966 resultados para quantifying heteroskedasticity


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Telecentric optical computed tomography (optical-CT) is a state-of-the-art method for visualizing and quantifying 3-dimensional dose distributions in radiochromic dosimeters. In this work a prototype telecentric system (DFOS-Duke Fresnel Optical-CT Scanner) is evaluated which incorporates two substantial design changes: the use of Fresnel lenses (reducing lens costs from $10-30K t0 $1-3K) and the use of a 'solid tank' (which reduces noise, and the volume of refractively matched fluid from 1 ltr to 10 cc). The efficacy of DFOS was evaluated by direct comparison against commissioned scanners in our lab. Measured dose distributions from all systems were compared against the predicted dose distributions from a commissioned treatment planning system (TPS). Three treatment plans were investigated including a simple four-field box treatment, a multiple small field delivery, and a complex IMRT treatment. Dosimeters were imaged within 2 h post irradiation, using consistent scanning techniques (360 projections acquired at 1 degree intervals, reconstruction at 2mm). DFOS efficacy was evaluated through inspection of dose line-profiles, and 2D and 3D dose and gamma maps. DFOS/TPS gamma pass rates with 3%/3mm dose difference/distance-to-agreement criteria ranged from 89.3% to 92.2%, compared to from 95.6% to 99.0% obtained with the commissioned system. The 3D gamma pass rate between the commissioned system and DFOS was 98.2%. The typical noise rates in DFOS reconstructions were up to 3%, compared to under 2% for the commissioned system. In conclusion, while the introduction of a solid tank proved advantageous with regards to cost and convenience, further work is required to improve the image quality and dose reconstruction accuracy of the new DFOS optical-CT system.

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Vacuum Arc Remelting (VAR) is the accepted method for producing homogeneous, fine microstructures that are free of inclusions required for rotating grade applications. However, as ingot sizes are increasing INCONEL 718 becomes increasingly susceptible to defects such as freckles, tree rings, and white spots increases for large diameter billets. Therefore, predictive models of these defects are required to allow optimization of process parameters. In this paper, a multiscale and multi-physics model is presented to predict the development of microstructures in the VAR ingot during solidification. At the microscale, a combined stochastic nucleation approach and finite difference solution of the solute diffusion is applied in the semi-solid zone of the VAR ingot. The micromodel is coupled with a solution of the macroscale heat transfer, fluid flow and electromagnetism in the VAR process through the temperature, pressure and fluid flow fields. The main objective of this study is to achieve a better understanding of the formation of the defects in VAR by quantifying the influence of VAR processing parameters on grain nucleation and dendrite growth. In particular, the effect of different ingot growth velocities on the microstructure formation was investigated. It was found that reducing the velocity produces significantly more coarse grains.

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For structural health monitoring it is impractical to identify a large structure with complete measurement due to limited number of sensors and difficulty in field instrumentation. Furthermore, it is not desirable to identify a large number of unknown parameters in a full system because of numerical difficulty in convergence. A novel substructural strategy was presented for identification of stiffness matrices and damage assessment with incomplete measurement. The substructural approach was employed to identify large systems in a divide-and-conquer manner. In addition, the concept of model condensation was invoked to avoid the need for complete measurement, and the recovery process to obtain the full set of parameters was formulated. The efficiency of the proposed method is demonstrated numerically through multi-storey shear buildings subjected to random force. A fairly large structural system with 50 DOFs was identified with good results, taking into consideration the effects of noisy signals and the limited number of sensors. Two variations of the method were applied, depending on whether the sensor could be repositioned. The proposed strategy was further substantiated experimentally using an eight-storey steel plane frame model subjected to shaker and impulse hammer excitations. Both numerical and experimental results have shown that the proposed substructural strategy gave reasonably accurate identification in terms of locating and quantifying structural damage.

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Reviews the guidance given by the House of Lords in Stack v Dowden on quantifying the beneficial interests of cohabiting parties in their former family home when one party seeks to rebut the presumption of joint beneficial ownership. Comments on the subsequent application of the principles by the county court in Adekunle v Ritchie and by the Privy Council in Abbott v Abbott, highlighting the approaches used to establish an equitable interest and to quantify the parties' shares in the properties. Considers whether statutory intervention is now needed to resolve the difficulties. [From Legal Journals Index]

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The links between fuel poverty and poor health are well documented, yet there is no statutory requirement on local authorities to develop fuel poverty strategies, which tend to be patchy nationally and differ substantially in quality. Fuel poverty starts from the perspective of income, even though interventions can improve health. The current public health agenda calls for more partnership-based, cost-effective strategies based on sound evidence. Fuel poverty represents a key area where there is currently little local evidence quantifying and qualifying health gain arising from strategic interventions. As a result, this initial study sought to apply the principles of a health impact assessment to Luton’s Affordable Warmth Strategy, exploring the potential to identify health impact arising – as a baseline for future research – in the context of the public health agenda. A national strategy would help ensure the promotion of targeted fuel poverty strategies.

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There are two major types of erosion testing devices that are used throughout the world for quantifying particle impact erosion against a solid surface. The first of these uses pressurised air to accelerate abrasive particles through a nozzle so that they impinge upon a target specimen. The second adopts a rotating disc to accelerate abrasive particles using the centripetal effect so that they impinge upon a series of targets arranged around the periphery of the disc. This paper reports the findings of a collaborative project that was designed to compare the performance and results obtained from a rig of each of the two types mentioned above. The sand blast type rig was provided by The Department of Powder Science Technology (POSTEC) at The Telemark Technological Research and Development Centre (TEL-TEK), Porsgrunn, Norway while the centripetal effect accelerator was provided by The Wolfson Centre for Bulk Solids Handling Technology, University of Greenwich, London, UK. The test programme included tests against a wide range of materials that are commonly used in pneumatic handling facilities. (Pneumatic handling is a means of conveying and transporting powders and granular solid materials in bulk in industrial process plant, through pipelines using a gas as the carrier medium.) Olivine sand was used as the abrasive and it was projected against the test specimens at velocities and concentrations commensurate with those seen in pneumatic conveyors. In all instances the materials used in the test programme were taken from the same batch so that scatter of experimental results due to specimen variation was minimised. The paper contains a series of recommendations for erosion testing equipment. A discussion based on the results and their applicability to the prediction of wear in pneumatic conveyors concludes the paper.

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Multiple regression equations and response surfaces are used to describe the combined effects of body size, food concentration, acclimation temperature and season on physiological integrations such as the scope for growth, growth efficiency and O:N ratio. Maintenance and optimum ration levels are estimated for Mytilus edulis adapted to different factor combinations. Response surfaces illustrate the validity and sensitivity of the physiological integrations in quantifying the 'physiological condition' and the degree of stress experienced, under conditions ranging from near-optimal, through sub-lethal to lethal.

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Jerry Blackford of the Plymouth Marine Laboratory leads the UK Research Council funded Quantifying and Monitoring Potential Ecosystem Impacts of Geological Carbon Storage (QICS) program, and is a founding member of the new UK CCS Research Centre leading the environment research team. Here he talks to Muriel Cozier about how the world's first experiment to simulate a CO2 leak from underground storage in a marine environment will go a long way toward improving our understanding of a series of complex interactions.

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The rapid increase in renewable energy generation from wind has increased concerns about the impacts that wind arrays have on the marine environment and what these impacts mean for society. One method for identifying the impacts of offshore wind farms (OWFs) on human welfare is through the assessment and valuation of ecosystem services. Using an ecosystem services approach, this paper reviews the impacts of OWFs on the ecosystem services delivered by marine environments. During the construction phase, supporting services such as reduced energy capture and nutrient cycling are changed due to the introduction of hard substrate and the reduction in soft sediment habitat at turbine bases. This may lead to changes in all other ecosystem services, both negative and positive. Quantifying these changes, however, is a challenge partly due to data limitations and a lack of clear understanding of the impacts of OWFs on the marine ecosystems. Scientific effort needs to quantitatively explore the impacts of OWFs on ecosystem functionality and the gathering of data that enables the assessment of changes to ecosystem services. Data needed to better quantify and value the impacts of OWFs on ecosystem services are suggested. The development of methods which integrate socioeconomic valuation of ecosystem services into the evaluation of renewable energy devices compliments efforts in assessing the environmental impacts and should enable a holistic assessment of the impact of renewable energy production and greenhouse gas mitigation technologies on the U. K. carbon footprint.

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A well documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968–2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.

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A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968–2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities.

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Very short-lived halocarbons are significant sources of reactive halogen in the marine boundary layer, and likely in the upper troposphere and lower stratosphere. Quantifying ambient concentrations in the surface ocean and atmosphere is essential for understanding the atmospheric impact of these trace gas fluxes. Despite the body of literature increasing substantially over recent years, calibration issues complicate the comparison of results and limit the utility of building larger-scale databases that would enable further development of the science (e.g. sea-air flux quantification, model validation, etc.). With this in mind, thirty-one scientists from both atmospheric and oceanic halocarbon communities in eight nations gathered in London in February 2008 to discuss the scientific issues and plan an international effort toward developing common calibration scales (http://tinyurl.com/c9cg58). Here, we discuss the outputs from this meeting, suggest the compounds that should be targeted initially, identify opportunities for beginning calibration and comparison efforts, and make recommendations for ways to improve the comparability of previous and future measurements.

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The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of ~6 Pg C yr−1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump.

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The decisions animals make about how long to wait between activities can determine the success of diverse behaviours such as foraging, group formation or risk avoidance. Remarkably, for diverse animal species, including humans, spontaneous patterns of waiting times show random ‘burstiness’ that appears scale-invariant across a broad set of scales. However, a general theory linking this phenomenon across the animal kingdom currently lacks an ecological basis. Here, we demonstrate from tracking the activities of 15 sympatric predator species (cephalopods, sharks, skates and teleosts) under natural and controlled conditions that bursty waiting times are an intrinsic spontaneous behaviour well approximated by heavy-tailed (power-law) models over data ranges up to four orders of magnitude. Scaling exponents quantifying ratios of frequent short to rare very long waits are species-specific, being determined by traits such as foraging mode (active versus ambush predation), body size and prey preference. A stochastic–deterministic decision model reproduced the empirical waiting time scaling and species-specific exponents, indicating that apparently complex scaling can emerge from simple decisions. Results indicate temporal power-law scaling is a behavioural ‘rule of thumb’ that is tuned to species’ ecological traits, implying a common pattern may have naturally evolved that optimizes move–wait decisions in less predictable natural environments.

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Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.