Στόχος της παρούσας διπλωματικής εργασίας είναι η μελέτη των τεχνολογιών RSS καθώς και η ανάπτυξη ενός RSS aggregator. Αυτό το σύστημα aggregator θα μπορεί να πραγματοποιεί αναζητήσεις στα περιεχόμενα των feeds τόσο για εύρεση ειδήσεων γεωγραφικού περιεχομένου όσο και θεματολογικού. / The goal of the current thesis is the study of the RSS technologies as well as the development of an RSS aggregator. This system will be able to search the contents of the feeds for geographic content as well as semantic content.

Sistemas de Recomendação ajudam na personalização de sites na Internet oferecendo conteúdo ou produtos específicos aos usuários. Com dispositivos móveis, aumentou o interesse do usuário em ter recomendações personalizadas de locais para ir de acordo com o seu histórico de navegação e avaliações como restaurantes e pontos turísticos. Para que as recomendações personalizadas por locais sejam mais precisas é necessário contextualizá-las de acordo com o interesse do usuário que caracterizado por locais que ele visitou e por regiões de interesse como moradia, onde trabalha ou mesmo onde passará férias. Várias técnicas de contextualização utilizaram todos os locais que o usuário visitou para geração da recomendação contextual do local, outras técnicas trabalham na arquitetura híbrida. Muitas assumem que é necessário a posição exata do usuário para que as recomendações sejam online, o que muitas vezes não é possível por limitações técnicas ou mesmo indisponibilização do usuário por questões de privacidade. O objetivo principal deste trabalho é geração de recomendações usando multicontextos de forma offline, gerando vários contextos de cada usuário. Os locais são recomendados utilizando apenas dados históricos, sem a localização exata no usuário do momento da recomendação. Para atingir este objetivo foram utilizadas técnicas de clustering para mapeamento e divisão dos contextos em regiões indicando o interesse do usuário gerando a recomendação final dos locais a partir de um método híbrido de recomendação que usa filtragem colaborativa e a recomendação contextual proposta. Os resultados mostraram que a técnica proposta apresenta recomendações melhores do que apenas a recomendação colaborativa pura e, para usuários assíduos, as recomendações são melhores do que as técnicas base usadas para comparação. / Recommender Systems help in web sites personalization, offering specific content or products to users. With mobile devices, user interest in Point-of-Interest (POI) recommendation has increased to receive recommendations about places to go according to your navigation and evaluation history in the web site. POI recommendation are improved by contextualizing according to users interest, based on places to where user has been and on regions of interest such as the region where the user lives, works or the region intends go on vacation. Many contextualization techniques use all places that user visited for generation of POI contextual recommendation. Other techniques use hybrid architectures and many of them assume that is necessary the exact point where the user is for online recommendation and this in not possible always due technical limitations or user privacy. The main objective of this work is the offline generation of recommendations using multicontexts. Places to be recommended use only user historical data, without the user current localization at the moment of recommendation. Several techniques have been used for clustering for mapping and division of contexts in regions, indicating the user interests and, finally, generating the final recommendation using a hybrid method with collaborative filtering and contextual recommendation proposed. The results indicate that the proposed technique builds better recommendations than the pure collaborative filtering technique and for heavy users the proposed technique has better results the baseline technique used for comparison.

Sistemas de Recomendação ajudam na personalização de sites na Internet oferecendo conteúdo ou produtos específicos aos usuários. Com dispositivos móveis, aumentou o interesse do usuário em ter recomendações personalizadas de locais para ir de acordo com o seu histórico de navegação e avaliações como restaurantes e pontos turísticos. Para que as recomendações personalizadas por locais sejam mais precisas é necessário contextualizá-las de acordo com o interesse do usuário que caracterizado por locais que ele visitou e por regiões de interesse como moradia, onde trabalha ou mesmo onde passará férias. Várias técnicas de contextualização utilizaram todos os locais que o usuário visitou para geração da recomendação contextual do local, outras técnicas trabalham na arquitetura híbrida. Muitas assumem que é necessário a posição exata do usuário para que as recomendações sejam online, o que muitas vezes não é possível por limitações técnicas ou mesmo indisponibilização do usuário por questões de privacidade. O objetivo principal deste trabalho é geração de recomendações usando multicontextos de forma offline, gerando vários contextos de cada usuário. Os locais são recomendados utilizando apenas dados históricos, sem a localização exata no usuário do momento da recomendação. Para atingir este objetivo foram utilizadas técnicas de clustering para mapeamento e divisão dos contextos em regiões indicando o interesse do usuário gerando a recomendação final dos locais a partir de um método híbrido de recomendação que usa filtragem colaborativa e a recomendação contextual proposta. Os resultados mostraram que a técnica proposta apresenta recomendações melhores do que apenas a recomendação colaborativa pura e, para usuários assíduos, as recomendações são melhores do que as técnicas base usadas para comparação. / Recommender Systems help in web sites personalization, offering specific content or products to users. With mobile devices, user interest in Point-of-Interest (POI) recommendation has increased to receive recommendations about places to go according to your navigation and evaluation history in the web site. POI recommendation are improved by contextualizing according to users interest, based on places to where user has been and on regions of interest such as the region where the user lives, works or the region intends go on vacation. Many contextualization techniques use all places that user visited for generation of POI contextual recommendation. Other techniques use hybrid architectures and many of them assume that is necessary the exact point where the user is for online recommendation and this in not possible always due technical limitations or user privacy. The main objective of this work is the offline generation of recommendations using multicontexts. Places to be recommended use only user historical data, without the user current localization at the moment of recommendation. Several techniques have been used for clustering for mapping and division of contexts in regions, indicating the user interests and, finally, generating the final recommendation using a hybrid method with collaborative filtering and contextual recommendation proposed. The results indicate that the proposed technique builds better recommendations than the pure collaborative filtering technique and for heavy users the proposed technique has better results the baseline technique used for comparison.

Submitted by Mario BC (mario@bc.ufrpe.br) on 2016-06-17T12:04:51Z No. of bitstreams: 1 Fernando Jorge Rodrigues Magalhaes.pdf: 3340571 bytes, checksum: 190faaa50a18c056123ab2a8a9e3e659 (MD5) / Made available in DSpace on 2016-06-17T12:04:51Z (GMT). No. of bitstreams: 1 Fernando Jorge Rodrigues Magalhaes.pdf: 3340571 bytes, checksum: 190faaa50a18c056123ab2a8a9e3e659 (MD5) Previous issue date: 2016-02-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This study analyzed a total of 1,863 serum samples from cats (domestic and feral), dogs, sheep, cattle, pigs, chickens and horses from Fernando de Noronha, Pernambuco-Brazil, to study the prevalence and spatial distribution of Toxoplasma gondii, and identify risk factors for some species. Indirect immunofluorescence test was performed by using cutoff 1:64 for pigs, sheep, cattle, horses and 1:16 to chickens, dogs and cats. To identify risk factors associated with infection by T. gondii was used univariate analysis and logistic regression for sheep, cattle and chickens. The spatial distribution of infection by this parasite was obtained by intensity Kernel estimator. Of all the animals sampled, 63.5% (1,183/1,863) were positive with titles ranging 16 to 1024 with high prevalence rates for chickens (88.4%), sheep (85.0%), cats domestic (71.26%), feral cats (54.74%) and dogs (48.75%). T. gondii infection is widespread in animals from Archipelago with high prevalence of infection observed in the definitive host (cats), also identified as a risk factor for some species studied. The results indicate to the urgent need for health intervention to strengthen the strategic and integrated measures to prevent and control this disease to prevent infection in animals and humans on this island. / Nesse estudo foram analisadas um total de 1.863 amostras de soro de felinos (domésticos e ferais), caninos, ovinos, bovinos, suínos, galinhas e equinos criados no arquipélago de Fernando de Noronha, Pernambuco para estudar a prevalência e distribuição espacial da infecção por Toxoplasma gondii, além de identificar os fatores de risco para algumas espécies de produção. A pesquisa de anticorpos IgG anti-T. gondii foi realizada pela reação de Imunofluorescência indireta (RIFI), utilizando-se ponto de corte 1:64 para os suínos, ovinos, bovinos, equinos e 1:16 para galinhas, cães e gatos. Para identificar os fatores de risco associados à infecção por T. gondii foi empregada a análise univariada e regressão logística para ovinos, bovino e galinhas. A distribuição espacial da infecção por este protozoário foi obtida por meio do estimador de intensidade de Kernel. Do total dos animais amostrados, 63,5% (1.183/1.863) foram positivos com títulos que variaram de 16 a 1024 com destaque para as elevadas prevalências obtidas para galinhas (88,4%), ovinos (85,0%), bovinos (10,7%), gatos domésticos (71,26%), gatos ferais (60,74%), cães (48,75%), suínos (51,85%) e equinos (22,7%). A infecção por T. gondii está disseminada nos animais do Arquipélago com focos distribuídos por toda a ilha, resultado da alta prevalência da infecção observada no hospedeiro definitivo (felinos), também identificado como fator de risco para algumas espécies estudadas. Os resultados sinalizam para a necessidade urgente de intervenção sanitária para reforçar as medidas estratégicas e integradas na prevenção e controle dessa enfermidade para prevenir a infecção em animais e humanos desta ilha.

There is a need to define a more efficient and accurate approach to aquatic habitat mapping. Traditional approaches have focused on intense biological/non-biological sampling and observation analysis within specific and restrained scales. Therefore, an underwater video mapping system (UVMS) has been developed in efforts to identify federally protected aquatic species’ habitats within the Obed Wild and Scenic River (OBRI). The UVMS kayak apparatus provides georeferenced video footage correlated with GPS (global positioning systems) for GIS (geographic information systems) mapping applications. Based on its fluvial and geomorphological trends, OBRI was dissected quantitatively and integrated into databases for species-specific GIS habitat queries. Substrate type, depth, above water river characteristics (pool/riffle/run), and substrate embeddedness were extracted to access specific habitats. To better pinpoint optimal microhabitat locations, a physical habitat suitability model was developed to rank preferred habitat locales. Rankings were sequentially broken into five categories: optimal, sub-optimal, marginal, sub-marginal, and poor habitat criteria. Habitat suitability findings for the interested species habitats varied tremendously, favoring fish species. Spotfin chub, Erimonax monacha, optimal habitat was found to cover 22.14 km of river length within OBRI (30 % of OBRI’s spatial extent). The blackside dace, Phoxinus cumberlandensis, (38.9 km) and the duskytail darter, Etheostoma percnurum, (50.9 km) met optimal habitat conditions that yielded 51% and 69% of OBRI’s spatial extent, respectively. In general, optimal habitats for the six mussels were sporadically distributed and had low occurrences. Primarily, these mussel species prefer highly embedded areas with very specific depths and pool/riffle/run conditions. Cumberland elktoe, Alasmidonta atropurea, optimal habitat ranges spanned across 4.32 km (6% of OBRI’s spatial extent) with most of the habitat characteristics in OBRI being marginal. The purple bean, Villosa perpurpurea, optimal habitat was identified within 2.61 km of OBRI (3.5% of OBRI’s spatial extent). Most of the physical conditions of OBRI supplied poor to sub-marginal habitat for the purple bean, at least from a thalweg perspective. Only 385 m coincided with optimal habitat for the cumberland bean, Villosa trabalis, (0.5% of OBRI’s spatial extent) with most habitats in long sub-marginal reaches. Optimal habitats for the cumberlandian combshell, Epioblasma brevidens, the tan riffleshell, Epioblasma florentina walkeri, and the littlewing pearlymussel, Pegias fibula, were deficient, only occurring in 484 m, 276 m, and 252 m of OBRI, respectively (0.7%, 0.4%, and 0.3% of OBRI’s spatial extent). Marginal to sub-marginal habitats dominated the park for these three mussel species.

There is a need to define a more efficient and accurate approach to aquatic habitat mapping. Traditional approaches have focused on intense biological/non-biological sampling and observation analysis within specific and restrained scales. Therefore, an underwater video mapping system (UVMS) has been developed in efforts to identify federally protected aquatic species’ habitats within the Obed Wild and Scenic River (OBRI). The UVMS kayak apparatus provides georeferenced video footage correlated with GPS (global positioning systems) for GIS (geographic information systems) mapping applications. Based on its fluvial and geomorphological trends, OBRI was dissected quantitatively and integrated into databases for species-specific GIS habitat queries. Substrate type, depth, above water river characteristics (pool/riffle/run), and substrate embeddedness were extracted to access specific habitats. To better pinpoint optimal microhabitat locations, a physical habitat suitability model was developed to rank preferred habitat locales. Rankings were sequentially broken into five categories: optimal, sub-optimal, marginal, sub-marginal, and poor habitat criteria. Habitat suitability findings for the interested species habitats varied tremendously, favoring fish species. Spotfin chub, Erimonax monacha, optimal habitat was found to cover 22.14 km of river length within OBRI (30 % of OBRI’s spatial extent). The blackside dace, Phoxinus cumberlandensis, (38.9 km) and the duskytail darter, Etheostoma percnurum, (50.9 km) met optimal habitat conditions that yielded 51% and 69% of OBRI’s spatial extent, respectively. In general, optimal habitats for the six mussels were sporadically distributed and had low occurrences. Primarily, these mussel species prefer highly embedded areas with very specific depths and pool/riffle/run conditions. Cumberland elktoe, Alasmidonta atropurea, optimal habitat ranges spanned across 4.32 km (6% of OBRI’s spatial extent) with most of the habitat characteristics in OBRI being marginal. The purple bean, Villosa perpurpurea, optimal habitat was identified within 2.61 km of OBRI (3.5% of OBRI’s spatial extent). Most of the physical conditions of OBRI supplied poor to sub-marginal habitat for the purple bean, at least from a thalweg perspective. Only 385 m coincided with optimal habitat for the cumberland bean, Villosa trabalis, (0.5% of OBRI’s spatial extent) with most habitats in long sub-marginal reaches. Optimal habitats for the cumberlandian combshell, Epioblasma brevidens, the tan riffleshell, Epioblasma florentina walkeri, and the littlewing pearlymussel, Pegias fibula, were deficient, only occurring in 484 m, 276 m, and 252 m of OBRI, respectively (0.7%, 0.4%, and 0.3% of OBRI’s spatial extent). Marginal to sub-marginal habitats dominated the park for these three mussel species.