42 resultados para Spatio-temporal environmental variations


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Interferometry has been used to investigate the spatio-temporal evolution of the electron number density in the initial stages of expansion following 248 nm ablation of a titanium target. Three-dimensional electron number densities are obtained from an interferogram of the plasma plume using the Abel inversion technique.

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The fourteen essays of this volume engage in distinct ways with the matter of motion in early modern Spanish poetics, without limiting the dialectic of stasis and movement to any single sphere or manifestation. Interrogation of the interdependence of tradition and innovation, poetry, power and politics, shifting signifiers, the intersection of topography and deviant temporalities, the movement between the secular and the sacred, tensions between centres and peripheries, issues of manuscript circulation and reception, poetic calls and echoes across continents and centuries, and between creative writing and reading subjects, all demonstrate that Helgerson's central notion of conspicuous movement is relevant beyond early sixteenth-century secular poetics, By opening it up we approximate a better understanding of poetry's flexible spatio-temporal co-ordinates in a period of extraordinary historical circumstances and conterminous radical cultural transformation

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Both embodied and symbolic accounts of conceptual organization would predict partial sharing and partial differentiation between the neural activations seen for concepts activated via different stimulus modalities. But cross-participant and cross-session variability in BOLD activity patterns makes analyses of such patterns with MVPA methods challenging. Here, we examine the effect of cross-modal and individual variation on the machine learning analysis of fMRI data recorded during a word property generation task. We present the same set of living and non-living concepts (land-mammals, or work tools) to a cohort of Japanese participants in two sessions: the first using auditory presentation of spoken words; the second using visual presentation of words written in Japanese characters. Classification accuracies confirmed that these semantic categories could be detected in single trials, with within-session predictive accuracies of 80-90%. However cross-session prediction (learning from auditory-task data to classify data from the written-word-task, or vice versa) suffered from a performance penalty, achieving 65-75% (still individually significant at p « 0.05). We carried out several follow-on analyses to investigate the reason for this shortfall, concluding that distributional differences in neither time nor space alone could account for it. Rather, combined spatio-temporal patterns of activity need to be identified for successful cross-session learning, and this suggests that feature selection strategies could be modified to take advantage of this.

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Managing gait disturbances in people with Parkinson’s disease is a pressing challenge, as symptoms can contribute to injury and morbidity through an increased risk of falls. While drug-based interventions have limited efficacy in alleviating gait impairments, certain non-pharmacological methods, such as cueing, can also induce transient improvements to gait. The approach adopted here is to use computationally-generated sounds to help guide and improve walking actions. The first method described uses recordings of force data taken from the steps of a healthy adult which in turn were used to synthesize realistic gravel-footstep sounds that represented different spatio-temporal parameters of gait, such as step duration and step length. The second method described involves a novel method of sonifying, in real time, the swing phase of gait using real-time motion-capture data to control a sound synthesis engine. Both approaches explore how simple but rich auditory representations of action based events can be used by people with Parkinson’s to guide and improve the quality of their walking, reducing the risk of falls and injury. Studies with Parkinson’s disease patients are reported which show positive results for both techniques in reducing step length variability. Potential future directions for how these sound approaches can be used to manage gait disturbances in Parkinson’s are also discussed.

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We have performed an experiment aimed at measuring self-generated magnetic fields produced in solids by high electron currents following high-intensity and high contrast short-pulse laser irradiation. This was done using longitudinal high resolution proton deflectometry. The experiment was performed at the Titan-JLF laser facility with a high-power short-pulse beam (700 fs, ~ 110 J) split into two beams irradiating two solid targets. One beam is used for the generation of protons and the other beam for the generation of the ultra-high currents of electrons and of the associated magnetic fields. This capability allows us to study the spatio-temporal evolution of the magnetic fields and its dependence on the laser intensity and target material. © Owned by the authors, published by EDP Sciences, 2013.

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Human occupants within indoor environments are not always stationary and their movement will lead to temporal channel variations that strongly affect the quality of indoor wireless communication systems. This paper describes a statistical channel characterization, based on experimental measurements, of human body effects on line-of-sight indoor narrowband propagation at 5.2 GHz. The analysis shows that, as the number of pedestrians within the measurement location increases, the Ricean K-factor that best fits the empirical data tends to decrease proportionally, ranging from K=7 with 1 pedestrian to K=0 with 4 pedestrians. Level crossing rate results were Rice distributed, while average fade duration results were significantly higher than theoretically computed Rice and Rayleigh, due to the fades caused by pedestrians. A novel CDF that accurately characterizes the 5.2 GHz channel in the considered indoor environment is proposed. For the first time, the received envelope CDF is explicitly described in terms of a quantitative measurement of pedestrian traffic within the indoor environment.

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The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.

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This paper presents a new framework for multi-subject event inference in surveillance video, where measurements produced by low-level vision analytics usually are noisy, incomplete or incorrect. Our goal is to infer the composite events undertaken by each subject from noise observations. To achieve this, we consider the temporal characteristics of event relations and propose a method to correctly associate the detected events with individual subjects. The Dempster–Shafer (DS) theory of belief functions is used to infer events of interest from the results of our vision analytics and to measure conflicts occurring during the event association. Our system is evaluated against a number of videos that present passenger behaviours on a public transport platform namely buses at different levels of complexity. The experimental results demonstrate that by reasoning with spatio-temporal correlations, the proposed method achieves a satisfying performance when associating atomic events and recognising composite events involving multiple subjects in dynamic environments.

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Birefringence is one of the fascinating properties of the vacuum of quantum electrodynamics (QED) in strong electromagnetic fields. The scattering of linearly polarized incident probe photons into a perpendicularly polarized mode provides a distinct signature of the optical activity of the quantum vacuum and thus offers an excellent opportunity for a precision test of nonlinear QED. Precision tests require accurate predictions and thus a theoretical framework that is capable of taking the detailed experimental geometry into account. We derive analytical solutions for vacuum birefringence which include the spatio-temporal field structure of a strong optical pump laser field and an x-ray probe. We show that the angular distribution of the scattered photons depends strongly on the interaction geometry and find that scattering of the perpendicularly polarized scattered photons out of the cone of the incident probe x-ray beam is the key to making the phenomenon experimentally accessible with the current generation of FEL/high-field laser facilities.

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Quantifying the similarity between two trajectories is a fundamental operation in analysis of spatio-temporal databases. While a number of distance functions exist, the recent shift in the dynamics of the trajectory generation procedure violates one of their core assumptions; a consistent and uniform sampling rate. In this paper, we formulate a robust distance function called Edit Distance with Projections (EDwP) to match trajectories under inconsistent and variable sampling rates through dynamic interpolation. This is achieved by deploying the idea of projections that goes beyond matching only the sampled points while aligning trajectories. To enable efficient trajectory retrievals using EDwP, we design an index structure called TrajTree. TrajTree derives its pruning power by employing the unique combination of bounding boxes with Lipschitz embedding. Extensive experiments on real trajectory databases demonstrate EDwP to be up to 5 times more accurate than the state-of-the-art distance functions. Additionally, TrajTree increases the efficiency of trajectory retrievals by up to an order of magnitude over existing techniques.

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Many wildlife studies use chemical analyses to explore spatio-temporal variation in diet, migratory patterns and contaminant exposure. Intrinsic markers are particularly valuable for studying non-breeding marine predators, when direct methods of investigation are rarely feasible. However, any inferences regarding foraging ecology are dependent upon the time scale over which tissues such as feathers are formed. In this study, we validate the use of body feathers for studying non-breeding foraging patterns in a pelagic seabird, the northern fulmar. Analysis of carcasses of successfully breeding adult fulmars indicated that body feathers moulted between September and March, whereas analyses of carcasses and activity patterns suggested that wing feather and tail feather moult occurred during more restricted periods (September to October and September to January, respectively). By randomly sampling relevant body feathers, average values for individual birds were shown to be consistent. We also integrated chemical analyses of body feather with geolocation tracking data to demonstrate that analyses of δ13C and δ15N values successfully assigned 88 % of birds to one of two broad wintering regions used by breeding adult fulmars from a Scottish study colony. These data provide strong support for the use of body feathers as a tool for exploring non-breeding foraging patterns and diet in wide-ranging, pelagic seabirds.

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A major weakness among loading models for pedestrians walking on flexible structures proposed in recent years is the various uncorroborated assumptions made in their development. This applies to spatio-temporal characteristics of pedestrian loading and the nature of multi-object interactions. To alleviate this problem, a framework for the determination of localised pedestrian forces on full-scale structures is presented using a wireless attitude and heading reference systems (AHRS). An AHRS comprises a triad of tri-axial accelerometers, gyroscopes and magnetometers managed by a dedicated data processing unit, allowing motion in three-dimensional space to be reconstructed. A pedestrian loading model based on a single point inertial measurement from an AHRS is derived and shown to perform well against benchmark data collected on an instrumented treadmill. Unlike other models, the current model does not take any predefined form nor does it require any extrapolations as to the timing and amplitude of pedestrian loading. In order to assess correctly the influence of the moving pedestrian on behaviour of a structure, an algorithm for tracking the point of application of pedestrian force is developed based on data from a single AHRS attached to a foot. A set of controlled walking tests with a single pedestrian is conducted on a real footbridge for validation purposes. A remarkably good match between the measured and simulated bridge response is found, indeed confirming applicability of the proposed framework.