11 research outputs found

    Multifaceted Geotagging for Streaming News

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    News sources on the Web generate constant streams of information, describing the events that shape our world. In particular, geography plays a key role in the news, and understanding the geographic information present in news allows for its useful spatial browsing and retrieval. This process of understanding is called geotagging, and involves first finding in the document all textual references to geographic locations, known as toponyms, and second, assigning the correct lat/long values to each toponym, steps which are termed toponym recognition and toponym resolution, respectively. These steps are difficult due to ambiguities in natural language: some toponyms share names with non-location entities, and further, a given toponym can have many location interpretations. Removing these ambiguities is crucial for successful geotagging. To this end, geotagging methods are described which were developed for streaming news. First, a spatio-textual search engine named STEWARD, and an interactive map-based news browsing system named NewsStand are described, which feature geotaggers as central components, and served as motivating systems and experimental testbeds for developing geotagging methods. Next, a geotagging methodology is presented that follows a multifaceted approach involving a variety of techniques. First, a multifaceted toponym recognition process is described that uses both rule-based and machine learning–based methods to ensure high toponym recall. Next, various forms of toponym resolution evidence are explored. One such type of evidence is lists of toponyms, termed comma groups, whose toponyms share a common thread in their geographic properties that enables correct resolution. In addition to explicit evidence, authors take advantage of the implicit geographic knowledge of their audiences. Understanding the local places known by an audience, termed its local lexicon, affords great performance gains when geotagging articles from local newspapers, which account for the vast majority of news on the Web. Finally, considering windows of text of varying size around each toponym, termed adaptive context, allows for a tradeoff between geotagging execution speed and toponym resolution accuracy. Extensive experimental evaluations of all the above methods, using existing and two newly-created, large corpora of streaming news, show great performance gains over several competing prominent geotagging methods

    Personalizable Knowledge Integration

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    Large repositories of data are used daily as knowledge bases (KBs) feeding computer systems that support decision making processes, such as in medical or financial applications. Unfortunately, the larger a KB is, the harder it is to ensure its consistency and completeness. The problem of handling KBs of this kind has been studied in the AI and databases communities, but most approaches focus on computing answers locally to the KB, assuming there is some single, epistemically correct solution. It is important to recognize that for some applications, as part of the decision making process, users consider far more knowledge than that which is contained in the knowledge base, and that sometimes inconsistent data may help in directing reasoning; for instance, inconsistency in taxpayer records can serve as evidence of a possible fraud. Thus, the handling of this type of data needs to be context-sensitive, creating a synergy with the user in order to build useful, flexible data management systems. Inconsistent and incomplete information is ubiquitous and presents a substantial problem when trying to reason about the data: how can we derive an adequate model of the world, from the point of view of a given user, from a KB that may be inconsistent or incomplete? In this thesis we argue that in many cases users need to bring their application-specific knowledge to bear in order to inform the data management process. Therefore, we provide different approaches to handle, in a personalized fashion, some of the most common issues that arise in knowledge management. Specifically, we focus on (1) inconsistency management in relational databases, general knowledge bases, and a special kind of knowledge base designed for news reports; (2) management of incomplete information in the form of different types of null values; and (3) answering queries in the presence of uncertain schema matchings. We allow users to define policies to manage both inconsistent and incomplete information in their application in a way that takes both the user's knowledge of his problem, and his attitude to error/risk, into account. Using the frameworks and tools proposed here, users can specify when and how they want to manage/solve the issues that arise due to inconsistency and incompleteness in their data, in the way that best suits their needs

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    A comparison of the CAR and DAGAR spatial random effects models with an application to diabetics rate estimation in Belgium

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    When hierarchically modelling an epidemiological phenomenon on a finite collection of sites in space, one must always take a latent spatial effect into account in order to capture the correlation structure that links the phenomenon to the territory. In this work, we compare two autoregressive spatial models that can be used for this purpose: the classical CAR model and the more recent DAGAR model. Differently from the former, the latter has a desirable property: its ρ parameter can be naturally interpreted as the average neighbor pair correlation and, in addition, this parameter can be directly estimated when the effect is modelled using a DAGAR rather than a CAR structure. As an application, we model the diabetics rate in Belgium in 2014 and show the adequacy of these models in predicting the response variable when no covariates are available

    A Statistical Approach to the Alignment of fMRI Data

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    Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods

    In pursuit of autonomous distributed satellite systems

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    Satellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global

    In pursuit of autonomous distributed satellite systems

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    A la pàgina 265 diu: "In an effort to facilitate the reproduction of results, both the source code of the simulation environment and the configuration files that were prepared for the design characterisation are available in an open repository: https://github.com/carlesaraguz/aeossSatellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global.Postprint (published version
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