122 resultados para Homogeneous function
Resumo:
To support the development and analysis of engineering designs at the embodiment stage, designers work iteratively with representations of those designs as they consider the function and form of their constituent parts. Detailed descriptions of "what a machine does" usually include flows of forces and active principles within the technical system, and their localization within parts and across the interfaces between them. This means that a representation should assist a designer in considering form and function at the same time and at different levels of abstraction. This paper describes a design modelling approach that enables designers to break down a system architecture into its subsystems and parts, while assigning functions and flows to parts and the interfaces between them. In turn, this may reveal further requirements to fulfil functions in order to complete the design. The approach is implemented in a software tool which provides a uniform, computable language allowing the user to describe functions and flows as they are iteratively discovered, created and embodied. A database of parts allows the user to search for existing design solutions. The approach is illustrated through an example: modelling the complex mechanisms within a humanoid robot. Copyright © 2010 by ASME.
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A recent study demonstrates involvement of primary motor cortex in task-dependent modulation of rapid feedback responses; cortical neurons resolve locally ambiguous sensory information, producing sophisticated responses to disturbances.
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This work addresses the problem of deriving F0 from distanttalking speech signals acquired by a microphone network. The method here proposed exploits the redundancy across the channels by jointly processing the different signals. To this purpose, a multi-microphone periodicity function is derived from the magnitude spectrum of all the channels. This function allows to estimate F0 reliably, even under reverberant conditions, without the need of any post-processing or smoothing technique. Experiments, conducted on real data, showed that the proposed frequency-domain algorithm is more suitable than other time-domain based ones.
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A strategy to extract turbulence structures from direct numerical simulation (DNS) data is described along with a systematic analysis of geometry and spatial distribution of the educed structures. A DNS dataset of decaying homogeneous isotropic turbulence at Reynolds number Reλ = 141 is considered. A bandpass filtering procedure is shown to be effective in extracting enstrophy and dissipation structures with their smallest scales matching the filter width, L. The geometry of these educed structures is characterized and classified through the use of two non-dimensional quantities, planarity' and filamentarity', obtained using the Minkowski functionals. The planarity increases gradually by a small amount as L is decreased, and its narrow variation suggests a nearly circular cross-section for the educed structures. The filamentarity increases significantly as L decreases demonstrating that the educed structures become progressively more tubular. An analysis of the preferential alignment between the filtered strain and vorticity fields reveals that vortical structures of a given scale L are most likely to align with the largest extensional strain at a scale 3-5 times larger than L. This is consistent with the classical energy cascade picture, in which vortices of a given scale are stretched by and absorb energy from structures of a somewhat larger scale. The spatial distribution of the educed structures shows that the enstrophy structures at the 5η scale (where η is the Kolmogorov scale) are more concentrated near the ones that are 3-5 times larger, which gives further support to the classical picture. Finally, it is shown by analysing the volume fraction of the educed enstrophy structures that there is a tendency for them to cluster around a larger structure or clusters of larger structures. Copyright © 2012 Cambridge University Press.
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We report on the topographical and electrical characterisations of 1 nm thick Al2O3 dielectric films on graphene. The Al 2O3 is grown by sputtering a 0.6 nm Al layer on graphene and subsequentially oxidizing it in an O2 atmosphere. The Al 2O3 layer presents no pinholes and is homogeneous enough to act as a tunnel barrier. A resistance-area product in the mega-ohm micrometer-square range is found. Comparatively, the growth of Al 2O3 by evaporation does not lead to well-wetted films on graphene. Application of this high quality sputtered tunnel barrier to efficient spin injection in graphene is discussed. © 2012 American Institute of Physics.
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A fundamental problem in the analysis of structured relational data like graphs, networks, databases, and matrices is to extract a summary of the common structure underlying relations between individual entities. Relational data are typically encoded in the form of arrays; invariance to the ordering of rows and columns corresponds to exchangeable arrays. Results in probability theory due to Aldous, Hoover and Kallenberg show that exchangeable arrays can be represented in terms of a random measurable function which constitutes the natural model parameter in a Bayesian model. We obtain a flexible yet simple Bayesian nonparametric model by placing a Gaussian process prior on the parameter function. Efficient inference utilises elliptical slice sampling combined with a random sparse approximation to the Gaussian process. We demonstrate applications of the model to network data and clarify its relation to models in the literature, several of which emerge as special cases.
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Concepts of function are central to design but statements about a device's functions can be interpreted in different ways. This raises problems for researchers trying to clarify the foundations of design theory and for those developing design support-tools that can represent and reason about function. By showing how functions relate systems to their sub-systems and super-systems, this article illustrates some limitations of existing function terminology and some problems with existing function statements. To address these issues, a system-relative function terminology is introduced. This is used to demonstrate that systems function not only with respect to their most local super-system, but also with respect to their more global super-systems. © 2012 Elsevier Ltd. All rights reserved.
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Networks of controlled dynamical systems exhibit a variety of interconnection patterns that could be interpreted as the structure of the system. One such interpretation of system structure is a system's signal structure, characterized as the open-loop causal dependencies among manifest variables and represented by its dynamical structure function. Although this notion of structure is among the weakest available, previous work has shown that if no a priori structural information is known about the system, not even the Boolean structure of the dynamical structure function is identifiable. Consequently, one method previously suggested for obtaining the necessary a priori structural information is to leverage knowledge about target specificity of the controlled inputs. This work extends these results to demonstrate precisely the a priori structural information that is both necessary and sufficient to reconstruct the network from input-output data. This extension is important because it significantly broadens the applicability of the identifiability conditions, enabling the design of network reconstruction experiments that were previously impossible due to practical constraints on the types of actuation mechanisms available to the engineer or scientist. The work is motivated by the proteomics problem of reconstructing the Per-Arnt-Sim Kinase pathway used in the metabolism of sugars. © 2012 IEEE.