999 resultados para Spatial search


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Tracking objects that are hidden and then moved is a crucial ability related to object permanence, which develops across several stages in early childhood. In spatial rotation tasks, children observe a target object that is hidden in one of two or more containers before the containers are rotated around a fixed axis. Usually, 30-month-olds fail to find the hidden object after it was rotated by 180°. We examined whether visual discriminability of the containers improves 30-month-olds’ success in this task and whether children perform better after 90° than after 180° rotations. Two potential hiding containers with same or different colors were placed on a board that was rotated by 90° or 180° in a within-subjects design. Children (N D 29) performed above chance level in all four conditions. Their overall success in finding the object did not improve by differently colored containers. However, different colors prevented children from showing an inhibition bias in 90° rotations, that is, choosing the empty container more often when it was located close to them than when it was farther away: This bias emerged in the same colors condition but not in the different colors condition. Results are discussed in view of particular challenges that might facilitate or deteriorate spatial rotation tasks for young children.

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Random walks describe diffusion processes, where movement at every time step is restricted to only the neighboring locations. We construct a quantum random walk algorithm, based on discretization of the Dirac evolution operator inspired by staggered lattice fermions. We use it to investigate the spatial search problem, that is, to find a marked vertex on a d-dimensional hypercubic lattice. The restriction on movement hardly matters for d > 2, and scaling behavior close to Grover's optimal algorithm (which has no restriction on movement) can be achieved. Using numerical simulations, we optimize the proportionality constants of the scaling behavior, and demonstrate the approach to that for Grover's algorithm (equivalent to the mean-field theory or the d -> infinity limit). In particular, the scaling behavior for d = 3 is only about 25% higher than the optimal d -> infinity value.

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We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evolution operator discretized according to the staggered lattice fermion formalism. d = 2 is the critical dimension for the spatial search problem, where infrared divergence of the evolution operator leads to logarithmic factors in the scaling behavior. As a result, the construction used in our accompanying article A. Patel and M. A. Rahaman, Phys. Rev. A 82, 032330 (2010)] provides an O(root N ln N) algorithm, which is not optimal. The scaling behavior can be improved to O(root N ln N) by cleverly controlling the massless Dirac evolution operator by an ancilla qubit, as proposed by Tulsi Phys. Rev. A 78, 012310 (2008)]. We reinterpret the ancilla control as introduction of an effective mass at the marked vertex, and optimize the proportionality constants of the scaling behavior of the algorithm by numerically tuning the parameters.

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We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evolution operator discretized according to the staggered lattice fermion formalism. d=2 is the critical dimension for the spatial search problem, where infrared divergence of the evolution operator leads to logarithmic factors in the scaling behavior. As a result, the construction used in our accompanying article [ A. Patel and M. A. Rahaman Phys. Rev. A 82 032330 (2010)] provides an O(√NlnN) algorithm, which is not optimal. The scaling behavior can be improved to O(√NlnN) by cleverly controlling the massless Dirac evolution operator by an ancilla qubit, as proposed by Tulsi Phys. Rev. A 78 012310 (2008). We reinterpret the ancilla control as introduction of an effective mass at the marked vertex, and optimize the proportionality constants of the scaling behavior of the algorithm by numerically tuning the parameters.

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The spatial search problem on regular lattice structures in integer number of dimensions d >= 2 has been studied extensively, using both coined and coinless quantum walks. The relativistic Dirac operator has been a crucial ingredient in these studies. Here, we investigate the spatial search problem on fractals of noninteger dimensions. Although the Dirac operator cannot be defined on a fractal, we construct the quantum walk on a fractal using the flip-flop operator that incorporates a Klein-Gordon mode. We find that the scaling behavior of the spatial search is determined by the spectral (and not the fractal) dimension. Our numerical results have been obtained on the well-known Sierpinski gaskets in two and three dimensions.

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Recently it has been discovered---contrary to expectations of physicists as well as biologists---that the energy transport during photosynthesis, from the chlorophyll pigment that captures the photon to the reaction centre where glucose is synthesised from carbon dioxide and water, is highly coherent even at ambient temperature and in the cellular environment. This process and the key molecular ingredients that it depends on are described. By looking at the process from the computer science view-point, we can study what has been optimised and how. A spatial search algorithmic model based on robust features of wave dynamics is presented.

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The computational program called GIS_EM (Geographic Information System for Environmental Monitoring), a software devised to manage geographic information for monitoring soil, surface, and ground water, developed for use in the Health, Safety, and Environment Division of Paulinia Refinery is presented. This program enables registering and management of alphanumeric information pertaining to specific themes such as drilling performed for sample collection and for installation of monitoring wells, geophysical and other tests, results of chemical analyses of soil, surface, and groundwater, as well as reference values providing orientation for soil and water quality, such as EPA, Dutch List, etc. Management of such themes is performed by means of alphanumeric search tools, with specific filters and, in the case of spatial search, through the selection of spatial elements (themes) in map view. Documents existing in digital form, such as reports, photos, maps, may be registered and managed in the network environment. As the system centralizes information generated upon environmental investigations, it expedites access to and search of documents produced and stored in the network environment, minimizing search time and the need to file printed documents. This is an abstract of a paper presented at the AIChE Annual Meeting and Fall Showcase (Cincinnati, OH 10/30/2005-11/4/2005).

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Este trabalho descreve a implementação computacional de um sistema de busca avançada em plataforma Web, para dados de empreendimentos e atividades passíveis de licenciamento ambiental, cadastrados no Estado do Mato Grosso do Sul - Brasil, com suporte a pesquisa espacial. Será também detalhada o aplicativo para cadastramento destes empreendimento e atividades. Estes módulos foram integrados ao Sistema Interativo de Suporte ao Licenciamento ambiental ? SISLA e estão em etapa de teste pelos técnicos do IMASUL. O aplicativo de cadastro pretende contribuir para a integração dos empreendimentos rurais neste Estado e a busca avançada tem se mostrado uma ferramenta poderosa de informação aos sistema de monitoramento ambiental.

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Air Force Office of Scientific Research (F49620-01-1-0397); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624)

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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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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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Research over the last decade has shown that auditorily cuing the location of visual targets reduces the time taken to locate and identify targets for both free-field and virtually presented sounds. The first study conducted for this thesis confirmed these findings over an extensive region of free-field space. However, the number of sound locations that are measured and stored in the data library of most 3-D audio spatial systems is limited, so that there is often a discrepancy in position between the cued and physical location of the target. Sampling limitations in the systems also produce temporal delays in which the stored data can be conveyed to operators. To investigate the effects of spatial and temporal disparities in audio cuing of visual search, and to provide evidence to alleviate concerns that psychological research lags behind the capabilities to design and implement synthetic interfaces, experiments were conducted to examine (a) the magnitude of spatial separation, and (b) the duration of temporal delay that intervened between auditory spatial cues and visual targets to alter response times to locate targets and discriminate their shape, relative to when the stimuli were spatially aligned, and temporally synchronised, respectively. Participants listened to free-field sound localisation cues that were presented with a single, highly visible target that could appear anywhere across 360° of azimuthal space on the vertical mid-line (spatial separation), or extended to 45° above and below the vertical mid-line (temporal delay). A vertical or horizontal spatial separation of 40° between the stimuli significantly increased response times, while separations of 30° or less did not reach significance. Response times were slowed at most target locations when auditory cues occurred 770 msecs prior to the appearance of targets, but not with similar durations of temporal delay (i.e., 440 msecs or less). When sounds followed the appearance of targets, the stimulus onset asynchrony that affected response times was dependent on target location, and ranged from 440 msecs at higher elevations and rearward of participants, to 1,100 msecs on the vertical mid-line. If targets appeared in the frontal field of view, no delay of acoustical stimulation affected performance. Finally, when conditions of spatial separation and temporal delay were combined, visual search times were degraded with a shorter stimulus onset asynchrony than when only the temporal relationship between the stimuli was varied, but responses to spatial separation were unaffected. The implications of the results for the development of synthetic audio spatial systems to aid visual search tasks was discussed.