976 resultados para HIERARCHICAL CONTROL


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Ramp signalling is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, ramp signalling algorithms fall into two categories: local control and coordinated control by their effective scope. Coordinated ramp signalling strategies make use of measurements from the entire motorway network to operate individual ramp signals for the optimal performances at the network level. This study proposes a multi-hierarchical strategy for coordinated ramp signalling. The strategy is structured in two layers. At the higher layer with a longer update interval, coordination group is assembled and disassembled based on the location of high-risk breakdown flow. At the lower layer with a shorter update interval, individual ramps are hired to serve the coordination and are also released based on the prevailing congestion level on the ramp. This strategy is modelled and applied to the northbound Pacific Motorway micro-simulation platform (AIMSUN). The simulation results show an effective congestion mitigation of the proposed strategy.

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We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

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Ramp metering (RM) is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, RM algorithms fall into two categories by their effective scope: local control and coordinated control. Local control algorithm determines the metering rate based on the traffic condition on adjacent motorway mainline and the on-ramp. Conversely, coordinated RM strategies make use of measurements from the entire motorway network to operate individual ramp signals for optimal performance at the network level. This study proposes a multi-hierarchical strategy for on-ramp coordination. The strategy is structured in two layers. At the higher layer, a centralised, predictive controller plans the coordination control within a long update interval based on the location of high-risk breakdown flow. At the lower layer, reactive controllers determine the metering rates of those ramps involved in the ramp coordination with a short update interval. This strategy is modelled and applied to the northbound model of the Pacific Motorway in a micro-simulation platform (AIMSUN). The simulation results show that the proposed strategy effectively delays the onset of congestion and reduces total congestion with better managed on-ramp queues.

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Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

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In this paper, the control aspects of a hierarchical organization under the influence of "proportionality" policies are analyzed. Proportionality policies are those that restrict the recruitment to every level of the hierarchy (except the bottom most level or base level) to be in strict proportion to the promotions into that level. Both long term and short term control analysis have been discussed. In long term control the specific roles of the parameters of the system with regard to control of the shape and size of the system have been analyzed and yield suitable control strategies. In short term control, the attainability of a target or goal structure within a specific time from a given initial structure has been analyzed and yields the required recruitment strategies. The theoretical analyses have been illustrated with computational examples and also with real world data.

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In this paper, the control aspects of a hierarchical organization under the influence of "proportionality" policies are analyzed. Proportionality policies are those that restrict the recruitment to every level of the hierarchy (except the bottom most level or base level) to be in strict proportion to the promotions into that level. Both long term and short term control analysis have been discussed. In long term control the specific roles of the parameters of the system with regard to control of the shape and size of the system have been analyzed and yield suitable control strategies. In short term control, the attainability of a target or goal structure within a specific time from a given initial structure has been analyzed and yields the required recruitment strategies. The theoretical analyses have been illustrated with computational examples and also with real world data. The control of such proportionality systems is then compared with that of the general systems (which do not follow such policies) with some significant conclusions. The control relations of such proportionality systems are found to be simpler and more practically feasible than those of general Markov systems, which do not have such restrictions. Such proportionality systems thus not only retain and match the flexibility of general Markov systems but also have the added advantage of simpler and more practically feasible controls. The proportionality policies hence act as an alternative and more practicably feasible means of control. (C) 2004 Elsevier Inc. All rights reserved.

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Stem cell response to a library of scaffolds with varied 3D structures was investigated. Microarray screening revealed that each type of scaffold structure induced a unique gene expression signature in primary human bone marrow stromal cells (hBMSCs). Hierarchical cluster analysis showed that treatments sorted by scaffold structure and not by polymer chemistry suggesting that scaffold structure was more influential than scaffold composition. Further, the effects of scaffold structure on hBMSC function were mediated by cell shape. Of all the scaffolds tested, only scaffolds with a nanofibrous morphology were able to drive the hBMSCs down an osteogenic lineage in the absence of osteogenic supplements. Nanofiber scaffolds forced the hBMSCs to assume an elongated, highly branched morphology. This same morphology was seen in osteogenic controls where hBMSCs were cultured on flat polymer films in the presence of osteogenic supplements (OS). In contrast, hBMSCs cultured on flat polymer films in the absence of OS assumed a more rounded and less-branched morphology. These results indicate that cells are more sensitive to scaffold structure than previously appreciated and suggest that scaffold efficacy can be optimized by tailoring the scaffold structure to force cells into morphologies that direct them to differentiate down the desired lineage. Published by Elsevier Ltd.

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The transcriptional regulation of gene expression is orchestrated by complex networks of interacting genes. Increasing evidence indicates that these `transcriptional regulatory networks' (TRNs) in bacteria have an inherently hierarchical architecture, although the design principles and the specific advantages offered by this type of organization have not yet been fully elucidated. In this study, we focussed on the hierarchical structure of the TRN of the gram-positive bacterium Bacillus subtilis and performed a comparative analysis with the TRN of the gram-negative bacterium Escherichia coli. Using a graph-theoretic approach, we organized the transcription factors (TFs) and sigma-factors in the TRNs of B. subtilis and E. coli into three hierarchical levels (Top, Middle and Bottom) and studied several structural and functional properties across them. In addition to many similarities, we found also specific differences, explaining the majority of them with variations in the distribution of s-factors across the hierarchical levels in the two organisms. We then investigated the control of target metabolic genes by transcriptional regulators to characterize the differential regulation of three distinct metabolic subsystems (catabolism, anabolism and central energy metabolism). These results suggest that the hierarchical architecture that we observed in B. subtilis represents an effective organization of its TRN to achieve flexibility in response to a wide range of diverse stimuli.

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We report results of controlled tuning of the local density of states (LDOS) in versatile, flexible, and hierarchical self assembled plasmonic templates. Using 5 nm diameter gold (Au) spherical nanoantenna within a polymer template randomly dispersed with quantum dots, we show how the photoluminescence intensity and lifetime anisotropy of these dots can be significantly enhanced through LDOS tuning. Finite difference time domain simulations corroborate the experimental observations and extend the regime of enhancement to a wider range of geometric and spectral parameters bringing out the versatility of these functional plasmonic templates. It is also demonstrated how the templates act as plasmonic resonators for effectively engineer giant enhancement of the scattering efficiency of these nano antenna embedded in the templates. Our work provides an alternative method to achieve spontaneous emission intensity and anisotropy enhancement with true nanoscale plasmon resonators. (C) 2015 AIP Publishing LLC.

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Despite the complexity of biological networks, we find that certain common architectures govern network structures. These architectures impose fundamental constraints on system performance and create tradeoffs that the system must balance in the face of uncertainty in the environment. This means that while a system may be optimized for a specific function through evolution, the optimal achievable state must follow these constraints. One such constraining architecture is autocatalysis, as seen in many biological networks including glycolysis and ribosomal protein synthesis. Using a minimal model, we show that ATP autocatalysis in glycolysis imposes stability and performance constraints and that the experimentally well-studied glycolytic oscillations are in fact a consequence of a tradeoff between error minimization and stability. We also show that additional complexity in the network results in increased robustness. Ribosome synthesis is also autocatalytic where ribosomes must be used to make more ribosomal proteins. When ribosomes have higher protein content, the autocatalysis is increased. We show that this autocatalysis destabilizes the system, slows down response, and also constrains the system’s performance. On a larger scale, transcriptional regulation of whole organisms also follows architectural constraints and this can be seen in the differences between bacterial and yeast transcription networks. We show that the degree distributions of bacterial transcription network follow a power law distribution while the yeast network follows an exponential distribution. We then explored the evolutionary models that have previously been proposed and show that neither the preferential linking model nor the duplication-divergence model of network evolution generates the power-law, hierarchical structure found in bacteria. However, in real biological systems, the generation of new nodes occurs through both duplication and horizontal gene transfers, and we show that a biologically reasonable combination of the two mechanisms generates the desired network.

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This paper describes work performed as part of the U.K. Alvey sponsored Voice Operated Database Inquiry System (VODIS) project in the area of intelligent dialogue control. The principal aims of the work were to develop a habitable interface for the untrained user; to investigate the degree to which dialogue control can be used to compensate for deficiencies in recognition performance; and to examine the requirements on dialogue control for generating natural speech output. A data-driven methodology is described based on the use of frames in which dialogue topics are organized hierarchically. The concept of a dynamically adjustable scope is introduced to permit adaptation to recognizer performance and the use of historical and hierarchical contexts are described to facilitate the construction of contextually relevant output messages. © 1989.

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This paper aims to solve the fault tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre-compensators, a global model predictive controller and a supervisory controller is proposed. In the model predictive pre-compensator, an extended Kalman Filter is designed to estimate the system states and various fault parameters. Based on the estimation, a group of model predictive controllers are designed to compensate the fault effects for each component of the wind turbine. The global MPC is used to schedule the operation of the components and exploit potential system-level redundancies. Extensive simulations of various fault conditions show that the proposed controller has small transients when faults occur and uses smoother and smaller generator torque and pitch angle inputs than the default controller. This paper shows that MPC can be a good candidate for fault tolerant controllers, especially the one with an adaptive internal model combined with a parameter estimation and update mechanism, such as an extended Kalman Filter. © 2012 IFAC.

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Electron and hole conducting 10-nm-wide polymer morphologies hold great promise for organic electro-optical devices such as solar cells and light emitting diodes. The self-assembly of block-copolymers (BCPs) is often viewed as an efficient way to generate such materials. Here, a functional block copolymer that contains perylene bismide (PBI) side chains which can crystallize via π-π stacking to form an electron conducting microphase is patterned harnessing hierarchical electrohydrodynamic lithography (HEHL). HEHL film destabilization creates a hierarchical structure with three distinct length scales: (1) micrometer-sized polymer pillars, containing (2) a 10-nm BCP microphase morphology that is aligned perpendicular to the substrate surface and (3) on a molecular length scale (0.35-3 nm) PBI π-π-stacks traverse the HEHL-generated plugs in a continuous fashion. The good control over BCP and PBI alignment inside the generated vertical microstructures gives rise to liquid-crystal-like optical dichroism of the HEHL patterned films, and improves the electron conductivity across the film by 3 orders of magnitude. © 2013 American Chemical Society.

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Surfaces coated with nanoscale filaments such as silicon nanowires and carbon nanotubes are potentially compelling for high-performance battery and capacitor electrodes, photovoltaics, electrical interconnects, substrates for engineered cell growth, dry adhesives, and other smart materials. However, many of these applications require a wet environment or involve wet processing during their synthesis. The capillary forces introduced by these wet environments can lead to undesirable aggregation of nanoscale filaments, but control of capillary forces can enable manipulation of the filaments into discrete aggregates and novel hierarchical structures. Recent studies suggest that the elastocapillary self-assembly of nanofilaments can be a versatile and scalable means to build complex and robust surface architectures. To enable a wider understanding and use of elastocapillary self-assembly as a fabrication technology, we give an overview of the underlying fundamentals and classify typical implementations and surface designs for nanowires, nanotubes, and nanopillars made from a wide variety of materials. Finally, we discuss exemplary applications and future opportunities to realize new engineered surfaces by the elastocapillary self-assembly of nanofilaments. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Hierarchical heterostructures of zinc antimonate nanoislands on ZnO nanobelts were prepared by simple annealing of the polymeric precursor. Sb can promote the growth of ZnO nanobelts along the [552] direction because of the segregation of Sb dopants on the +(001) and (110) surfaces of ZnO nanobelts. Furthermore, the ordered nanoislands of toothlike ZnSb2O6 along the [001](ZnO) direction and rodlike Zn7Sb2O12 along the [110](ZnO) direction can be formed because of the match relation of the lattice and polar charges between ZnO and zinc antimonate. The incorporation of Sb in a ZnO lattice induces composition fluctuation, and the growth of zinc antimonate nanoislands on nanobelt sides induces interface fluctuation, resulting in dominance of the bound exciton transition in the room temperature near-band-edge (NBE) emission at relatively low excitation intensity. At high excitation intensity, however, Auger recombination makes photogenerated electrons release phonon and relax from the conduction band to the trap states, causing the NBE emission to gradually saturate and redshift with increasing excitation intensity. The green emission more reasonably originates from the recombination of electrons in shallow traps with doubly charged V-O** oxygen vacancies. Because a V-O** center can trap a photoactivated electron and change to a singly charged oxygen vacancy V-O* state, its emission intensity exhibits a maximum with increasing excitation intensity.