184 resultados para Stochastic Matrix


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The optimal control of problems that are constrained by partial differential equations with uncertainties and with uncertain controls is addressed. The Lagrangian that defines the problem is postulated in terms of stochastic functions, with the control function possibly decomposed into an unknown deterministic component and a known zero-mean stochastic component. The extra freedom provided by the stochastic dimension in defining cost functionals is explored, demonstrating the scope for controlling statistical aspects of the system response. One-shot stochastic finite element methods are used to find approximate solutions to control problems. It is shown that applying the stochastic collocation finite element method to the formulated problem leads to a coupling between stochastic collocation points when a deterministic optimal control is considered or when moments are included in the cost functional, thereby forgoing the primary advantage of the collocation method over the stochastic Galerkin method for the considered problem. The application of the presented methods is demonstrated through a number of numerical examples. The presented framework is sufficiently general to also consider a class of inverse problems, and numerical examples of this type are also presented. © 2011 Elsevier B.V.

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The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

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Bone is a complex material with a hierarchical multi-scale organization from the molecule to the organ scale. The genetic bone disease, osteogenesis imperfecta, is primarily caused by mutations in the collagen type I genes, resulting in bone fragility. Because the basis of the disease is molecular with ramifications at the whole bone level, it provides a platform for investigating the relationship between structure, composition, and mechanics throughout the hierarchy. Prior studies have individually shown that OI leads to: 1. increased bone mineralization, 2. decreased elastic modulus, and 3. smaller apatite crystal size. However, these have not been studied together and the mechanism for how mineral structure influences tissue mechanics has not been identified. This lack of understanding inhibits the development of more accurate models and therapies. To address this research gap, we used a mouse model of the disease (oim) to measure these outcomes together in order to propose an underlying mechanism for the changes in properties. Our main finding was that despite increased mineralization, oim bones have lower stiffness that may result from the poorly organized mineral matrix with significantly smaller, highly packed and disoriented apatite crystals. Using a composite framework, we interpret the lower oim bone matrix elasticity observed as the result of a change in the aspect ratio of apatite crystals and a disruption of the crystal connectivity.

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To investigate how substrate properties influence stem-cell fate, we cultured single human epidermal stem cells on polydimethylsiloxane (PDMS) and polyacrylamide (PAAm) hydrogel surfaces, 0.1 kPa-2.3 MPa in stiffness, with a covalently attached collagen coating. Cell spreading and differentiation were unaffected by polydimethylsiloxane stiffness. However, cells on polyacrylamide of low elastic modulus (0.5 kPa) could not form stable focal adhesions and differentiated as a result of decreased activation of the extracellular-signal-related kinase (ERK)/mitogen-activated protein kinase (MAPK) signalling pathway. The differentiation of human mesenchymal stem cells was also unaffected by PDMS stiffness but regulated by the elastic modulus of PAAm. Dextran penetration measurements indicated that polyacrylamide substrates of low elastic modulus were more porous than stiff substrates, suggesting that the collagen anchoring points would be further apart. We then changed collagen crosslink concentration and used hydrogel-nanoparticle substrates to vary anchoring distance at constant substrate stiffness. Lower collagen anchoring density resulted in increased differentiation. We conclude that stem cells exert a mechanical force on collagen fibres and gauge the feedback to make cell-fate decisions.

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Matrix anisotropy is important for long term in vivo functionality. However, it is not fully understood how to guide matrix anisotropy in vitro. Experiments suggest actin-mediated cell traction contributes. Although F-actin in 2D displays a stretch-avoidance response, 3D data are lacking. We questioned how cyclic stretch influences F-actin and collagen orientation in 3D. Small-scale cell-populated fibrous tissues were statically constrained and/or cyclically stretched with or without biochemical agents. A rectangular array of silicone posts attached to flexible membranes constrained a mixture of cells, collagen I and matrigel. F-actin orientation was quantified using fiber-tracking software, fitted using a bi-model distribution function. F-actin was biaxially distributed with static constraint. Surprisingly, uniaxial cyclic stretch, only induced a strong stretch-avoidance response (alignment perpendicular to stretching) at tissue surfaces and not in the core. Surface alignment was absent when a ROCK-inhibitor was added, but also when tissues were only statically constrained. Stretch-avoidance was also observed in the tissue core upon MMP1-induced matrix perturbation. Further, a strong stretch-avoidance response was obtained for F-actin and collagen, for immediate cyclic stretching, i.e. stretching before polymerization of the collagen. Results suggest that F-actin stress-fibers avoid cyclic stretch in 3D, unless collagen contact guidance dictates otherwise.

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Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.

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Matrix anisotropy is important for long term in vivo functionality. However, it is not fully understood how to guide matrix anisotropy in vitro. Experiments suggest actin-mediated cell traction contributes. Although F-actin in 2D displays a stretch-avoidance response, 3D data are lacking. We questioned how cyclic stretch influences F-actin and collagen orientation in 3D. Small-scale cell-populated fibrous tissues were statically constrained and/or cyclically stretched with or without biochemical agents. A rectangular array of silicone posts attached to flexible membranes constrained a mixture of cells, collagen I and matrigel. F-actin orientation was quantified using fiber-tracking software, fitted using a bi-model distribution function. F-actin was biaxially distributed with static constraint. Surprisingly, uniaxial cyclic stretch, only induced a strong stretch-avoidance response (alignment perpendicular to stretching) at tissue surfaces and not in the core. Surface alignment was absent when a ROCK-inhibitor was added, but also when tissues were only statically constrained. Stretch-avoidance was also observed in the tissue core upon MMP1-induced matrix perturbation. Further, a strong stretch-avoidance response was obtained for F-actin and collagen, for immediate cyclic stretching, i.e. stretching before polymerization of the collagen. Results suggest that F-actin stress-fibers avoid cyclic stretch in 3D, unless collagen contact guidance dictates otherwise. © 2012 Elsevier Ltd.

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Engineering changes (ECs) are raised throughout the lifecycle of engineering products. A single change to one component produces knock-on effects on others necessitating additional changes. This change propagation significantly affects the development time and cost and determines the product's success. Predicting and managing such ECs is, thus, essential to companies. Some prediction tools model change propagation by algorithms, whereof a subgroup is numerical. Current numerical change propagation algorithms either do not account for the exclusion of cyclic propagation paths or are based on exhaustive searching methods. This paper presents a new matrix-calculation-based algorithm which can be applied directly to a numerical product model to analyze change propagation and support change prediction. The algorithm applies matrix multiplications on mutations of a given design structure matrix accounting for the exclusion of self-dependences and cyclic propagation paths and delivers the same results as the exhaustive search-based Trail Counting algorithm. Despite its factorial time complexity, the algorithm proves advantageous because of its straightforward matrix-based calculations which avoid exhaustive searching. Thereby, the algorithm can be implemented in established numerical programs such as Microsoft Excel which promise a wider application of the tools within and across companies along with better familiarity, usability, practicality, security, and robustness. © 1988-2012 IEEE.

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This paper provides a direct comparison of two stochastic optimisation techniques (Markov Chain Monte Carlo and Sequential Monte Carlo) when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The two methods are then also compared to another existing technique of Mixed-Integer Linear Programming which is also popular in distributed control. © 2011 IFAC.

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In this paper we formulate the nonnegative matrix factorisation (NMF) problem as a maximum likelihood estimation problem for hidden Markov models and propose online expectation-maximisation (EM) algorithms to estimate the NMF and the other unknown static parameters. We also propose a sequential Monte Carlo approximation of our online EM algorithm. We show the performance of the proposed method with two numerical examples. © 2012 IFAC.