142 resultados para Evaluation model


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THE OXIDATIVE STABILITY OF OIL-IN-WATER EMULSIONS, CONTAINING BOVINE SERUM ALBUMIN (BSA) AND VIRGIN OLIVE OIL PHENOLIC COMPOUNDS, WAS STUDIED BY THE DETERMINATION OF THE FORMATION OF VOLATILE OXIDATION PRODUCTS. FOUR OIL-IN-WATER EMULSIONS WITH AND WITHOUT PHENOLS ISOLATED FROM VIRGIN OLIVE OIL AND BSA WERE PREPARED. THESE MODEL SYSTEMS WERE STORED AT 60 degrees C TO ACCELERATE LIPID OXIDATION. VOLATILE OXIDATION PRODUCTS WERE MONITORED EVERY THREE DAYS BY HEADSPACE SOLID-PHASE MICROEXTRACTION COUPLED WITH GAS CHROMATOGRAPHY. ALTHOUGH INDIVIDUALLY OLIVE OIL PHENOLIC COMPOUNDS AND BSA SHOWED A SIGNIFICANT ANTIOXIDANT ACTIVITY, THE COMBINATION OF THESE COMPONENTS SHOWED A VERY GOOD SYNERGY, QUANTIFIED AS 127%. IN FACT, THE EMULSION CONTAINING BOTH PHENOLIC COMPOUNDS AND BSA SHOWED A VERY LOW LEVEL OF OXIDATIVE DETERIORATION AFTER 45 DAYS STORAGE.

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OBJECTIVES: To determine the cost-effectiveness of influenza vaccination in people aged 65-74 years in the absence of co-morbidity. DESIGN: Primary research: randomised controlled trial. SETTING: Primary care. PARTICIPANTS: People without risk factors for influenza or contraindications to vaccination were identified from 20 general practitioner (GP) practices in Liverpool in September 1999 and invited to participate in the study. There were 5875/9727 (60.4%) people aged 65-74 years identified as potentially eligible and, of these, 729 (12%) were randomised. INTERVENTION: Participants were randomised to receive either influenza vaccine or placebo (ratio 3:1), with all individuals receiving pneumococcal vaccine unless administered in the previous 10 years. Of the 729 people randomised, 552 received vaccine and 177 received placebo; 726 individuals were administered pneumococcal vaccine. MAIN OUTCOME MEASURES AND METHODOLOGY OF ECONOMIC EVALUATION: GP attendance with influenza-like illness (ILI) or pneumonia (primary outcome measure); or any respiratory symptoms; hospitalisation with a respiratory illness; death; participant self-reported ILI; quality of life (QoL) measures at 2, 4 and 6 months post-study vaccination; adverse reactions 3 days after vaccination. A cost-effectiveness analysis was undertaken to identify the incremental cost associated with the avoidance of episodes of influenza in the vaccination population and an impact model was used to extrapolate the cost-effectiveness results obtained from the trial to assess their generalisability throughout the NHS. RESULTS: In England and Wales, weekly consultations for influenza and ILI remained at baseline levels (less than 50 per 100,000 population) until week 50/1999 and then increased rapidly, peaking during week 2/2000 with a rate of 231/100,000. This rate fell within the range of 'higher than expected seasonal activity' of 200-400/100,000. Rates then quickly declined, returning to baseline levels by week 5/2000. The predominant circulating strain during this period was influenza A (H3N2). Five (0.9%) people in the vaccine group were diagnosed by their GP with an ILI compared to two (1.1%) in the placebo group [relative risk (RR), 0.8; 95% confidence interval (CI) = 0.16 to 4.1]. No participants were diagnosed with pneumonia by their GP and there were no hospitalisations for respiratory illness in either group. Significantly fewer vaccinated individuals self-reported a single ILI (4.6% vs 8.9%, RR, 0.51; 95% CI for RR, 0.28 to 0.96). There was no significant difference in any of the QoL measurements over time between the two groups. Reported systemic side-effects showed no significant differences between groups. Local side-effects occurred with a significantly increased incidence in the vaccine group (11.3% vs 5.1%, p = 0.02). Each GP consultation avoided by vaccination was estimated from trial data to generate a net NHS cost of 174 pounds. CONCLUSIONS: No difference was seen between groups for the primary outcome measure, although the trial was underpowered to demonstrate a true difference. Vaccination had no significant effect on any of the QoL measures used, although vaccinated individuals were less likely to self-report ILI. The analysis did not suggest that influenza vaccination in healthy people aged 65-74 years would lead to lower NHS costs. Future research should look at ways to maximise vaccine uptake in people at greatest risk from influenza and also the level of vaccine protection afforded to people from different age and socio-economic populations.

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This paper addresses the need for accurate predictions on the fault inflow, i.e. the number of faults found in the consecutive project weeks, in highly iterative processes. In such processes, in contrast to waterfall-like processes, fault repair and development of new features run almost in parallel. Given accurate predictions on fault inflow, managers could dynamically re-allocate resources between these different tasks in a more adequate way. Furthermore, managers could react with process improvements when the expected fault inflow is higher than desired. This study suggests software reliability growth models (SRGMs) for predicting fault inflow. Originally developed for traditional processes, the performance of these models in highly iterative processes is investigated. Additionally, a simple linear model is developed and compared to the SRGMs. The paper provides results from applying these models on fault data from three different industrial projects. One of the key findings of this study is that some SRGMs are applicable for predicting fault inflow in highly iterative processes. Moreover, the results show that the simple linear model represents a valid alternative to the SRGMs, as it provides reasonably accurate predictions and performs better in many cases.

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Several pixel-based people counting methods have been developed over the years. Among these the product of scale-weighted pixel sums and a linear correlation coefficient is a popular people counting approach. However most approaches have paid little attention to resolving the true background and instead take all foreground pixels into account. With large crowds moving at varying speeds and with the presence of other moving objects such as vehicles this approach is prone to problems. In this paper we present a method which concentrates on determining the true-foreground, i.e. human-image pixels only. To do this we have proposed, implemented and comparatively evaluated a human detection layer to make people counting more robust in the presence of noise and lack of empty background sequences. We show the effect of combining human detection with a pixel-map based algorithm to i) count only human-classified pixels and ii) prevent foreground pixels belonging to humans from being absorbed into the background model. We evaluate the performance of this approach on the PETS 2009 dataset using various configurations of the proposed methods. Our evaluation demonstrates that the basic benchmark method we implemented can achieve an accuracy of up to 87% on sequence ¿S1.L1 13-57 View 001¿ and our proposed approach can achieve up to 82% on sequence ¿S1.L3 14-33 View 001¿ where the crowd stops and the benchmark accuracy falls to 64%.

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In this paper, we evaluate the Probabilistic Occupancy Map (POM) pedestrian detection algorithm on the PETS 2009 benchmark dataset. POM is a multi-camera generative detection method, which estimates ground plane occupancy from multiple background subtraction views. Occupancy probabilities are iteratively estimated by fitting a synthetic model of the background subtraction to the binary foreground motion. Furthermore, we test the integration of this algorithm into a larger framework designed for understanding human activities in real environments. We demonstrate accurate detection and localization on the PETS dataset, despite suboptimal calibration and foreground motion segmentation input.

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An automatic nonlinear predictive model-construction algorithm is introduced based on forward regression and the predicted-residual-sums-of-squares (PRESS) statistic. The proposed algorithm is based on the fundamental concept of evaluating a model's generalisation capability through crossvalidation. This is achieved by using the PRESS statistic as a cost function to optimise model structure. In particular, the proposed algorithm is developed with the aim of achieving computational efficiency, such that the computational effort, which would usually be extensive in the computation of the PRESS statistic, is reduced or minimised. The computation of PRESS is simplified by avoiding a matrix inversion through the use of the orthogonalisation procedure inherent in forward regression, and is further reduced significantly by the introduction of a forward-recursive formula. Based on the properties of the PRESS statistic, the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation. Numerical examples are used to demonstrate the efficacy of the algorithm.

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Little attention has been focussed on a precise definition and evaluation mechanism for project management risk specifically related to contractors. When bidding, contractors traditionally price risks using unsystematic approaches. The high business failure rate our industry records may indicate that the current unsystematic mechanisms contractors use for building up contingencies may be inadequate. The reluctance of some contractors to include a price for risk in their tenders when bidding for work competitively may also not be a useful approach. Here, instead, we first define the meaning of contractor contingency, and then we develop a facile quantitative technique that contractors can use to estimate a price for project risk. This model will help contractors analyse their exposure to project risks; and help them express the risk in monetary terms for management action. When bidding for work, they can decide how to allocate contingencies strategically in a way that balances risk and reward.

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BACKGROUND: The absorption of cocoa flavanols in the small intestine is limited, and the majority of the flavanols reach the large intestine where they may be metabolized by resident microbiota. OBJECTIVE: We assessed the prebiotic potential of cocoa flavanols in a randomized, double-blind, crossover, controlled intervention study. DESIGN: Twenty-two healthy human volunteers were randomly assigned to either a high-cocoa flavanol (HCF) group (494 mg cocoa flavanols/d) or a low-cocoa flavanol (LCF) group (23 mg cocoa flavanols/d) for 4 wk. This was followed by a 4-wk washout period before volunteers crossed to the alternant arm. Fecal samples were recovered before and after each intervention, and bacterial numbers were measured by fluorescence in situ hybridization. A number of other biochemical and physiologic markers were measured. RESULTS: Compared with the consumption of the LCF drink, the daily consumption of the HCF drink for 4 wk significantly increased the bifidobacterial (P < 0.01) and lactobacilli (P < 0.001) populations but significantly decreased clostridia counts (P < 0.001). These microbial changes were paralleled by significant reductions in plasma triacylglycerol (P < 0.05) and C-reactive protein (P < 0.05) concentrations. Furthermore, changes in C-reactive protein concentrations were linked to changes in lactobacilli counts (P < 0.05, R(2) = -0.33 for the model). These in vivo changes were closely paralleled by cocoa flavanol-induced bacterial changes in mixed-batch culture experiments. CONCLUSION: This study shows, for the first time to our knowledge, that consumption of cocoa flavanols can significantly affect the growth of select gut microflora in humans, which suggests the potential prebiotic benefits associated with the dietary inclusion of flavanol-rich foods. This trial was registered at clinicaltrials.gov as NCT01091922.

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A series of model experiments with the coupled Max-Planck-Institute ECHAM5/OM climate model have been investigated and compared with microwave measurements from the Microwave Sounding Unit (MSU) and re-analysis data for the period 1979–2008. The evaluation is carried out by computing the Temperature in the Lower Troposphere (TLT) and Temperature in the Middle Troposphere (TMT) using the MSU weights from both University of Alabama (UAH) and Remote Sensing Systems (RSS) and restricting the study to primarily the tropical oceans. When forced by analysed sea surface temperature the model reproduces accurately the time-evolution of the mean outgoing tropospheric microwave radiation especially over tropical oceans but with a minor bias towards higher temperatures in the upper troposphere. The latest reanalyses data from the 25 year Japanese re-analysis (JRA25) and European Center for Medium Range Weather Forecasts Interim Reanalysis are in very close agreement with the time-evolution of the MSU data with a correlation of 0.98 and 0.96, respectively. The re-analysis trends are similar to the trends obtained from UAH but smaller than the trends from RSS. Comparison of TLT, computed from observations from UAH and RSS, with Sea Surface Temperature indicates that RSS has a warm bias after 1993. In order to identify the significance of the tropospheric linear temperature trends we determined the natural variability of 30-year trends from a 500 year control integration of the coupled ECHAM5 model. The model exhibits natural unforced variations of the 30 year tropospheric trend that vary within ±0.2 K/decade for the tropical oceans. This general result is supported by similar results from the Geophysical Fluid Dynamics Laboratory (GFDL) coupled climate model. Present MSU observations from UAH for the period 1979–2008 are well within this range but RSS is close to the upper positive limit of this variability. We have also compared the trend of the vertical lapse rate over the tropical oceans assuming that the difference between TLT and TMT is an approximate measure of the lapse rate. The TLT–TMT trend is larger in both the measurements and in the JRA25 than in the model runs by 0.04–0.06 K/decade. Furthermore, a calculation of all 30 year TLT–TMT trends of the unforced 500-year integration vary between ±0.03 K/decade suggesting that the models have a minor systematic warm bias in the upper troposphere.

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An in vitro study was conducted to investigate the effect of tannins on the extent and rate of gas and methane production, using an automated pressure evaluation system (APES). In this study three condensed tannins (CT; quebracho, grape seed and green tea tannins) and four hydrolysable tannins (HT; tara, valonea, myrabolan and chestnut tannins) were evaluated, with lucerne as a control substrate. CT and HT were characterised by matrix assisted laser desorption ionisation-time of flight mass spectrometry (MALDI-TOF-MS). Tannins were added to the substrate at an effective concentration of 100 g/kg either with or without polyethylene glycol (PEG6000), and incubated for 72 h in pooled, buffered rumen liquid from four lactating dairy cows. After inoculation, fermentation bottles were immediately connected to the APES to measure total cumulative gas production (GP). During the incubation, 11 gas samples were collected from each bottle at 0, 1, 4, 7, 11, 15, 23, 30, 46, 52 and 72 h of incubation and analysed for methane. A modified Michaelis-Menten model was fitted to the methane concentration patterns and model estimates were used to calculate the total cumulative methane production (GPCH4). GP and GPCH4 curves were fitted using a modified monophasic Michaelis-Menten model. Addition of quebracho reduced GP (P=0.002), whilst the other tannins did not affect GP. Addition of PEG increased GP for quebracho (P=0.003), valonea (P=0.058) and grape seed tannins (P=0.071), suggesting that these tannins either inhibited or tended to inhibit fermentation. Addition of quebracho and grape seed tannins also reduced (P≤0.012) the maximum rate of gas production, indicating that microbial activity was affected. Quebracho, valonea, myrabolan and grape seed decreased (P≤0.003) GPCH4 and the maximum rate (0.001≤ P≤ 0.102) of CH4 production. Addition of chestnut, green tea and tara tannins did not affect total gas nor methane production. Valonea and myrabolan tannins have most promise for reducing methane production as they had only a minor impact on gas production.

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Ice cloud representation in general circulation models remains a challenging task, due to the lack of accurate observations and the complexity of microphysical processes. In this article, we evaluate the ice water content (IWC) and ice cloud fraction statistical distributions from the numerical weather prediction models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office, exploiting the synergy between the CloudSat radar and CALIPSO lidar. Using the last three weeks of July 2006, we analyse the global ice cloud occurrence as a function of temperature and latitude and show that the models capture the main geographical and temperature-dependent distributions, but overestimate the ice cloud occurrence in the Tropics in the temperature range from −60 °C to −20 °C and in the Antarctic for temperatures higher than −20 °C, but underestimate ice cloud occurrence at very low temperatures. A global statistical comparison of the occurrence of grid-box mean IWC at different temperatures shows that both the mean and range of IWC increases with increasing temperature. Globally, the models capture most of the IWC variability in the temperature range between −60 °C and −5 °C, and also reproduce the observed latitudinal dependencies in the IWC distribution due to different meteorological regimes. Two versions of the ECMWF model are assessed. The recent operational version with a diagnostic representation of precipitating snow and mixed-phase ice cloud fails to represent the IWC distribution in the −20 °C to 0 °C range, but a new version with prognostic variables for liquid water, ice and snow is much closer to the observed distribution. The comparison of models and observations provides a much-needed analysis of the vertical distribution of IWC across the globe, highlighting the ability of the models to reproduce much of the observed variability as well as the deficiencies where further improvements are required.

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Purpose – The purpose of this paper is to investigate the effect of choices of model structure and scale in development viability appraisal. The paper addresses two questions concerning the application of development appraisal techniques to viability modelling within the UK planning system. The first relates to the extent to which, given intrinsic input uncertainty, the choice of model structure significantly affects model outputs. The second concerns the extent to which, given intrinsic input uncertainty, the level of model complexity significantly affects model outputs. Design/methodology/approach – Monte Carlo simulation procedures are applied to a hypothetical development scheme in order to measure the effects of model aggregation and structure on model output variance. Findings – It is concluded that, given the particular scheme modelled and unavoidably subjective assumptions of input variance, that simple and simplistic models may produce similar outputs to more robust and disaggregated models. Evidence is found of equifinality in the outputs of a simple, aggregated model of development viability relative to more complex, disaggregated models. Originality/value – Development viability appraisal has become increasingly important in the planning system. Consequently, the theory, application and outputs from development appraisal are under intense scrutiny from a wide range of users. However, there has been very little published evaluation of viability models. This paper contributes to the limited literature in this area.

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As in any technology systems, analysis and design issues are among the fundamental challenges in persuasive technology. Currently, the Persuasive Systems Development (PSD) framework is considered to be the most comprehensive framework for designing and evaluation of persuasive systems. However, the framework is limited in terms of providing detailed information which can lead to selection of appropriate techniques depending on the variable nature of users or use over time. In light of this, we propose a model which is intended for analysing and implementing behavioural change in persuasive technology called the 3D-RAB model. The 3D-RAB model represents the three dimensional relationships between attitude towards behaviour, attitude towards change or maintaining a change, and current behaviour, and distinguishes variable levels in a user’s cognitive state. As such it provides a framework which could be used to select appropriate techniques for persuasive technology.

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This paper investigates the effect of choices of model structure and scale in development viability appraisal. The paper addresses two questions concerning the application of development appraisal techniques to viability modelling within the UK planning system. The first relates to the extent to which, given intrinsic input uncertainty, the choice of model structure significantly affects model outputs. The second concerns the extent to which, given intrinsic input uncertainty, the level of model complexity significantly affects model outputs. Monte Carlo simulation procedures are applied to a hypothetical development scheme in order to measure the effects of model aggregation and structure on model output variance. It is concluded that, given the particular scheme modelled and unavoidably subjective assumptions of input variance, that simple and simplistic models may produce similar outputs to more robust and disaggregated models.

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This study investigates whether commercial offices designed by signature architects in the United States achieve rental premiums compared to commercial offices designed by nonsignature architects. Focusing on buildings designed by winners of the Prizker Prize and the Gold Medal awarded by the American Institute of Architects, we create a sample of commercial office buildings designed by signature architects drawing on CoStar's national database. We use a combination of hedonic regression model and a logit model to estimate the various rent determinants. While the first stage measures the typical rental price differential above the typical building in a particular sub-market over a specific timeframe, the second stage identifies a potential price differential over a set of buildings closely matched on important characteristics (such as age, size, location etc.). We find that in both stages offices design by signature architects exhibit a premium. However these results are preliminary. The premium could be indeed an effect of the name of the architect, but others factors such as micro-market conditions might be the cause. Further tests are needed to confirm the validity of our results.