not the use of these labels to generate language models is optimal in terms of recognition accuracy. For this reason, we propose a second approach, an unsupervised one, in which the objective is to group the data in the training set into automatic topic clusters based on the semantic similarity between the documents. By means of clustering approaches we expect to obtain a more cohesive association of the documents that are related by similar concepts, thus improving the coverage of the topic-based language models and enhancing the performance of the recognition system. – We develop various strategies in order to create a context-dependent language model. Our aim is that this model reflects the semantic context of the current utterance, i.e. the most relevant topics that are being discussed. This model is generated by means of a linear interpolation between the topic-based language models related to the most relevant topics. The estimation of the interpolation weights is based mainly on the outcome of the topic identification process. – Finally, we propose a methodology for the dynamic adaptation of a background language model. The adaptation process takes into account the context-dependent model as well as the information provided by the topic identification process. The scheme used for the adaptation is a linear interpolation between the background model and the context-dependent one. We also study different approaches to determine the interpolation weights used in this adaptation scheme. Once we defined the basis of our topic-motivated contextualization framework, we propose its application into an automatic speech recognition system. We focus on two aspects: the contextualization of the language models used by the system, and the incorporation of semantic-related information into a topic-based adaptation process. To achieve this, we propose an experimental framework based in ‘a two stages’ recognition architecture. In the first stage of the architecture, Information Retrieval and Machine Learning techniques are used to identify the topics in a transcription of an audio segment. This transcription is generated by the recognition system using a background language model. According to the confidence on the topics that have been identified, the dynamic language model adaptation is carried out. In the second stage of the recognition architecture, an adapted language model is used to re-decode the utterance. To test the benefits of the proposed framework, we carry out the evaluation of each of the major systems aforementioned. The evaluation is conducted on speeches of political domain using the EPPS (European Parliamentary Plenary Sessions) database from the European TC-STAR project. We analyse several performance metrics that allow us to compare the improvements of the proposed systems against the baseline ones.

Development and improvement of protection-system algorithms for ground-fault detection and location in synchronous machines

Uno de los defectos más frecuentes en los generadores síncronos son los defectos a tierra tanto en el devanado estatórico, como de excitación. Se produce un defecto cuando el aislamiento eléctrico entre las partes activas de cualquiera de estos devanados y tierra se reduce considerablemente o desaparece. La detección de los defectos a tierra en ambos devanados es un tema ampliamente estudiado a nivel industrial. Tras la detección y confirmación de la existencia del defecto, dicha falta debe ser localizada a lo largo del devanado para su reparación, para lo que habitualmente el rotor debe ser extraído del estator. Esta operación resulta especialmente compleja y cara. Además, el hecho de limitar la corriente de defecto en ambos devanados provoca que el defecto no sea localizable visualmente, pues apenas existe daño en el generador. Por ello, se deben aplicar técnicas muy laboriosas para localizar exactamente el defecto y poder así reparar el devanado. De cara a reducir el tiempo de reparación, y con ello el tiempo en que el generador esta fuera de servicio, cualquier información por parte del relé de protección acerca de la localización del defecto resultaría de gran utilidad. El principal objetivo de esta tesis doctoral ha sido el desarrollo de nuevos algoritmos que permitan la estimación de la localización de los defectos a tierra tanto en el devanado rotórico como estatórico de máquinas síncronas. Respecto al devanado de excitación, se ha presentado un nuevo método de localización de defectos a tierra para generadores con excitación estática. Este método permite incluso distinguir si el defecto se ha producido en el devanado de excitación, o en cualquiera de los componentes del sistema de excitación, esto es, transformador de excitación, conductores de alimentación del rectificador controlado, etc. En caso de defecto a tierra en del devanado rotórico, este método proporciona una estimación de su localización. Sin embargo, para poder obtener la localización del defecto, se precisa conocer el valor de resistencia de defecto. Por ello, en este trabajo se presenta además un nuevo método para la estimación de este parámetro de forma precisa. Finalmente, se presenta un nuevo método de detección de defectos a tierra, basado en el criterio direccional, que complementa el método de localización, permitiendo tener en cuenta la influencia de las capacidades a tierra del sistema. Estas capacidades resultan determinantes a la hora de localizar el defecto de forma adecuada. En relación con el devanado estatórico, en esta tesis doctoral se presenta un nuevo algoritmo de localización de defectos a tierra para generadores que dispongan de la protección de faltas a tierra basada en la inyección de baja frecuencia. Se ha propuesto un método general, que tiene en cuenta todos los parámetros del sistema, así como una versión simplificada del método para generadores con capacidades a tierra muy reducida, que podría resultar de fácil implementación en relés de protección comercial. Los algoritmos y métodos presentados se han validado mediante ensayos experimentales en un generador de laboratorio de 5 kVA, así como en un generador comercial de 106 MVA con resultados satisfactorios y prometedores. ABSTRACT One of the most common faults in synchronous generators is the ground fault in both the stator winding and the excitation winding. In case of fault, the insulation level between the active part of any of these windings and ground lowers considerably, or even disappears. The detection of ground faults in both windings is a very researched topic. The fault current is typically limited intentionally to a reduced level. This allows to detect easily the ground faults, and therefore to avoid damage in the generator. After the detection and confirmation of the existence of a ground fault, it should be located along the winding in order to repair of the machine. Then, the rotor has to be extracted, which is a very complex and expensive operation. Moreover, the fact of limiting the fault current makes that the insulation failure is not visually detectable, because there is no visible damage in the generator. Therefore, some laborious techniques have to apply to locate accurately the fault. In order to reduce the repair time, and therefore the time that the generator is out of service, any information about the approximate location of the fault would be very useful. The main objective of this doctoral thesis has been the development of new algorithms and methods to estimate the location of ground faults in the stator and in the rotor winding of synchronous generators. Regarding the excitation winding, a new location method of ground faults in excitation winding of synchronous machines with static excitation has been presented. This method allows even to detect if the fault is at the excitation winding, or in any other component of the excitation system: controlled rectifier, excitation transformer, etc. In case of ground fault in the rotor winding, this method provides an estimation of the fault location. However, in order to calculate the location, the value of fault resistance is necessary. Therefore, a new fault-resistance estimation algorithm is presented in this text. Finally, a new fault detection algorithm based on directional criterion is described to complement the fault location method. This algorithm takes into account the influence of the capacitance-to-ground of the system, which has a remarkable impact in the accuracy of the fault location. Regarding the stator winding, a new fault-location algorithm has been presented for stator winding of synchronous generators. This algorithm is applicable to generators with ground-fault protection based in low-frequency injection. A general algorithm, which takes every parameter of the system into account, has been presented. Moreover, a simplified version of the algorithm has been proposed for generators with especially low value of capacitance to ground. This simplified algorithm might be easily implementable in protective relays. The proposed methods and algorithms have been tested in a 5 kVA laboratory generator, as well as in a 106 MVA synchronous generator with satisfactory and promising results.

A procedure to track vibration modes under changing external factors: application to a pedestrian bridge

A low-cost vibration monitoring system has been developed and installed on an urban steel- plated stress-ribbon footbridge. The system continuously measures: the acceleration (using 18 triaxial MEMS accelerometers distributed along the structure), the ambient temperature and the wind velocity and direction. Automated output-only modal parameter estimation based on the Stochastic Subspace Identification (SSI) is carried out in order to extract the modal parameters, i.e., the natural frequencies, damping ratios and modal shapes. Thus, this paper analyzes the time evolution of the modal parameters over a whole-year data monitoring. Firstly, for similar environmental/operational factors, the uncertainties associated to the time window size used are studied and quantified. Secondly, a methodology to track the vibration modes has been established since several of them with closely-spaced natural frequencies are identified. Thirdly, the modal parameters have been correlated against external factors. It has been shown that this stress-ribbon structure is highly sensitive to temperature variation (frequency changes of more than 20%) with strongly seasonal and daily trends

A Novel Ground Fault Identification Method for 2 x 5 kV Railway Power Supply Systems

The location of ground faults in railway electric lines in 2 × 5 kV railway power supply systems is a difficult task. In both 1 × 25 kV and transmission power systems it is common practice to use distance protection relays to clear ground faults and localize their positions. However, in the particular case of this 2 × 25 kV system, due to the widespread use of autotransformers, the relation between the distance and the impedance seen by the distance protection relays is not linear and therefore the location is not accurate enough. This paper presents a simple and economical method to identify the subsection between autotransformers and the conductor (catenary or feeder) where the ground fault is happening. This method is based on the comparison of the angle between the current and the voltage of the positive terminal in each autotransformer. Consequently, after the identification of the subsection and the conductor with the ground defect, only the subsection where the ground fault is present will be quickly removed from service, with the minimum effect on rail traffic. This method has been validated through computer simulations and laboratory tests with positive results.

A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters

On-line partial discharge (PD) measurements have become a common technique for assessing the insulation condition of installed high voltage (HV) insulated cables. When on-line tests are performed in noisy environments, or when more than one source of pulse-shaped signals are present in a cable system, it is difficult to perform accurate diagnoses. In these cases, an adequate selection of the non-conventional measuring technique and the implementation of effective signal processing tools are essential for a correct evaluation of the insulation degradation. Once a specific noise rejection filter is applied, many signals can be identified as potential PD pulses, therefore, a classification tool to discriminate the PD sources involved is required. This paper proposes an efficient method for the classification of PD signals and pulse-type noise interferences measured in power cables with HFCT sensors. By using a signal feature generation algorithm, representative parameters associated to the waveform of each pulse acquired are calculated so that they can be separated in different clusters. The efficiency of the clustering technique proposed is demonstrated through an example with three different PD sources and several pulse-shaped interferences measured simultaneously in a cable system with a high frequency current transformer (HFCT).