966 resultados para Multi-item scales
Resumo:
Wireless technology based pervasive healthcare has been proposed in many applications such as disease management and accident prevention for cost saving and promoting citizen’s wellbeing. However, the emphasis so far is on the artefacts with limited attentions to guiding the development of an effective and efficient solution for pervasive healthcare. Therefore, this paper aims to propose a framework of multi-agent systems design for pervasive healthcare by adopting the concept of pervasive informatics and using the methods of organisational semiotics. The proposed multi-agent system for pervasive healthcare utilises sensory information to support healthcare professionals for providing appropriate care. The key contributions contain theoretical aspect and practical aspect. In theory, this paper articulates the information interactions between the pervasive healthcare environment and stakeholders by using the methods of organisational semiotics; in practice, the proposed framework improves the healthcare quality by providing appropriate medical attentions when and as needed. In this paper, both systems and functional architecture of the multi-agent system are elaborated with the use of wireless technologies such as RFID and wireless sensor networks. The future study will focus on the implementation of the proposed framework.
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This study puts forward a method to model and simulate the complex system of hospital on the basis of multi-agent technology. The formation of the agents of hospitals with intelligent and coordinative characteristics was designed, the message object was defined, and the model operating mechanism of autonomous activities and coordination mechanism was also designed. In addition, the Ontology library and Norm library etc. were introduced using semiotic method and theory, to enlarge the method of system modelling. Swarm was used to develop the multi-agent based simulation system, which is favorable for making guidelines for hospital's improving it's organization and management, optimizing the working procedure, improving the quality of medical care as well as reducing medical charge costs.
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Nowadays the changing environment becomes the main challenge for most of organizations, since they have to evaluate proper policies to adapt to the environment. In this paper, we propose a multi-agent simulation method to evaluate policies based on complex adaptive system theory. Furthermore, we propose a semiotic EDA (Epistemic, Deontic, Axiological) agent model to simulate agent's behavior in the system by incorporating the social norms reflecting the policy. A case study is also provided to validate our approach. Our research present better adaptability and validity than the qualitative analysis and experiment approach and the semiotic agent model provides high creditability to simulate agents' behavior.
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Forests are a store of carbon and an eco-system that continually removes carbon dioxide from the atmosphere. If they are sustainably managed, the carbon store can be maintained at a constant level, while the trees removed and converted to timber products can form an additional long term carbon store. The total carbon store in the forest and associated ‘wood chain’ therefore increases over time, given appropriate management. This increasing carbon store can be further enhanced with afforestation. The UK’s forest area has increased continually since the early 1900s, although the rate of increase has declined since its peak in the late 1980s, and it is a similar picture in the rest of Europe. The increased sustainable use of timber in construction is a key market incentive for afforestation, which can make a significant contribution to reducing carbon emissions. The case study presented in this paper demonstrates the carbon benefits of a Cross Laminated Timber (CLT) solution for a multi-storey residential building in comparison with a more conventional reinforced concrete solution. The embodied carbon of the building up to completion of construction is considered, together with the stored carbon during the life of the building and the impact of different end of life scenarios. The results of the study show that the total stored carbon in the CLT structural frame is 1215tCO2 (30tCO2 per housing unit). The choice of treatment at end of life has a significant effect on the whole life embodied carbon of the CLT frame, which ranges from -1017 tCO2e for re-use to +153tCO2e for incinerate without energy recovery. All end of life scenarios considered result in lower total CO2e emissions for the CLT frame building compared with the reinforced concrete frame solution.
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Diurnal warming events between 5 and 7 K, spatially coherent over large areas (∼1000 km), are observed in independent satellite measurements of ocean surface temperature. The majority of the large events occurred in the extra-tropics. Given sufficient heating (from solar radiation), the location and magnitude of these events appears to be primarily determined by large-scale wind patterns. The amplitude of the measured diurnal heating scales inversely with the spatial resolution of the different sensors used in this study. These results indicate that predictions of peak diurnal warming using wind speeds with a 25 km spatial resolution available from satellite sensors and those with 50–100 km resolution from Numerical Weather Prediction models may have underestimated warming. Thus, the use of these winds in modeling diurnal effects will be limited in accuracy by both the temporal and spatial resolution of the wind fields.
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The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.
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Sensible heat fluxes (QH) are determined using scintillometry and eddy covariance over a suburban area. Two large aperture scintillometers provide spatially integrated fluxes across path lengths of 2.8 km and 5.5 km over Swindon, UK. The shorter scintillometer path spans newly built residential areas and has an approximate source area of 2-4 km2, whilst the long path extends from the rural outskirts to the town centre and has a source area of around 5-10 km2. These large-scale heat fluxes are compared with local-scale eddy covariance measurements. Clear seasonal trends are revealed by the long duration of this dataset and variability in monthly QH is related to the meteorological conditions. At shorter time scales the response of QH to solar radiation often gives rise to close agreement between the measurements, but during times of rapidly changing cloud cover spatial differences in the net radiation (Q*) coincide with greater differences between heat fluxes. For clear days QH lags Q*, thus the ratio of QH to Q* increases throughout the day. In summer the observed energy partitioning is related to the vegetation fraction through use of a footprint model. The results demonstrate the value of scintillometry for integrating surface heterogeneity and offer improved understanding of the influence of anthropogenic materials on surface-atmosphere interactions.
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Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.
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The integration of ecological principles into agricultural systems presents major opportunities for spreading risk at the crop and farm scale. This paper presents mechanisms by which diversity at several scales within the farming system can increase the stability of production. Diversity of above- and below-ground biota, but also genetic and phenotypic diversity within crops, has an essential role in safeguarding farm production. Novel mixtures of legume-grass leys have been shown to potentially provide significant benefits for pollinator and decomposer ecosystem services but to realise the greatest improvements carefully tailored farm management is needed such as mowing or grazing time, and the type and depth of cutivation. Complex farmland landscapes such as agroforestry systems have the potential to support pollinator abundance and diversity and spread risk across production enterprises. At the crop level, early results indicate that the vulnerability of pollen development, flowering and early grain set to abiotic stress can be ameliorated by managing flowering time through genotypic selection, and through the buffering effects of pollinators. Finally, the risk of sub-optimal quality in cereals can be mitigated through integration of near isogenic lines selected to escape specific abiotic stress events. We conclude that genotypic, phenotypic and community diversity can all be increased at multiple scales to enhance resilience in agricultural systems.
A benchmark-driven modelling approach for evaluating deployment choices on a multi-core architecture
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The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.
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Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.
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We present the first multi-event study of the spatial and temporal structuring of the aurora to provide statistical evidence of the near-Earth plasma instability which causes the substorm onset arc. Using data from ground-based auroral imagers, we study repeatable signatures of along-arc auroral beads, which are thought to represent the ionospheric projection of magnetospheric instability in the near-Earth plasma sheet. We show that the growth and spatial scales of these wave-like fluctuations are similar across multiple events, indicating that each sudden auroral brightening has a common explanation. We find statistically that growth rates for auroral beads peak at low wavenumber with the most unstable spatial scales mapping to an azimuthal wavelength λ≈1700 − 2500 km in the equatorial magnetosphere at around 9-12 RE. We compare growth rates and spatial scales with a range of theoretical predictions of magnetotail instabilities, including the cross-field current instability and the shear-flow ballooning instability. We conclude that, although the cross-field current instability can generate similar magnitude of growth rates, the range of unstable wavenumbers indicates that the shear-flow ballooning instability is the most likely explanation for our observations.
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The degree to which habitat fragmentation affects bird incidence is species specific and may depend on varying spatial scales. Selecting the correct scale of measurement is essential to appropriately assess the effects of habitat fragmentation on bird occurrence. Our objective was to determine which spatial scale of landscape measurement best describes the incidence of three bird species (Pyriglena leucoptera, Xiphorhynchus fuscus and Chiroxiphia caudata) in the fragmented Brazilian Atlantic forest and test if multi-scalar models perform better than single-scalar ones. Bird incidence was assessed in 80 forest fragments. The surrounding landscape structure was described with four indices measured at four spatial scales (400-, 600-, 800- and 1,000-m buffers around the sample points). The explanatory power of each scale in predicting bird incidence was assessed using logistic regression, bootstrapped with 1,000 repetitions. The best results varied between species (1,000-m radius for P. leucoptera; 800-m for X. fuscus and 600-m for C. caudata), probably due to their distinct feeding habits and foraging strategies. Multi-scale models always resulted in better predictions than single-scale models, suggesting that different aspects of the landscape structure are related to different ecological processes influencing bird incidence. In particular, our results suggest that local extinction and (re)colonisation processes might simultaneously act at different scales. Thus, single-scale models may not be good enough to properly describe complex pattern-process relationships. Selecting variables at multiple ecologically relevant scales is a reasonable procedure to optimise the accuracy of species incidence models.
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Recent developments have highlighted the importance of forest amount at large spatial scales and of matrix quality for ecological processes in remnants. These developments, in turn, suggest the potential for reducing biodiversity loss through the maintenance of a high percentage of forest combined with sensitive management of anthropogenic areas. We conducted a multi-taxa survey to evaluate the potential for biodiversity maintenance in an Atlantic forest landscape that presented a favorable context from a theoretical perspective (high proportion of mature forest partly surrounded by structurally complex matrices). We sampled ferns, butterflies, frogs, lizards, bats, small mammals and birds in interiors and edges of large and small mature forest remnants and two matrices (second-growth forests and shade cacao plantations), as well as trees in interiors of small and large remnants. By considering richness, abundance and composition of forest specialists and generalists, we investigated the biodiversity value of matrix habitats (comparing them with interiors of large remnants for all groups except tree), and evaluated area (for all groups) and edge effects (for all groups except trees) in mature forest remnants. our results suggest that in landscapes comprising high amounts of mature forest and low contrasting matrices: (1) shade cacao plantations and second-growth forests harbor an appreciable number of forest specialists; (2) most forest specialist assemblages are not affected by area or edge effects, while most generalist assemblages proliferate at edges of small remnants. Nevertheless, differences in tree assemblages, especially among smaller trees, Suggest that observed patterns are unlikely to be stable over time. (C) 2009 Elsevier Ltd. All rights reserved.
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So Paulo is the most developed state in Brazil and contains few fragments of native ecosystems, generally surrounded by intensive agriculture lands. Despite this, some areas still shelter large native animals. We aimed at understanding how medium and large carnivores use a mosaic landscape of forest/savanna and agroecosystems, and how the species respond to different landscape parameters (percentage of landcover and edge density), in a multi-scale perspective. The response variables were: species richness, carnivore frequency and frequency for the three most recorded species (Puma concolor, Chrysocyon brachyurus and Leopardus pardalis). We compared 11 competing models using Akaike`s information criterion (AIC) and assessed model support using weight of AIC. Concurrent models were combinations of landcover types (native vegetation, ""cerrado"" formations, ""cerrado"" and eucalypt plantation), landscape feature (percentage of landcover and edge density) and spatial scale. Herein, spatial scale refers to the radius around a sampling point defining a circular landscape. The scales analyzed were 250 (fine), 1,000 (medium) and 2,000 m (coarse). The shape of curves for response variables (linear, exponential and power) was also assessed. Our results indicate that species with high mobility, P. concolor and C. brachyurus, were best explained by edge density of the native vegetation at a coarse scale (2,000 m). The relationship between P. concolor and C. brachyurus frequency had a negative power-shaped response to explanatory variables. This general trend was also observed for species richness and carnivore frequency. Species richness and P. concolor frequency were also well explained by a second concurrent model: edge density of cerrado at the fine (250 m) scale. A different response was recorded for L. pardalis, as the frequency was best explained for the amount of cerrado at the fine (250 m) scale. The curve of response was linearly positive. The contrasting results (P. concolor and C. brachyurus vs L. pardalis) may be due to the much higher mobility of the two first species, in comparison with the third. Still, L. pardalis requires habitat with higher quality when compared with other two species. This study highlights the importance of considering multiple spatial scales when evaluating species responses to different habitats. An important and new finding was the prevalence of edge density over the habitat extension to explain overall carnivore distribution, a key information for planning and management of protected areas.