994 resultados para spatial agency


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Esta investigación es un acercamiento a las formas de estructurar los cuidados en el incipiente fenómeno de las viviendas colaborativas de personas mayores (senior cohousing) en el Estado Español. Desde el enfoque de la arquitectura feminista se ha realizado una etnografía en base a entrevistas a personas mayores implicadas en procesos de desarrollo de viviendas colaborativas. También nos hemos basado en la observación del Centro Convivencial para personas Mayores Trabensol y el centro socio-cultural La Casa de Lx Abuelx de la Fundación 26 de Diciembre para mayores gays. Mediante este estudio cualitativo se analizan las diferentes implicaciones que estas nuevas organizaciones espaciales domésticas conllevan en relación con los cuidados, los dispositivos comunitarios y la vida cotidiana en las viviendas colaborativas. Además hemos prestado atención a como las estructuras de género operan en el espacio, doméstico en este caso, y la vivencia y socialización que se desarrolla en el mismo.

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Sweden’s recent report on Urban Sustainable Development calls out a missing link between the urban design process and citizens. This paper investigates if engaging citizens as design agents by providing a platform for alternate participation can bridge this gap, through the transfer of spatial agency and new modes of critical cartography. To assess whether this is the case, the approaches are applied to Stockholm’s urban agriculture movement in a staged intervention. The aim of the intervention was to engage citizens in locating existing and potential places for growing food and in gathering information from these sites to inform design in urban agriculture. The design-based methodologies incorporated digital and bodily interfaces for this cartography to take place. The Urban CoMapper, a smartphone digital app, captured real-time perspectives through crowd-sourced mapping. In the bodily cartography, participant’s used their bodies to trace the site and reveal their sensorial perceptions. The data gathered from these approaches gave way to a mode of artistic research for exploring urban agriculture, along with inviting artists to be engaged in the dialogues. In sum, results showed that a combination of digital and bodily approaches was necessary for a critical cartography if we want to engage citizens holistically into the urban design process as spatial agents informing urban policy. Such methodologies formed a reflective interrogation and encouraged a new intimacy with nature, in this instance, one that can transform our urban conduct by questioning our eating habits: where we get our food from and how we eat it seasonally.

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This work shows a theoretical analysis together with numerical and experimental results of transmission characteristics from the microstrip bandpass filters with different geometries. These filters are built over isotropic dielectric substrates. The numerical analysis is made by specifical commercial softwares, like Ansoft Designer and Agilent Advanced Design System (ADS). In addition to these tools, a Matlab Script was built to analyze the filters through the Finite-Difference Time-Domain (FDTD) method. The filters project focused the development of the first stage of filtering in the ITASAT s Transponder receptor, and its integration with the others systems. Some microstrip filters architectures have been studied, aiming the viability of implementation and suitable practical application for the purposes of the ITASAT Project due to its lowspace occupation in the lower UHF frequencies. The ITASAT project is a Universityexperimental project which will build a satellite to integrate the Brazilian Data Collect System s satellite constellation, with efforts of many Brazilian institutes, like for example AEB (Brazilian Spatial Agency), ITA (Technological Institute of Aeronautics), INPE/CRN (National Institute of Spatial Researches/Northeastern Regional Center) and UFRN (Federal University of Rio Grande do Norte). Comparisons were made between numerical and experimental results of all filters, where good agreements could be noticed, reaching the most of the objectives. Also, post-work improvements were suggested.

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Urban green infrastructure can help cities adapt to climate change. Spatial planning can play an important role in utilizing green infrastructure for adaptation. Yet climate change risks represent a different sort of challenge for planning institutions. This paper aims to address two issues arising from this challenge. First, it defines the concept of green infrastructure within the context of climate adaptation. Second, it identifies and puts into perspective institutional barriers to adopting green infrastructure for climate adaptation, including path dependence. We begin by arguing that there is growing confusion among planners and policy makers about what constitutes green infrastructure. Definitional ambiguity may contribute to inaction on climate change adaptation, because it muddies existing programs and initiatives that are to do with green-space more broadly, which in turn feeds path dependency. We then report empirical findings about how planners perceive the institutional challenge arising from climate change and the adoption of green infrastructure as an adaptive response. The paper concludes that spatial planners generally recognize multiple rationales associated with green infrastructure. However they are not particularly keen on institutional innovation and there is a tendency for path dependence. We propose a conceptual model that explicitly recognizes such institutional factors. This paper contributes to the literature by showing that agency and institutional dimensions are a limiting factor in advancing the concept of green infrastructure within the context of climate change adaptation.

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Development of an internet based spatial data delivery and reporting system for the Australian Cotton Industry.

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How do humans use predictive contextual information to facilitate visual search? How are consistently paired scenic objects and positions learned and used to more efficiently guide search in familiar scenes? For example, a certain combination of objects can define a context for a kitchen and trigger a more efficient search for a typical object, such as a sink, in that context. A neural model, ARTSCENE Search, is developed to illustrate the neural mechanisms of such memory-based contextual learning and guidance, and to explain challenging behavioral data on positive/negative, spatial/object, and local/distant global cueing effects during visual search. The model proposes how global scene layout at a first glance rapidly forms a hypothesis about the target location. This hypothesis is then incrementally refined by enhancing target-like objects in space as a scene is scanned with saccadic eye movements. The model clarifies the functional roles of neuroanatomical, neurophysiological, and neuroimaging data in visual search for a desired goal object. In particular, the model simulates the interactive dynamics of spatial and object contextual cueing in the cortical What and Where streams starting from early visual areas through medial temporal lobe to prefrontal cortex. After learning, model dorsolateral prefrontal cortical cells (area 46) prime possible target locations in posterior parietal cortex based on goalmodulated percepts of spatial scene gist represented in parahippocampal cortex, whereas model ventral prefrontal cortical cells (area 47/12) prime possible target object representations in inferior temporal cortex based on the history of viewed objects represented in perirhinal cortex. The model hereby predicts how the cortical What and Where streams cooperate during scene perception, learning, and memory to accumulate evidence over time to drive efficient visual search of familiar scenes.

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Advanced Research Projects Agency (ONR N00014-92-J-4015); National Science Foundation (IRI-90-24877); Office of Naval Research (N00014-91-J-4100)

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The distributed outstar, a generalization of the outstar neural network for spatial pattern learning, is introduced. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes. The distributed outstar replaces the outstar source node with a source field of arbitrarily many nodes, whose activity pattern may be arbitrarily distributed or compressed. Learning proceeds according to a principle of atrophy due to disuse, whereby a path weight decreases in joint proportion to the transmitted path signal and the degree of disuse of the target node. During learning, the total signal to a target node converges toward that node's activity level. Weight changes at a node are apportioned according to the distributed pattern of converging signals. Three synaptic transmission functions, by a product rule, a capacity rule, and a threshold rule, are examined for this system. The three rules are computationally equivalent when source field activity is maximally compressed, or winner-take-all. When source field activity is distributed, catastrophic forgetting may occur. Only the threshold rule solves this problem. Analysis of spatial pattern learning by distributed codes thereby leads to the conjecture that the unit of long-term memory in such a system is an adaptive threshold, rather than the multiplicative path weight widely used in neural models.

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Visual search data are given a unified quantitative explanation by a model of how spatial maps in the parietal cortex and object recognition categories in the inferotemporal cortex deploy attentional resources as they reciprocally interact with visual representations in the prestriate cortex. The model visual representations arc organized into multiple boundary and surface representations. Visual search in the model is initiated by organizing multiple items that lie within a given boundary or surface representation into a candidate search grouping. These items arc compared with object recognition categories to test for matches or mismatches. Mismatches can trigger deeper searches and recursive selection of new groupings until a target object io identified. This search model is algorithmically specified to quantitatively simulate search data using a single set of parameters, as well as to qualitatively explain a still larger data base, including data of Aks and Enns (1992), Bravo and Blake (1990), Chellazzi, Miller, Duncan, and Desimone (1993), Egeth, Viri, and Garbart (1984), Cohen and Ivry (1991), Enno and Rensink (1990), He and Nakayarna (1992), Humphreys, Quinlan, and Riddoch (1989), Mordkoff, Yantis, and Egeth (1990), Nakayama and Silverman (1986), Treisman and Gelade (1980), Treisman and Sato (1990), Wolfe, Cave, and Franzel (1989), and Wolfe and Friedman-Hill (1992). The model hereby provides an alternative to recent variations on the Feature Integration and Guided Search models, and grounds the analysis of visual search in neural models of preattentive vision, attentive object learning and categorization, and attentive spatial localization and orientation.

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The What-and-Where filter forms part of a neural network architecture for spatial mapping, object recognition, and image understanding. The Where fllter responds to an image figure that has been separated from its background. It generates a spatial map whose cell activations simultaneously represent the position, orientation, ancl size of all tbe figures in a scene (where they are). This spatial map may he used to direct spatially localized attention to these image features. A multiscale array of oriented detectors, followed by competitve and interpolative interactions between position, orientation, and size scales, is used to define the Where filter. This analysis discloses several issues that need to be dealt with by a spatial mapping system that is based upon oriented filters, such as the role of cliff filters with and without normalization, the double peak problem of maximum orientation across size scale, and the different self-similar interpolation properties across orientation than across size scale. Several computationally efficient Where filters are proposed. The Where filter rnay be used for parallel transformation of multiple image figures into invariant representations that are insensitive to the figures' original position, orientation, and size. These invariant figural representations form part of a system devoted to attentive object learning and recognition (what it is). Unlike some alternative models where serial search for a target occurs, a What and Where representation can he used to rapidly search in parallel for a desired target in a scene. Such a representation can also be used to learn multidimensional representations of objects and their spatial relationships for purposes of image understanding. The What-and-Where filter is inspired by neurobiological data showing that a Where processing stream in the cerebral cortex is used for attentive spatial localization and orientation, whereas a What processing stream is used for attentive object learning and recognition.

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It is a neural network truth universally acknowledged, that the signal transmitted to a target node must be equal to the product of the path signal times a weight. Analysis of catastrophic forgetting by distributed codes leads to the unexpected conclusion that this universal synaptic transmission rule may not be optimal in certain neural networks. The distributed outstar, a network designed to support stable codes with fast or slow learning, generalizes the outstar network for spatial pattern learning. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a target field of nodes. The distributed outstar replaces the outstar source node with a source field, of arbitrarily many nodes, where the activity pattern may be arbitrarily distributed or compressed. Learning proceeds according to a principle of atrophy due to disuse whereby a path weight decreases in joint proportion to the transmittcd path signal and the degree of disuse of the target node. During learning, the total signal to a target node converges toward that node's activity level. Weight changes at a node are apportioned according to the distributed pattern of converging signals three types of synaptic transmission, a product rule, a capacity rule, and a threshold rule, are examined for this system. The three rules are computationally equivalent when source field activity is maximally compressed, or winner-take-all when source field activity is distributed, catastrophic forgetting may occur. Only the threshold rule solves this problem. Analysis of spatial pattern learning by distributed codes thereby leads to the conjecture that the optimal unit of long-term memory in such a system is a subtractive threshold, rather than a multiplicative weight.

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This study concerns the spatial allocation of material flows, with emphasis on construction material in the Irish housing sector. It addresses some of the key issues concerning anthropogenic impact on the environment through spatial temporal visualisation of the flow of materials, wastes and emissions at different spatial levels. This is presented in the form of a spatial model, Spatial Allocation of Material Flow Analysis (SAMFA), which enables the simulation of construction material flows and associated energy use. SAMFA parallels the Island Limits project (EPA funded under 2004-SD-MS-22-M2), which aimed to create a material flow analysis of the Irish economy classified by industrial sector. SAMFA further develops this by attempting to establish the material flows at the subnational geographical scale that could be used in the development of local authority (LA) sustainability strategies and spatial planning frameworks by highlighting the cumulative environmental impacts of the development of the built environment. By drawing on the idea of planning support systems, SAMFA also aims to provide a cross-disciplinary, integrative medium for involving stakeholders in strategies for a sustainable built environment and, as such, would help illustrate the sustainability consequences of alternative The pilot run of the model in Kildare has shown that the model can be successfully calibrated and applied to develop alternative material flows and energy-use scenarios at the ED level. This has been demonstrated through the development of an integrated and a business-as-usual scenario, with the former integrating a range of potential material efficiency and energysaving policy options and the latter replicating conditions that best describe the current trend. Their comparison shows that the former is better than the latter in terms of both material and energy use. This report also identifies a number of potential areas of future research and areas of broader application. This includes improving the accuracy of the SAMFA model (e.g. by establishing actual life expectancy of buildings in the Irish context through field surveys) and the extension of the model to other Irish counties. This would establish SAMFA as a valuable predicting and monitoring tool that is capable of integrating national and local spatial planning objectives with actual environmental impacts. Furthermore, should the model prove successful at this level, it then has the potential to transfer the modelling approach to other areas of the built environment, such as commercial development and other key contributors of greenhouse emissions. The ultimate aim is to develop a meta-model for predicting the consequences of consumption patterns at the local scale. This therefore offers the possibility of creating critical links between socio technical systems with the most important challenge of all the limitations of the biophysical environment.

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Stakeholder participation is viewed as a key element of ecosystem-based marine spatial planning (MSP). There is much debate over the effectiveness of stakeholder participation in ecosystem-based management (EBM) in general and over the form it should take. Particular challenges relating to participation in the marine environment are highlighted. A study of the Eastern Scotian Shelf Integrated Management initiative, which uses a collaborative planning model to implement EBM, is presented in order to explore these issues further. Criteria derived from a review of collaborative planning literature are employed to evaluate the effectiveness of this model, which is found to be a useful consensus-building tool. Although a strategic-level plan has been adopted, the initiative has encountered difficulties transitioning from plan development to plan implementation. These are attributable in large measure to deficiencies in the design of the collaborative model. Useful lessons relating mainly to stakeholder engagement, the role of the lead agency, and implementation strategies are advanced for those engaging in MSP processes.

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The Knowledge Exchange, Spatial Analysis and Healthy Urban Environments (KESUE) project has extended work previously undertaken by a QUB team of inter-disciplinary researchers engaged with the Physical Activity in the Regeneration of Connswater (PARC) project (Tully et al, 2013). The PARC project focussed on parts of East Belfast to assess the health impact of the Connswater Community Greenway. The KESUE project has aimed to extend some of the tools used initially in East Belfast so that they have data coverage of all of Belfast and Derry-Londonderry. The purpose of this has been to enable the development of evidence and policy tools that link features of the built environment with physical activity in these two cities. The project has used this data to help shape policy decisions in areas such as physical activity, park management, public transport and planning.

Working with a range of local partners who part-funded the project (City Councils in Belfast and Derry-Londonderry, Public Health Agency, Belfast Healthy Cities and Department of Regional Development), this project has mapped all the footpaths in the two cities (covering 37% of the NI population) and employed this to develop evidence used in strategies related to healthy urban planning. Using Geographic Information Systems (GIS), the footpath network has been used as a basis for a wide range of policy-relevant analyses including pedestrian accessibility to public facilities, site options for new infrastructure and assessing how vulnerable groups can access services such as pharmacies. Key outputs have been Accessibility Atlases and maps showing how walkability of the built environment varies across the two cities.

In addition to generating this useful data, the project included intense engagement with potential users of the research, which has led to its continued uptake in a number of policies and strategies, creating a virtuous circle of research, implementation and feedback. The project has proved so valuable to Belfast City Council that they have now taken on one of the researchers to continue the work in-house.