103 resultados para Modelling lifetime data


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Unmanned surface vehicles (USVs) are able to accomplish difficult and challenging tasks both in civilian and defence sectors without endangering human lives. Their ability to work round the clock makes them well-suited for matters that demand immediate attention. These issues include but not limited to mines countermeasures, measuring the extent of an oil spill and locating the source of a chemical discharge. A number of USV programmes have emerged in the last decade for a variety of aforementioned purposes. Springer USV is one such research project highlighted in this paper. The intention herein is to report results emanating from data acquired from experiments on the Springer vessel whilst testing its advanced navigation, guidance and control (NGC) subsystems. The algorithms developed for these systems are based on soft-computing methodologies. A novel form of data fusion navigation algorithm has been developed and integrated with a modified optimal controller. Experimental results are presented and analysed for various scenarios including single and multiple waypoints tracking and fixed and time-varying reference bearings. It is demonstrated that the proposed NGC system provides promising results despite the presence of modelling uncertainty and external disturbances.

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Simple pictures under everyday viewing conditions evoke impressions of surfaces oriented in depth. These impressions have been studied by measuring the slants of perceived surfaces, with probes (rotating arrowheads) designed to respect the distinctive character of depicted scenes. Converging arguments indicated that the perceived orientation of the probes was near theoretical values. A series of experiments showed that subjects formed well-defined impressions of depicted surface orientation. The literature suggests that perceived objects might be flattened', but that was not the general rule. Instead, both mean slant and uncertainty fitted models in which slant estimates are derived in a relatively straightforward way from local relations in the picture. Simplifying pictures tended to make orientation estimates less certain, particularly away from the natural anchor points (vertical and horizontal). The shape of the object affected all aspects of the observed-object/percept relationship. Individual differences were large, and suggest that different individuals used different relationships as a basis for their estimates. Overall, data suggest that everyday picture perception is strongly selective and weakly integrative. In particular, depicted slant is estimated by finding a picture feature which will be strongly related to it if the object contains a particular regularity, not by additive integration of evidence from multiple directly and indirectly relevant sources.

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The advantage of using an available and abundant residual biomass, such as lignin, as a raw material for activated carbons is that it provides additional economical interest to the technical studies. In the current investigation, a more complete understanding of adsorption of Cr(VI) from aqueous systems onto H PO -acid activated lignin has been achieved via microcolumns, which were operated under various process conditions. The practice of using microcolumn is appropriate for defining the adsorption parameters and for screening a large number of potential adsorbents. The effects of solution pH (2-8), initial metal ion concentration (0.483-1.981 mmol·L ), flow rate (1.0-3.1 cm ·min ), ionic strength (0.01-0.30 mmol·L ) and adsorbent mass (0.11-0.465 g) on Cr(VI) adsorption were studied by assessing the microcolumn breakthrough curve. The microcolumn data were fitted by the Thomas model, the modified Dose model and the BDST model. As expected, the adsorption capacity increased with initial Cr(VI) concentration. High linear flow rates, pH values and ionic strength led to early breakthrough of Cr(VI). The model constants obtained in this study can be used for the design of pilot scale adsorption process. © 2012 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press (CIP).

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The injection stretch blow moulding process is used to manufacture PET containers used in the soft drinks and carbonated soft drinks industry. The process consists of a test tube like specimen known as a preform which is heated, stretch and blown into a mould to form the container. This research is focused on developing a validated simulation of the process thus enabling manufacturers to design their products in a virtual environment without the need to waste time, material and energy. The simulation has been developed using the commercial FEA package Abaqus and has been validated using state of the art data acquisition system consisting of measurements for preform temperature (inner and outer wall) using a device known as THERMOscan (Figure 1), stretch rod force and velocity, internal pressure and air temperature inside the preform using an instrumented stretch rod and the?exact?timing of when the preform touches the mould wall using contact sensors.? In addition, validation studies have also been performed by blowing a perform without a mould and using high sped imaging technology in cooperation with an advanced digital image correlation system (VIC 3D) to provided new quantitative information on the behaviour of PET during blowing.? The approach has resulted in a realistic simulation in terms of accurate input parameters, preform shape evolution and prediction of final properties.

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In many environmental valuation applications standard sample sizes for choice modelling surveys are impractical to achieve. One can improve data quality using more in-depth surveys administered to fewer respondents. We report on a study using high quality rank-ordered data elicited with the best-worst approach. The resulting "exploded logit" choice model, estimated on 64 responses per person, was used to study the willingness to pay for external benefits by visitors for policies which maintain the cultural heritage of alpine grazing commons. We find evidence supporting this approach and reasonable estimates of mean WTP, which appear theoretically valid and policy informative. © The Author (2011).

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The fate and cycling of two selected POPs is investigated for the North Sea system with an improved version of a fate and transport ocean model (FANTOM). The model uses atmospheric data from the EMEP MSC East POP model (Gusev et al., 2009), giving reasonable concentrations and seasonal distributions for the entire region, as opposed to the three observation stations that Ilyina et al. (2006) were limited to. Other model improvements include changes in the calculation of POP exchange between the water column and sediment.

We chose to simulate the fate of two POPs with very different properties, ?-HCH and PCB 153. Since the fate and cycling of POPs are strongly affected by hydrodynamic processes, a high resolution version of the Hamburg Shelf Ocean Model (HAMSOM) was developed and utilised. Simulations were made for the period 1996–2005. Both models were validated by comparing results with available data, which showed that the simulations were of very satisfactory quality.

Model results show that the North Sea is a net sink for ?-HCH and a net source to the atmosphere of PCB 153. Total masses of ?-HCH and PCB 153 in 2005 are reduced to 30% and 50%, respectively, of 1996 values.

Storms resuspending bottom sediments into the water column mobilise POPs into the atmosphere and have the potential to deliver substantial loads of these POPs into Europe.

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Approach:
In-situ passive gradient comparative artificial tracer testing, undertaken using solutes (Uranine and Iodide), Bacteria (E.coli and P.putida) and bacteriophage (H40/1), permitted comparison of the mobility of different sized microorganisms relative to solutes in the sand and gravel aquifer underlying Dornach, Germany.
Tracer breakthrough curves reveal that even though uranine initially arrived at observation wells at the same time as microbiological tracers, maximum relative concentrations were sometimes less than those of microbiological tracers, while solute breakthrough curves proved more disperse.
Monitoring uranine breakthrough with depth suggested tracers arrived in observation wells in discrete 0.5m-1m thick intervals, over the aquifer’s 12m saturated thickness. Nearby exposures of aquifer material suggested that the aquifer consisted of sandy gravels enveloping sequences of open framework (OW) gravel up to 1m thick. Detailed examination of OW units revealed that they contained lenses of silty sand up to 1m long x 30cm thick., while granulometric data suggested that the gravel was two to three orders of magnitude more permeable than the enveloping sandy gravel.
Solute and microorganism tracer responses could not be simulated using conventional advective-dispersive equation solutions employing the same velocity and dispersion terms. By contrast solute tracer responses, modelled using a dual porosity approach for fractured media (DP-1D) corresponded well to observed field data. Simulating microorganism responses using the same transport terms, but no dual porosity term, generated good model fits and explained the higher relative concentration of the bacteria, compared to the non-reactive solute, even with first order removal to account for lower RR. Geologically, model results indicate that the silty units within open framework gravels are accessible to solute tracers, but not to microorganisms.
Importance:
Results highlight the benefits of geological observations developing appropriate conceptual models of solute and micro organism transport and in developing suitable numerical approaches to quantifying microorganism mobility at scales appropriate for the development of groundwater supply (wellhead) protection zones.

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Longevity risk has become one of the major risks facing the insurance and pensions markets globally. The trade in longevity risk is underpinned by accurate forecasting of mortality rates. Using techniques from macroeconomic forecasting, we propose a dynamic factor model of mortality that fits and forecasts mortality rates parsimoniously.We compare the forecasting quality of this model and of existing models and find that the dynamic factor model generally provides superior forecasts when applied to international mortality data. We also show that existing multifactorial models have superior fit but their forecasting performance worsens as more factors are added. The dynamic factor approach used here can potentially be further improved upon by applying an appropriate stopping rule for the number of static and dynamic factors. 

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The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

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Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.

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This paper compares the applicability of three ground survey methods for modelling terrain: one man electronic tachymetry (TPS), real time kinematic GPS (GPS), and terrestrial laser scanning (TLS). Vertical accuracy of digital terrain models (DTMs) derived from GPS, TLS and airborne laser scanning (ALS) data is assessed. Point elevations acquired by the four methods represent two sections of a mountainous area in Cumbria, England. They were chosen so that the presence of non-terrain features is constrained to the smallest amount. The vertical accuracy of the DTMs was addressed by subtracting each DTM from TPS point elevations. The error was assessed using exploratory measures including statistics, histograms, and normal probability plots. The results showed that the internal measurement accuracy of TPS, GPS, and TLS was below a centimetre. TPS and GPS can be considered equally applicable alternatives for sampling the terrain in areas accessible on foot. The highest DTM vertical accuracy was achieved with GPS data, both on sloped terrain (RMSE 0.16. m) and flat terrain (RMSE 0.02. m). TLS surveying was the most efficient overall but veracity of terrain representation was subject to dense vegetation cover. Therefore, the DTM accuracy was the lowest for the sloped area with dense bracken (RMSE 0.52. m) although it was the second highest on the flat unobscured terrain (RMSE 0.07. m). ALS data represented the sloped terrain more realistically (RMSE 0.23. m) than the TLS. However, due to a systematic bias identified on the flat terrain the DTM accuracy was the lowest (RMSE 0.29. m) which was above the level stated by the data provider. Error distribution models were more closely approximated by normal distribution defined using median and normalized median absolute deviation which supports the use of the robust measures in DEM error modelling and its propagation. © 2012 Elsevier Ltd.

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In recent years, several phenomenological dynamical models have been formulated that describe how perceptual variables are incorporated in the control of motor variables. We call these short-route models as they do not address how perception-action patterns might be constrained by the dynamical properties of the sensory, neural and musculoskeletal subsystems of the human action system. As an alternative, we advocate a long-route modelling approach in which the dynamics of these subsystems are explicitly addressed and integrated to reproduce interceptive actions. The approach is exemplified through a discussion of a recently developed model for interceptive actions consisting of a neural network architecture for the online generation of motor outflow commands, based on time-to-contact information and information about the relative positions and velocities of hand and ball. This network is shown to be consistent with both behavioural and neurophysiological data. Finally, some problems are discussed with regard to the question of how the motor outflow commands (i.e. the intended movement) might be modulated in view of the musculoskeletal dynamics.

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Medical geology research has recognised a number of potentially toxic elements (PTEs), such as arsenic, cobalt, chromium, copper, nickel, lead, vanadium, uranium and zinc, known to influence human disease by their respective deficiency or toxicity. As the impact of infectious diseases has decreased and the population ages, so cancer has become the most common cause of death in developed countries including Northern Ireland. This research explores the relationship between environmental exposure to potentially toxic elements in soil and cancer disease data across Northern Ireland. The incidence of twelve different cancer types (lung, stomach, leukaemia, oesophagus, colorectal, bladder, kidney, breast, mesothelioma, melanoma and non melanoma(NM) both basal and squamous, were examined in the form of twenty-five coded datasets comprising aggregates over the 12 year period from 1993 to 2006. A local modelling technique,geographically weighted regression (GWR) is usedto explore the relationship between environmental exposure and cancer disease data. The results show comparisons of the geographical incidence of certain cancers (stomach and NM squamous skin cancer) in relation to concentrations of certain PTEs (arsenic levels in soils and radon were identified). Findings from the research have implications for regional human health risk assessments.

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We use a multidimensional Monte Carlo code to compute X-ray spectra for a variety of active galactic nucleus (AGN) disc-wind outflow geometries. We focus on the formation of blueshifted absorption features in the Fe K band and show that line features similar to those which have been reported in observations are often produced for lines of sight through disc-wind geometries. We also discuss the formation of other spectral features in highly ionized outflows. In particular, we show that, for sufficiently high wind densities, moderately strong Fe K emission lines can form and that electron scattering in the flow may cause these lines to develop extended red wings. We illustrate the potential relevance of such models to the interpretation of real X-ray data by comparison with observations of a well-known AGN, Mrk 766. Journal compilation © 2008 RAS.

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High-velocity outflows from supermassive black holes have been invoked to explain the recent identification of strong absorption features in the hard X-ray spectra of several quasars. Here, Monte Carlo radiative transfer calculations are performed to synthesize X-ray spectra from models of such flows. It is found that simple, parametric biconical outflow models with plausible choices for the wind parameters predict spectra that are in good qualitative agreement with observations in the 2-10 keV band. The influence on the spectrum of both the mass-loss rate and opening angle of the flow are considered: the latter is important since photon leakage plays a significant role in establishing an ionization gradient within the flow, a useful discriminant between spherical and conical outflow for this and other applications. Particular attention is given to the bright quasar PG 1211+143 for which constraints on the outflow geometry and mass-loss rate are discussed subject to the limitations of the currently available observational data.