1,438 research outputs found
Multimedia kiosks and the ancient times : an archaeological reconstruction and history of Braga’s cathedral
Ein vom CCG, in Kooperation mit
der Unidade de Arqueologia da
Universidade do Minho – UAUM
(Portugal), entwickelter Multimedia
Kiosk präsentiert auf mehreren
thematischen Ebenen die Kathedrale
und die mit ihr verbundenen
archäologischen Ausgrabungen.
Zu jeder Ausgrabungsstätte ist der
Fortgang der archäologischen
Arbeiten durch kurze Textbeschreibungen,
Fotografien und
Zeichnungen dokumentiert. Ein
Modell der Kathedrale lädt zu
einem virtuellen Rundgang ein.
Ziel der Präsentation ist es, nicht
nur Finanzmittel für die Fortführung
der archäologischen
Arbeiten einzuwerben bzw. das
Interesse potentieller Sponsoren
zu wecken, aber auch den Besuchern
der Kathedrale eine bessere
und interessantere Übersicht der
Geschichte des Gebäudes zu
geben
Cloud-to-ground lightning in Portugal: patterns and dynamical forcing
An analysis of the cloud-to-ground discharges (CGD) over Portugal is carried out using data collected by a network of sensors maintained by the Portuguese Meteorological Institute for 2003–2009 (7 yr). Only cloud-to-ground flashes are considered and negative polarity CGD are largely dominant. The total number of discharges reveals a considerable interannual variability and a large irregularity in their distribution throughout the year. However, it is shown that a large number of discharges occur in the May–September period (71%), with a bimodal distribution that peaks in May and September, with most of the lightning activity recorded in the afternoon (from 16:00 to 18:00 UTC). In spring and autumn the lightning activity tends to be scattered throughout the country, whereas in summer it tends to be more concentrated over northeastern Portugal. Winter generally presents low lightning activity. Furthermore, two significant couplings between the monthly number of days with discharges and the large-scale atmospheric circulation are isolated: a regional forcing, predominantly in summer, and a remote forcing. In fact, the identification of daily lightning regimes revealed three important atmospheric conditions for triggering lightning activity: regional cut-off lows, cold troughs induced by remote low pressure systems and summertime regional low pressures at low-tropospheric levels combined with a mid-tropospheric cold trough
From problem structuring to optimization: a multi-methodological framework to assist the planning of medical training
Medical training is an intricate and long process, which is compulsory to medical practice and often lasts up to twelve years for some specialties. Health stakeholders recognise that an adequate planning is crucial for health systems to deliver necessary care services. However, proper planning needs to account for complexity related with the setting of medical school vacancies and of residency programs, which are highly influenced by multiple stakeholders with diverse perspectives and views, as well as by the specificities of medical training. Aiming at building comprehensive models with a potential to assist health decision-makers, this article develops a multi-methodological framework to assist the planning of medical training under such a complex environment. It combines the structuring of the objectives and specificities of the medical training problem with a Soft Systems Methodology through the CATWOE (Customer, Actor, Transformation, Weltanschauung, Owner, Environment) approach, and the formulation of a Mixed Integer Linear Programming model that considers all relevant aspects. Considering the specificities of countries based on a National Health Service structure, a multi-objective planning model emerges, informing on how many vacancies should be opened/closed per year in medical schools and in each specialty. This model aims at (i) minimizing imbalances between medical demand and supply; (ii) minimizing costs; and (iii) maximizing equity across medical specialties. A case study in Portugal is explored so as to illustrate the applicability of the proposed multi-methodology, showing the relevance of proper structuring for planning models having the potential to inform health decision-makers and planners in practice.info:eu-repo/semantics/acceptedVersio
Adaptive Semantic Annotation of Entity and Concept Mentions in Text
The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc or application-specific databases.
These knowledge repositories figure as a central provider of unambiguous identifiers and semantic relationships between entities. As such, these shared entity descriptions serve as a common vocabulary to exchange and organize information in different formats and for different purposes. Therefore, there has been remarkable interest in systems that are able to automatically tag textual documents with identifiers from shared knowledge repositories so that the content in those documents is described in a vocabulary that is unambiguously understood across applications.
Tagging textual documents according to these knowledge bases is a challenging task. It involves recognizing the entities and concepts that have been mentioned in a particular passage and attempting to resolve eventual ambiguity of language in order to choose one of many possible meanings for a phrase. There has been substantial work on recognizing and disambiguating entities for specialized applications, or constrained to limited entity types and particular types of text. In the context of shared knowledge bases, since each application has potentially very different needs, systems must have unprecedented breadth and flexibility to ensure their usefulness across applications. Documents may exhibit different language and discourse characteristics, discuss very diverse topics, or require the focus on parts of the knowledge repository that are inherently harder to disambiguate. In practice, for developers looking for a system to support their use case, is often unclear if an existing solution is applicable, leading those developers to trial-and-error and ad hoc usage of multiple systems in an attempt to achieve their objective.
In this dissertation, I propose a conceptual model that unifies related techniques in this space under a common multi-dimensional framework that enables the elucidation of strengths and limitations of each technique, supporting developers in their search for a suitable tool for their needs. Moreover, the model serves as the basis for the development of flexible systems that have the ability of supporting document tagging for different use cases. I describe such an implementation, DBpedia Spotlight, along with extensions that we performed to the knowledge base DBpedia to support this implementation. I report evaluations of this tool on several well known data sets, and demonstrate applications to diverse use cases for further validation
A graph-based framework for data retrieved from criminal-related documents
A digitalização das empresas e dos serviços tem potenciado o tratamento e análise de um crescente volume
de dados provenientes de fontes heterogeneas, com desafios emergentes, nomeadamente ao nível da representação
do conhecimento. Também os Órgãos de Polícia Criminal (OPC) enfrentam o mesmo desafio,
tendo em conta o volume de dados não estruturados, provenientes de relatórios policiais, sendo analisados
manualmente pelo investigadores criminais, consumindo tempo e recursos.
Assim, a necessidade de extrair e representar os dados não estruturados existentes em documentos relacionados
com o crime, de uma forma automática, permitindo a redução da análise manual efetuada pelos
investigadores criminais. Apresenta-se como um desafio para a ciência dos computadores, dando a possibilidade
de propor uma alternativa computacional que permita extrair e representar os dados, adaptando
ou propondo métodos computacionais novos.
Actualmente existem vários métodos computacionais aplicados ao domínio criminal, nomeadamente a identificação
e classificação de entidades nomeadas, por exemplo narcóticos, ou a extracção de relações entre
entidades relevantes para a investigação criminal. Estes métodos são maioritariamente aplicadas à lingua
inglesa, e em Portugal não há muita atenção à investigação nesta área, inviabilizando a sua aplicação no
contexto da investigação criminal.
Esta tese propõe uma solução integrada para a representação dos dados não estruturados existentes em
documentos, usando um conjunto de métodos computacionais: Preprocessamento de Documentos, que
agrupa uma tarefa de Extracção, Transformação e Carregamento adaptado aos documentos relacionados
com o crime, seguido por um pipeline de Processamento de Linguagem Natural aplicado à lingua portuguesa,
para uma análise sintática e semântica dos dados textuais; Método de Extracção de Informação 5W1H
que agrupa métodos de Reconhecimento de Entidades Nomeadas, a detecção da função semântica e a
extracção de termos criminais; Preenchimento da Base de Dados de Grafos e Enriquecimento, permitindo
a representação dos dados obtidos numa base de dados de grafos Neo4j. Globalmente a solução integrada apresenta resultados promissores, cujos resultados foram validados usando
protótipos desemvolvidos para o efeito. Demonstrou-se ainda a viabilidade da extracção dos dados não
estruturados, a sua interpretação sintática e semântica, bem como a representação na base de dados de
grafos; Abstract:
The digitalization of companies processes has enhanced the treatment and analysis of a growing volume
of data from heterogeneous sources, with emerging challenges, namely those related to knowledge representation.
The Criminal Police has similar challenges, considering the amount of unstructured data from
police reports manually analyzed by criminal investigators, with the corresponding time and resources.
There is a need to automatically extract and represent the unstructured data existing in criminal-related
documents and reduce the manual analysis by criminal investigators. Computer science faces a challenge
to apply emergent computational models that can be an alternative to extract and represent the data using
new or existing methods.
A broad set of computational methods have been applied to the criminal domain, such as the identification
and classification named-entities (NEs) or extraction of relations between the entities that are relevant for
the criminal investigation, like narcotics. However, these methods have mainly been used in the English
language. In Portugal, the research on this domain, applying computational methods, lacks related works,
making its application in criminal investigation unfeasible.
This thesis proposes an integrated solution for the representation of unstructured data retrieved from
documents, using a set of computational methods, such as Preprocessing Criminal-Related Documents
module. This module is supported by Extraction, Transformation, and Loading tasks. Followed by a
Natural Language Processing pipeline applied to the Portuguese language, for syntactic and semantic
analysis of textual data. Next, the 5W1H Information Extraction Method combines the Named-Entity
Recognition, Semantic Role Labelling, and Criminal Terms Extraction tasks. Finally, the Graph Database
Population and Enrichment allows us the representation of data retrieved into a Neo4j graph database.
Globally, the framework presents promising results that were validated using prototypes developed for this
purpose. In addition, the feasibility of extracting unstructured data, its syntactic and semantic interpretation,
and the graph database representation has also been demonstrated
An Experiment of Use and Reuse of Verb Valency in Morphosyntactic Disambiguation and Machine Translation for Euskara and North Sámi
Proceedings of the NODALIDA 2011 Workshop
Constraint Grammar Applications.
Editors: Eckhard Bick, Kristin Hagen, Kaili Müürisep, Trond Trosterud.
NEALT Proceedings Series, Vol. 14 (2011), 61–69.
© 2011 The editors and contributors.
Published by
Northern European Association for Language
Technology (NEALT)
http://omilia.uio.no/nealt .
Electronically published at
Tartu University Library (Estonia)
http://hdl.handle.net/10062/19231
- …