886 resultados para Cloud Fraction


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Nearly one billion smart mobile devices are now used for a growing number of tasks, such as browsing the web and accessing online services. In many communities, such devices are becoming the platform of choice for tasks traditionally carried out on a personal computer. However, despite the advances, these devices are still lacking in resources compared to their traditional desktop counterparts. Mobile cloud computing is seen as a new paradigm that can address the resource shortcomings in these devices with the plentiful computing resources of the cloud. This can enable the mobile device to be used for a large range of new applications hosted in the cloud that are too resource demanding to run locally. Bringing these two technologies together presents various difficulties. In this paper, we examine the advantages of the mobile cloud and the new approaches to applications it enables. We present our own solution to create a positive user experience for such applications and describe how it enables these applications.

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This paper presents our efforts to bridge the gap between mobile context awareness, and mobile cloud services, using the Cloud Personal Assistant (CPA). The CPA is a part of the Context Aware Mobile Cloud Services (CAMCS) middleware, which we continue to develop. Specifically, we discuss the development and evaluation of the Context Processor component of this middleware. This component collects context data from the mobile devices of users, which is then provided to the CPA of each user, for use with mobile cloud services. We discuss the architecture and implementation of the Context Processor, followed by the evaluation. We introduce context profiles for the CPA, which influence its operation by using different context types. As part of the evaluation, we present two experimental context-aware mobile cloud services to illustrate how the CPA works with user context, and related context profiles, to complete tasks for the user.

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The mobile cloud computing model promises to address the resource limitations of mobile devices, but effectively implementing this model is difficult. Previous work on mobile cloud computing has required the user to have a continuous, high-quality connection to the cloud infrastructure. This is undesirable and possibly infeasible, as the energy required on the mobile device to maintain a connection, and transfer sizeable amounts of data is large; the bandwidth tends to be quite variable, and low on cellular networks. The cloud deployment itself needs to efficiently allocate scalable resources to the user as well. In this paper, we formulate the best practices for efficiently managing the resources required for the mobile cloud model, namely energy, bandwidth and cloud computing resources. These practices can be realised with our mobile cloud middleware project, featuring the Cloud Personal Assistant (CPA). We compare this with the other approaches in the area, to highlight the importance of minimising the usage of these resources, and therefore ensure successful adoption of the model by end users. Based on results from experiments performed with mobile devices, we develop a no-overhead decision model for task and data offloading to the CPA of a user, which provides efficient management of mobile cloud resources.

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Cloud services provide its users with flexible resource provisioning. But in the current market, a user has to choose from a limited set of configurations at a fixed price. This paper presents an autonomous negotiation system termed CloudNeg for negotiating cloud services. CloudNeg provides buyers and sellers of cloud services with autonomous agents to negotiate on the specifications of a cloud instance, including price, on their behalf. These agents elicit their buyers’ time preferences and use them in negotiations. Further, this paper presents two artifacts: a negotiation algorithm and a prototype which together form CloudNeg.

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The mobile cloud computing paradigm can offer relevant and useful services to the users of smart mobile devices. Such public services already exist on the web and in cloud deployments, by implementing common web service standards. However, these services are described by mark-up languages, such as XML, that cannot be comprehended by non-specialists. Furthermore, the lack of common interfaces for related services makes discovery and consumption difficult for both users and software. The problem of service description, discovery, and consumption for the mobile cloud must be addressed to allow users to benefit from these services on mobile devices. This paper introduces our work on a mobile cloud service discovery solution, which is utilised by our mobile cloud middleware, Context Aware Mobile Cloud Services (CAMCS). The aim of our approach is to remove complex mark-up languages from the description and discovery process. By means of the Cloud Personal Assistant (CPA) assigned to each user of CAMCS, relevant mobile cloud services can be discovered and consumed easily by the end user from the mobile device. We present the discovery process, the architecture of our own service registry, and service description structure. CAMCS allows services to be used from the mobile device through a user's CPA, by means of user defined tasks. We present the task model of the CPA enabled by our solution, including automatic tasks, which can perform work for the user without an explicit request.

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Attempts were made to measure the fraction of elemental carbon (EC) in ultrafine aerosol by modifying an Ambient Carbonaceous Particulate Monitor (ACPM, R&P 5400). The main modification consisted in placing a quartz filter in one of the sampling lines of this dual-channel instrument. With the filter all aerosol and EC contained in it is collected, while in the other line of the instrument the standard impactor samples only particles larger than 0.14 μm. The fraction of EC in particles smaller than 0.14 μm is derived from the difference in concentration as measured via the two sampling lines. Measurements with the modified instrument were made at a suburban site in Amsterdam, The Netherlands. An apparent adsorption artefact, which could not be eliminated by the use of denuders, precluded meaningful evaluation of the data for total carbon. Blanks in the measurements of EC were negligible and the EC data were hence further evaluated. We found that the concentration of EC obtained via the channel with the impactor was systematically lower than that in the filter-line. The average ratio of the concentrations was close to 0.6, which indicates that approximately 40% of the EC was in particles smaller than 0.14 μm. Alternative explanations for the difference in the concentration in the two sampling lines could be excluded, such as a difference in the extent of oxidation. This should be a function of loading, which is not the case. Another reason for the difference could be that less material is collected by the impactor due to rebound, but such bounce of aerosol is very unlikely in The Netherlands due to co-deposition of abundant deliquesced and thus viscous ammonium compounds. The conclusion is that a further modification to assess the true fraction of ultrafine EC, by installing an impactor with cut-off diameter at 0.1 μm, would be worth pursuing. © 2005 Elsevier Ltd. All rights reserved.

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© 2005-2012 IEEE.Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies.

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A mixed Lagrangian-Eulerian model of a Water Curtain barrier is presented. The heat, mass and momentum processes are modelled in a Lagrangian framework for the dispersed phase and in an Eulerian framework for the carrier phase. The derivation of the coupling source terms is illustrated with reference to a given carrier phase cell. The turbulent character of the flow is treated with a single equation model, modified to directly account for the influence of the particles on the flow. The model is implemented in the form of a 2 D incompressible Navier Stokes solver, coupled to an adaptive Rung Kutta method for the Lagrangian sub-system. Simulations of a free standing full cone water spray show satisfactory agreement with experiment. Predictions of a Water Curtain barrier impacted by a cold gas cloud point to markedly different flow fields for the upward and downward configurations, which could influence the effectiveness of chemical absorption in the liquid phase.

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Paper presented at the Cloud Forward Conference 2015, October 6th-8th, Pisa

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Individuals of Mytilus edulis L., collected from the Erme estuary (S.W. England) in 1978, were exposed to low concentrations (7 to 68 μg l-1) of the water-accommodated fraction (WAF) of North Sea crude oil. The pattern of accumulation of petroleum hydrocarbons in the body tissues was affected by the presence of algal food cells, the period of exposure, the hydrocarbon concentration in seawater, the type of body tissue and the nature of the hydrocarbon. Many physiological responses (e.g. rates of oxygen consumption, feeding, excretion, and scope for growth), cellular responses (e.g. lysosomal latency and digestive cell size) and biochemical responses (e.g. specific activities of several enzymes) were significantly altered by short-term (4 wk) and/or long-term (5 mo) exposure to WAF. Stress indices such as scope for growth and lysosomal latency were negatively correlated with tissue aromatic hydrocarbons.

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Laboratory studies were conducted to investigate the interactions of nanoparticles (NPs) formed via simulated cloud processing of mineral dust with seawater under environmentally relevant conditions. The effect of sunlight and the presence of exopolymeric substances (EPS) were assessed on the: (1) colloidal stability of the nanoparticle aggregates (i.e. size distribution, zeta potential, polydispersity); (2) micromorphology and (3) Fe dissolution from particles. We have demonstrated that: (i) synthetic nano-ferrihydrite has distinct aggregation behaviour from NPs formed from mineral dusts in that the average hydrodynamic diameter remained unaltered upon dispersion in seawater (~1500 nm), whilst all dust derived NPs increased about three fold in aggregate size; (ii) relatively stable and monodisperse aggregates of NPs formed during simulated cloud processing of mineral dust become more polydisperse and unstable in contact with seawater; (iii) EPS forms stable aggregates with both the ferrihydrite and the dust derived NPs whose hydrodynamic diameter remains unchanged in seawater over 24h; (iv) dissolved Fe concentration from NPs, measured here as <3 kDa filter-fraction, is consistently >30% higher in seawater in the presence of EPS and the effect is even more pronounced in the absence of light; (v) micromorphology of nanoparticles from mineral dusts closely resemble that of synthetic ferrihydrite in MQ water, but in seawater with EPS they form less compact aggregates, highly variable in size, possibly due to EPS-mediated steric and electrostatic interactions. The larger scale implications on real systems of the EPS solubilising effect on Fe and other metals with the additional enhancement of colloidal stability of the resulting aggregates are discussed.