60 resultados para Application methods


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A research has been conducted over methodological issues concerning the Theory of Planned Behaviour (TPB) by determining an appropriate measurement (direct and indirect) of constructs and selection of a plausible scaling techniques (unipolar and bipolar) of constructs: attitude, subjective norm, perceived behavioural control and intention that are important in explaining farm level tree planting in Pakistan. Unipolar scoring of beliefs showed higher correlation among the constructs of TPB than bipolar scaling technique. Both direct and indirect methods yielded significant results in explaining intention to perform farm forestry except the belief based measure of perceived behavioural control, which were analysed as statistically non-significant. A need to examine more carefully the scoring of perceived behavioural control (PBC) has been expressed

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Load forecasting is an important task in the management of a power utility. The most recent developments in forecasting involve the use of artificial intelligence techniques, which offer powerful modelling capabilities. This paper discusses these techniques and provides a review of their application to load forecasting.

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An algorithm for tracking multiple feature positions in a dynamic image sequence is presented. This is achieved using a combination of two trajectory-based methods, with the resulting hybrid algorithm exhibiting the advantages of both. An optimizing exchange algorithm is described which enables short feature paths to be tracked without prior knowledge of the motion being studied. The resulting partial trajectories are then used to initialize a fast predictor algorithm which is capable of rapidly tracking multiple feature paths. As this predictor algorithm becomes tuned to the feature positions being tracked, it is shown how the location of occluded or poorly detected features can be predicted. The results of applying this tracking algorithm to data obtained from real-world scenes are then presented.

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Addition of the dithioethers (−)-DIOSR2 (R=Me, iPr) (2,3-O-isopropylidene-1,4-dimethyl (and diisopropyl) thioether-L-threitol) to a dichloromethane solution of [Rh(COD)2]ClO4 (COD=1,5-cyclooctadiene) yielded the mononuclear complexes [Rh(COD)(DIOSR2)]ClO4. X-ray diffraction methods showed that the [Rh(COD)(DIOSiPr2)]ClO4 complex had an square-planar coordination geometry at the rhodium atom with the iPr groups in anti position. Cyclooctadiene complexes react with carbon monoxide to form dinuclear tetracarbonylated complexes [(CO)2Rh(μ-DIOSR2)2(CO)2](ClO4)2. [Rh(COD)(DIOSR2)]ClO4 are active catalyst precursors in styrene hydroformylation at 30 atm and 65°C which give conversions of up to 99% with a regioselectivity in 2-phenylpropanal as high as 74%. In all cases enantioselectivities are low.

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Addition of 1,4-dithiols to dichloromethane solutions of [PtCl2(P-P)] (P-P = (PPh3)2, Ph2P(CH2)3PPh2, Phd2P(CH2)4PPh2; 1,4-dithiols = HS(CH2)4SH, (−)DIOSH2 (2,3-O-isopropylidene-1,4-dithiol-l-threitol), BINASH2 (1,1′-dinaphthalene-2,2′-dithiol)) in the presence of NEt3 yielded the mononuclear complexes [Pt(1,4-dithiolato)(P-P)]. Related palladium(II) complexes [Pd(dithiolato)(P-P)] (P-P=Ph2P(CH2)3PPh2, Ph2P(CH2)4PPh2; dithiolato = −S(CH2)4S−, (−)-DIOS) were prepared by the same method. The structure of [Pt((−)DIOS)(PPh3)2] and [Pd(S(CH2)4S)(Ph2P(CH2)3PPh2)] complexes was determined by X-ray diffraction methods. Pt—dithiolato—SnC12 systems are active in the hydroformylation of styrene. At 100 atm and 125°C [Pt(dithiolate)(P-P)]/SnCl2 (Pt:Sn = 20) systems provided aldehyde conversion up to 80%.

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This paper reviews the current state of development of both near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for process monitoring, quality control, and authenticity determination in cheese processing. Infrared spectroscopy has been identified as an ideal process analytical technology tool, and recent publications have demonstrated the potential of both NIR and MIR spectroscopy, coupled with chemometric techniques, for monitoring coagulation, syneresis, and ripening as well as determination of authenticity, composition, sensory, and rheological parameters. Recent research is reviewed and compared on the basis of experimental design, spectroscopic and chemometric methods employed to assess the potential of infrared spectroscopy as a technology for improving process control and quality in cheese manufacture. Emerging research areas for these technologies, such as cheese authenticity and food chain traceability, are also discussed.

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This paper describes advances in ground-based thermodynamic profiling of the lower troposphere through sensor synergy. The well-documented integrated profiling technique (IPT), which uses a microwave profiler, a cloud radar, and a ceilometer to simultaneously retrieve vertical profiles of temperature, humidity, and liquid water content (LWC) of nonprecipitating clouds, is further developed toward an enhanced performance in the boundary layer and lower troposphere. For a more accurate temperature profile, this is accomplished by including an elevation scanning measurement modus of the microwave profiler. Height-dependent RMS accuracies of temperature (humidity) ranging from 0.3 to 0.9 K (0.5–0.8 g m−3) in the boundary layer are derived from retrieval simulations and confirmed experimentally with measurements at distinct heights taken during the 2005 International Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH) of the German Weather Service. Temperature inversions, especially of the lower boundary layer, are captured in a very satisfactory way by using the elevation scanning mode. To improve the quality of liquid water content measurements in clouds the authors incorporate a sophisticated target classification scheme developed within the European cloud observing network CloudNet. It allows the detailed discrimination between different types of backscatterers detected by cloud radar and ceilometer. Finally, to allow IPT application also to drizzling cases, an LWC profiling method is integrated. This technique classifies the detected hydrometeors into three different size classes using certain thresholds determined by radar reflectivity and/or ceilometer extinction profiles. By inclusion into IPT, the retrieved profiles are made consistent with the measurements of the microwave profiler and an LWC a priori profile. Results of IPT application to 13 days of the LAUNCH campaign are analyzed, and the importance of integrated profiling for model evaluation is underlined.

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Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation period. It is found that both methods yield merged fields of better quality than the original radar field or fields obtained by OK of gauge data. The newly suggested KED formulation is shown to be beneficial, in particular in mountainous regions where the quality of the Swiss radar composite is comparatively low. An analysis of the Kriging variances shows that none of the methods tested here provides a satisfactory uncertainty estimate. A suitable variable transformation is expected to improve this.

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Oligosaccharides are attracting increasing interest as prebiotic functional food ingredients. They can be extracted or obtained by enzymatic hydrolysis from a variety of biomass sources or synthesized from simple oligosaccharides by enzymatic transfer reactions. The major prebiotic oligosaccharides on the market are inulin, fructo-oligosaccharides, and galacto-oligosaccharides. They have been evaluated using a range of in vitro and in vivo methods, although there is a need for more large-scale human trials using modern microbiological methods. Prebiotics are being studied for their effects on gut health and well being and specific clinical conditions, including colon cancer, inflammatory bowel disease (IBD), acute infections, and mineral absorption. Developing understanding of the functional ecology of the human gut is influencing current thinking on what a prebiotic might achieve and is providing new targets for prebiotic intervention.

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A systematic approach is presented for obtaining cylindrical distribution functions (CDF's) of noncrystalline polymers which have been oriented by extension. The scattering patterns and CDF's are also sharpened by the method proposed by Deas and by Ruland. Data from atactic poly(methyl methacrylate) and polystyrene are analysed by these techniques. The methods could also be usefully applied to liquid crystals.

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The aim of this paper is to critically examine the application of development appraisal to viability assessment in the planning system. This evaluation is of development appraisal models in general and also their use in particular applications associated with estimating planning obligation capacity. The paper is organised into four themes: · The context and conceptual basis for development viability appraisal · A review of development viability appraisal methods · A discussion of selected key inputs into a development viability appraisal · A discussion of the applications of development viability appraisals in the planning system It is assumed that readers are familiar with the basic models and information needs of development viability appraisal rather than at the cutting edge of practice and/or academe

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A statistical methodology is proposed and tested for the analysis of extreme values of atmospheric wave activity at mid-latitudes. The adopted methods are the classical block-maximum and peak over threshold, respectively based on the generalized extreme value (GEV) distribution and the generalized Pareto distribution (GPD). Time-series of the ‘Wave Activity Index’ (WAI) and the ‘Baroclinic Activity Index’ (BAI) are computed from simulations of the General Circulation Model ECHAM4.6, which is run under perpetual January conditions. Both the GEV and the GPD analyses indicate that the extremes ofWAI and BAI areWeibull distributed, this corresponds to distributions with an upper bound. However, a remarkably large variability is found in the tails of such distributions; distinct simulations carried out under the same experimental setup provide sensibly different estimates of the 200-yr WAI return level. The consequences of this phenomenon in applications of the methodology to climate change studies are discussed. The atmospheric configurations characteristic of the maxima and minima of WAI and BAI are also examined.

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Data assimilation is predominantly used for state estimation; combining observational data with model predictions to produce an updated model state that most accurately approximates the true system state whilst keeping the model parameters fixed. This updated model state is then used to initiate the next model forecast. Even with perfect initial data, inaccurate model parameters will lead to the growth of prediction errors. To generate reliable forecasts we need good estimates of both the current system state and the model parameters. This paper presents research into data assimilation methods for morphodynamic model state and parameter estimation. First, we focus on state estimation and describe implementation of a three dimensional variational(3D-Var) data assimilation scheme in a simple 2D morphodynamic model of Morecambe Bay, UK. The assimilation of observations of bathymetry derived from SAR satellite imagery and a ship-borne survey is shown to significantly improve the predictive capability of the model over a 2 year run. Here, the model parameters are set by manual calibration; this is laborious and is found to produce different parameter values depending on the type and coverage of the validation dataset. The second part of this paper considers the problem of model parameter estimation in more detail. We explain how, by employing the technique of state augmentation, it is possible to use data assimilation to estimate uncertain model parameters concurrently with the model state. This approach removes inefficiencies associated with manual calibration and enables more effective use of observational data. We outline the development of a novel hybrid sequential 3D-Var data assimilation algorithm for joint state-parameter estimation and demonstrate its efficacy using an idealised 1D sediment transport model. The results of this study are extremely positive and suggest that there is great potential for the use of data assimilation-based state-parameter estimation in coastal morphodynamic modelling.

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Shiga toxin producing Escherichia coli (STEC) strains are foodborne pathogens whose ability to produce Shiga toxin (Stx) is due to the integration of Stx-encoding lambdoid bacteriophage (Stx phage). Circulating, infective Stx phages are very difficult to isolate, purify and propagate such that there is no information on their genetic composition and properties. Here we describe a novel approach that exploits the phage's ability to infect their host and form a lysogen, thus enabling purification of Stx phages by a series of sequential lysogen isolation and induction steps. A total of 15 Stx phages were rigorously purified from water samples in this way, classified by TEM and genotyped using a PCR-based multi-loci characterisation system. Each phage possessed only one variant of each target gene type, thus confirming its purity, with 9 of the 15 phages possessing a short tail-spike gene and identified by TEM as Podoviridae. The remaining 6 phages possessed long tails, four of which appeared to be contractile in nature (Myoviridae) and two of which were morphologically very similar to bacteriophage lambda (Siphoviridae).