937 resultados para Amazon Cloud Player
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Aquest treball final de carrera consisteix en la realització d'un estudi de la usabilitat i accessibilitat de tres gestors de medis multimèdia: iTunes, Google Music i Amazon Cloud Player. A través d'observacions contextuals, avaluacions heurístiques i tests d'usuaris he realitzat una anàlisi comparativa. Per tal d'esquematitzar tota aquesta informació he confeccionat una taula amb els punts forts i punts febles de cada aplicació per concloure amb la proposta de millores per a cada un dels gestors de medis.
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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.
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In global scientific experiments with collaborative scenarios involving multinational teams there are big challenges related to data access, namely data movements are precluded to other regions or Clouds due to the constraints on latency costs, data privacy and data ownership. Furthermore, each site is processing local data sets using specialized algorithms and producing intermediate results that are helpful as inputs to applications running on remote sites. This paper shows how to model such collaborative scenarios as a scientific workflow implemented with AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic), a decentralized framework offering a feasible solution to run the workflow activities on distributed data centers in different regions without the need of large data movements. The AWARD workflow activities are independently monitored and dynamically reconfigured and steering by different users, namely by hot-swapping the algorithms to enhance the computation results or by changing the workflow structure to support feedback dependencies where an activity receives feedback output from a successor activity. A real implementation of one practical scenario and its execution on multiple data centers of the Amazon Cloud is presented including experimental results with steering by multiple users.
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Cloud streets are common feature in the Amazon Basin. They form from the combination of the vertical trade wind stress and moist convection. Here, satellite imagery, data collected during the COBRA-PARA (Caxiuan Observations in the Biosphere, River and Atmosphere of Para) field campaign, and high resolution modeling are used to understand the streets` formation and behavior. The observations show that the streets have an aspect ratio of about 3.5 and they reach their maximum activity around 15:00 UTC when the wind shear is weaker, and the convective boundary layer reaches its maximum height. The simulations reveal that the cloud streets onset is caused by the local circulations and convection produced at the interfaces between forest and rivers of the Amazon. The satellite data and modeling show that the large rivers anchor the cloud streets producing a quasi-stationary horizontal pattern. The streets are associated with horizontal roll vortices parallel to the mean flow that organizes the turbulence causing advection of latent heat flux towards the upward branches. The streets have multiple warm plumes that promote a connection between the rolls. These spatial patterns allow fundamental insights on the interpretation of the Amazon exchanges between surface and atmosphere with important consequences for the climate change understanding.
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This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.
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As a contribution to the Large-Scale Biosphere-Atmosphere Experiment in Amazonia - Cooperative LBA Airborne Regional Experiment (LBA-CLAIRE-2001) field campaign in the heart of the Amazon Basin, we analyzed the temporal and spatial dynamics of the urban plume of Manaus City during the wet-to-dry season transition period in July 2001. During the flights, we performed vertical stacks of crosswind transects in the urban outflow downwind of Manaus City, measuring a comprehensive set of trace constituents including O(3), NO, NO(2), CO, VOC, CO(2), and H(2)O. Aerosol loads were characterized by concentrations of total aerosol number (CN) and cloud condensation nuclei (CCN), and by light scattering properties. Measurements over pristine rainforest areas during the campaign showed low levels of pollution from biomass burning or industrial emissions, representative of wet season background conditions. The urban plume of Manaus City was found to be joined by plumes from power plants south of the city, all showing evidence of very strong photochemical ozone formation. One episode is discussed in detail, where a threefold increase in ozone mixing ratios within the atmospheric boundary layer occurred within a 100 km travel distance downwind of Manaus. Observation-based estimates of the ozone production rates in the plume reached 15 ppb h(-1). Within the plume core, aerosol concentrations were strongly enhanced, with Delta CN/Delta CO ratios about one order of magnitude higher than observed in Amazon biomass burning plumes. Delta CN/Delta CO ratios tended to decrease with increasing transport time, indicative of a significant reduction in particle number by coagulation, and without substantial new particle nucleation occurring within the time/space observed. While in the background atmosphere a large fraction of the total particle number served as CCN (about 60-80% at 0.6% supersaturation), the CCN/CN ratios within the plume indicated that only a small fraction (16 +/- 12 %) of the plume particles were CCN. The fresh plume aerosols showed relatively weak light scattering efficiency. The CO-normalized CCN concentrations and light scattering coefficients increased with plume age in most cases, suggesting particle growth by condensation of soluble organic or inorganic species. We used a Single Column Chemistry and Transport Model (SCM) to infer the urban pollution emission fluxes of Manaus City, implying observed mixing ratios of CO, NO(x) and VOC. The model can reproduce the temporal/spatial distribution of ozone enhancements in the Manaus plume, both with and without accounting for the distinct (high NO(x)) contribution by the power plants; this way examining the sensitivity of ozone production to changes in the emission rates of NO(x). The VOC reactivity in the Manaus region was dominated by a high burden of biogenic isoprene from the background rainforest atmosphere, and therefore NO(x) control is assumed to be the most effective ozone abatement strategy. Both observations and models show that the agglomeration of NO(x) emission sources, like power plants, in a well-arranged area can decrease the ozone production efficiency in the near field of the urban populated cores. But on the other hand remote areas downwind of the city then bear the brunt, being exposed to increased ozone production and N-deposition. The simulated maximum stomatal ozone uptake fluxes were 4 nmol m(-2) s(-1) close to Manaus, and decreased only to about 2 nmol m(-2) s(-1) within a travel distance >1500 km downwind from Manaus, clearly exceeding the critical threshold level for broadleaf trees. Likewise, the simulated N deposition close to Manaus was similar to 70 kg N ha(-1) a(-1) decreasing only to about 30 kg N ha(-1) a(-1) after three days of simulation.
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Number fluxes of particles with diameter larger than 10 nm were measured with the eddy covariance method over the Amazon rain forest during the wet season as part of the LBA (The Large Scale Biosphere Atmosphere Experiment in Amazonia) campaign 2008. The primary goal was to investigate whether sources or sinks dominate the aerosol number flux in the tropical rain forest-atmosphere system. During the measurement campaign, from 12 March to 18 May, 60% of the particle fluxes pointed downward, which is a similar fraction to what has been observed over boreal forests. The net deposition flux prevailed even in the absolute cleanest atmospheric conditions during the campaign and therefore cannot be explained only by deposition of anthropogenic particles. The particle transfer velocity v(t) increased with increasing friction velocity and the relation is described by the equation v(t) = 2.4x10(-3)xu(*) where u(*) is the friction velocity. Upward particle fluxes often appeared in the morning hours and seem to a large extent to be an effect of entrainment fluxes into a growing mixed layer rather than primary aerosol emission. In general, the number source of primary aerosol particles within the footprint area of the measurements was small, possibly because the measured particle number fluxes reflect mostly particles less than approximately 200 nm. This is an indication that the contribution of primary biogenic aerosol particles to the aerosol population in the Amazon boundary layer may be low in terms of number concentrations. However, the possibility of horizontal variations in primary aerosol emission over the Amazon rain forest cannot be ruled out.
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In-situ measurements in convective clouds (up to the freezing level) over the Amazon basin show that smoke from deforestation fires prevents clouds from precipitating until they acquire a vertical development of at least 4 km, compared to only 1-2 km in clean clouds. The average cloud depth required for the onset of warm rain increased by similar to 350 m for each additional 100 cloud condensation nuclei per cm(3) at a super-saturation of 0.5% (CCN0.5%). In polluted clouds, the diameter of modal liquid water content grows much slower with cloud depth (at least by a factor of similar to 2), due to the large number of droplets that compete for available water and to the suppressed coalescence processes. Contrary to what other studies have suggested, we did not observe this effect to reach saturation at 3000 or more accumulation mode particles per cm(3). The CCN0.5% concentration was found to be a very good predictor for the cloud depth required for the onset of warm precipitation and other microphysical factors, leaving only a secondary role for the updraft velocities in determining the cloud drop size distributions. The effective radius of the cloud droplets (r(e)) was found to be a quite robust parameter for a given environment and cloud depth, showing only a small effect of partial droplet evaporation from the cloud's mixing with its drier environment. This supports one of the basic assumptions of satellite analysis of cloud microphysical processes: the ability to look at different cloud top heights in the same region and regard their r(e) as if they had been measured inside one well developed cloud. The dependence of r(e) on the adiabatic fraction decreased higher in the clouds, especially for cleaner conditions, and disappeared at r(e)>=similar to 10 mu m. We propose that droplet coalescence, which is at its peak when warm rain is formed in the cloud at r(e)=similar to 10 mu m, continues to be significant during the cloud's mixing with the entrained air, cancelling out the decrease in r(e) due to evaporation.
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The quantification of sources of carbonaceous aerosol is important to understand their atmospheric concentrations and regulating processes and to study possible effects on climate and air quality, in addition to develop mitigation strategies. In the framework of the European Integrated Project on Aerosol Cloud Climate Interactions (EUCAARI) fine (D(p) < 2.5 mu m) and coarse (2.5 mu m < Dp < 10 mu m) aerosol particles were sampled from February to June (wet season) and from August to September (dry season) 2008 in the central Amazon basin. The mass of fine particles averaged 2.4 mu g m(-3) during the wet season and 4.2 mu g m(-3) during the dry season. The average coarse aerosol mass concentration during wet and dry periods was 7.9 and 7.6 mu g m(-3), respectively. The overall chemical composition of fine and coarse mass did not show any seasonality with the largest fraction of fine and coarse aerosol mass explained by organic carbon (OC); the average OC to mass ratio was 0.4 and 0.6 in fine and coarse aerosol modes, respectively. The mass absorbing cross section of soot was determined by comparison of elemental carbon and light absorption coefficient measurements and it was equal to 4.7 m(2) g(-1) at 637 nm. Carbon aerosol sources were identified by Positive Matrix Factorization (PMF) analysis of thermograms: 44% of fine total carbon mass was assigned to biomass burning, 43% to secondary organic aerosol (SOA), and 13% to volatile species that are difficult to apportion. In the coarse mode, primary biogenic aerosol particles (PBAP) dominated the carbonaceous aerosol mass. The results confirmed the importance of PBAP in forested areas. The source apportionment results were employed to evaluate the ability of global chemistry transport models to simulate carbonaceous aerosol sources in a regional tropical background site. The comparison showed an overestimation of elemental carbon (EC) by the TM5 model during the dry season and OC both during the dry and wet periods. The overestimation was likely due to the overestimation of biomass burning emission inventories and SOA production over tropical areas.
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Biogeochemistry is hosting this special thematic issue devoted to studies of land-water interactions, as part of the Large-scale Biosphere-Atmosphere Experiment in Amaznia (LBA). This compilation of papers covers a broad range of topics with a common theme of coupling land and water processes, across pristine and impacted systems. Findings highlighted that hydrologic flowpaths are clearly important across basin size and structure in determining how water and solutes reach streams. Land-use changes have pronounced impacts on flowpaths, and subsequently, on stream chemistry, from small streams to large rivers. Carbon is produced and transformed across a broad array of fluvial environments and wetlands. Surface waters are not only driven by, but provide feedback to, the atmosphere.
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O presente projecto tem como objectivo a disponibilização de uma plataforma de serviços para gestão e contabilização de tempo remunerável, através da marcação de horas de trabalho, férias e faltas (com ou sem justificação). Pretende-se a disponibilização de relatórios com base nesta informação e a possibilidade de análise automática dos dados, como por exemplo excesso de faltas e férias sobrepostas de trabalhadores. A ênfase do projecto está na disponibilização de uma arquitectura que facilite a inclusão destas funcionalidades. O projecto está implementado sobre a plataforma Google App Engine (i.e. GAE), de forma a disponibilizar uma solução sob o paradigma de Software as a Service, com garantia de disponibilidade e replicação de dados. A plataforma foi escolhida a partir da análise das principais plataformas cloud existentes: Google App Engine, Windows Azure e Amazon Web Services. Foram analisadas as características de cada plataforma, nomeadamente os modelos de programação, os modelos de dados disponibilizados, os serviços existentes e respectivos custos. A escolha da plataforma foi realizada com base nas suas características à data de iniciação do presente projecto. A solução está estruturada em camadas, com as seguintes componentes: interface da plataforma, lógica de negócio e lógica de acesso a dados. A interface disponibilizada está concebida com observação dos princípios arquitecturais REST, suportando dados nos formatos JSON e XML. A esta arquitectura base foi acrescentada uma componente de autorização, suportada em Spring-Security, sendo a autenticação delegada para os serviços Google Acounts. De forma a permitir o desacoplamento entre as várias camadas foi utilizado o padrão Dependency Injection. A utilização deste padrão reduz a dependência das tecnologias utilizadas nas diversas camadas. Foi implementado um protótipo, para a demonstração do trabalho realizado, que permite interagir com as funcionalidades do serviço implementadas, via pedidos AJAX. Neste protótipo tirou-se partido de várias bibliotecas javascript e padrões que simplificaram a sua realização, tal como o model-view-viewmodel através de data binding. Para dar suporte ao desenvolvimento do projecto foi adoptada uma abordagem de desenvolvimento ágil, baseada em Scrum, de forma a implementar os requisitos do sistema, expressos em user stories. De forma a garantir a qualidade da implementação do serviço foram realizados testes unitários, sendo também feita previamente a análise da funcionalidade e posteriormente produzida a documentação recorrendo a diagramas UML.
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Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Informática e de Computadores
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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If widespread deforestation in Amazon results in reduced evaporative water flux, then either a decrease in evaporation is compensated locally by reduced rainfall,or else changed moisture balance expresses itself downwind in the yet undisturbed forest. The question of where rain will occur is crucial. It is suggested that the appearance of clouds and the occurrence of rainout is governed primarily by the interplay of local meteorologic and physical geography parameters with the atmospheric stability structure except for a few well-defined periods when rain is dominated by large scale atmospheric instability. This means that the study of these phenomena (local heat balances,studies on cloud formation mechanism, vertical atmospheric stability, etc.) must be made on the scale of the cloud size, a few tens of kilometers at most.
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En aquest Treball Final de Grau s'ha implementat un clúster d'alta eficiència (HTC) amb nodes físics d'una aula d'informàtica i nodes virtuals a partir d'instàncies d'Amazon EC2 (Elastic Compute Cloud). Mitjançant la creació de dos bash scripts es gestionarà la posada en marxa dels nodes del clúster, tant físics com virtuals, per tal d'optimitzar l'ús dels recursos físics, reduir el cost energètic i disposar de la flexibilitat que ofereix el sistema de màquines virtuals d'Amazon EC2.