979 resultados para multi-point haptic


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By using Lagrangian method, the flow properties of a dusty-gas point source in a supersonic free stream were studied and the particle parameters in the near-symmetry-axis region were obtained. It is demonstrated that fairly inertial particles travel along oscillating and intersecting trajectories between the bow and termination shock waves. In this region,formation of "multi-layer structure" in particle distribution with alternating low- and highdensity layers is revealed. Moreover, sharp accumulation of particles occurs near the envelopes of particle trajectories.

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A global numerical model for shallow water flows on the cubed-sphere grid is proposed in this paper. The model is constructed by using the constrained interpolation profile/multi-moment finite volume method (CIP/MM FVM). Two kinds of moments, i.e. the point value (PV) and the volume-integrated average (VIA) are defined and independently updated in the present model by different numerical formulations. The Lax-Friedrichs upwind splitting is used to update the PV moment in terms of a derivative Riemann problem, and a finite volume formulation derived by integrating the governing equations over each mesh element is used to predict the VIA moment. The cubed-sphere grid is applied to get around the polar singularity and to obtain uniform grid spacing for a spherical geometry. Highly localized reconstruction in CIP/MM FVM is well suited for the cubed-sphere grid, especially in dealing with the discontinuity in the coordinates between different patches. The mass conservation is completely achieved over the whole globe. The numerical model has been verified by Williamson's standard test set for shallow water equation model on sphere. The results reveal that the present model is competitive to most existing ones. (C) 2008 Elsevier Inc. All rights reserved.

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This paper considers a class of dynamic Spatial Point Processes (PP) that evolves over time in a Markovian fashion. This Markov in time PP is hidden and observed indirectly through another PP via thinning, displacement and noise. This statistical model is important for Multi object Tracking applications and we present an approximate likelihood based method for estimating the model parameters. The work is supported by an extensive numerical study.

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Market squid (Loligo opalescens) plays a vital role in the California ecosystem and serves as a major link in the food chain as both a predator and prey species. For over a century, market squid has also been harvested off the California coast from Monterey to San Pedro. Expanding global markets, coupled with a decline in squid product from other parts of the world, in recent years has fueled rapid expansion of the virtually unregulated California fishery. Lack of regulatory management, in combination with dramatic increases in fishing effort and landings, has raised numerous concerns from the scientific, fishing, and regulatory communities. In an effort to address these concerns, the National Oceanic and Atmospheric Administration’s (NOAA) Channel Islands National Marine Sanctuary (CINMS) hosted a panel discussion at the October 1997 California Cooperative Oceanic and Fisheries Investigations (CalCOFI) Conference; it focused on ecosystem management implications for the burgeoning market squid fishery. Both panel and audience members addressed issues such as: the direct and indirect effects of commercial harvesting upon squid biomass; the effects of harvest and the role of squid in the broader marine community; the effects of environmental variation on squid population dynamics; the sustainability of the fishery from the point of view of both scientists and the fishers themselves; and the conservation management options for what is currently an open access and unregulated fishery. Herein are the key points of the ecosystem management panel discussion in the form of a preface, an executive summary, and transcript. (PDF contains 33 pages.)

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A new high-order finite volume method based on local reconstruction is presented in this paper. The method, so-called the multi-moment constrained finite volume (MCV) method, uses the point values defined within single cell at equally spaced points as the model variables (or unknowns). The time evolution equations used to update the unknowns are derived from a set of constraint conditions imposed on multi kinds of moments, i.e. the cell-averaged value and the point-wise value of the state variable and its derivatives. The finite volume constraint on the cell-average guarantees the numerical conservativeness of the method. Most constraint conditions are imposed on the cell boundaries, where the numerical flux and its derivatives are solved as general Riemann problems. A multi-moment constrained Lagrange interpolation reconstruction for the demanded order of accuracy is constructed over single cell and converts the evolution equations of the moments to those of the unknowns. The presented method provides a general framework to construct efficient schemes of high orders. The basic formulations for hyperbolic conservation laws in 1- and 2D structured grids are detailed with the numerical results of widely used benchmark tests. (C) 2009 Elsevier Inc. All rights reserved.

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Dutos de transmissão são tubulações especialmente desenvolvidas para transportar produtos diversos a longas distâncias e representam a forma mais segura e econômica de transporte para grandes quantidades de fluidos. Os dutos de gás natural, denominados gasodutos, são usados para transportar o gás desde os campos de produção até os centros consumidores, onde o gás é inserido em redes de distribuição para entrega aos consumidores finais. Os gasodutos de transporte apresentam diversas características de monopólio natural, que são o principal argumento econômico para sua regulação. A regulação visa garantir que esta atividade seja explorada de maneira eficiente, refletindo em tarifas de transporte justas para os consumidores e que proporcionem o retorno adequado aos investidores, levando-se em consideração a quantidade de gás transportado. Neste contexto, o presente trabalho tem como objetivo propor metodologias de otimização multi-objetivo de projetos de redes de gasodutos de transporte, envolvendo métodos a posteriori. O problema de otimização formulado contempla restrições associadas ao escoamento do gás e o comportamento das estações de compressão. A solução do problema fornece um conjunto de projetos ótimos de redes de transporte em função da maximização da quantidade de gás natural transportado e da minimização da tarifa associada a esse serviço. A ferramenta foi aplicada a diversos estudos de caso com configurações típicas da indústria de transporte de gás natural. Os resultados mostraram que as metodologias propostas são capazes de fornecer subsídios que permitem ao tomador de decisão do ponto de vista regulatório realizar uma análise de trade-off entre a quantidade de gás transportado e a tarifa, buscando assim atender ao interesse da sociedade em relação à exploração do serviço de transporte

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Robotic manipulanda are extensively used in investigation of the motor control of human arm movements. They permit the application of translational forces to the arm based on its state and can be used to probe issues ranging from mechanisms of neural control to biomechanics. However, most current designs are optimized for studying either motor learning or stiffness. Even fewer include end-point torque control which is important for the simulation of objects and the study of tool use. Here we describe a modular, general purpose, two-dimensional planar manipulandum (vBOT) primarily optimized for dynamic learning paradigms. It employs a carbon fibre arm arranged as a parallelogram which is driven by motors via timing pulleys. The design minimizes the intrinsic dynamics of the manipulandum without active compensation. A novel variant of the design (WristBOT) can apply torques at the handle using an add-on cable drive mechanism. In a second variant (StiffBOT) a more rigid arm can be substituted and zero backlash belts can be used, making the StiffBOT more suitable for the study of stiffness. The three variants can be used with custom built display rigs, mounting, and air tables. We investigated the performance of the vBOT and its variants in terms of effective end-point mass, viscosity and stiffness. Finally we present an object manipulation task using the WristBOT. This demonstrates that subjects can perceive the orientation of the principal axis of an object based on haptic feedback arising from its rotational dynamics.

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Gasoline Homogeneous Charge Compression Ignition (HCCI) combustion has been studied widely in the past decade. However, in HCCI engines using negative valve overlap (NVO), there is still uncertainty as to whether the effect of pilot injection during NVO on the start of combustion is primarily due to heat release of the pilot fuel during NVO or whether it is due to pilot fuel reformation. This paper presents data taken on a 4-cylinder gasoline direct injection, spark ignition/HCCI engine with a dual cam system, capable of recompressing residual gas. Engine in-cylinder samples are extracted at various points during the engine cycle through a high-speed sampling system and directly analysed with a gas chromatograph and flame ionisation detector. Engine parameter sweeps are performed for different pilot injection timings and quantities at a medium load point. Results show that for lean engine running conditions, earlier pilot injection timing leads to partial oxidation of the injected pilot fuel during NVO, while the fraction of light hydrocarbons remains constant for all parameter variations investigated. The same applies for a variation in pilot fuel amount. Thus there is evidence that in lean conditions, pilot injection-related NVO effects are dominated by heat release rather than fuel reformation. © 2009 SAE International.

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Hip fracture is the leading cause of acute orthopaedic hospital admission amongst the elderly, with around a third of patients not surviving one year post-fracture. Although various preventative therapies are available, patient selection is difficult. The current state-of-the-art risk assessment tool (FRAX) ignores focal structural defects, such as cortical bone thinning, a critical component in characterizing hip fragility. Cortical thickness can be measured using CT, but this is expensive and involves a significant radiation dose. Instead, Dual-Energy X-ray Absorptiometry (DXA) is currently the preferred imaging modality for assessing hip fracture risk and is used routinely in clinical practice. Our ambition is to develop a tool to measure cortical thickness using multi-view DXA instead of CT. In this initial study, we work with digitally reconstructed radiographs (DRRs) derived from CT data as a surrogate for DXA scans: this enables us to compare directly the thickness estimates with the gold standard CT results. Our approach involves a model-based femoral shape reconstruction followed by a data-driven algorithm to extract numerous cortical thickness point estimates. In a series of experiments on the shaft and trochanteric regions of 48 proximal femurs, we validated our algorithm and established its performance limits using 20 views in the range 0°-171°: estimation errors were 0:19 ± 0:53mm (mean +/- one standard deviation). In a more clinically viable protocol using four views in the range 0°-51°, where no other bony structures obstruct the projection of the femur, measurement errors were -0:07 ± 0:79 mm. © 2013 SPIE.

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Design optimisation of compressor systems is a computationally expensive problem due to the large number of variables, complicated design space and expense of the analysis tools. One approach to reduce the expense of the process and make it achievable in industrial timescales is to employ multi-fidelity techniques, which utilise more rapid tools in conjunction with the highest fidelity analyses. The complexity of the compressor design landscape is such that the starting point for these optimisations can influence the achievable results; these starting points are often existing (optimised) compressor designs, which form a limited set in terms of both quantity and diversity of the design. To facilitate the multi-fidelity optimisation procedure, a compressor synthesis code was developed which allowed the performance attributes (e.g. stage loadings, inlet conditions) to be stipulated, enabling the generation of a variety of compressors covering a range of both design topology and quality to act as seeding geometries for the optimisation procedures. Analysis of the performance of the multi-fidelity optimisation system when restricting its exploration space to topologically different areas of the design space indicated little advantage over allowing the system to search the design space itself. However, comparing results from optimisations started from seed designs with different aerodynamic qualites indicated an improved performance could be achieved by starting an optimisation from a higher quality point, and thus that the choice of starting point did affect the final outcome of the optimisations. Both investigations indicated that the performance gains through the optimisation were largely defined by the early exploration of the design space where the multi-fidelity speedup could be exploited, thus extending this region is likely to have the greatest effect on performance of the optimisation system. © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

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Avalanches, debris flows, and landslides are geophysical hazards, which involve rapid mass movement of granular solids, water and air as a single-phase system. The dynamics of a granular flow involve at least three distinct scales: the micro-scale, meso-scale, and the macro-scale. This study aims to understand the ability of continuum models to capture the micro-mechanics of dry granular collapse. Material Point Method (MPM), a hybrid Lagrangian and Eulerian approach, with Mohr-Coulomb failure criterion is used to describe the continuum behaviour of granular column collapse, while the micromechanics is captured using Discrete Element Method (DEM) with tangential contact force model. The run-out profile predicted by the continuum simulations matches with DEM simulations for columns with small aspect ratios ('h/r' < 2), however MPM predicts larger run-out distances for columns with higher aspect ratios ('h/r' > 2). Energy evolution studies in DEM simulations reveal higher collisional dissipation in the initial free-fall regime for tall columns. The lack of a collisional energy dissipation mechanism in MPM simulations results in larger run-out distances. Micro-structural effects, such as shear band formations, were observed both in DEM and MPM simulations. A sliding flow regime is observed above the distinct passive zone at the core of the column. Velocity profiles obtained from both the scales are compared to understand the reason for a slow flow run-out mobilization in MPM simulations. © 2013 AIP Publishing LLC.

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Design optimisation of compressor systems is a computationally expensive problem due to the large number of variables, complicated design space and expense of the analysis tools. One approach to reduce the expense of the process and make it achievable in industrial timescales is to employ multi-fidelity techniques, which utilise more rapid tools in conjunction with the highest fidelity analyses. The complexity of the compressor design landscape is such that the starting point for these optimisations can influence the achievable results; these starting points are often existing (optimised) compressor designs, which form a limited set in terms of both quantity and diversity of the design. To facilitate the multi-fidelity optimisation procedure, a compressor synthesis code was developed which allowed the performance attributes (e.g. stage loadings, inlet conditions) to be stipulated, enabling the generation of a variety of compressors covering a range of both design topology and quality to act as seeding geometries for the optimisation procedures. Analysis of the performance of the multi-fidelity optimisation system when restricting its exploration space to topologically different areas of the design space indicated little advantage over allowing the system to search the design space itself. However, comparing results from optimisations started from seed designs with different aerodynamic qualites indicated an improved performance could be achieved by starting an optimisation from a higher quality point, and thus that the choice of starting point did affect the final outcome of the optimisations. Both investigations indicated that the performance gains through the optimisation were largely defined by the early exploration of the design space where the multi-fidelity speedup could be exploited, thus extending this region is likely to have the greatest effect on performance of the optimisation system. © 2012 AIAA.

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We present Multi Scale Shape Index (MSSI), a novel feature for 3D object recognition. Inspired by the scale space filtering theory and Shape Index measure proposed by Koenderink & Van Doorn [6], this feature associates different forms of shape, such as umbilics, saddle regions, parabolic regions to a real valued index. This association is useful for representing an object based on its constituent shape forms. We derive closed form scale space equations which computes a characteristic scale at each 3D point in a point cloud without an explicit mesh structure. This characteristic scale is then used to estimate the Shape Index. We quantitatively evaluate the robustness and repeatability of the MSSI feature for varying object scales and changing point cloud density. We also quantify the performance of MSSI for object category recognition on a publicly available dataset. © 2013 Springer-Verlag.

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The design of wind turbine blades is a true multi-objective engineering task. The aerodynamic effectiveness of the turbine needs to be balanced with the system loads introduced by the rotor. Moreover the problem is not dependent on a single geometric property, but besides other parameters on a combination of aerofoil family and various blade functions. The aim of this paper is therefore to present a tool which can help designers to get a deeper insight into the complexity of the design space and to find a blade design which is likely to have a low cost of energy. For the research we use a Computational Blade Optimisation and Load Deflation Tool (CoBOLDT) to investigate the three extreme point designs obtained from a multi-objective optimisation of turbine thrust, annual energy production as well as mass for a horizontal axis wind turbine blade. The optimisation algorithm utilised is based on Multi-Objective Tabu Search which constitutes the core of CoBOLDT. The methodology is capable to parametrise the spanning aerofoils with two-dimensional Free Form Deformation and blade functions with two tangentially connected cubic splines. After geometry generation we use a panel code to create aerofoil polars and a stationary Blade Element Momentum code to evaluate turbine performance. Finally, the obtained loads are fed into a structural layout module to estimate the mass and stiffness of the current blade by means of a fully stressed design. For the presented test case we chose post optimisation analysis with parallel coordinates to reveal geometrical features of the extreme point designs and to select a compromise design from the Pareto set. The research revealed that a blade with a feasible laminate layout can be obtained, that can increase the energy capture and lower steady state systems loads. The reduced aerofoil camber and an increased L/. D-ratio could be identified as the main drivers. This statement could not be made with other tools of the research community before. © 2013 Elsevier Ltd.

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In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.