103 resultados para exploit


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Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

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We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy yields a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.

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We describe infinitely scalable pipeline machines with perfect parallelism, in the sense that every instruction of an inline program is executed, on successive data, on every clock tick. Programs with shared data effectively execute in less than a clock tick. We show that pipeline machines are faster than single or multi-core, von Neumann machines for sufficiently many program runs of a sufficiently time consuming program. Our pipeline machines exploit the totality of transreal arithmetic and the known waiting time of statically compiled programs to deliver the interesting property that they need no hardware or software exception handling.

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It is known that roots can respond to patches of fertility; however, root proliferation is often too slow to exploit resources fully, and organic nutrient patches may be broken down and leached, immobilized or chemically fixed before they are invaded by the root system. The ability of fungal hyphae to exploit resource patches is far greater than that of roots due to their innate physiological and morphological plasticity, which allows comprehensive exploration and rapid colonization of resource patches in soils. The fungal symbionts of ectomycorrhizal plants excrete significant quantities of enzymes such as chitinases, phosphatases and proteases. These might allow the organic residue to be tapped directly for nutrients such as N and P. Pot experiments conducted with nutrient-stressed ectomycorrhizal and control willow plants showed that when high quality organic nutrient patches were added, they were colonized rapidly by the ectomycorrhizal mycelium. These established willows (0.5 m tall) were colonized by Hebeloma syrjense P. Karst. for 1 year prior to nutrient patch addition. Within days after patch addition, colour changes in the leaves of the mycorrhizal plants (reflecting improved nutrition) were apparent, and after I month the concentration of N and P in the foliage of mycorrhizal plants was significantly greater than that in non-mycorrhizal plants subject to the same nutrient addition. It seems likely that the mycorrhizal plants were able to compete effectively with the wider soil microbiota and tap directly into the high quality organic resource patch via their extra-radical mycelium. We hypothesize that ectomycorrhizal plants may reclaim some of the N and P invested in seed production by direct recycling from failed seeds in the soil. The rapid exploitation of similar discrete, transient, high-quality nutrient patches may have led to underestimations when determining the nutritional benefits of ectomycorrhizal colonization.

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This paper takes a fresh look at the relationship between Christian conversion and economic change in Anglo-Saxon England, drawing upon new archaeological evidence from Kent. One of its primary aims is to exploit the archaeological record to provide a critical perspective on how these two processes may have related to one another, paying particular attention to previous assumptions concerning the role played by monastic institutions in the process of rural intensification in Anglo-Saxon England.

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European beech (Fagus sylvatica L.) and Norway spruce (Picea abies Karst.) are two of the most ecologically and economically important forest tree species in Europe. These two species co-occur in many locations in Europe, leading to direct competition for canopy space. Foliage characteristics of two naturally regenerated pure stands of beech and spruce with fully closed canopies were contrasted to assess the dynamic relationship between foliage adaptability to shading, stand LAI and tree growth. We found that individual leaf size is far more conservative in spruce than in beech. Individual leaf and needle area was larger at the top than at the bottom of the canopy in both species. Inverse relationship was found for specific leaf area (SLA), highest SLA values were found at lowest light availability under the canopy. There was no difference in leaf area index (LAI) between the two stands, however LAI increased from 10.8 to 14.6 m2m-2 between 2009 and 2011. Dominant trees of both species were more efficient in converting foliage mass or area to produce stem biomass, although this relationship changed with age and was species-specific. Overall, we found larger foliage plasticity in beech than in spruce in relation to light conditions, indicating larger capacity to exploit niche openings.

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The theory of evolution by sexual selection for sexual size dimorphism (SSD) postulates that SSD primarily reflects the adaptation of males and females to their different reproductive roles. For example, competition among males for access to females increases male body size because larger males are better able to maintain dominant status than smaller males. Larger dominant males sire most offspring while smaller subordinate males are unsuccessful, leading to skew in reproductive success. Therefore, species with male-biased SSD are predicted to have greater variance in male reproductive success than those in which both sexes are similar in size. We tested this prediction among the Pinnipedia, a mammalian group with a great variation in SSD. From a literature review, we identified genetic estimates of male reproductive success for 10 pinniped taxa (eight unique species and two subspecies of a ninth species) that range from seals with similarly sized males and females to species in which males are more than four times as large as females. We found no support for a positive relationship between variance in reproductive success and SSD among pinnipeds after excluding the elephant seals Mirounga leonina and Mirounga angustirostris, which we discuss as distinctive cases. Several explanations for these results are presented, including the revival of one of Darwin's original ideas. Darwin proposed that natural selection may explain SSD based on differences in energetic requirements between sexes and the potential for sexual niche segregation. Males may develop larger bodies to exploit resources that remain unavailable to females due to the energetic constraints imposed on female mammals by gestation and lactation. The importance of this alternative explanation remains to be tested.

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Human observers exhibit large systematic distance-dependent biases when estimating the three-dimensional (3D) shape of objects defined by binocular image disparities. This has led some to question the utility of disparity as a cue to 3D shape and whether accurate estimation of 3D shape is at all possible. Others have argued that accurate perception is possible, but only with large continuous perspective transformations of an object. Using a stimulus that is known to elicit large distance-dependent perceptual bias (random dot stereograms of elliptical cylinders) we show that contrary to these findings the simple adoption of a more naturalistic viewing angle completely eliminates this bias. Using behavioural psychophysics, coupled with a novel surface-based reverse correlation methodology, we show that it is binocular edge and contour information that allows for accurate and precise perception and that observers actively exploit and sample this information when it is available.

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Global change drivers are known to interact in their effects on biodiversity, but much research to date ignores this complexity. As a consequence, there are problems in the attribution of biodiversity change to different drivers and, therefore, our ability to manage habitats and landscapes appropriately. Few studies explicitly acknowledge and account for interactive (i.e., nonadditive) effects of land use and climate change on biodiversity. One reason is that the mechanisms by which drivers interact are poorly understood. We evaluate such mechanisms, including interactions between demographic parameters, evolutionary trade-offs and synergies and threshold effects of population size and patch occupancy on population persistence. Other reasons for the lack of appropriate research are limited data availability and analytical issues in addressing interaction effects. We highlight the influence that attribution errors can have on biodiversity projections and discuss experimental designs and analytical tools suited to this challenge. Finally, we summarize the risks and opportunities provided by the existence of interaction effects. Risks include ineffective conservation management; but opportunities also arise, whereby the negative impacts of climate change on biodiversity can be reduced through appropriate land management as an adaptation measure. We hope that increasing the understanding of key mechanisms underlying interaction effects and discussing appropriate experimental and analytical designs for attribution will help researchers, policy makers, and conservation practitioners to better minimize risks and exploit opportunities provided by land use-climate change interactions.

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In order to exploit the passive energy potential of the building envelope, it is important to provide a right combination of insulation thickness, heat capacity and night-time ventilation. In this paper, this issue will be tackled with reference to an historic building in Catania (Southern Italy). The building was built at the end of the XIX century, and its opaque envelope is entirely made with lava stones, which is typical of traditional architecture in this area. Starting from the current configuration of the building, many hypotheses for refurbishment are considered, combined with different strategies for passive cooling, such as night-time ventilation, use of shading devices and adoption of highly-reflective coatings. The effectiveness of each solution in terms of summer thermal comfort is evaluated through dynamic thermal simulations carried out with EnergyPlus. The results show the synergic effect of these strategies, as well as their individual impact, and allow to draw some general conclusions about the behaviour of heavyweight buildings under moderately hot weather conditions.

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This article reports on a study investigating the relative influence of the first and dominant language on L2 and L3 morpho-lexical processing. A lexical decision task compared the responses to English NV-er compounds (e.g., taxi driver) and non-compounds provided by a group of native speakers and three groups of learners at various levels of English proficiency: L1 Spanish-L2 English sequential bilinguals and two groups of early Spanish-Basque bilinguals with English as their L3. Crucially, the two trilingual groups differed in their first and dominant language (i.e., L1 Spanish-L2 Basque vs. L1 Basque-L2 Spanish). Our materials exploit an (a)symmetry between these languages: while Basque and English pattern together in the basic structure of (productive) NV-er compounds, Spanish presents a construction that differs in directionality as well as inflection of the verbal element (V[3SG] + N). Results show between and within group differences in accuracy and response times that may be ascribable to two factors besides proficiency: the number of languages spoken by a given participant and their dominant language. An examination of response bias reveals an influence of the participants' first and dominant language on the processing of NV-er compounds. Our data suggest that morphological information in the nonnative lexicon may extend beyond morphemic structure and that, similarly to bilingualism, there are costs to sequential multilingualism in lexical retrieval.

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In this article we explore issues around the impact of continuing professional development (CPD) for secondary teachers of English offered by an overseas provider through the lens of participants from the Western provinces of China who completed courses at a UK university between 2003 and 2012. We start by offering an overview of English teaching in China. We then report two complementary studies of the same programme. The first aimed for breadth of understanding and involved the collection and analysis of interviews and focus groups discussions with former participants, their teaching colleagues and senior management, as well as classroom observation. The second aimed for depth and drew on data collected from a cohort of 38 teachers on one of the courses, using pre- and post-course surveys; focus group discussions at the end of the course with the whole cohort; and interviews with five of the participants both before they left the UK and again six months later. Evidence is presented for changes in teachers’ philosophies of education directly attributable to participation in the courses; for improved teacher competencies (linguistic, cultural and pedagogical) in the classroom; and for the ways in which returnees are undertaking new roles and responsibilities that exploit their new understandings. Finally, we discuss the implications of these findings for both providers and sponsors of CPD for English language teachers.

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Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.