922 resultados para Attribute-file map
Resumo:
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
Resumo:
MSC Dissertation in Computer Engineering
Resumo:
Dissertação apresentada para obtenção do Grau de Doutor em Informática Pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
Resumo:
Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
Resumo:
Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
Resumo:
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
Resumo:
Text file evaluation is an emergent topic in e-learning that responds to the shortcomings of the assessment based on questions with predefined answers. Questions with predefined answers are formalized in languages such as IMS Question & Test Interoperability Specification (QTI) and supported by many e-learning systems. Complex evaluation domains justify the development of specialized evaluators that participate in several business processes. The goal of this paper is to formalize the concept of a text file evaluation in the scope of the E-Framework – a service oriented framework for development of e-learning systems maintained by a community of practice. The contribution includes an abstract service type and a service usage model. The former describes the generic capabilities of a text file evaluation service. The later is a business process involving a set of services such as repositories of learning objects and learning management systems.
Resumo:
The Evidence Accumulation Clustering (EAC) paradigm is a clustering ensemble method which derives a consensus partition from a collection of base clusterings obtained using different algorithms. It collects from the partitions in the ensemble a set of pairwise observations about the co-occurrence of objects in a same cluster and it uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix. The Probabilistic Evidence Accumulation for Clustering Ensembles (PEACE) algorithm is a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix based on a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters. In this paper we extend the PEACE algorithm by deriving a consensus solution according to a MAP approach with Dirichlet priors defined for the unknown probabilistic cluster assignments. In particular, we study the positive regularization effect of Dirichlet priors on the final consensus solution with both synthetic and real benchmark data.
Resumo:
Dissertação apresentada como requisito parcial para a obtenção do grau de mestre em Estatística e Gestão de Informação.
Resumo:
Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.
Resumo:
Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.
Resumo:
Leadership and Management in Engineering, January 2009
Resumo:
Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
Resumo:
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies
Resumo:
Information technologies (ITs), and sports resources and services aid the potential to transform governmental organizations, and play an important role in contributing to sustainable communities development, respectively. Spatial data is a crucial source to support sports planning and management. Low-cost mobile geospatial tools bring productive and accurate data collection, and their use combining a handy and customized graphical user interface (GUI) (forms, mapping, media support) is still in an early stage. Recognizing the benefits — efficiency, effectiveness, proximity to citizens — that Mozambican Minister of Youth and Sports (MJD) can achieve with information resulted from the employment of a low-cost data collection platform, this project presents the development of a mobile mapping application (app) — m-SportGIS — under Open Source (OS) technologies and a customized evolutionary software methodology. The app development embraced the combination of mobile web technologies and Application Programming Interfaces (APIs) (e.g. Sencha Touch (ST), Apache Cordova, OpenLayers) to deploy a native-to-the-device (Android operating system) product, taking advantage of device’s capabilities (e.g. File system, Geolocation, Camera). In addition to an integrated Web Map Service (WMS), was created a local and customized Tile Map Service (TMS) to serve up cached data, regarding the IT infrastructures limitations in several Mozambican regions. m-SportGIS is currently being exploited by Mozambican Government staff to inventory all kind of sports facilities, which resulted and stored data feeds a WebGIS platform to manage Mozambican sports resources.