88 resultados para Film cover


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The literature has identified issues around transitions among phases for all pupils (Cocklin, 1999) including pupils with special educational needs (SEN) (Morgan 1999, Maras and Aveling 2006). These issues include pupils’ uncertainties and worries about building size and spatial orientation, exposure to a range of teaching styles, relationships with peers and older pupils as well as parents’ difficulties in establishing effective communications with prospective secondary schools. Research has also identified that interventions to facilitate these educational transitions should consider managerial support, social and personal familiarisation with the new setting as well as personalised learning strategies (BECTA 2004). However, the role that digital technologies can play in supporting these strategies or facilitating the role of the professionals such as SENCos and heads of departments involved in supporting effective transitions for pupils with SEN has not been widely discussed. Uses of ICT include passing references of student-produced media presentations (Higgins 1993) and use of photographs of activities attached to a timetable to support familiarisation with the secondary curriculum for pupils with autism (Cumine et al. 1998).

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Large-scale bottom-up estimates of terrestrial carbon fluxes, whether based on models or inventory, are highly dependent on the assumed land cover. Most current land cover and land cover change maps are based on satellite data and are likely to be so for the foreseeable future. However, these maps show large differences, both at the class level and when transformed into Plant Functional Types (PFTs), and these can lead to large differences in terrestrial CO2 fluxes estimated by Dynamic Vegetation Models. In this study the Sheffield Dynamic Global Vegetation Model is used. We compare PFT maps and the resulting fluxes arising from the use of widely available moderate (1 km) resolution satellite-derived land cover maps (the Global Land Cover 2000 and several MODIS classification schemes), with fluxes calculated using a reference high (25 m) resolution land cover map specific to Great Britain (the Land Cover Map 2000). We demonstrate that uncertainty is introduced into carbon flux calculations by (1) incorrect or uncertain assignment of land cover classes to PFTs; (2) information loss at coarser resolutions; (3) difficulty in discriminating some vegetation types from satellite data. When averaged over Great Britain, modeled CO2 fluxes derived using the different 1 km resolution maps differ from estimates made using the reference map. The ranges of these differences are 254 gC m−2 a−1 in Gross Primary Production (GPP); 133 gC m−2 a−1 in Net Primary Production (NPP); and 43 gC m−2 a−1 in Net Ecosystem Production (NEP). In GPP this accounts for differences of −15.8% to 8.8%. Results for living biomass exhibit a range of 1109 gC m−2. The types of uncertainties due to land cover confusion are likely to be representative of many parts of the world, especially heterogeneous landscapes such as those found in western Europe.

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Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

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This chapter looks at L’Homme qui aimait les femmes (1977) as a privileged instance of the self-effacing, obliquely disruptive, reflexive aesthetics that characterizes Truffaut’s cinema, by means of an intermedial approach. Although an original story, written by Truffaut in collaboration with Suzanne Schiffman and Michel Fermaud, the film’s subject is the writing of a book containing the protagonist’s story. More importantly, its mode of address presents this story as literature, through a complex network of flashbacks and voiceover narrations that comment on and make sense of the fragmentary present-tense action scenes. As well as a film, this method resulted in an actual novel, or cinéroman, this time authored exclusively by the director under the same title of L’Homme qui aimait les femmes, thus giving material form to the literary aim of the cinematic enterprise: a book.

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This article departs from the assumption that a certain section of world cinema, usually defined as ‘independent’, has been evolving on the basis of good scripts. Between the late 1980s and early 90s, there has been a boom of new cinemas in the world, such as the new Iranian, Taiwanese, Japanese, Mexican, Argentine and Brazilian cinemas. A significant part of this production shows a renewed interest in local and national peculiarities of their respective countries, going against the grain of globalisation and its typical cultural dilution. Most of these films are also engaged in reassessing narrative cinema, as a kind of reaction against the deconstructive work carried out by postmodern cinema of the 1980s.Recent new cinemas are supported by a combination of local and international resources, derived from public and private sponsors at home, and funding agencies, festivals and TV channels abroad. In most cases funds are granted after the film script has been analysed and approved by commissions of experts. The New Brazilian Cinema, or cinema da retomada as it is locally called, has been enormously affected by this scheme, which has even caused a ‘script boom’ in Brazil in the past decade. The chapter examins the results of this process.

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Television’s long-form storytelling has the potential to allow the rippling of music across episodes and seasons in interesting ways. In the integration of narrative, music and meaning found in The O.C. (Fox, FOX 2003-7), popular song’s allusive and referential qualities are drawn upon to particularly televisual ends. At times embracing its ‘disruptive’ presence, at others suturing popular music into narrative, at times doing both at once. With television studies largely lacking theories of music, this chapter draws on film music theory and close textual analysis to analyse some of the programme's music moments in detail. In particular it considers the series-spanning use of Jeff Buckley’s cover of ‘Hallelujah’ (and its subsequent oppressive presence across multiple televisual texts), the end of episode musical montage and the use of recurring song fragments as theme within single episodes. In doing so it highlights music's role in the fragmentation and flow of the television aesthetic and popular song’s structural presence in television narrative. Illustrating the multiplicity of popular song’s use in television, these moments demonstrate song’s ability to provide narrative commentary, yet also make particular use of what Ian Garwood describes as the ability of ‘a non-diegetic song to exceed the emotional range displayed by diegetic characters’ (2003:115), to ‘speak’ for characters or to their feelings, contributing to both teen TV’s melodramatic affect and narrative expression.

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Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.

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A steady decline in Arctic sea ice has been observed over recent decades. General circulation models predict further decreases under increasing greenhouse gas scenarios. Sea ice plays an important role in the climate system in that it influences ocean-to-atmosphere fluxes, surface albedo, and ocean buoyancy. The aim of this study is to isolate the climate impacts of a declining Arctic sea ice cover during the current century. The Hadley Centre Atmospheric Model (HadAM3) is forced with observed sea ice from 1980 to 2000 (obtained from satellite passive microwave radiometer data derived with the Bootstrap algorithm) and predicted sea ice reductions until 2100 under one moderate scenario and one severe scenario of ice decline, with a climatological SST field and increasing SSTs. Significant warming of the Arctic occurs during the twenty-first century (mean increase of between 1.6° and 3.9°C), with positive anomalies of up to 22°C locally. The majority of this is over ocean and limited to high latitudes, in contrast to recent observations of Northern Hemisphere warming. When a climatological SST field is used, statistically significant impacts on climate are only seen in winter, despite prescribing sea ice reductions in all months. When correspondingly increasing SSTs are incorporated, changes in climate are seen in both winter and summer, although the impacts in summer are much smaller. Alterations in atmospheric circulation and precipitation patterns are more widespread than temperature, extending down to midlatitude storm tracks. Results suggest that areas of Arctic land ice may even undergo net accumulation due to increased precipitation that results from loss of sea ice. Intensification of storm tracks implies that parts of Europe may experience higher precipitation rates.