Desing and development of a robotic platform for the evaluation of search algorithms

Plant diseases represent a major economic and environmental problem in agriculture and forestry. Upon infection, a plant develops symptoms that affect different parts of the plant causing a significant agronomic impact. As many such diseases spread in time over the whole crop, a system for early disease detection can aid to mitigate the losses produced by the plant diseases and can further prevent their spread [1]. In recent years, several mathematical algorithms of search have been proposed [2,3] that could be used as a non-invasive, fast, reliable and cost-effective methods to localize in space infectious focus by detecting changes in the profile of volatile organic compounds. Tracking scents and locating odor sources is a major challenge in robotics, on one hand because odour plumes consists of non-uniform intermittent odour patches dispersed by the wind and on the other hand because of the lack of precise and reliable odour sensors. Notwithstanding, we have develop a simple robotic platform to study the robustness and effectiveness of different search algorithms [4], with respect to specific problems to be found in their further application in agriculture, namely errors committed in the motion and sensing and to the existence of spatial constraints due to land topology or the presence of obstacles.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

iCarer Project: Intelligent Care Guidance and Learning Services Platform for Informal Carers of the Elderly

The increasing ageing population is demanding new care approaches to maintain the quality of life of elderly people. Informal carers are becoming crucial agents in the care and support of elderly people, which can lead to those carers suffering from additional stress due to competing priorities with employment or due to lack of knowledge about elderly people?s care needs. Thus, support and stress relief in carers should be a key issue in the home-care process of these older adults. Considering this context, this work presents the iCarer project aimed at developing a personalized and adaptive platform to offer informal carers support by means of monitoring their activities of daily care and psychological state, as well as providing an orientation to help them improve the care provided. Additionally, iCarer will provide e-Learning services and an informal carers learning network. As a result, carers will be able to expand their knowledge, supported by the experience provided by expert counsellors and fellow carers. Additionally, the coordination between formal and informal carers will be improved, offering the informal carers flexibility to organize and combine their assistance and social activities.

Global research alliance modelling platform (GRAMP): an open web platform for modelling greenhouse gas emissions from agro-ecosystems

Carbon (C) and nitrogen (N) process-based models are important tools for estimating and reporting greenhouse gas emissions and changes in soil C stocks. There is a need for continuous evaluation, development and adaptation of these models to improve scientific understanding, national inventories and assessment of mitigation options across the world. To date, much of the information needed to describe different processes like transpiration, photosynthesis, plant growth and maintenance, above and below ground carbon dynamics, decomposition and nitrogen mineralization. In ecosystem models remains inaccessible to the wider community, being stored within model computer source code, or held internally by modelling teams. Here we describe the Global Research Alliance Modelling Platform (GRAMP), a web-based modelling platform to link researchers with appropriate datasets, models and training material. It will provide access to model source code and an interactive platform for researchers to form a consensus on existing methods, and to synthesize new ideas, which will help to advance progress in this area. The platform will eventually support a variety of models, but to trial the platform and test the architecture and functionality, it was piloted with variants of the DNDC model. The intention is to form a worldwide collaborative network (a virtual laboratory) via an interactive website with access to models and best practice guidelines; appropriate datasets for testing, calibrating and evaluating models; on-line tutorials and links to modelling and data provider research groups, and their associated publications. A graphical user interface has been designed to view the model development tree and access all of the above functions.

Advanced data acquisition system implementation for the ITER Neutron Diagnostic use case using EPICS and FlexRIO technology on a PXIe platform

In the framework of the ITER Control Breakdown Structure (CBS), Plant System Instrumentation & Control (I&C) defines the hardware and software required to control one or more plant systems [1]. For diagnostics, most of the complex Plant System I&C are to be delivered by ITER Domestic Agencies (DAs). As an example for the DAs, ITER Organization (IO) has developed several use cases for diagnostics Plant System I&C that fully comply with guidelines presented in the Plant Control Design Handbook (PCDH) [2]. One such use case is for neutron diagnostics, specifically the Fission Chamber (FC), which is responsible for delivering time-resolved measurements of neutron source strength and fusion power to aid in assessing the functional performance of ITER [3]. ITER will deploy four Fission Chamber units, each consisting of three individual FC detectors. Two of these detectors contain Uranium 235 for Neutron detection, while a third "dummy" detector will provide gamma and noise detection. The neutron flux from each MFC is measured by the three methods: . Counting Mode: measures the number of individual pulses and their location in the record. Pulse parameters (threshold and width) are user configurable. . Campbelling Mode (Mean Square Voltage): measures the RMS deviation in signal amplitude from its average value. .Current Mode: integrates the signal amplitude over the measurement period

Virtual science hub: an open source platform to enrich science teaching

This paper presents the Virtual Science Hub platform. It is an open source platform that combines a social network, an e-learning authoring tool, a videoconference service and a learning object repository for science teaching enrichment. These four main functionalities fit very well together. The platform was released in April 2012 and since then it has not stopped growing. Finally we present the results of the surveys conducted and the statistics gathered to validate this approach.

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.

Conceptual design of offshore platform supply vessel based on hybrid diesel generator-fuel cell power plant

Nowadays increasing fuel prices and upcoming pollutant emission regulations are becoming a growing concern for the shipping industry worldwide. While fuel prices will keep rising in future years, the new International Convention for the Prevention of Pollution from Ships (MARPOL) and Sulphur Emissions Control Areas (SECA) regulations will forbid ships to use heavy fuel oils at certain situations. To fulfil with these regulations, the next step in the marine shipping business will comprise the use of cleaner fuels on board as well as developing new propulsion concept. In this work a new conceptual marine propulsion system is developed, based on the integration of diesel generators with fuel cells in a 2850 metric tonne of deadweight platform supply vessel. The efficiency of the two 250 kW methanol-fed Solid Oxide Fuel Cell (SOFC) system installed on board combined with the hydro dynamically optimized design of the hull of the ship will allow the ship to successfully operate at certain modes of operation while notably reduce the pollutant emissions to the atmosphere. Besides the cogeneration heat obtained from the fuel cell system will be used to answer different heating needs on board the vessel

A flexible open source web platform to facilitate Learning Object evaluation

Systematic evaluation of Learning Objects is essential to make high quality Web-based education possible. For this reason, several educational repositories and e-Learning systems have developed their own evaluation models and tools. However, the differences of the context in which Learning Objects are produced and consumed suggest that no single evaluation model is sufficient for all scenarios. Besides, no much effort has been put in developing open tools to facilitate Learning Object evaluation and use the quality information for the benefit of end users. This paper presents LOEP, an open source web platform that aims to facilitate Learning Object evaluation in different scenarios and educational settings by supporting and integrating several evaluation models and quality metrics. The work exposed in this paper shows that LOEP is capable of providing Learning Object evaluation to e-Learning systems in an open, low cost, reliable and effective way. Possible scenarios where LOEP could be used to implement quality control policies and to enhance search engines are also described. Finally, we report the results of a survey conducted among reviewers that used LOEP, showing that they perceived LOEP as a powerful and easy to use tool for evaluating Learning Objects.

The usefulness of Usability and User Experience evaluation methods on an e-Learning platform development from a developer's perspective: A case study

The development of a web platform is a complex and interdisciplinary task, where people with different roles such as project manager, designer or developer participate. Different usability and User Experience evaluation methods can be used in each stage of the development life cycle, but not all of them have the same influence in the software development and in the final product or system. This article presents the study of the impact of these methods applied in the context of an e-Learning platform development. The results show that the impact has been strong from a developer's perspective. Developer team members considered that usability and User Experience evaluation allowed them mainly to identify design mistakes, improve the platform's usability and understand the end users and their needs in a better way. Interviews with potential users, clickmaps and scrollmaps were rated as the most useful methods. Finally, these methods were considered unanimously very useful in the context of the entire software development, only comparable to SCRUM meetings and overcoming the rest of involved factors.

Data consistency management in an open smart home management platform

In this paper, the authors introduce a novel mechanism for data management in a middleware for smart home control, where a relational database and semantic ontology storage are used at the same time in a Data Warehouse. An annotation system has been designed for instructing the storage format and location, registering new ontology concepts and most importantly, guaranteeing the Data Consistency between the two storage methods. For easing the data persistence process, the Data Access Object (DAO) pattern is applied and optimized to enhance the Data Consistency assurance. Finally, this novel mechanism provides an easy manner for the development of applications and their integration with BATMP. Finally, an application named "Parameter Monitoring Service" is given as an example for assessing the feasibility of the system.

A Linked Data Platform adapter for the Bugzilla issue tracker

The W3C Linked Data Platform (LDP) specification defines a standard HTTP-based protocol for read/write Linked Data and pro- vides the basis for application integration using Linked Data. This paper presents an LDP adapter for the Bugzilla issue tracker and demonstrates how to use the LDP protocol to expose a traditional application as a read/write Linked Data application. This approach provides a exible LDP adoption strategy with minimal changes to existing applications.

morph-LDP: an R2RML-based Linked Data Platform implementation

The W3C Linked Data Platform (LDP) candidate recom- mendation defines a standard HTTP-based protocol for read/write Linked Data. The W3C R2RML recommendation defines a language to map re- lational databases (RDBs) and RDF. This paper presents morph-LDP, a novel system that combines these two W3C standardization initiatives to expose relational data as read/write Linked Data for LDP-aware ap- plications, whilst allowing legacy applications to continue using their relational databases.

A case study on cross-platform development frameworks for mobile applications and UX

Cross-platform development frameworks for mobile applications promise important advantages in cost cuttings and easy maintenance, posing as a very good option for organizations interested in the design of mobile applications for several platforms. Given that platform conventions are especially important for the User eXperience (UX) of mobile applications, the usage of a framework where the same code defines the behavior of the app in different platforms could have a negative impact in the UX. This paper describes a study where two independent teams have designed two different versions of a mobile application, one using a framework that generates Android and iOS versions automatically, and another team using native tools. The alternative versions for each platform have been evaluated with 37 users with a combination of a laboratory usability test and a longitudinal study. The results show that differences are minimal in the Android platform, but in iOS, even if a reasonably good UX can be obtained with the usage of this framework by an UX-conscious design team, a higher level of UX can be obtained directly developing with a native tool.

p-medicine: a medical informatics platform for integrated large scale heterogeneous patient data

Secure access to patient data is becoming of increasing importance, as medical informatics grows in significance, to both assist with population health studies, and patient specific medicine in support of treatment. However, assembling the many different types of data emanating from the clinic is in itself a difficulty, and doing so across national borders compounds the problem. In this paper we present our solution: an easy to use distributed informatics platform embedding a state of the art data warehouse incorporating a secure pseudonymisation system protecting access to personal healthcare data. Using this system, a whole range of patient derived data, from genomics to imaging to clinical records, can be assembled and linked, and then connected with analytics tools that help us to understand the data. Research performed in this environment will have immediate clinical impact for personalised patient healthcare.