976 resultados para Information Requirements: Data Availability
Resumo:
A management information system (MIS) provides a means for collecting, reporting, and analyzing data from all segments of an organization. Such systems are common in business but rare in libraries. The Houston Academy of Medicine-Texas Medical Center Library developed an MIS that operates on a system of networked IBM PCs and Paradox, a commercial database software package. The data collected in the system include monthly reports, client profile information, and data collected at the time of service requests. The MIS assists with enforcement of library policies, ensures that correct information is recorded, and provides reports for library managers. It also can be used to help answer a variety of ad hoc questions. Future plans call for the development of an MIS that could be adapted to other libraries' needs, and a decision-support interface that would facilitate access to the data contained in the MIS databases.
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Extending phenological records into the past is essential for the understanding of past ecological change and evaluating the effects of climate change on ecosystems. A growing body of historical phenological information is now available for Europe, North America, and Asia. In East Asia, long-term phenological series are still relatively scarce. This study extracted plant phenological observations from old diaries in the period 1834–1962. A spring phenology index (SPI) for the modern period (1963–2009) was defined as the mean flowering time of three shrubs (first flowering of Amygdalus davidiana and Cercis chinensis, 50% of full flowering of Paeonia suffruticosa) according to the data availability. Applying calibrated transfer functions from the modern period to the historical data, we reconstructed a continuous SPI time series across eastern China from 1834 to 2009. In the recent 30 years, the SPI is 2.1–6.3 days earlier than during any other consecutive 30 year period before 1970. A moving linear trend analysis shows that the advancing trend of SPI over the past three decades reaches upward of 4.1 d/decade, which exceeds all previously observed trends in the past 30 year period. In addition, the SPI series correlates significantly with spring (February to April) temperatures in the study area, with an increase in spring temperature of 1°C inducing an earlier SPI by 3.1 days. These shifts of SPI provide important information regarding regional vegetation-climate relationships, and they are helpful to assess long term of climate change impacts on biophysical systems and biodiversity.
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A wide variety of spatial data collection efforts are ongoing throughout local, state and federal agencies, private firms and non-profit organizations. Each effort is established for a different purpose but organizations and individuals often collect and maintain the same or similar information. The United States federal government has undertaken many initiatives such as the National Spatial Data Infrastructure, the National Map and Geospatial One-Stop to reduce duplicative spatial data collection and promote the coordinated use, sharing, and dissemination of spatial data nationwide. A key premise in most of these initiatives is that no national government will be able to gather and maintain more than a small percentage of the geographic data that users want and desire. Thus, national initiatives depend typically on the cooperation of those already gathering spatial data and those using GIs to meet specific needs to help construct and maintain these spatial data infrastructures and geo-libraries for their nations (Onsrud 2001). Some of the impediments to widespread spatial data sharing are well known from directly asking GIs data producers why they are not currently involved in creating datasets that are of common or compatible formats, documenting their datasets in a standardized metadata format or making their datasets more readily available to others through Data Clearinghouses or geo-libraries. The research described in this thesis addresses the impediments to wide-scale spatial data sharing faced by GIs data producers and explores a new conceptual data-sharing approach, the Public Commons for Geospatial Data, that supports user-friendly metadata creation, open access licenses, archival services and documentation of parent lineage of the contributors and value- adders of digital spatial data sets.
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The distribution of seagrass and associated benthic communities on the reef and lagoon of Low Isles, Great Barrier Reef, was mapped between the 29 July and 29 August 1997. For this survey, observers walked or free-dived at survey points positioned approximately 50 m apart along a series of transects. Visual estimates of above-ground seagrass biomass and % cover of each benthos and substrate type were recorded at each survey point. A differential handheld global positioning system (GPS) was used to locate each survey point (accuracy ±3m). A total of 349 benthic survey points were examined. To assist with mapping meadow/habitat type boundaries, an additional 177 field points were assessed and a georeferenced 1:12,000 aerial photograph (26th August 1997) was used as a secondary source of information. Bathymetric data (elevation below Mean Sea Level) measured at each point assessed and from Ellison (1997) supplemented information used to determine boundaries, particularly in the subtidal lagoon. 127.8 ±29.6 hectares was mapped. Seagrass and associated benthic community data was derived by haphazardly placing 3 quadrats (0.25m**2) at each survey point. Seagrass above ground biomass (standing crop, grams dry weight (g DW m**-2)) was determined within each quadrat using a non-destructive visual estimates of biomass technique and the seagrass species present identified. In addition, the cover of all benthos was measured within each of the 3 quadrats using a systematic 5 point method. For each quadrat, frequency of occurrence for each benthic category was converted to a percentage of the total number of points (5 per quadrat). Data are presented as the average of the 3 quadrats at each point. Polygons of discrete seagrass meadow/habitat type boundaries were created using the on-screen digitising functions of ArcGIS (ESRI Inc.), differentiated on the basis of colour, texture, and the geomorphic and geographical context. The resulting seagrass and benthic cover data of each survey point and for each seagrass meadow/habitat type was linked to GPS coordinates, saved as an ArcMap point and polygon shapefile, respectively, and projected to Universal Transverse Mercator WGS84 Zone 55 South.
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The Weddell Gyre plays a crucial role in the regulation of climate by transferring heat into the deep ocean through deep and bottom water mass formation. However, our understanding of Weddell Gyre water mass properties is limited to regions of data availability, primarily along the Prime Meridian. The aim is to provide a dataset of the upper water column properties of the entire Weddell Gyre. Objective mapping was applied to Argo float data in order to produce spatially gridded, time composite maps of temperature and salinity for fixed pressure levels ranging from 50 to 2000 dbar, as well as temperature, salinity and pressure at the level of the sub-surface temperature maximum. While the data are currently too limited to incorporate time into the gridded structure, the data are extensive enough to produce maps of the entire region across three time composite periods (2002-2005, 2006-2009 and 2010-2013), which can be used to determine how representative conclusions drawn from data collected along general RV transect lines are on a gyre scale perspective. The time composite data sets are provided as netCDF files; one for each time period. Mapped fields of conservative temperature, absolute salinity and potential density are provided for 41 vertical pressure levels. The above variables as well as pressure are provided at the level of the sub-surface temperature maximum. Corresponding mapping errors are also included in the netCDF files. Further details are provided in the global attributes, such as the unit variables and structure of the corresponding data array (i.e. latitude x longitude x vertical pressure level). In addition, all files ending in "_potTpSal" provide mapped fields of potential temperature and practical salinity.
Resumo:
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.
Resumo:
The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.
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In just a few years cloud computing has become a very popular paradigm and a business success story, with storage being one of the key features. To achieve high data availability, cloud storage services rely on replication. In this context, one major challenge is data consistency. In contrast to traditional approaches that are mostly based on strong consistency, many cloud storage services opt for weaker consistency models in order to achieve better availability and performance. This comes at the cost of a high probability of stale data being read, as the replicas involved in the reads may not always have the most recent write. In this paper, we propose a novel approach, named Harmony, which adaptively tunes the consistency level at run-time according to the application requirements. The key idea behind Harmony is an intelligent estimation model of stale reads, allowing to elastically scale up or down the number of replicas involved in read operations to maintain a low (possibly zero) tolerable fraction of stale reads. As a result, Harmony can meet the desired consistency of the applications while achieving good performance. We have implemented Harmony and performed extensive evaluations with the Cassandra cloud storage on Grid?5000 testbed and on Amazon EC2. The results show that Harmony can achieve good performance without exceeding the tolerated number of stale reads. For instance, in contrast to the static eventual consistency used in Cassandra, Harmony reduces the stale data being read by almost 80% while adding only minimal latency. Meanwhile, it improves the throughput of the system by 45% while maintaining the desired consistency requirements of the applications when compared to the strong consistency model in Cassandra.
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This paper proposes a methodology for developing a speech into sign language translation system considering a user-centered strategy. This method-ology consists of four main steps: analysis of technical and user requirements, data collection, technology adaptation to the new domain, and finally, evalua-tion of the system. The two most demanding tasks are the sign generation and the translation rules generation. Many other aspects can be updated automatical-ly from a parallel corpus that includes sentences (in Spanish and LSE: Lengua de Signos Española) related to the application domain. In this paper, we explain how to apply this methodology in order to develop two translation systems in two specific domains: bus transport information and hotel reception.
Resumo:
El sector de la edificación es uno de los principales sectores económicos en España y, además, es un componente básico de la actividad económica y social, debido a su importante papel como generador de empleo, proveedor de bienes e incentivador del crecimiento. Curiosamente, es uno de los sectores con menos regulación y organización y que, además, está formado mayoritariamente por empresas de pequeña y mediana dimensión (pymes) que, por su menor capacidad, a menudo, se quedan detrás de las grandes empresas en términos de adopción de soluciones innovadoras. La complejidad en la gestión de toda la información relacionada con un proyecto de edificación ha puesto de manifiesto claras ineficiencias que se traducen en un gasto innecesario bastante representativo. La información y los conocimientos aprendidos rara vez son transmitidos de una fase a otra dentro del proyecto de edificación y, mucho menos, reutilizados en otros proyectos similares. De este modo, no sólo se produce un gasto innecesario, sino que incluso podemos encontrar información contradictoria y obsoleta y, por tanto, inútil para la toma de decisiones. A lo largo de los años, esta situación ha sido motivada por la propia configuración del sector, poniendo de manifiesto la necesidad de una solución que pudiera solventar este reto de gestión interorganizacional. Así, la cooperación interorganizacional se ha convertido en un factor clave para mejorar la competitividad de las organizaciones, típicamente pymes, que componen el sector de la edificación. La información es la piedra angular de cualquier proceso de negocio. Durante la última década, una amplia gama de industrias han experimentado importantes mejoras de productividad con la aplicación eficiente de las TIC, asociadas, principalmente, a incrementos en la velocidad de proceso de información y una mayor coherencia en la generación de datos, accesibilidad e intercambio de información. La aplicación eficaz de las TIC en el sector de la edificación requiere una combinación de aspectos estratégicos y tácticos, puesto que no sólo se trata de utilizar soluciones puntuales importadas de otros sectores para su aplicación en diferentes áreas, sino que se buscaría que la información multi-agente estuviera integrada y sea coherente para los proyectos de edificación. El sector de la construcción ha experimentado un descenso significativo en los últimos años en España y en Europa como resultado de la crisis financiera que comenzó en 2007. Esta disminución está acompañada de una baja penetración de las TIC en la interorganizacionales orientadas a los procesos de negocio. El descenso del mercado ha provocado una desaceleración en el sector de la construcción, donde sólo las pymes flexibles han sido capaces de mantener el ritmo a pesar de la especialización y la innovación en los servicios adaptados a las nuevas demandas del mercado. La industria de la edificación está muy fragmentada en comparación con otras industrias manufactureras. El alto grado de esta fragmentación está íntimamente relacionado con un impacto significativo en la productividad y el rendimiento. Muchos estudios de investigación han desarrollado y propuesto una serie de modelos de procesos integrados. Por desgracia, en la actualidad todavía no se está en condiciones para la formalización de cómo debe ser la comunicación y el intercambio de información durante el proceso de construcción. El paso del proceso secuencial tradicional a los procesos de interdependencia recíproca sin lugar a duda son una gran demanda asociada a la comunicación y el flujo de información en un proyecto de edificación. Recientemente se está poniendo mucho énfasis en los servicios para el hogar como un primer paso hacia esta mejora en innovación ya que la industria de los servicios digitales interactivos tiene un alto potencial para generar innovación y la ventaja estratégica para las empresas existentes. La multiplicidad de servicios para el hogar digital (HD) y los proveedores de servicios demandan, cada vez más, la aparición de una plataforma capaz de coordinar a todos los agentes del sector con el usuario final. En consecuencia, las estructuras organizacionales tienden a descentralizarse en busca de esa coordinación y, como respuesta a esta demanda, se plantea, también en este ámbito, el concepto de cooperación interorganizacional. Por lo tanto, ambos procesos de negocio -el asociado a la construcción y el asociado a la provisión de servicios del hogar digital, también considerado como la propia gestión de ese hogar digital o edificio, inteligente o no- deben de ser vistos en su conjunto mediante una plataforma tecnológica que les dé soporte y que pueda garantizar la agregación e integración de los diversos procesos, relacionados con la construcción y gestión, que se suceden durante el ciclo de vida de un edificio. Sobre esta idea y atendiendo a la evolución permanente de los sistemas de información en un entorno de interrelación y cooperación daría lugar a una aplicación del concepto de sistema de información interorganizacional (SIIO). El SIIO proporciona a las organizaciones la capacidad para mejorar los vínculos entre los socios comerciales a lo largo de la cadena de suministro, por lo que su importancia ha sido reconocida por organizaciones de diversos sectores. Sin embargo, la adopción de un SIIO en diferentes ámbitos ha demostrado ser complicada y con una alta dependencia de las características particulares de cada sector, siendo, en este momento, una línea de investigación abierta. Para contribuir a esta línea de investigación, este trabajo pretende recoger, partiendo de una revisión de la literatura relacionada, un enfoque en un modelo de adopción de un SIIO para el objeto concreto de esta investigación. El diseño de un SIIO está basado principalmente, en la identificación de las necesidades de información de cada uno de sus agentes participantes, de ahí la importancia en concretar un modelo de SIIO en el ámbito de este trabajo. Esta tesis doctoral presenta el modelo de plataforma virtual de la asociación entre diferentes agentes del sector de la edificación, el marco de las relaciones, los flujos de información correspondientes a diferentes procesos y la metodología que subyace tras el propio modelo, todo ello, con el objeto de contribuir a un modelo unificado que dé soporte tanto a los procesos relacionados con la construcción como con la gestión de servicios en el hogar digital y permitiendo cubrir los requisitos importantes que caracterizan este tipo de proyectos: flexibilidad, escalabilidad y robustez. El SIIO se ha convertido en una fuente de innovación y una herramienta estratégica que permite a las pymes obtener ventajas competitivas. Debido a la complejidad inherente de la adopción de un SIIO, esta investigación extiende el modelo teórico de adopción de un SIIO de Kurnia y Johnston (2000) con un modelo empírico para la caracterización de un SIIO. El modelo resultante tiene como objetivo fomentar la innovación de servicios en el sector mediante la identificación de los factores que influyen en la adopción de un SIIO por las pymes en el sector de la edificación como fuente de ventaja competitiva y de colaboración. Por tanto, esta tesis doctoral, proyectada sobre una investigación empírica, proporciona un enfoque para caracterizar un modelo de SIIO que permita dar soporte a la gestión integrada de los procesos de construcción y gestión de servicios para el hogar digital. La validez del modelo de SIIO propuesto, como fuente y soporte de ventajas competitivas, está íntimamente relacionada con la necesidad de intercambio de información rápido y fiable que demandan los agentes del sector para mejorar la gestión de su interrelación y cooperación con el fin de abordar proyectos más complejos en el sector de la edificación, relacionados con la implantación del hogar digital, y contribuyendo, así a favorecer el desarrollo de la sociedad de la información en el segmento residencial. ABSTRACT The building industry is the largest industry in the world. Land purchase, building design, construction, furnishing, building equipment, operations maintenance and the disposition of real estate have an unquestionable prominence not only at economic but also at social level. In Spain, the building sector is one of the main drivers of economy and also a basic component of economic activity and its role in generating employment, supply of goods or incentive for growth is crucial in the evolution of the economy. Surprisingly, it is one of the sectors with less regulation and organization. Another consistent problem is that, in this sector, the majority of companies are small and medium (SMEs), and often behind large firms in terms of their adoption of innovative solutions. The complexity of managing all information related to this industry has lead to a waste of money and time. The information and knowledge gathered is frequently stored in multiple locations, involving the work of thousands of people, and is rarely transferred on to the next phase. This approach is inconsistent and makes that incorrect information is used for decisions. This situation needs a viable solution for interorganizational information management. So, interorganizational co-operation has become a key factor for organization competitiveness within the building sector. Information is the cornerstone of any business process. Therefore, information and communication technologies (ICT) offer a means to change the way business is conducted. During the last decade, significant productivity improvements were experienced by a wide range of industries with ICT implementation. ICT has provided great advantages in speed of operation, consistency of data generation, accessibility and exchange of information. The wasted money resulting from reentering information, errors and omissions caused through poor decisions and actions, and the delays caused while waiting for information, represent a significant percentage of the global benefits. The effective application of ICT in building construction sector requires a combination of strategic and tactical developments. The building sector has experienced a significant decline in recent years in Spain and in Europe as a result of the financial crisis that began in 2007. This drop goes hand in hand with a low penetration of ICT in inter-organizational-oriented business processes. The market decrease has caused a slowdown in the building sector, where only flexible SMEs have been able to keep the pace though specialization and innovation in services adapted to new market demands. The building industry is highly fragmented compared with other manufacturing industries. This fragmentation has a significant negative impact on productivity and performance. Many research studies have developed and proposed a number of integrated process models. Unfortunately, these studies do not suggest how communication and information exchange within the construction process can be achieved, without duplication or lost in quality. A change from the traditional sequential process to reciprocal interdependency processes would increase the demand on communication and information flow over the edification project. Focusing on home services, the digital interactive service industry has the potential to generate innovation and strategic advantage for existing business. Multiplicity of broadband home services (BHS) and suppliers suggest the need for a figure able to coordinate all the agents in sector with the final user. Consequently, organizational structures tend to be decentralized. Responding to this fact, the concept of interorganizational co-operation also is raising in the residential market. Therefore, both of these business processes, building and home service supply, must be complemented with a technological platform that supports these processes and guarantees the aggregation and integration of the several services over building lifecycle. In this context of a technological platform and the permanent evolution of information systems is where the relevance of the concept of inter-organizational information system (IOIS) emerges. IOIS improves linkages between trading partners along the supply chain. However, IOIS adoption has proved to be difficult and not fully accomplished yet. This research reviews the literature in order to focus a model of IOIS adoption. This PhD Thesis presents a model of virtual association, a framework of the relationships, an identification of the information requirements and the corresponding information flows, using the multi-agent system approach. IOIS has become a source of innovation and a strategic tool for SMEs to obtain competitive advantage. Because of the inherent complexity of IOIS adoption, this research extends Kurnia and Johnston’s (2000) theoretical model of IOIS adoption with an empirical model of IOIS characterization. The resultant model aims to foster further service innovation in the sector by identifying the factors influencing IOIS adoption by the SMEs in the building sector as a source of competitive and collaborative advantage. Therefore, this PhD Thesis characterizes an IOIS model to support integrated management of building processes and home services. IOIS validity, as source and holder of competitive advantages, is related to the need for reliable information interchanges to improve interrelationship management. The final goal is to favor tracking of more complex projects in building sector and to contribute to consolidation of the information society through the provision of broadband home services and home automation.
Resumo:
La minería de datos es un campo de las ciencias de la computación referido al proceso que intenta descubrir patrones en grandes volúmenes de datos. La minería de datos busca generar información similar a la que podría producir un experto humano. Además es el proceso de descubrir conocimientos interesantes, como patrones, asociaciones, cambios, anomalías y estructuras significativas a partir de grandes cantidades de datos almacenadas en bases de datos, data warehouses o cualquier otro medio de almacenamiento de información. El aprendizaje automático o aprendizaje de máquinas es una rama de la Inteligencia artificial cuyo objetivo es desarrollar técnicas que permitan a las computadoras aprender. De forma más concreta, se trata de crear programas capaces de generalizar comportamientos a partir de una información no estructurada suministrada en forma de ejemplos. La minería de datos utiliza métodos de aprendizaje automático para descubrir y enumerar patrones presentes en los datos. En los últimos años se han aplicado las técnicas de clasificación y aprendizaje automático en un número elevado de ámbitos como el sanitario, comercial o de seguridad. Un ejemplo muy actual es la detección de comportamientos y transacciones fraudulentas en bancos. Una aplicación de interés es el uso de las técnicas desarrolladas para la detección de comportamientos fraudulentos en la identificación de usuarios existentes en el interior de entornos inteligentes sin necesidad de realizar un proceso de autenticación. Para comprobar que estas técnicas son efectivas durante la fase de análisis de una determinada solución, es necesario crear una plataforma que de soporte al desarrollo, validación y evaluación de algoritmos de aprendizaje y clasificación en los entornos de aplicación bajo estudio. El proyecto planteado está definido para la creación de una plataforma que permita evaluar algoritmos de aprendizaje automático como mecanismos de identificación en espacios inteligentes. Se estudiarán tanto los algoritmos propios de este tipo de técnicas como las plataformas actuales existentes para definir un conjunto de requisitos específicos de la plataforma a desarrollar. Tras el análisis se desarrollará parcialmente la plataforma. Tras el desarrollo se validará con pruebas de concepto y finalmente se verificará en un entorno de investigación a definir. ABSTRACT. The data mining is a field of the sciences of the computation referred to the process that it tries to discover patterns in big volumes of information. The data mining seeks to generate information similar to the one that a human expert might produce. In addition it is the process of discovering interesting knowledge, as patterns, associations, changes, abnormalities and significant structures from big quantities of information stored in databases, data warehouses or any other way of storage of information. The machine learning is a branch of the artificial Intelligence which aim is to develop technologies that they allow the computers to learn. More specifically, it is a question of creating programs capable of generalizing behaviors from not structured information supplied in the form of examples. The data mining uses methods of machine learning to discover and to enumerate present patterns in the information. In the last years there have been applied classification and machine learning techniques in a high number of areas such as healthcare, commercial or security. A very current example is the detection of behaviors and fraudulent transactions in banks. An application of interest is the use of the techniques developed for the detection of fraudulent behaviors in the identification of existing Users inside intelligent environments without need to realize a process of authentication. To verify these techniques are effective during the phase of analysis of a certain solution, it is necessary to create a platform that support the development, validation and evaluation of algorithms of learning and classification in the environments of application under study. The project proposed is defined for the creation of a platform that allows evaluating algorithms of machine learning as mechanisms of identification in intelligent spaces. There will be studied both the own algorithms of this type of technologies and the current existing platforms to define a set of specific requirements of the platform to develop. After the analysis the platform will develop partially. After the development it will be validated by prove of concept and finally verified in an environment of investigation that would be define.
Resumo:
La sequía afecta a todos los sectores de la sociedad y se espera que su frecuencia e intensidad aumente debido al cambio climático. Su gestión plantea importantes retos en el futuro. El enfoque de riesgo, que promueve una respuesta proactiva, se identifica como un marco de gestión apropiado que se está empezando a consolidar a nivel internacional. Sin embargo, es necesario contar con estudios sobre las características de la gestión de la sequía bajo este enfoque y sus implicaciones en la práctica. En esta tesis se evalúan diversos elementos que son relevantes para la gestión de la sequía, desde diferentes perspectivas, con especial énfasis en el componente social de la sequía. Para esta investigación se han desarrollado cinco estudios: (1) un análisis de las leyes de emergencia aprobadas durante la sequía 2005-2008 en España; (2) un estudio sobre la percepción de la sequía de los agricultores a nivel local; (3) una evaluación de las características y enfoque de gestión en seis casos de estudio a nivel europeo; (4) un análisis sistemático de los estudios de cuantificación de la vulnerabilidad a la sequía a nivel global; y (5) un análisis de los impactos de la sequía a partir en una base de datos europea. Los estudios muestran la importancia de la capacidad institucional como un factor que promueve y facilita la adopción del enfoque de riesgo. Al mismo tiempo, la falta de estudios de vulnerabilidad, el escaso conocimiento de los impactos y una escasa cultura de la evaluación post-sequía destacan como importantes limitantes para aprovechar el conocimiento que se genera en la gestión de un evento. A través del estudio de las leyes de sequía se evidencia la existencia de incoherencias entre cómo se define el problema de la sequía y las soluciones que se plantean, así como el uso de un discurso de securitización para perseguir objetivos más allá de la gestión de la sequía. El estudio de percepción permite identificar la existencia de diferentes problemas y percepciones de la sequía y muestra cómo los regantes utilizan principalmente los impactos para identificar y caracterizar la severidad de un evento, lo cual difiere de las definiciones predominantes a otros niveles de gestión. Esto evidencia la importancia de considerar la diversidad de definiciones y percepciones en la gestión, para realizar una gestión más ajustada a las necesidades de los diferentes sectores y colectivos. El análisis de la gestión de la sequía en seis casos de estudio a nivel europeo ha permitido identificar diferentes niveles de adopción del enfoque de riesgo en la práctica. El marco de análisis establecido, que se basa en seis dimensiones de análisis y 21 criterios, ha resultado ser una herramienta útil para diagnosticar los elementos que funcionan y los que es necesario mejorar en relación a la gestión del riesgo a la sequía. El análisis sistemático de los estudios de vulnerabilidad ha evidenciado la heterogeneidad en los marcos conceptuales utilizados así como debilidades en los factores de vulnerabilidad que se suelen incluir, en muchos casos derivada de la falta de datos. El trabajo sistemático de recolección de información sobre impactos de la sequía ha evidenciado la escasez de información sobre el tema a nivel europeo y la importancia de la gestión de la información. La base de datos de impactos desarrollada tiene un gran potencial como herramienta exploratoria y orientativa del tipo de impactos que produce la sequía en cada región, pero todavía presenta algunos retos respecto a su contenido, proceso de gestión y utilidad práctica. Existen importantes limitaciones vinculadas con el acceso y la disponibilidad de información y datos relevantes vinculados con la gestión de la sequía y todos sus componentes. La participación, los niveles de gestión, la perspectiva sectorial y las relaciones entre los componentes de gestión del riesgo considerados constituyen aspectos críticos que es necesario mejorar en el futuro. Así, los cinco artículos en su conjunto presentan ejemplos concretos que ayudan a conocer mejor la gestión de la sequía y que pueden resultar de utilidad para políticos, gestores y usuarios. ABSTRACT Drought affects all sectors and their frequency and intensity is expected to increase due to climate change. Drought management poses significant challenges in the future. Undertaking a drought risk management approach promotes a proactive response, and it is starting to consolidate internationally. However, it is still necessary to conduct studies on the characteristics of drought risk management and its practical implications. This thesis provides an evaluation of various relevant aspects of drought management from different perspectives and with special emphasis on the social component of droughts. For the purpose of this research a number of five studies have been carried out: (1) analysis of the emergency laws adopted during the 2005-2008 drought in Spain; (2) study of farmers perception of drought at a local level; (3) assessment of the characteristics and drought management issues in six case studies across Europe; (4) systematic analysis of drought vulnerability assessments; and (5) analysis of drought impacts from an European impacts text-based database. The results show the importance of institutional capacity as a factor that promotes and facilitates the adoption of a risk approach. In contrast, the following issues are identified as the main obstacles to take advantage of the lessons learnt: (1) lack of vulnerability studies, (2) limited knowledge about the impact and (3) limited availability of post-drought assessments Drought emergency laws evidence the existence of inconsistencies between drought problem definition and the measures proposed as solutions. Moreover, the securitization of the discourse pursue goals beyond management drought. The perception of drought by farmers helps to identify the existence of several definitions of drought. It also highlights the importance of impacts in defining and characterizing the severity of an event. However, this definition differs from the one used at other institutional and management level. As a conclusion, this remarks the importance of considering the diversity of definitions and perceptions to better tailor drought management to the needs of different sectors and stakeholders. The analysis of drought management in six case studies across Europe show different levels of risk adoption approach in practice. The analytical framework proposed is based on six dimensions and 21 criteria. This method has proven to be a useful tool in diagnosing the elements that work and those that need to be improved in relation to drought risk management. The systematic analysis of vulnerability assessment studies demonstrates the heterogeneity of the conceptual frameworks used. Driven by the lack of relevant data, the studies point out significant weaknesses of the vulnerabilities factors that are typically included The heterogeneity of the impact data collected at European level to build the European Drought Impact Reports Database (EDII) highlights the importance of information management. The database has great potential as exploratory tool and provides indicative useful information of the type of impacts that occurred in a particular region. However, it still presents some challenges regarding their content, the process of data collection and management and its usefulness. There are significant limitations associated with the access and availability of relevant information and data related to drought management and its components. The following improvement areas on critical aspects have been identified for the near future: participation, levels of drought management, sectorial perspective and in-depth assessment of the relationships between the components of drought risk management The five articles presented in this dissertation provides concrete examples of drought management evaluation that help to better understand drought management from a risk-based perspective which can be useful for policy makers, managers and users.
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Durante las últimas décadas el objetivo principal de la silvicultura y la gestión forestal en Europa ha pasado de ser la producción de madera a ser la gestión sostenible de los ecosistemas, por lo que se deben considerar todos los bienes y servicios que proporcionan los bosques. En consecuencia, es necesario contar con información forestal periódica de diversos indicadores forestales a nivel europeo para apoyar el desarrollo y la implementación de políticas medioambientales y que se realice una gestión adecuada. Para ello, se requiere un seguimiento intensivo sobre el estado de los bosques, por lo que los Inventarios Forestales Nacionales (IFN), (principal fuente de información forestal a gran escala), han aumentado el número de variables muestreadas para cumplir con los crecientes requerimientos de información. Sin embargo, las estimaciones proporcionadas por los diferentes países no son fácilmente comparables debido a las diferencias en las definiciones, los diseños de muestreo, las variables medidas y los protocolos de medición. Por esto, la armonización de los datos que proporcionan los diferentes países es fundamental para la contar con una información forestal sólida y fiable en la Unión europea (UE). La presente tesis tiene dos objetivos principales: (i) establecer el diseño de una metodología para evaluar la biodiversidad forestal en el marco del Inventario forestal nacional de España teniendo en cuenta las diferentes iniciativas nacionales e internacionales, con el objetivo de producir estimaciones comparables con las de otros países de la UE y (ii) armonizar los indicadores más relevantes para satisfacer los requerimientos nacionales e internacionales. Como consecuencia del estudio realizado para alcanzar el primer objetivo, la metodología diseñada para estimar la biodiversidad fue adoptada por el Tercer Inventario forestal nacional. Ésta se componía de indicadores agrupados en: cobertura del suelo, composición de árboles y especies de arbustos, riqueza de especies herbáceas y helechos, especies amenazadas, estructura, madera muerta, y líquenes epífitos. Tras el análisis del diseño metodológico y de los datos proporcionados, se observó la conveniencia de modificarla con el fin de optimizar los costes, viabilidad, calidad y cantidad de los datos registrados. En consecuencia, en el Cuarto Inventario Forestal Nacional se aplica una metodología modificada, puesto que se eliminó el muestreo de especies herbáceas y helechos, de líquenes epífitos y de especies amenazadas, se modificaron los protocolos de la toma de datos de estructura y madera muerta y se añadió el muestreo de especies invasoras, edad, ramoneo y grado de naturalidad de la masa. En lo que se refiere al segundo objetivo, se ha avanzado en la armonización de tres grupos de variables considerados como relevantes en el marco de los IFN: los indicadores de vegetación no arbórea (que juegan un papel relevante en los ecosistemas, es donde existe la mayor diversidad de plantas y hasta ahora no se conocían los datos muestreados en los IFN), la determinación de los árboles añosos (que tienen un importante papel como nicho ecológico y su identificación es especialmente relevante para la evaluación de la biodiversidad forestal) y el bosque disponible para el suministro de madera (indicador básico de los requerimientos internacionales de información forestal). Se llevó a cabo un estudio completo de la posible armonización de los indicadores de la vegetación no arbórea en los IFN. Para ello, se identificaron y analizaron las diferentes definiciones y diseños de muestreo empleados por los IFN, se establecieron definiciones de referencia y se propusieron y analizaron dos indicadores que pudiesen ser armonizados: MSC (mean species cover) que corresponde a la media de la fracción de cabida cubierta de cada especie por tipo de bosque y MTC (mean total cover). Se estableció una nueva metodología que permite identificar los árboles añosos con los datos proporcionados por los inventarios forestales nacionales con el objetivo de proporcionar una herramienta eficaz para facilitar la gestión forestal considerando la diversidad de los sistemas forestales. Se analizó el concepto de "bosque disponible para el suministro de madera" (FAWS) estudiando la consistencia de la información internacional disponible con el fin de armonizar su estimación y de proporcionar recomendaciones para satisfacer los requerimientos europeos. Como resultado, se elaboró una nueva definición de referencia de FAWS (que será adoptada por el proceso paneuropeo) y se analiza el impacto de la adopción de esta nueva definición en siete países europeos. El trabajo realizado en esta tesis, puede facilitar el suministrar y/o armonizar parcial o totalmente casi la mitad de los indicadores de información forestal solicitados por los requerimientos internacionales (47%). De éstos, prácticamente un 85% tienen relación con los datos inventariados empleando la metodología propuesta para la estimación de la biodiversidad forestal, y el resto, con el establecimiento de la definición de bosque disponible para el suministro de madera. No obstante, y pese a que esta tesis supone un avance importante, queda patente que las necesidades de información forestal son cambiantes y es imprescindible continuar el proceso de armonización de los IFN europeos. ABSTRACT Over the last few decades, the objectives on forestry and forest management in Europe have shifted from being primarily focused on wood production to sustainable ecosystem management, which should consider all the goods and services provided by the forest. Therefore, there is a continued need for forest indicators and assessments at EU level to support the development and implementation of a number of European environmental policies and to conduct a proper forest management. To address these questions, intensive monitoring on the status of forests is required. Therefore, the scope of National Forest Inventories (NFIs), (primary source of data for national and large-area assessments), has been broadened to include new variables to meet these increasing information requirements. However, estimates produced by different countries are not easily comparable because of differences in NFI definitions, plot configurations, measured variables, and measurement protocols. As consequence, harmonizing data produced at national level is essential for the production of sound EU forest information. The present thesis has two main aims: (i) to establish a methodology design to assess forest biodiversity in the frame of the Spanish National Forest Inventory taking into account the different national and international initiatives with the intention to produce comparable estimates with other EU countries and (ii) to harmonize relevant indicators for national and international requirements. In consequence of the work done related to the first objective, the established methodology to estimate forest biodiversity was adopted and launched under the Third National Forest Inventory. It was composed of indicators grouped into: cover, woody species composition, richness of herbaceous species and ferns, endangered species, stand structure, dead wood, and epiphytic lichens. This methodology was analyzed considering the provided data, time costs, feasibility, and requirements. Consequently, in the ongoing Fourth National Forest Inventory a modified methodology is applied: sampling of herbaceous species and ferns, epiphytic lichens and endangered species were removed, protocols regarding structure and deadwood were modified, and sampling of invasive species, age, browsing impact and naturalness were added. As regards the second objective, progress has been made in harmonizing three groups of variables considered relevant in the context of IFN: Indicators of non-tree vegetation (which play an important role in forest ecosystems, it is where the highest diversity of plants occur and so far the related sampled data in NFIs were not known), the identification of old-growth trees (which have an important role as ecological niche and its identification is especially relevant for the assessment of forest biodiversity) and the available forest for wood supply (basic indicator of international forestry information requirements). A complete analysis of ground vegetation harmonization possibilities within NFIs frame was carried on by identifying and analyzing the different definitions and sampling techniques used by NFIs, providing reference definitions related to ground vegetation and proposing and analyzing two ground vegetation harmonized indicators: “Mean species cover” (MSC) and “Mean total cover” (MTC) for shrubs by European forest categories. A new methodology based on NFI data was established with the aim to provide an efficient tool for policy makers to estimate the number of old-growth trees and thus to be able to perform the analysis of the effect of forest management on the diversity associated to forest systems. The concept of “forest available for wood supply” (FAWS) was discussed and clarified, analyzing the consistency of the available international information on FAWS in order to provide recommendations for data harmonization at European level regarding National Forest Inventories (NFIs). As a result, a new reference definition of FAWS was provided (which will be adopted in the pan-European process) and the consequences of the use of this new definition in seven European countries are analyzed. The studies carried on in this thesis, can facilitate the supply and/or harmonization partially or fully of almost half of the forest indicators (47%) needed for international requirements. Of these, nearly 85% are related to inventoried data using the proposed methodology for the estimation of forest biodiversity, and the rest, with the establishment of the definition of forest available for wood supply. However, despite this thesis imply an important development, forest information needs are changing and it is imperative to continue the process of harmonization of European NFIs.
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We thank Karim Gharbi and Urmi Trivedi for their assistance with RNA sequencing, carried out in the GenePool genomics facility (University of Edinburgh). We also thank Susan Fairley and Eduardo De Paiva Alves (Centre for Genome Enabled Biology and Medicine, University of Aberdeen) for help with the initial bioinformatics analysis. We thank Aaron Mitchell for kindly providing the ALS3 mutant, Julian Naglik for the gift of TR146 cells, and Jon Richardson for technical assistance. We thank the Genomics and Bioinformatics core of the Faculty of Health Sciences for Next Generation Sequencing and Bioinformatics support, the Information and Communication Technology Office at the University of Macau for providing access to a High Performance Computer and Jacky Chan and William Pang for their expert support on the High Performance Computer. Finally, we thank Amanda Veri for generating CaLC2928. M.D.L. is supported by a Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust 096072), R.A.F. by a Wellcome Trust-Massachusetts Institute of Technology (MIT) Postdoctoral Fellowship, L.E.C. by a Canada Research Chair in Microbial Genomics and Infectious Disease and by Canadian Institutes of Health Research Grants MOP-119520 and MOP-86452, A.J. P.B. was supported by the UK Biotechnology and Biological Sciences Research Council (BB/F00513X/1) and by the European Research Council (ERC-2009-AdG-249793-STRIFE), KHW is supported by the Science and Technology Development Fund of Macau S.A.R (FDCT) (085/2014/A2) and the Research and Development Administrative Office of the University of Macau (SRG2014-00003-FHS) and R.T.W. by the Burroughs Wellcome fund and NIH R15AO094406. Data availability RNA-sequencing data sets are available at ArrayExpress (www.ebi.ac.uk) under accession code E-MTAB-4075. ChIP-seq data sets are available at the NCBI SRA database (http://www.ncbi.nlm.nih.gov) under accession code SRP071687. The authors declare that all other data supporting the findings of this study are available within the article and its supplementary information files, or from the corresponding author upon request.
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In the current Information Age, data production and processing demands are ever increasing. This has motivated the appearance of large-scale distributed information. This phenomenon also applies to Pattern Recognition so that classic and common algorithms, such as the k-Nearest Neighbour, are unable to be used. To improve the efficiency of this classifier, Prototype Selection (PS) strategies can be used. Nevertheless, current PS algorithms were not designed to deal with distributed data, and their performance is therefore unknown under these conditions. This work is devoted to carrying out an experimental study on a simulated framework in which PS strategies can be compared under classical conditions as well as those expected in distributed scenarios. Our results report a general behaviour that is degraded as conditions approach to more realistic scenarios. However, our experiments also show that some methods are able to achieve a fairly similar performance to that of the non-distributed scenario. Thus, although there is a clear need for developing specific PS methodologies and algorithms for tackling these situations, those that reported a higher robustness against such conditions may be good candidates from which to start.