Bryophytes distribution along an altitudinal gradient of native forest in Pico island (Azores): preliminary results of epiphytic genera

MOVECLIM, Mid Course Meeting, 2-6 September 2013, Réunion (Mascarenes).

Android as a cloud ticket validator

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Informática e de Computadores

Structural, physical, and chemical modifications induced by microwave heating on native agar-like galactans

Native agars from Gracilaria vermiculophylla produced in sustainable aquaculture systems (IMTA) were extracted under conventional (TWE) and microwave (MAE) heating. The optimal extracts from both processes were compared in terms of their properties. The agars’ structure was further investigated through Fourier transform infrared and NMR spectroscopy. Both samples showed a regular structure with an identical backbone, β-D-galactose (G) and 3,6-anhydro-α-L-galactose (LA) units; a considerable degree of methylation was found at C6 of the G units and, to a lesser extent, at C2 of the LA residues. The methylation degree in the G units was lower for MAEopt agar; the sulfate content was also reduced. MAE led to higher agar recoveries with drastic extraction time and solvent volume reductions. Two times lower values of [η] and Mv obtained for the MAEopt sample indicate substantial depolymerization of the polysaccharide backbone; this was reflected in its gelling properties; yet it was clearly appropriate for commercial application in soft-texture food products.

Efficiency of sampling methods and effort to assess arthropod diversity in Azorean native forests

The BALA project (Biodiversity of Arthropods of Laurisilva of the Azores) is a research initiative to quantify the spatial distribution of arthropod biodiversity in native forests of the Azores archipelago. Arthropods were collected using a combination of two techniques, targeting epigean (ground dwelling) and canopy (arboreal) arthropods: pitfall traps (with Turquin and Ethylene solutions) and beating samples (using the three most dominant plant species). A total of 109 transects distributed amongst 18 forest fragments in seven of the nine Azorean islands were used in this study. The performance of alternative sampling methods and effort were tested. No significant differences were found in the accumulated number of species captured whether an alternative method was used or whether another transect with similar effort was established in another location within the same fragment. A combination of Ethylene and Turquin traps captured more species per individual, Turquin and beating captured more species per sample, and Turquin captured more species per unit time. An optimization exercise was performed and we found that the protocol applied during recent years is very close to optimal, allowing its future replication with confidence. The minimum combinations of sampling effort and methods, in order to monitor or to inventory diversity, taking into account different proportions of sample completeness are discussed.

Explorador integrado de serviços de armazenamento na cloud: cloud cockpit

Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Private cloud computing platforms. Analysis and implementation in a Higher Education Institution

The constant evolution of the Internet and its increasing use and subsequent entailing to private and public activities, resulting in a strong impact on their survival, originates an emerging technology. Through cloud computing, it is possible to abstract users from the lower layers to the business, focusing only on what is most important to manage and with the advantage of being able to grow (or degrades) resources as needed. The paradigm of cloud arises from the necessity of optimization of IT resources evolving in an emergent and rapidly expanding and technology. In this regard, after a study of the most common cloud platforms and the tactic of the current implementation of the technologies applied at the Institute of Biomedical Sciences of Abel Salazar and Faculty of Pharmacy of Oporto University a proposed evolution is suggested in order adorn certain requirements in the context of cloud computing.

Sensing Cloud Optimization applied to a non-convex constrained economical dispatch

Conferência: 39th Annual Conference of the IEEE Industrial-Electronics-Society (IECON) - NOV 10-14, 2013

Cloud computing sobre a plataforma Windows Azure

A utilização massiva da internet e dos serviços que oferece por parte do utilizador final potencia a evolução dos mesmos, motivando as empresas a apostarem no desenvolvimento deste tipo de soluções. Requisitos como o poder de computação, flexibilidade e escalabilidade tornam-se cada vez mais indissociáveis do desenvolvimento aplicacional, o que leva ao surgimento de paradigmas como o de Cloud Computing. É neste âmbito que surge o presente trabalho. Com o objetivo de estudar o paradigma de Cloud Computing inicia-se um estudo sobre esta temática, onde é detalhado o seu conceito, a sua evolução histórica e comparados os diferentes tipos de implementações que suporta. O estudo detalha posteriormente a plataforma Azure, sendo analisada a sua topologia e arquitetura, detalhando-se os seus componentes e a forma como esta mitiga alguns dos problemas mencionados. Com o conhecimento teórico é desenvolvido um protótipo prático sobre esta plataforma, em que se exploram algumas das particularidades da topologia e se interage com as principais redes sociais. O estudo culmina com uma análise sobre os benefícios e desvantagens do Azure e através de um levantamento das necessidades da empresa, determinam-se as oportunidades que a utilização da plataforma poderá proporcionar.

Informal learning recognition through a cloud ecosystem

Learning and teaching processes, like all human activities, can be mediated through the use of tools. Information and communication technologies are now widespread within education. Their use in the daily life of teachers and learners affords engagement with educational activities at any place and time and not necessarily linked to an institution or a certificate. In the absence of formal certification, learning under these circumstances is known as informal learning. Despite the lack of certification, learning with technology in this way presents opportunities to gather information about and present new ways of exploiting an individual’s learning. Cloud technologies provide ways to achieve this through new architectures, methodologies, and workflows that facilitate semantic tagging, recognition, and acknowledgment of informal learning activities. The transparency and accessibility of cloud services mean that institutions and learners can exploit existing knowledge to their mutual benefit. The TRAILER project facilitates this aim by providing a technological framework using cloud services, a workflow, and a methodology. The services facilitate the exchange of information and knowledge associated with informal learning activities ranging from the use of social software through widgets, computer gaming, and remote laboratory experiments. Data from these activities are shared among institutions, learners, and workers. The project demonstrates the possibility of gathering information related to informal learning activities independently of the context or tools used to carry them out.

Exploração da Point Cloud Library aplicada à percepção em sistemas autónomos

A navegação e a interpretação do meio envolvente por veículos autónomos em ambientes não estruturados continua a ser um grande desafio na actualidade. Sebastian Thrun, descreve em [Thr02], que o problema do mapeamento em sistemas robóticos é o da aquisição de um modelo espacial do meio envolvente do robô. Neste contexto, a integração de sistemas sensoriais em plataformas robóticas, que permitam a construção de mapas do mundo que as rodeia é de extrema importância. A informação recolhida desses dados pode ser interpretada, tendo aplicabilidade em tarefas de localização, navegação e manipulação de objectos. Até à bem pouco tempo, a generalidade dos sistemas robóticos que realizavam tarefas de mapeamento ou Simultaneous Localization And Mapping (SLAM), utilizavam dispositivos do tipo laser rangefinders e câmaras stereo. Estes equipamentos, para além de serem dispendiosos, fornecem apenas informação bidimensional, recolhidas através de cortes transversais 2D, no caso dos rangefinders. O paradigma deste tipo de tecnologia mudou consideravelmente, com o lançamento no mercado de câmaras RGB-D, como a desenvolvida pela PrimeSense TM e o subsequente lançamento da Kinect, pela Microsoft R para a Xbox 360 no final de 2010. A qualidade do sensor de profundidade, dada a natureza de baixo custo e a sua capacidade de aquisição de dados em tempo real, é incontornável, fazendo com que o sensor se tornasse instantaneamente popular entre pesquisadores e entusiastas. Este avanço tecnológico deu origem a várias ferramentas de desenvolvimento e interacção humana com este tipo de sensor, como por exemplo a Point Cloud Library [RC11] (PCL). Esta ferramenta tem como objectivo fornecer suporte para todos os blocos de construção comuns que uma aplicação 3D necessita, dando especial ênfase ao processamento de nuvens de pontos de n dimensões adquiridas a partir de câmaras RGB-D, bem como scanners laser, câmaras Time-of-Flight ou câmaras stereo. Neste contexto, é realizada nesta dissertação, a avaliação e comparação de alguns dos módulos e métodos constituintes da biblioteca PCL, para a resolução de problemas inerentes à construção e interpretação de mapas, em ambientes indoor não estruturados, utilizando os dados provenientes da Kinect. A partir desta avaliação, é proposta uma arquitectura de sistema que sistematiza o registo de nuvens de pontos, correspondentes a vistas parciais do mundo, num modelo global consistente. Os resultados da avaliação realizada à biblioteca PCL atestam a sua viabilidade, para a resolução dos problemas propostos. Prova da sua viabilidade, são os resultados práticos obtidos, da implementação da arquitectura de sistema proposta, que apresenta resultados de desempenho interessantes, como também boas perspectivas de integração deste tipo de conceitos e tecnologia em plataformas robóticas desenvolvidas no âmbito de projectos do Laboratório de Sistemas Autónomos (LSA).

Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud

3D laser scanning is becoming a standard technology to generate building models of a facility's as-is condition. Since most constructions are constructed upon planar surfaces, recognition of them paves the way for automation of generating building models. This paper introduces a new logarithmically proportional objective function that can be used in both heuristic and metaheuristic (MH) algorithms to discover planar surfaces in a point cloud without exploiting any prior knowledge about those surfaces. It can also adopt itself to the structural density of a scanned construction. In this paper, a metaheuristic method, genetic algorithm (GA), is used to test this introduced objective function on a synthetic point cloud. The results obtained show the proposed method is capable to find all plane configurations of planar surfaces (with a wide variety of sizes) in the point cloud with a minor distance to the actual configurations. © 2014 IEEE.

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

Testing native speakers of German and Portuguese on the understanding of topological operators-line-region relations in gvSIG

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Meios de partilha de recursos educativos digitais: LMS, CMS e Cloud Computing

Para muitos, o ato de ensinar, era e continua a ser uma “arte”, em que os professores e os grandes mestres mais eficientes são aqueles que têm a capacidade e a arte de fazer passar as suas mensagens e conhecimentos, de forma simples e apelativa, independentemente da área de estudo. A informação relacionada com a aula, é cada vez mais digital, sendo importante, por parte dos docentes, o domínio de tecnologias de criação, organização e disponibilização de conteúdos. Essa partilha foi inicialmente possível pelas páginas Web e mais tarde pelas plataformas LMS (Learning Management System). Criar um Website era uma tarefa complicada quer ao nível do seu custo quer ao nível do domínio da tecnologia Web e era por vezes necessário contratar profissionais para o efeito. Surgiram então as CMS (Content Management System) que são tecnologias Open Source, que permitem a gestão de conteúdos. Neste sentido foi realizado um estudo com o objetivo de aferir sobre as competências dos professores no domínio da partilha de Gestão de Conteúdos Digitais. O presente estudo permitiu retirar conclusões sobre o potencial e aplicabilidade das CMS no ensino. O principal objetivo do presente estudo incidiu no potencial de distribuição e partilha de Recursos Educativos Digitais organizados sobre o ponto de vista pedagógico aos alunos. Foi ainda analisado e estudado o papel do Cloud Computing no processo de partilha colaborativa de documentos. Foi delineado como suporte à presente investigação um curso modelo que por sua vez foi implementado nas três principais CMS da atualidade e avaliado o potencial de cada uma neste contexto. Finalmente foram apresentadas as conclusões retiradas do presente estudo.

Towards high-available and energy-efficient virtual computing environments in the cloud

Empowered by virtualisation technology, cloud infrastructures enable the construction of flexi- ble and elastic computing environments, providing an opportunity for energy and resource cost optimisation while enhancing system availability and achieving high performance. A crucial re- quirement for effective consolidation is the ability to efficiently utilise system resources for high- availability computing and energy-efficiency optimisation to reduce operational costs and carbon footprints in the environment. Additionally, failures in highly networked computing systems can negatively impact system performance substantially, prohibiting the system from achieving its initial objectives. In this paper, we propose algorithms to dynamically construct and readjust vir- tual clusters to enable the execution of users’ jobs. Allied with an energy optimising mechanism to detect and mitigate energy inefficiencies, our decision-making algorithms leverage virtuali- sation tools to provide proactive fault-tolerance and energy-efficiency to virtual clusters. We conducted simulations by injecting random synthetic jobs and jobs using the latest version of the Google cloud tracelogs. The results indicate that our strategy improves the work per Joule ratio by approximately 12.9% and the working efficiency by almost 15.9% compared with other state-of-the-art algorithms.