762 resultados para Trusted computing platform


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This paper describes a failure alert system and a methodology for content reuse in a new instructional design system called InterMediActor (IMA). IMA provides an environment for instructional content design, production and reuse, and for students’ evaluation based in content specification through a hierarchical structure of competences. The student assessment process and information extraction process for content reuse are explained.

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The alignment between competences, teaching-learning methodologies and assessment is a key element of the European Higher Education Area. This paper presents the efforts carried out by six Telematics, Computer Science and Electronic Engineering Education teachers towards achieving this alignment in their subjects. In a joint work with pedagogues, a set of recommended actions were identified. A selection of these actions were applied and evaluated in the six subjects. The cross-analysis of the results indicate that the actions allow students to better understand the methodologies and assessment planned for the subjects, facilitate (self-) regulation and increase students’ involvement in the subjects.

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The increasing volume of data describing humandisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases.Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers cliniciansthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medicalresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed informationsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access andwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand forperforming computationally intensive simulations for treatment planning and research.

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El objetivo de PANACEA es engranar diferentes herramientas avanzadas para construir una fábrica de Recursos Lingüísticos (RL), una línea de producción que automatice los pasos implicados en la adquisición, producción, actualización y mantenimiento de los RL que la Traducción Automática y otras tecnologías lingüísticas, necesitan.

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Classical planning has been notably successful in synthesizing finite plans to achieve states where propositional goals hold. In the last few years, classical planning has also been extended to incorporate temporally extended goals, expressed in temporal logics such as LTL, to impose restrictions on the state sequences generated by finite plans. In this work, we take the next step and consider the computation of infinite plans for achieving arbitrary LTL goals. We show that infinite plans can also be obtained efficiently by calling a classical planner once over a classical planning encoding that represents and extends the composition of the planningdomain and the B¨uchi automaton representingthe goal. This compilation scheme has been implemented and a number of experiments are reported.

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The objective of PANACEA is to build a factory of LRs that automates the stages involved in the acquisition, production, updating and maintenance of LRs required by MT systems and by other applications based on language technologies, and simplifies eventual issues regarding intellectual property rights. This automation will cut down the cost, time and human effort significantly. These reductions of costs and time are the only way to guarantee the continuous supply of LRs that MT and other language technologies will be demanding in the multilingual Europe.

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The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition,production, updating and maintenance of the large language resources required by, among others, MT systems. The development of a Corpus Acquisition Component (CAC) for extracting monolingual and bilingual data from the web is one of the most innovative building blocks of PANACEA. The CAC, which is the first stage in the PANACEA pipeline for building Language Resources, adopts an efficient and distributed methodology to crawl for web documents with rich textual content in specific languages and predefined domains. The CAC includes modules that can acquire parallel data from sites with in-domain content available in more than one language. In order to extrinsically evaluate the CAC methodology, we have conducted several experiments that used crawled parallel corpora for the identification and extraction of parallel sentences using sentence alignment. The corpora were then successfully used for domain adaptation of Machine Translation Systems.

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This paper presents the platform developed in the PANACEA project, a distributed factory that automates the stages involved in the acquisition, production, updating and maintenance of Language Resources required by Machine Translation and other Language Technologies. We adopt a set of tools that have been successfully used in the Bioinformatics field, they are adapted to the needs of our field and used to deploy web services, which can be combined to build more complex processing chains (workflows). This paper describes the platform and its different components (web services, registry, workflows, social network and interoperability). We demonstrate the scalability of the platform by carrying out a set of massive data experiments. Finally, a validation of the platform across a set of required criteria proves its usability for different types of users (non-technical users and providers).

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In order to investigate the spatial and temporal variability (daily, seasonal and inter-annual) of CO2 and O2 air-sea fluxes and their underlying processes, a dense network of observations is required. For this purpose, the Cape Verde Ocean Observatory (CVOO) provides a unique infrastructure. Information thus obtained also links biological productivity and atmospheric composition. To expand these capabilities, a novel “virtual mooring” approach for high resolution measurements, based on a modified NEMO profiling float, is pursued. This Profiling Float was equipped with O2 and pCO2 sensors for the first time, in order to collect daily depth profiles (0-200 m) in the vicinity of the ocean site. Data access and remote control is provided through Iridium satellite telemetry. Recalibrations and redeployments are carried out every 1-3 month. First, we present the new developed instrument and the innovative in situ and real-time approach behind. Second, we show the inter-disciplinary scientific objectives which will benefit from this approach as a result of the intensive partnership between IFM-GEOMAR and INDP during the last years.

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Adjuvants are increasingly used by the vaccine research and development community, particularly for their ability to enhance immune responses and for their dose-sparing properties. However, they are not readily available to the majority of public sector vaccine research groups, and even those with access to suitable adjuvants may still fail in the development of their vaccines because of lack of knowledge on how to correctly formulate the adjuvants. This shortcoming led the World Health Organization to advocate for the establishment of the Vaccine Formulation Laboratory at the University of Lausanne, Switzerland. The primary mission of the laboratory is to transfer adjuvants and formulation technology free of intellectual property rights to academic institutions, small biotechnology companies and developing countries vaccine manufacturers. In this context, the transfer of an oil-in-water emulsion to Bio Farma, an Indonesian vaccine manufacturer, was initiated to increase domestic pandemic influenza vaccine production capacity as part of the national pandemic influenza preparedness plan.

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BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package