973 resultados para Unstructured content search
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In this paper a new PCA-based positioning sensor and localization system for mobile robots to operate in unstructured environments (e. g. industry, services, domestic ...) is proposed and experimentally validated. The inexpensive positioning system resorts to principal component analysis (PCA) of images acquired by a video camera installed onboard, looking upwards to the ceiling. This solution has the advantage of avoiding the need of selecting and extracting features. The principal components of the acquired images are compared with previously registered images, stored in a reduced onboard image database, and the position measured is fused with odometry data. The optimal estimates of position and slippage are provided by Kalman filters, with global stable error dynamics. The experimental validation reported in this work focuses on the results of a set of experiments carried out in a real environment, where the robot travels along a lawn-mower trajectory. A small position error estimate with bounded co-variance was always observed, for arbitrarily long experiments, and slippage was estimated accurately in real time.
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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This paper describes a communication model to integrate repositories of programming problems with other e-Learning software components. The motivation for this work comes from the EduJudge project that aims to connect an existing repository of programming problems to learning management systems. When trying to use the existing repositories of learning objects we realized that they are mainly specialized search engines and lack features for integration with other e-Learning systems. With this model we intend to clarify the main features of a programming problem repository, in order to enable the design and development of software components that use it. The two main points of this model are the definition of programming problems as learning objects and the definition of the core functions exposed by the repository. In both cases, this model follows the existing specifications of the IMS standard and proposes extensions to deal with the special requirements of automatic evaluation and grading of programming exercises. In the definition of programming problems as learning objects we introduced a new schema for meta-data. This schema is used to represent meta-data related to automatic evaluation that cannot be conveniently represented using the standard: the type of automatic evaluation; the requirements of the evaluation engine; or the roles of different assets - tests cases, program solutions, etc. In the definition of the core functions we used two different web services flavours - SOAP and REST - and described each function as an operation for each type of interface. We describe also the data types of the arguments of each operation. These data types consist mainly on learning objects and their identifications, but include also usage reports and queries using XQuery.
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Mestrado em Engenharia Qumica
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As the variety of mobile devices connected to the Internet growts there is a correponding increase in the need to deliver content tailored to their heterogeneous characteristics. At the same time, we watch to the increase of e-learning in universities through the adoption of electronic platforms and standards. Not surprisingly, the concept of mLearning (Mobile Learning) appeared in recent years decreasing the limitation of learning location with the mobility of general portable devices. However, this large number and variety of Web-enabled devices poses several challenges for Web content creators who want to automatic get the delivery context and adapt the content to the client mobile devices. In this paper we analyze several approaches to defining delivery context and present an architecture for deliver uniform mLearning content to mobile devices denominated eduMCA - Educational Mobile Content Adaptation. With the eduMCA system the Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.
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Dissertao apresentada para obteno do Grau de Mestre em Informtica, pela Universidade Nova de Lisboa, Faculdade de Cincias e Tecnologia
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A quantidade e variedade de contedos multimdia actualmente disponveis cons- tituem um desafio para os utilizadores dado que o espao de procura e escolha de fontes e contedos excede o tempo e a capacidade de processamento dos utilizado- res. Este problema da seleco, em funo do perfil do utilizador, de informao em grandes conjuntos heterogneos de dados complexo e requer ferramentas especficas. Os Sistemas de Recomendao surgem neste contexto e so capazes de sugerir ao utilizador itens que se coadunam com os seus gostos, interesses ou necessidades, i.e., o seu perfil, recorrendo a metodologias de inteligncia artificial. O principal objectivo desta tese demonstrar que possvel recomendar em tempo til contedos multimdia a partir do perfil pessoal e social do utilizador, recorrendo exclusivamente a fontes pblicas e heterogneas de dados. Neste sen- tido, concebeu-se e desenvolveu-se um Sistema de Recomendao de contedos multimdia baseado no contedo, i.e., nas caractersticas dos itens, no historial e preferncias pessoais e nas interaces sociais do utilizador. Os contedos mul- timdia recomendados, i.e., os itens sugeridos ao utilizador, so provenientes da estao televisiva britnica, British Broadcasting Corporation (BBC), e esto classificados de acordo com as categorias dos programas da BBC. O perfil do utilizador construdo levando em conta o historial, o contexto, as preferncias pessoais e as actividades sociais. O YouTube a fonte do histo- rial pessoal utilizada, permitindo simular a principal fonte deste tipo de dados - a Set-Top Box (STB). O historial do utilizador constitudo pelo conjunto de vdeos YouTube e programas da BBC vistos pelo utilizador. O contedo dos vdeos do YouTube est classificado segundo as categorias de vdeo do prprio YouTube, sendo efectuado o mapeamento para as categorias dos programas da BBC. A informao social, que proveniente das redes sociais Facebook e Twit- ter, recolhida atravs da plataforma Beancounter. As actividades sociais do utilizador obtidas so filtradas para extrair os filmes e sries que so, por sua vez, enriquecidos semanticamente atravs do recurso a repositrios abertos de dados interligados. Neste caso, os filmes e sries so classificados atravs dos gneros da IMDb e, posteriormente, mapeados para as categorias de programas da BBC. Por ltimo, a informao do contexto e das preferncias explcitas, atravs da classificao dos itens recomendados, do utilizador so tambm contempladas. O sistema desenvolvido efectua recomendaes em tempo real baseado nas actividades das redes sociais Facebook e Twitter, no historial de vdeos Youtube e de programas da BBC vistos e preferncias explcitas. Foram realizados testes com cinco utilizadores e o tempo mdio de resposta do sistema para criar o conjunto inicial de recomendaes foi 30 s. As recomendaes personalizadas so geradas e actualizadas mediante pedido expresso do utilizador.
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Recent studies of mobile Web trends show a continuous explosion of mobile-friendly content. However, the increasing number and heterogeneity of mobile devices poses several challenges for Web programmers who want to automatically get the delivery context and adapt the content to mobile devices. In this process, the devices detection phase assumes an important role where an inaccurate detection could result in a poor mobile experience for the enduser. In this paper we compare the most promising approaches for mobile device detection. Based on this study, we present an architecture for a system to detect and deliver uniform m-Learning content to students in a Higher School. We focus mainly on the devices capabilities repository manageable and accessible through an API. We detail the structure of the capabilities XML Schema that formalizes the data within the devices capabilities XML repository and the REST Web Service API for selecting the correspondent devices capabilities data according to a specific request. Finally, we validate our approach by presenting the access and usage statistics of the mobile web interface of the proposed system such as hits and new visitors, mobile platforms, average time on site and rejection rate.
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The concept of Learning Object (LO) is crucial for the standardization on eLearning. The latest LO standard from IMS Global Learning Consortium is the IMS Common Cartridge (IMS CC) that organizes and distributes digital learning content. By analyzing this new specification we considered two interoperability levels: content and communication. A common content format is the backbone of interoperability and is the basis for content exchange among eLearning systems. Communication is more than just exchanging content; it includes also accessing to specialized systems and services and reporting on content usage. This is particularly important when LOs are used for evaluation. In this paper we analyze the Common Cartridge profile based on the two interoperability levels we proposed. We detail its data model that comprises a set of derived schemata referenced on the CC schema and we explore the use of the IMS Learning Tools Interoperability (LTI) to allow remote tools and content to be integrated into a Learning Management System (LMS). In order to test the applicability of IMS CC for automatic evaluation we define a representation of programming exercises using this standard. This representation is intended to be the cornerstone of a network of eLearning systems where students can solve computer programming exercises and obtain feedback automatically. The CC learning object is automatically generated based on a XML dialect called PExIL that aims to consolidate all the data need to describe resources within the programming exercise life-cycle. Finally, we test the generated cartridge on the IMS CC online validator to verify its conformance with the IMS CC specification.
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eLearning has been evolved in a gradual and consistent way. Along with this evolution several specialized and disparate systems appeared to fulfill the needs of teachers and students such as repositories of learning objects, intelligent tutors, or automatic evaluators. This heterogeneity poses issues that are necessary to address in order to promote interoperability among systems. Based on this fact, the standardization of content takes a leading role in the eLearning realm. This article presents a survey on current eLearning content standards. It gathers information on the most emergent standards and categorizes them according three distinct facets: metadata, content packaging and educational design.
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To meet the increasing demands of the complex inter-organizational processes and the demand for continuous innovation and internationalization, it is evident that new forms of organisation are being adopted, fostering more intensive collaboration processes and sharing of resources, in what can be called collaborative networks (Camarinha-Matos, 2006:03). Information and knowledge are crucial resources in collaborative networks, being their management fundamental processes to optimize. Knowledge organisation and collaboration systems are thus important instruments for the success of collaborative networks of organisations having been researched in the last decade in the areas of computer science, information science, management sciences, terminology and linguistics. Nevertheless, research in this area didnt give much attention to multilingual contexts of collaboration, which pose specific and challenging problems. It is then clear that access to and representation of knowledge will happen more and more on a multilingual setting which implies the overcoming of difficulties inherent to the presence of multiple languages, through the use of processes like localization of ontologies. Although localization, like other processes that involve multilingualism, is a rather well-developed practice and its methodologies and tools fruitfully employed by the language industry in the development and adaptation of multilingual content, it has not yet been sufficiently explored as an element of support to the development of knowledge representations - in particular ontologies - expressed in more than one language. Multilingual knowledge representation is then an open research area calling for cross-contributions from knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences. This workshop joined researchers interested in multilingual knowledge representation, in a multidisciplinary environment to debate the possibilities of cross-fertilization between knowledge engineering, terminology, ontology engineering, cognitive sciences, computational linguistics, natural language processing, and management sciences applied to contexts where multilingualism continuously creates new and demanding challenges to current knowledge representation methods and techniques. In this workshop six papers dealing with different approaches to multilingual knowledge representation are presented, most of them describing tools, approaches and results obtained in the development of ongoing projects. In the first case, Andrs Domnguez Burgos, Koen Kerremansa and Rita Temmerman present a software module that is part of a workbench for terminological and ontological mining, Termontospider, a wiki crawler that aims at optimally traverse Wikipedia in search of domainspecific texts for extracting terminological and ontological information. The crawler is part of a tool suite for automatically developing multilingual termontological databases, i.e. ontologicallyunderpinned multilingual terminological databases. In this paper the authors describe the basic principles behind the crawler and summarized the research setting in which the tool is currently tested. In the second paper, Fumiko Kano presents a work comparing four feature-based similarity measures derived from cognitive sciences. The purpose of the comparative analysis presented by the author is to verify the potentially most effective model that can be applied for mapping independent ontologies in a culturally influenced domain. For that, datasets based on standardized pre-defined feature dimensions and values, which are obtainable from the UNESCO Institute for Statistics (UIS) have been used for the comparative analysis of the similarity measures. The purpose of the comparison is to verify the similarity measures based on the objectively developed datasets. According to the author the results demonstrate that the Bayesian Model of Generalization provides for the most effective cognitive model for identifying the most similar corresponding concepts existing for a targeted socio-cultural community. In another presentation, Thierry Declerck, Hans-Ulrich Krieger and Dagmar Gromann present an ongoing work and propose an approach to automatic extraction of information from multilingual financial Web resources, to provide candidate terms for building ontology elements or instances of ontology concepts. The authors present a complementary approach to the direct localization/translation of ontology labels, by acquiring terminologies through the access and harvesting of multilingual Web presences of structured information providers in the field of finance, leading to both the detection of candidate terms in various multilingual sources in the financial domain that can be used not only as labels of ontology classes and properties but also for the possible generation of (multilingual) domain ontologies themselves. In the next paper, Manuel Silva, Antnio Lucas Soares and Rute Costa claim that despite the availability of tools, resources and techniques aimed at the construction of ontological artifacts, developing a shared conceptualization of a given reality still raises questions about the principles and methods that support the initial phases of conceptualization. These questions become, according to the authors, more complex when the conceptualization occurs in a multilingual setting. To tackle these issues the authors present a collaborative platform conceptME - where terminological and knowledge representation processes support domain experts throughout a conceptualization framework, allowing the inclusion of multilingual data as a way to promote knowledge sharing and enhance conceptualization and support a multilingual ontology specification. In another presentation Frieda Steurs and Hendrik J. Kockaert present us TermWise, a large project dealing with legal terminology and phraseology for the Belgian public services, i.e. the translation office of the ministry of justice, a project which aims at developing an advanced tool including expert knowledge in the algorithms that extract specialized language from textual data (legal documents) and whose outcome is a knowledge database including Dutch/French equivalents for legal concepts, enriched with the phraseology related to the terms under discussion. Finally, Deborah Grbac, Luca Losito, Andrea Sada and Paolo Sirito report on the preliminary results of a pilot project currently ongoing at UCSC Central Library, where they propose to adapt to subject librarians, employed in large and multilingual Academic Institutions, the model used by translators working within European Union Institutions. The authors are using User Experience (UX) Analysis in order to provide subject librarians with a visual support, by means of ontology tables depicting conceptual linking and connections of words with concepts presented according to their semantic and linguistic meaning. The organizers hope that the selection of papers presented here will be of interest to a broad audience, and will be a starting point for further discussion and cooperation.
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The need for better adaptation of networks to transported flows has led to research on new approaches such as content aware networks and network aware applications. In parallel, recent developments of multimedia and content oriented services and applications such as IPTV, video streaming, video on demand, and Internet TV reinforced interest in multicast technologies. IP multicast has not been widely deployed due to interdomain and QoS support problems; therefore, alternative solutions have been investigated. This article proposes a management driven hybrid multicast solution that is multi-domain and media oriented, and combines overlay multicast, IP multicast, and P2P. The architecture is developed in a content aware network and network aware application environment, based on light network virtualization. The multicast trees can be seen as parallel virtual content aware networks, spanning a single or multiple IP domains, customized to the type of content to be transported while fulfilling the quality of service requirements of the service provider.
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Computerized scheduling methods and computerized scheduling systems according to exemplary embodiments. A computerized scheduling method may be stored in a memory and executed on one or more processors. The method may include defining a main multi-machine scheduling problem as a plurality of single machine scheduling problems; independently solving the plurality of single machine scheduling problems thereby calculating a plurality of near optimal single machine scheduling problem solutions; integrating the plurality of near optimal single machine scheduling problem solutions into a main multi-machine scheduling problem solution; and outputting the main multi-machine scheduling problem solution.
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Phenylketonuria is an inborn error of metabolism, involving, in most cases, a deficient activity of phenylalanine hydroxylase. Neonatal diagnosis and a prompt special diet (low phenylalanine and natural-protein restricted diets) are essential to the treatment. The lack of data concerning phenylalanine contents of processed foodstuffs is an additional limitation for an already very restrictive diet. Our goals were to quantify protein (Kjeldahl method) and amino acid (18) content (HPLC/fluorescence) in 16 dishes specifically conceived for phenylketonuric patients, and compare the most relevant results with those of several international food composition databases. As might be expected, all the meals contained low protein levels (0.673.15 g/100 g) with the highest ones occurring in boiled rice and potatoes. These foods also contained the highest amounts of phenylalanine (158.51 and 62.65 mg/100 g, respectively). In contrast to the other amino acids, it was possible to predict phenylalanine content based on protein alone. Slight deviations were observed when comparing results with the different food composition databases.