901 resultados para Recommended Systems, Component Technolog, Customisation, Collaborative Filtering


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Based on a well-established stratigraphic framework and 47 AMS-14C dated sediment cores, the distribution of facies types on the NW Iberian margin is analysed in response to the last deglacial sea-level rise, thus providing a case study on the sedimentary evolution of a high-energy, low-accumulation shelf system. Altogether, four main types of sedimentary facies are defined. (1) A gravel-dominated facies occurs mostly as time-transgressive ravinement beds, which initially developed as shoreface and storm deposits in shallow waters on the outer shelf during the last sea-level lowstand; (2) A widespread, time-transgressive mixed siliceous/biogenic-carbonaceous sand facies indicates areas of moderate hydrodynamic regimes, high contribution of reworked shelf material, and fluvial supply to the shelf; (3) A glaucony-containing sand facies in a stationary position on the outer shelf formed mostly during the last-glacial sea-level rise by reworking of older deposits as well as authigenic mineral formation; and (4) A mud facies is mostly restricted to confined Holocene fine-grained depocentres, which are located in mid-shelf position. The observed spatial and temporal distribution of these facies types on the high-energy, low-accumulation NW Iberian shelf was essentially controlled by the local interplay of sediment supply, shelf morphology, and strength of the hydrodynamic system. These patterns are in contrast to high-accumulation systems where extensive sediment supply is the dominant factor on the facies distribution. This study emphasises the importance of large-scale erosion and material recycling on the sedimentary buildup during the deglacial drowning of the shelf. The presence of a homogenous and up to 15-m thick transgressive cover above a lag horizon contradicts the common assumption of sparse and laterally confined sediment accumulation on high-energy shelf systems during deglacial sea-level rise. In contrast to this extensive sand cover, laterally very confined and maximal 4-m thin mud depocentres developed during the Holocene sea-level highstand. This restricted formation of fine-grained depocentres was related to the combination of: (1) frequently occurring high-energy hydrodynamic conditions; (2) low overall terrigenous input by the adjacent rivers; and (3) the large distance of the Galicia Mud Belt to its main sediment supplier.

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Nowadays, the amount of customers using sites for shopping is greatly increasing, mainly due to the easiness and rapidity of this way of consumption. The sites, differently from physical stores, can make anything available to customers. In this context, Recommender Systems (RS) have become indispensable to help consumers to find products that may possibly pleasant or be useful to them. These systems often use techniques of Collaborating Filtering (CF), whose main underlying idea is that products are recommended to a given user based on purchase information and evaluations of past, by a group of users similar to the user who is requesting recommendation. One of the main challenges faced by such a technique is the need of the user to provide some information about her preferences on products in order to get further recommendations from the system. When there are items that do not have ratings or that possess quite few ratings available, the recommender system performs poorly. This problem is known as new item cold-start. In this paper, we propose to investigate in what extent information on visual attention can help to produce more accurate recommendation models. We present a new CF strategy, called IKB-MS, that uses visual attention to characterize images and alleviate the new item cold-start problem. In order to validate this strategy, we created a clothing image database and we use three algorithms well known for the extraction of visual attention these images. An extensive set of experiments shows that our approach is efficient and outperforms state-of-the-art CF RS.

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Conventional reliability models for parallel systems are not applicable for the analysis of parallel systems with load transfer and sharing. In this short communication, firstly, the dependent failures of parallel systems are analyzed, and the reliability model of load-sharing parallel system is presented based on Miner cumulative damage theory and the full probability formula. Secondly, the parallel system reliability is calculated by Monte Carlo simulation when the component life follows the Weibull distribution. The research result shows that the proposed reliability mathematical model could analyze and evaluate the reliability of parallel systems in the presence of load transfer.

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Human motion monitoring is an important function in numerous applications. In this dissertation, two systems for monitoring motions of multiple human targets in wide-area indoor environments are discussed, both of which use radio frequency (RF) signals to detect, localize, and classify different types of human motion. In the first system, a coherent monostatic multiple-input multiple-output (MIMO) array is used, and a joint spatial-temporal adaptive processing method is developed to resolve micro-Doppler signatures at each location in a wide-area for motion mapping. The downranges are obtained by estimating time-delays from the targets, and the crossranges are obtained by coherently filtering array spatial signals. Motion classification is then applied to each target based on micro-Doppler analysis. In the second system, multiple noncoherent multistatic transmitters (Tx's) and receivers (Rx's) are distributed in a wide-area, and motion mapping is achieved by noncoherently combining bistatic range profiles from multiple Tx-Rx pairs. Also, motion classification is applied to each target by noncoherently combining bistatic micro-Doppler signatures from multiple Tx-Rx pairs. For both systems, simulation and real data results are shown to demonstrate the ability of the proposed methods for monitoring patient repositioning activities for pressure ulcer prevention.

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In the development of wave energy converters, the mooring system is a key component for a safe station-keeping and an important factor in the cost of the wave energy production. Generally, when designing a mooring system for a wave energy converter, two important conditions must be considered: (i) that the mooring system must be strong enough to limit the drifting motions, even in extreme waves, tidal and wind conditions and (ii) it must be compliant enough so that the impact on wave energy production can be minimised. It is frequently found that these two conditions are contradictory. The existing solutions mainly include the use of heavy chains, which create a catenary shaped mooring configuration, allowing limited flexibility within the mooring system, and hence very large forces may still be present on mooring lines and thus on anchors. This solution is normally quite expensive if the costs of the materials and installation are included. This paper presents a new solution to the mooring system for wave energy converters within the FP7 project, ‘GeoWAVE’, which is a project aiming to develop a new generation of the moorings system for minimising the loads on mooring lines and anchors, the impact on the device motions for power conversion, and the footprint if it is applicable, and meanwhile the new types of anchors are also addressed within the project. However this paper will focus on the new mooring system by presenting the wave tank test results of the Pelamis wave energy converter model and the new developed mooring system. It can be seen that the new generation of mooring system can significantly reduce the loads on mooring lines and anchors, and reduce the device excursions as a result of the new mooring system when compare to the conventional catenary mooring.

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As an alternative to transverse spiral or hoop steel reinforcement, fiber reinforced polymers (FRPs) were introduced to the construction industry in the 1980's. The concept of concrete-filled FRP tube (CFFT) has raised great interest amongst researchers in the last decade. FRP tube can act as a pour form, protective jacket, and shear and flexural reinforcement for concrete. However, seismic performance of CFFT bridge substructure has not yet been fully investigated. Experimental work in this study included four two-column bent tests, several component tests and coupon tests. Four 1/6-scale bridge pier frames, consisting of a control reinforced concrete frame (RCF), glass FRP-concrete frame (GFF), carbon FRP-concrete frame (CFF), and hybrid glass/carbon FRP-concrete frame (HFF) were tested under reverse cyclic lateral loading with constant axial loads. Specimen GFF did not show any sign of cracking at a drift ratio as high as 15% with considerable loading capacity, whereas Specimen CFF showed that lowest ductility with similar load capacity as in Specimen GFF. FRP-concrete columns and pier cap beams were then cut from the pier frame specimens, and were tested again in three point flexure under monotonic loading with no axial load. The tests indicated that bonding between FRP and concrete and yielding of steel both affect the flexural strength and ductility of the components. The coupon tests were carried out to establish the tensile strength and elastic modulus of each FRP tube and the FRP mold for the pier cap beam in the two principle directions of loading. A nonlinear analytical model was developed to predict the load-deflection responses of the pier frames. The model was validated against test results. Subsequently, a parametric study was conducted with variables such as frame height to span ratio, steel reinforcement ratio, FRP tube thickness, axial force, and compressive strength of concrete. A typical bridge was also simulated under three different ground acceleration records and damping ratios. Based on the analytical damage index, the RCF bridge was most severely damaged, whereas the GFF bridge only suffered minor repairable damages. Damping ratio was shown to have a pronounced effect on FRP-concrete bridges, just the same as in conventional bridges. This research was part of a multi-university project, which is founded by the National Science Foundation (NSF) Network for Earthquake Engineering Simulation Research (NEESR) program.

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This paper presents a vision that allows the combined use of model-driven engineering, run-time monitoring, and animation for the development and analysis of components in real-time embedded systems. Key building block in the tool environment supporting this vision is a highly-customizable code generation process. Customization is performed via a configuration specification which describes the ways in which input is provided to the component, the ways in which run-time execution information can be observed, and how these observations drive animation tools. The environment is envisioned to be suitable for different activities ranging from quality assurance to supporting certification, teaching, and outreach and will be built exclusively with open source tools to increase impact. A preliminary prototype implementation is described.

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The sense and avoid capability is one of the greatest challenges that has to be addressed to safely integrate unmanned aircraft systems into civil and nonsegregated airspace. This paper gives a review of existing regulations, recommended practices, and standards in sense and avoid for unmanned aircraft systems. Gaps and issues are identified, as are the different factors that are likely to affect actual sense and avoid requirements. It is found that the operational environment (flight altitude, meteorological conditions, and class of airspace) plays an important role when determining the type of flying hazards that the unmanned aircraft system might encounter. In addition, the automation level and the data-link architecture of the unmanned aircraft system are key factors that will definitely determine the sense and avoid system requirements. Tactical unmanned aircraft, performing similar missions to general aviation, are found to be the most challenging systems from an sense and avoid point of view, and further research and development efforts are still needed before their seamless integration into nonsegregated airspace

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This paper deals with the place of narrative, that is, storytelling, in public deliberation. A distinction is made between weak and strong conceptions of narrative. According to the weak one, storytelling is but one rhetorical device among others with which social actors produce and convey meaning. In contrast, the strong conception holds that narrative is necessary to communicate, and argue, about topics such as the human experience of time, collective identities and the moral and ethical validity of values. The upshot of this idea is that storytelling should be a necessary component of any ideal of public deliberation. Contrary to recent work by deliberative theorists, who tend to adopt the weak conception of narrative, the author argues for embracing the strong one. The main contention of this article is that stories not only have a legitimate place in deliberation, but are even necessary to formulate certain arguments in the fi rst place; for instance, arguments drawing on historical experience. This claim, namely that narrative is constitutive of certain arguments, in the sense that, without it, said reasons cannot be articulated, is illustrated by deliberative theory’s own narrative underpinnings. Finally, certain possible objections against the strong conception of narrative are dispelled.

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As part of the Prato Collaborative I am undertaking a Delphi Study to explore the developmental journeys that nine different countries (including NI and Ireland) have undertaken to better meet the needs of families where a parent has a mental illness in adult mental health and children’s services. This research has potential to impact FFP in adult mental health and children's services.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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The benefits of pavement management system when fully implemented are well known and the history of successful implementation is rich. Implementation occurs, for purposes of this paper, when the pavement management system is the critical component for making pavement decisions. This paper addresses the issues that act as barriers to full implementation of pavement management systems. Institutional barriers, not technical and financial barriers, are more commonly responsible for a pavement management systems falling short of full implementation. The paper groups these institutional issues into a general taxonomy. In general, more effort needs to be put forth by highway agencies to overcome institutional issues. Most agencies approach pavement management as a technical process, but more commonly, institutional issues become more problematic and thus require more attention paid to institutional issues. The paper concludes by summarizing the implementation process being taken by the Iowa Department of Transportation. The process was designed to overcome institutional barriers and facilitate the complete and full implementation of their pavement management system.

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Thesis (Ph.D.)--University of Washington, 2016-08