980 resultados para Supporting data


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Many recent studies have found genetically differentiated populations in microorganisms despite potentially high dispersal. We designed a study to specifically examine the importance of physical dispersal barriers, i.e. geographic distance and lack of hydrological connectivity, in restricting gene flow and enhancing divergence in limnic microorganisms. We focused on the nuisance microalga Gonyostomum semen, which has recently expanded in northern Europe and differentiated into genetically distinct populations. Gonyostomum semen was sampled from six lakes distributed in two adjacent watersheds, which thereby comprised, both connected and non-connected lakes. The individual isolates were genotyped by Amplified Fragment Length Polymorphism. Several lake populations were differentiated from each other, but connectivity within watersheds could not explain the observed population genetic pattern. However, isolation by distance was moderate and might limit the gene flow among distant populations. In addition, we found low, but significant linkage disequilibrium, which indicates regular sexual recombination in this species, despite its high degree of asexual reproduction. Therefore, we conclude that the genetic properties of microalgae with occasional sexual reproduction essentially mirror regularly recombining species. Furthermore, the data indicated bottlenecks supporting the hypothesized recent range expansion of this species.

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Increasing amounts of data is collected in most areas of research and application. The degree to which this data can be accessed, analyzed, and retrieved, is a decisive in obtaining progress in fields such as scientific research or industrial production. We present a novel methodology supporting content-based retrieval and exploratory search in repositories of multivariate research data. In particular, our methods are able to describe two-dimensional functional dependencies in research data, e.g. the relationship between ination and unemployment in economics. Our basic idea is to use feature vectors based on the goodness-of-fit of a set of regression models to describe the data mathematically. We denote this approach Regressional Features and use it for content-based search and, since our approach motivates an intuitive definition of interestingness, for exploring the most interesting data. We apply our method on considerable real-world research datasets, showing the usefulness of our approach for user-centered access to research data in a Digital Library system.

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The Web has witnessed an enormous growth in the amount of semantic information published in recent years. This growth has been stimulated to a large extent by the emergence of Linked Data. Although this brings us a big step closer to the vision of a Semantic Web, it also raises new issues such as the need for dealing with information expressed in different natural languages. Indeed, although the Web of Data can contain any kind of information in any language, it still lacks explicit mechanisms to automatically reconcile such information when it is expressed in different languages. This leads to situations in which data expressed in a certain language is not easily accessible to speakers of other languages. The Web of Data shows the potential for being extended to a truly multilingual web as vocabularies and data can be published in a language-independent fashion, while associated language-dependent (linguistic) information supporting the access across languages can be stored separately. In this sense, the multilingual Web of Data can be realized in our view as a layer of services and resources on top of the existing Linked Data infrastructure adding i) linguistic information for data and vocabularies in different languages, ii) mappings between data with labels in different languages, and iii) services to dynamically access and traverse Linked Data across different languages. In this article we present this vision of a multilingual Web of Data. We discuss challenges that need to be addressed to make this vision come true and discuss the role that techniques such as ontology localization, ontology mapping, and cross-lingual ontology-based information access and presentation will play in achieving this. Further, we propose an initial architecture and describe a roadmap that can provide a basis for the implementation of this vision.

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World Health Organization actively stresses the importance of health, nutrition and well-being of the mother to foster children development. This issue is critical in the rural areas of developing countries where monitoring of health status of children is hardly performed since population suffers from a lack of access to health care. The aim of this research is to design, implement and deploy an e-health information and communication system to support health care in 26 rural communities of Cusmapa, Nicaragua. The final solution consists of an hybrid WiMAX/WiFi architecture that provides good quality communications through VoIP taking advantage of low cost WiFi mobile devices. Thus, a WiMAX base station was installed in the health center to provide a radio link with the rural health post "El Carrizo" sited 7,4 km. in line of sight. This service makes possible personal broadband voice and data communication facilities with the health center based on WiFi enabled devices such as laptops and cellular phones without communications cost. A free software PBX was installed at "San José de Cusmapa" health care site to enable communications for physicians, nurses and a technician through mobile telephones with IEEE 802.11 b/g protocol and SIP provided by the project. Additionally, the rural health post staff (midwives, brigade) received two mobile phones with these same features. In a complementary way, the deployed health information system is ready to analyze the distribution of maternal-child population at risk and the distribution of diseases on a geographical baseline. The system works with four information layers: fertile women, children, people with disabilities and diseases. Thus, authorized staff can obtain reports about prenatal monitoring tasks, status of the communities, malnutrition, and immunization control. Data need to be updated by health care staff in order to timely detect the source of problem to implement measures addressed to alleviate and improve health status population permanently. Ongoing research is focused on a mobile platform that collects and automatically updates in the information system, the height and weight of the children locally gathered in the remote communities. This research is being granted by the program Millennium Rural Communities of the Technical University of Madrid.

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Linked data offers a promising setting to encode, publish and share metadata of resources. As the matter of fact, it is already adopted by data producers such as European Environment Agency, US and some EU Governs, whose first ambition is to share (meta)data making their processes more effective and transparent. Such as an increasing interest and involvement of data providers surely represents a genuine witness of the web of data success, but in a longer perspective, frameworks supporting linked data consumers in their decision making processes will be a compelling need. In this respect, the talk is introducing SSONDE, a framework enabling in detailed comparison, ranking and selection of linked data resources through the analysis of their RDF ontology driven metadata. SSONDE implements an instance similarity especially designed to support in resource selection, namely the process stakeholders engage to choose a set of resources suitable for a given analysis purpose: (i) it deploys an asymmetric similarity assessment to emphasize information about gains and losses the stakeholders get adopting a resource in place of another; (ii) it relies on an explicit formalization of contexts to tailor the similarity assessment with respect to specific user-defined selection goals. The talk aims at providing an insight on SSONDE instance similarity and it will briefly describe some examples of SSONDE deployment in the context of linked data consumption.

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El propósito de este proyecto de fin de Grado es el estudio y desarrollo de una aplicación basada en Android que proporcionará soporte y atención a los servicios de transporte público existentes en Cracovia, Polonia. La principal funcionalidad del sistema será consultar la posición de un determinado autobús o tranvía y mostrar su ubicación con exactitud. Para lograr esto, necesitaremos tres fases de desarrollo. En primer lugar, deberemos implementar un sistema que obtenga las coordenadas geográficas de los vehículos de transporte público en cada instante. A continuación, tendremos que registrar todos estos datos y almacenarlos en una base de datos en un servidor web. Por último, desarrollaremos un sistema cliente que realice consultas a tiempo real sobre estos datos almacenados, obteniendo la posición para una línea determinada y mostrando su ubicación con un marcador en el mapa. Para hacer el seguimiento de los vehículos, sería necesario tener acceso a una API pública que nos proporcionase la posición registrada por los GPS que integran cada uno de ellos. Como esta API no existe actualmente para los servicios de autobús, y para los tranvías es de uso meramente privado, desarrollaremos una segunda aplicación en Android que hará las funciones del lado servidor. En ella podremos elegir mediante una simple interfaz el número de línea y un código específico que identificará a cada vehículo en particular (e.g. podemos tener 6 tranvías recorriendo la red al mismo tiempo para la línea 24). Esta aplicación obtendrá las coordenadas geográficas del teléfono móvil, lo cual incluye latitud, longitud y orientación a través del proveedor GPS. De este modo, podremos realizar una simulación de como el sistema funcionará a tiempo real utilizando la aplicación servidora desde dentro de un tranvía o autobús y, al mismo tiempo, utilizando la aplicación cliente haciendo peticiones para mostrar la información de dicho tranvía. El cliente, además, podrá consultar la ruta de cualquier línea sin necesidad de tener acceso a Internet. Almacenaremos las rutas y paradas de cada línea en la memoria del teléfono móvil utilizando ficheros XML debido al poco espacio que ocupan y a lo útil que resulta poder consultar un trayecto en cualquier momento, independientemente del acceso a la red. El usuario también podrá consultar las tablas de horarios oficiales para cada línea. Aunque en este caso si será necesaria una conexión a Internet debido a que se realizará a través de la web oficial de MPK. Para almacenar todas las coordenadas de cada vehículo en cada instante necesitaremos crear una base de datos en un servidor. Esto se resolverá mediante el uso de MYSQL y PHP. Se enviarán peticiones de tipo GET y POST a los servicios PHP que se encargarán de traducir y realizar la consulta correspondiente a la base de datos MYSQL. Por último, gracias a todos los datos recogidos relativos a la posición de los vehículos de transporte público, podremos realizar algunas tareas de análisis. Comparando la hora exacta a la que los vehículos pasaron por cada parada y la hora a la que deberían haber pasado según los horarios oficiales, podremos descubrir fallos en estos. Seremos capaces de determinar si es un error puntual debido a factores externos (atascos, averías,…) o si por el contrario, es algo que ocurre muy a menudo y se debería corregir el horario oficial. ABSTRACT The aim of this final Project (for University) is to develop an Android application thatwill provide support and feedback to the public transport services in Krakow. The main functionality of the system will be to track the position of a desired bus or tram line, and display its position on the map. To achieve this, we will need 3 stages: the first one will be to implement a system that sends the geographical position of the public transport vehicles, the second one will be to collect this data in a web server, and the last one will be to get the last location registered for the desired line and display it on the map. For tracking the vehicles, we would need to have access to a public API that should be connected with each bus/tram GPS. As this doesn’t exist in Krakow or at least is not available for public use, we will develop a second android application that will do the server side job. We will be able to choose in a simple interface the line number and a code letter to identify each vehicle (e.g. we can have 6 trams that belong to the line number 24 working at the same time). It will take the current mobile geolocation; this includes getting latitude, longitude and bearing from the GPS provider. Thus, we will be able to make a simulation of how the system works in real time by using the server app inside a tram and at the same time, using the client app and making requests to display the information of that tram. The client will also be able to check the path of the desired line without internet access. We will store the path and stops for each line locally in the phone memory using xml files due to the few requirements of available space it needs and the usefulness of checking a path when needed. This app will also offer the functionality of checking the timetable for the line, but in this case, it will link to the official Mpk website, so Internet access will be required. For storing all the coordinates for each vehicle at every moment we will need to create a database on a server. We have decided that the easiest way is to use Mysql and PHP for the deployment of the service. We will send GET and POST requests to the php files and those files will make the according queries to our database. Finally, based on all the collected data, we will be able to get some information about errors in the system of public transport timetables. We will check at what time a line was in each specific stop and compare it with the official timetable to find mistakes of time. We will determine if it is something that happens occasionally and related to external factors (e.g. traffic jams, breakdowns…) or if on the other hand, it is something that happens very often and the public transport timetables should be looked over and corrected.

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We present a framework specially designed to deal with structurally complex data, where all individuals have the same structure, as is the case in many medical domains. A structurally complex individual may be composed of any type of singlevalued or multivalued attributes, including time series, for example. These attributes are structured according to domain-dependent hierarchies. Our aim is to generate reference models of population groups. These models represent the population archetype and are very useful for supporting such important tasks as diagnosis, detecting fraud, analyzing patient evolution, identifying control groups, etc.

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Remote reprogramming capabilities are one of the major concerns in WSN platforms due to the limitations and constraints that low power wireless nodes poses, especially when energy efficiency during the reprogramming process is a critical factor for extending the battery life of the devices. Moreover, WSNs are based on low-rate protocols in which as greater the amount of data is sent, the more the possibility to lose packets during the transmitting process is. In order to overcome these limitations, in this work a novel on-the-fly reprogramming technique for modifying and updating the application running on the wireless sensor nodes is designed and implemented, based on a partial reprogramming mechanism that significantly reduces the size of the files to be downloaded to the nodes, therefore diminishing their power/time consumption. This powerful mechanism also addresses multi-experimental capabilities because it provides the possibility to download, manage, test and debug multiple applications into the wireless nodes, based on a memory map segmentation of the core. Being an on-the-fly reprogramming process, no additional resources to store and download the configuration file are needed.

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Data-related properties of the activities involved in a service composition can be used to facilitate several design-time and run-time adaptation tasks, such as service evolution, distributed enactment, and instance-level adaptation. A number of these properties can be expressed using a notion of sharing. We present an approach for automated inference of data properties based on sharing analysis, which is able to handle service compositions with complex control structures, involving loops and sub-workflows. The properties inferred can include data dependencies, information content, domain-defined attributes, privacy or confidentiality levels, among others. The analysis produces characterizations of the data and the activities in the composition in terms of minimal and maximal sharing, which can then be used to verify compliance of potential adaptation actions, or as supporting information in their generation. This sharing analysis approach can be used both at design time and at run time. In the latter case, the results of analysis can be refined using the composition traces (execution logs) at the point of execution, in order to support run-time adaptation.

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To support the efficient execution of post-genomic multi-centric clinical trials in breast cancer we propose a solution that streamlines the assessment of the eligibility of patients for available trials. The assessment of the eligibility of a patient for a trial requires evaluating whether each eligibility criterion is satisfied and is often a time consuming and manual task. The main focus in the literature has been on proposing different methods for modelling and formalizing the eligibility criteria. However the current adoption of these approaches in clinical care is limited. Less effort has been dedicated to the automatic matching of criteria to the patient data managed in clinical care. We address both aspects and propose a scalable, efficient and pragmatic patient screening solution enabling automatic evaluation of eligibility of patients for a relevant set of trials. This covers the flexible formalization of criteria and of other relevant trial metadata and the efficient management of these representations.

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Real-world experimentation facilities accelerate the development of Future Internet technologies and services, advance the market for smart infrastructures, and increase the effectiveness of business processes through the Internet. The federation of facilities fosters the experimentation and innovation with larger and more powerful environment, increases the number and variety of the offered services and brings forth possibilities for new experimentation scenarios. This paper introduces a management solution for cloud federation that automates service provisioning to the largest possible extent, relieves the developers from time-consuming configuration settings, and caters for real-time information of all information related to the whole lifecycle of the provisioned services. This is achieved by proposing solutions to achieve the seamless deployment of services across the federation and ability of services to span across different infrastructures of the federation, as well as monitoring of the resources and data which can be aggregated with a common structure, offered as an open ecosystem for innovation at the developers' disposal. This solution consists of several federation management tools and components that are part of the work on Cloud Federation conducted within XIFI project to build the federation of cloud infrastructures for the Future Internet Lab (FIWARE Lab). We present the design and implementation of the solution-concerned FIWARE Lab management tools and components that are deployed within a federation of 17 cloud infrastructures distributed across Europe.

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This paper introduces a road map for ICTs (Information and communication technologies) supporting planning, operation and management of energy systems in smart cities. The road map summarises different elements that form energy systems in cities and proposes research and technical development (RTD) and innovation activities for the development and innovation of ICTs for holistic design, planning and operation of energy systems. In addition, synergies with other ICT systems for smart cities are considered. There are four main target groups for the road map: 1) citizen; 2) building sector; 3) energy sector; and 4) municipality level. As an example for enabling active participation of citizens, the road map proposes how ICT can enable citizens? involvement among others into building design. The building sector roadmap proposes how ICTs can support the planning of buildings and renovations in the future, as well as how to manage building energy systems. The energy sector road map focuses on city?s energy systems and their planning and management, including e.g. demand side management, management of different district level energy systems, energy performance validation and management, energy data models, and smarter use of open energy data. Moreover, the municipality level road map proposes among others ICTs for better integration of city systems and city planning enabling maximised energy efficiency. In addition, one road map section suggests development needs related to open energy data, including among others the use of energy data and the development and harmonisation of energy data models. The road map has been assembled in the READY4SmartCities project (funded by EU 7th Framework Programme), which focuses on the energy system at the city level, consisting of centralised energy systems and connections to the national level energy grids, as well as interconnections to the neighbourhood and building level energy systems.

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Semantic interoperability is essential to facilitate efficient collaboration in heterogeneous multi-site healthcare environments. The deployment of a semantic interoperability solution has the potential to enable a wide range of informatics supported applications in clinical care and research both within as ingle healthcare organization and in a network of organizations. At the same time, building and deploying a semantic interoperability solution may require significant effort to carryout data transformation and to harmonize the semantics of the information in the different systems. Our approach to semantic interoperability leverages existing healthcare standards and ontologies, focusing first on specific clinical domains and key applications, and gradually expanding the solution when needed. An important objective of this work is to create a semantic link between clinical research and care environments to enable applications such as streamlining the execution of multi-centric clinical trials, including the identification of eligible patients for the trials. This paper presents an analysis of the suitability of several widely-used medical ontologies in the clinical domain: SNOMED-CT, LOINC, MedDRA, to capture the semantics of the clinical trial eligibility criteria, of the clinical trial data (e.g., Clinical Report Forms), and of the corresponding patient record data that would enable the automatic identification of eligible patients. Next to the coverage provided by the ontologies we evaluate and compare the sizes of the sets of relevant concepts and their relative frequency to estimate the cost of data transformation, of building the necessary semantic mappings, and of extending the solution to new domains. This analysis shows that our approach is both feasible and scalable.