922 resultados para multi-column process


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Reconfigurable hardware can be used to build multi tasking systems that dynamically adapt themselves to the requirements of the running applications. This is especially useful in embedded systems, since the available resources are very limited and the reconfigurable hardware can be reused for different applications. In these systems computations are frequently represented as task graphs that are executed taking into account their internal dependencies and the task schedule. The management of the task graph execution is critical for the system performance. In this regard, we have developed two dif erent versions, a software module and a hardware architecture, of a generic task-graph execution manager for reconfigurable multi-tasking systems. The second version reduces the run-time management overheads by almost two orders of magnitude. Hence it is especially suitable for systems with exigent timing constraints. Both versions include specific support to optimize the reconfiguration process.

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Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.

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Dissertação de Mestrado, Tecnologia dos Alimentos, Instituto Superior de Engenharia, Universidade do Algarve, 2014

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The change in the carbonaceous skeleton of nanoporous carbons during their activation has received limited attention, unlike its counterpart process in the presence of an inert atmosphere. Here we adopt a multi-method approach to elucidate this change in a poly(furfuryl alcohol)-derived carbon activated using cyclic application of oxygen saturation at 250 °C before its removal (with carbon) at 800 °C in argon. The methods used include helium pycnometry, synchrotron-based X-ray diffraction (XRD) and associated radial distribution function (RDF) analysis, transmission electron microscopy (TEM) and, uniquely, electron energy-loss spectroscopy spectrum-imaging (EELS-SI), electron nanodiffraction and fluctuation electron microscopy (FEM). Helium pycnometry indicates the solid skeleton of the carbon densifies during activation from 78% to 93% of graphite. RDF analysis, EELS-SI, and FEM all suggest this densification comes through an in-plane growth of sp2 carbon out to the medium range without commensurate increase in order normal to the plane. This process could be termed ‘graphenization’. The exact way in which this process occurs is not clear, but TEM images of the carbon before and after activation suggest it may come through removal of the more reactive carbon, breaking constraining cross-links and creating space that allows the remaining carbon material to migrate in an annealing-like process.

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Lake sturgeon (Acipenser fulvescens) were historically abundant in the Huron-Erie Corridor (HEC), a 160 km river/channel network composed of the St. Clair River, Lake St. Clair, and the Detroit River that connects Lake Huron to Lake Erie. In the HEC, most natural lake sturgeon spawning substrates have been eliminated or degraded as a result of channelization and dredging. To address significant habitat loss in HEC, multi-agency restoration efforts are underway to restore spawning substrate by constructing artificial spawning reefs. The main objective of this study was to conduct post-construction monitoring of lake sturgeon egg deposition and larval emergence near two of these artificial reef projects; Fighting Island Reef in the Detroit River, and Middle Channel Spawning Reef in the lower St. Clair River. We also investigated seasonal and nightly timing of larval emergence, growth, and vertical distribution in the water column at these sites, and an additional site in the St. Clair River where lake sturgeon are known to spawn on a bed of ~100 year old coal clinkers. From 2010-12, we collected viable eggs and larvae at all three sites indicating that these artificial reefs are creating conditions suitable for egg deposition, fertilization, incubation, and larval emergence. The construction methods and materials, and physical site conditions present in HEC artificial reef projects can be used to inform future spawning habitat restoration or enhancement efforts. The results from this study have also identified the likelihood of additional uncharacterized natural spawning sites in the St. Clair River. In addition to the field study, we conducted a laboratory experiment involving actual substrate materials that have been used in artificial reef construction in this system. Although coal clinkers are chemically inert, some trace elements can be reincorporated with the clinker material during the combustion process. Since lake sturgeon eggs and larvae are developing in close proximity to this material, it is important to measure the concentration of potentially toxic trace elements. This study focused on arsenic, which occurs naturally in coal and can be toxic to fishes. Total arsenic concentration was measured in samples taken from four substrate treatments submerged in distilled water; limestone cobble, rinsed limestone cobble, coal clinker, and rinsed coal clinker. Samples were taken at three time intervals: 24 hours, 11 days, and 21 days. ICP-MS analysis showed that concentrations of total arsenic were below the EPA drinking water standard (10 ppb) for all samples. However, at the 24 hour sampling interval, a two way repeated measures ANOVA with a Holm-Sidak post hoc analysis (α= 0.05) showed that the mean arsenic concentration was significantly higher in the coal clinker substrate treatment then in the rinsed coal clinker treatment (p=0.006), the limestone cobble treatment (p

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A novel numerical model of a Bent Backwards Duct Buoy (BBDB) Oscillating Water Column (OWC) Wave Energy Converter was created based on existing isolated numerical models of the different energy conversion systems utilised by an OWC. The novel aspect of this numerical model is that it incorporates the interdependencies of the different power conversion systems rather than modelling each system individually. This was achieved by accounting for the dynamic aerodynamic damping caused by the changing turbine rotational velocity by recalculating the turbine damping for each simulation sample and applying it via a feedback loop. The accuracy of the model was validated using experimental data collected during the Components for Ocean Renewable Energy Systems (CORES) EU FP-7 project that was tested in Galway Bay, Ireland. During the verification process, it was discovered that the model could also be applied as a valuable tool when troubleshooting device performance. A new turbine was developed and added to a full scale model after being investigated using Computational Fluid Dynamics. The energy storage capacity of the impulse turbine was investigated by modelling the turbine with both high and low inertia and applying three turbine control theories to the turbine using the full scale model. A single Maximum Power Point Tracking algorithm was applied to the low-inertia turbine, while both a fixed and dynamic control algorithm was applied to the high-inertia turbine. These results suggest that the highinertia turbine could be used as a flywheel energy storage device that could help minimize output power variation despite the low operating speed of the impulse turbine. This research identified the importance of applying dynamic turbine damping to a BBDB OWC numerical model, revealed additional value of the model as a device troubleshooting tool, and found that an impulse turbine could be applied as an energy storage system.

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A continuous process strategy has been developed for the preparation of α-thio-β chloroacrylamides, a class of highly versatile synthetic intermediates. Flow platforms to generate the α-chloroamide and α-thioamide precursors were successfully adopted, progressing from the previously employed batch chemistry, and in both instances afford a readily scalable methodology. The implementation of the key α-thio-β-chloroacrylamide casade as a continuous flow reaction on a multi-gram scale is described, while the tuneable nature of the cascade, facilitated by continuous processing, is highlighted by selective generation of established intermediates and byproducts.

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The relationship between school belongingness and mental health functioning before and after the primary-secondary school transition has not been previously investigated in students with and without disabilities. This study used a prospective longitudinal design to test the bi-directional relationships between these constructs, by surveying 266 students with and without disabilities and their parents, 6-months before and after the transition to secondary school. Cross-lagged multi-group analyses found student perception of belongingness in the final year of primary school to contribute to change in their mental health functioning a year later. The beneficial longitudinal effects of school belongingness on subsequent mental health functioning were evident in all student subgroups; even after accounting for prior mental health scores and the cross-time stability in mental health functioning and school belongingness scores. Findings of the current study substantiate the role of school contextual influences on early adolescent mental health functioning. They highlight the importance for primary and secondary schools to assess students' school belongingness and mental health functioning and transfer these records as part of the transition process, so that appropriate scaffolds are in place to support those in need. Longer term longitudinal studies are needed to increase the understanding of the temporal sequencing between school belongingness and mental health functioning of all mainstream students.

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The usage of multi material structures in industry, especially in the automotive industry are increasing. To overcome the difficulties in joining these structures, adhesives have several benefits over traditional joining methods. Therefore, accurate simulations of the entire process of fracture including the adhesive layer is crucial. In this paper, material parameters of a previously developed meso mechanical finite element (FE) model of a thin adhesive layer are optimized using the Strength Pareto Evolutionary Algorithm (SPEA2). Objective functions are defined as the error between experimental data and simulation data. The experimental data is provided by previously performed experiments where an adhesive layer was loaded in monotonically increasing peel and shear. Two objective functions are dependent on 9 model parameters (decision variables) in total and are evaluated by running two FEsimulations, one is loading the adhesive layer in peel and the other in shear. The original study converted the two objective functions into one function that resulted in one optimal solution. In this study, however, a Pareto frontis obtained by employing the SPEA2 algorithm. Thus, more insight into the material model, objective functions, optimal solutions and decision space is acquired using the Pareto front. We compare the results and show good agreement with the experimental data.

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Effective and efficient implementation of intelligent and/or recently emerged networked manufacturing systems require an enterprise level integration. The networked manufacturing offers several advantages in the current competitive atmosphere by way to reduce, by shortening manufacturing cycle time and maintaining the production flexibility thereby achieving several feasible process plans. The first step in this direction is to integrate manufacturing functions such as process planning and scheduling for multi-jobs in a network based manufacturing system. It is difficult to determine a proper plan that meets conflicting objectives simultaneously. This paper describes a mobile-agent based negotiation approach to integrate manufacturing functions in a distributed manner; and its fundamental framework and functions are presented. Moreover, ontology has been constructed by using the Protégé software which possesses the flexibility to convert knowledge into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents. The generated XML schemas have been used to transfer information throughout the manufacturing network for the intelligent interoperable integration of product data models and manufacturing resources. To validate the feasibility of the proposed approach, an illustrative example along with varied production environments that includes production demand fluctuations is presented and compared the proposed approach performance and its effectiveness with evolutionary algorithm based Hybrid Dynamic-DNA (HD-DNA) algorithm. The results show that the proposed scheme is very effective and reasonably acceptable for integration of manufacturing functions.

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The use of biological processes with the aim of the recovery of gold from low-concentration solutions derived from leaching of secondary sources is gaining increasing importance owing to the scarcity of the primary resources and the economic and environmental advantages usually presented by these methods. Thus, the addition in batch and continuous processes of different solutions containing biogenic sulphide, which was generated by the activity of sulphate-reducing bacteria (SRB), to gold(III) solutions was investigated for that purpose. In the batch experiments, AuS nanoparticles with sizes of between 6 and 14 nm were obtained (corresponding to 100% removal of Au(III) from solution) if the biogenic sulphide was generated in a typical nutrient medium for SRB, whereas Au(0) nanoparticles with sizes of below 8 nm were obtained (corresponding to 62% removal of Au(III)) if effluent from a SRB bioremediation process for treating acid mine drainage (AMD) was used instead. These results stimulated the development of a continuous process of addition, in which two sulphide-rich effluents, which resulted from a SRB bioremediation process for treating two types of AMD (from a uranium mine and a polysulphide mine), were tested. In both cases, Au(0) nanoparticles with sizes of between 6 and 15 nm were mainly obtained, and the percentage removal of Au(III) from solution ranged from 76% to 100%. The processes described allow the simultaneous treatment of AMD and recovery of metallic gold nanoparticles, which are a product with a wide range of applications (e.g., in medicine, optical devices and catalysis) and high economic value. The synthesis process described in this work can be considered as novel, because it is the first time, to our knowledge, that the use of effluent from a SRB bioremediation process has been reported for the recovery of gold(III) as gold(0) nanoparticles.

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Transdisciplinarity gained importance in the 1970s, with the initial signs of weakness of both multi- and interdisciplinary approaches. This weakness was felt due to the increased complexity in the social and technological landscapes. Generally, discussion over the transdisciplinary topic is centred in social and health sciences. Therefore, the major challenge in this research is to adapt design research to the emerging transdisciplinary discussion. Based on a comparative and critical review of several engineering and design models for the design process, we advocate the importance of collaboration and conceptualisation for these disciplines. Therefore, a transdisciplinary and conceptual cooperation between engineering and industrial design disciplines is considered as decisive to create breakthroughs. Furthermore, a synthesis is proposed, in order to foster the cooperation between engineering and industrial design.

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The micro-chemical/mineralogical composition of samples of grey-paste imitations of Italic Late Republican black gloss tableware displaying a particular kind of lozenge-shaped decoration (“Losanga pottery”) from Portuguese and Spanish archaeological sites in SW Iberia has been analysed by BSEM + EDS, μXRD, Powder XRD, Portable XRF and μRaman spectroscopy. “Losanga” decorated ceramics have been found throughout the Western Mediterranean. Most of the sherds display a green-brown to greyish-black engobe at the surface resembling the gloss found in Attic pottery from Classical Greece. The overall chemical, mineralogical and fossiliferous homogeneities of the ceramic paste show common features (low K-feldspar/plagioclase ratio, high Ca content, abundance of well-preserved fragments of foraminifera microfossils) that indicate low firing conditions in the kiln ranging from 650 to 900 °C. With respect to the ceramic body, analytical results confirm an enrichment in the surface gloss layer of iron, potassium and aluminium and a depletion in silicon and calcium; the very fine grain size of the surface coating suggests elutriation of iron oxide-rich clays as confirmed by the presence of magnetite, maghemite and goethite in μ-XRD scan. Chemical and mineralogical data also suggest that the firing process was performed in a 600–850 °C temperature range, adopting the well-known technique of alternating oxidizing and reducing firing conditions largely employed at the time. The analytical results, while compatible with the archaeological hypothesis of a common provenance of the raw materials for pottery production from the Guadalquivir valley workshops cannot be considered conclusive due to the similarity in the geological substrate in the two SW Iberian regions under study.

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To reduce the amount of time needed to solve the most complex Constraint Satisfaction Problems (CSPs) usually multi-core CPUs are used. There are already many applications capable of harnessing the parallel power of these devices to speed up the CSPs solving process. Nowadays, the Graphics Processing Units (GPUs) possess a level of parallelism that surpass the CPUs, containing from a few hundred to a few thousand cores and there are much less applications capable of solving CSPs on GPUs, leaving space for possible improvements. This article describes the work in progress for solving CSPs on GPUs and CPUs and compares results with some state-of-the-art solvers, presenting already some good results on GPUs.