902 resultados para Application method


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This paper deals with the key issues encountered in testing during the development of high-speed networking hardware systems by documenting a practical method for "real-life like" testing. The proposed method is empowered by modern and commonly available Field Programmable Gate Array (FPGA) technology. Innovative application of standard FPGA blocks in combination with reconfigurability are used as a back-bone of the method. A detailed elaboration of the method is given so as to serve as a general reference. The method is fully characterised and compared to alternatives through a case study proving it to be the most efficient and effective one at a reasonable cost.

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Boolean input systems are in common used in the electric industry. Power supplies include such systems and the power converter represents these. For instance, in power electronics, the control variable are the switching ON and OFF of components as thyristors or transistors. The purpose of this paper is to use neural network (NN) to control continuous systems with Boolean inputs. This method is based on classification of system variations associated with input configurations. The classical supervised backpropagation algorithm is used to train the networks. The training of the artificial neural network and the control of Boolean input systems are presented. The design procedure of control systems is implemented on a nonlinear system. We apply those results to control an electrical system composed of an induction machine and its power converter.

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The kinetics of the reactions of the atoms O(P-3), S(P-3), Se(P-3), and Te((3)p) with a series of alkenes are examined for correlations relating the logarithms of the rate coefficients to the energies of the highest occupied molecular orbitals (HOMOs) of the alkenes. These correlations may be employed to predict rate coefficients from the calculated HOMO energy of any other alkene of interest. The rate coefficients obtained from the correlations were used to formulate structure-activity relations (SARs) for reactions of O((3)p), S(P-3), Se (P-3), and Te((3)p) with alkenes. A comparison of the values predicted by both the correlations and the SARs with experimental data where they exist allowed us to assess the reliability of our method. We demonstrate the applicability of perturbation frontier molecular orbital theory to gas-phase reactions of these atoms with alkenes. The correlations are apparently not applicable to reactions of C(P-3), Si(P-3), N(S-4), and Al(P-2) atoms with alkenes, a conclusion that could be explained in terms of a different mechanism for reaction of these atoms.

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Many well-established statistical methods in genetics were developed in a climate of severe constraints on computational power. Recent advances in simulation methodology now bring modern, flexible statistical methods within the reach of scientists having access to a desktop workstation. We illustrate the potential advantages now available by considering the problem of assessing departures from Hardy-Weinberg (HW) equilibrium. Several hypothesis tests of HW have been established, as well as a variety of point estimation methods for the parameter which measures departures from HW under the inbreeding model. We propose a computational, Bayesian method for assessing departures from HW, which has a number of important advantages over existing approaches. The method incorporates the effects-of uncertainty about the nuisance parameters--the allele frequencies--as well as the boundary constraints on f (which are functions of the nuisance parameters). Results are naturally presented visually, exploiting the graphics capabilities of modern computer environments to allow straightforward interpretation. Perhaps most importantly, the method is founded on a flexible, likelihood-based modelling framework, which can incorporate the inbreeding model if appropriate, but also allows the assumptions of the model to he investigated and, if necessary, relaxed. Under appropriate conditions, information can be shared across loci and, possibly, across populations, leading to more precise estimation. The advantages of the method are illustrated by application both to simulated data and to data analysed by alternative methods in the recent literature.

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We present a novel algorithm for joint state-parameter estimation using sequential three dimensional variational data assimilation (3D Var) and demonstrate its application in the context of morphodynamic modelling using an idealised two parameter 1D sediment transport model. The new scheme combines a static representation of the state background error covariances with a flow dependent approximation of the state-parameter cross-covariances. For the case presented here, this involves calculating a local finite difference approximation of the gradient of the model with respect to the parameters. The new method is easy to implement and computationally inexpensive to run. Experimental results are positive with the scheme able to recover the model parameters to a high level of accuracy. We expect that there is potential for successful application of this new methodology to larger, more realistic models with more complex parameterisations.

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BACKGROUND AND AIM: The atherogenic potential of dietary derived lipids, chylomicrons (CM) and their remnants (CMr) is now becoming more widely recognised. To investigate factors effecting levels of CM and CMr and their importance in coronary heart disease risk it is essential to use a specific method of quantification. Two studies were carried out to investigate: (i) effects of increased daily intake of long chain n-3 polyunsaturated fatty acid (LC n-3 PUFA), and (ii) effects of increasing meal monounsaturated fatty acid (MUFA) content on the postprandial response of intestinally-derived lipoproteins. The contribution of the intestinally-derived lipoproteins to total lipaemia was assessed by triacylglycerol-rich lipoprotein (TRL) apolipoprotein B-48 (apo B-48) and retinyl ester (RE) concentrations. METHODS AND RESULTS: In a randomised controlled crossover trial (placebo vs LC n-3 PUFA) a mean daily intake of 1.4 g/day of LC n-3 PUFA failed to reduce fasting and postprandial triacylglycerol (TAG) response in 9 healthy male volunteers. Although the pattern and nature of the apo B-48 response was consistent with the TAG response following the two diets, the postprandial RE response differed on the LC n-3 PUFA diet with a lower early RE response and a delayed and more marked increase in RE in the late postprandial period compared with the control diet, but the differences did not reach levels of statistical significance. In the meal study there was no effect of MUFA/SFA content on the total lipaemic response to the meals nor on the contribution of intestinally derived lipoproteins evaluated as TAG, apo B-48 and RE responses in the TRL fraction. In both studies, the RE and apo B-48 measurements provided broadly similar information with respect to lack of effects of dietary or meal fatty acid composition and the presence of single or multiple peak responses. However the apo B-48 and RE measurements differed with respect to the timing of their peak response times, with a delayed RE peak, relalive to apo B-48, of approximately 2-3 hours for the LC n-3 PUFA diet (p = 0.002) study and 1-1.5 hours for the meal MUFA/SFA study. CONCLUSIONS: It was concluded that there are limitations of using RE as a specific CM marker, apo B-48 quantitation was found to be a more appropriate method for CM and CMr quantitation. However it was still considered of value to measure RE as it provided additional information regarding the incorporation of other constituents into the CM particle.

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A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimisation and Parameter Estimation (DISOPE) which has been designed to achieve the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A method based on Broyden's ideas is used for approximating some derivative trajectories required. Ways for handling con straints on both manipulated and state variables are described. Further, a method for coping with batch-to- batch dynamic variations in the process, which are common in practice, is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch processes. The algorithm is success fully applied to a benchmark problem consisting of the input profile optimisation of a fed-batch fermentation process.

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This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process.

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A statistical technique for fault analysis in industrial printing is reported. The method specifically deals with binary data, for which the results of the production process fall into two categories, rejected or accepted. The method is referred to as logistic regression, and is capable of predicting future fault occurrences by the analysis of current measurements from machine parts sensors. Individual analysis of each type of fault can determine which parts of the plant have a significant influence on the occurrence of such faults; it is also possible to infer which measurable process parameters have no significant influence on the generation of these faults. Information derived from the analysis can be helpful in the operator's interpretation of the current state of the plant. Appropriate actions may then be taken to prevent potential faults from occurring. The algorithm is being implemented as part of an applied self-learning expert system.

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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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Pollination is one of the most important ecosystem services in agroecosystems and supports food production. Pollinators are potentially at risk being exposed to pesticides and the main route of exposure is direct contact, in some cases ingestion, of contaminated materials such as pollen, nectar, flowers and foliage. To date there are no suitable methods for predicting pesticide exposure for pollinators, therefore official procedures to assess pesticide risk are based on a Hazard Quotient. Here we develop a procedure to assess exposure and risk for pollinators based on the foraging behaviour of honeybees (Apis mellifera) and using this species as indicator representative of pollinating insects. The method was applied in 13 European field sites with different climatic, landscape and land use characteristics. The level of risk during the crop growing season was evaluated as a function of the active ingredients used and application regime. Risk levels were primarily determined by the agronomic practices employed (i.e. crop type, pest control method, pesticide use), and there was a clear temporal partitioning of risks through time. Generally the risk was higher in sites cultivated with permanent crops, such as vineyard and olive, than in annual crops, such as cereals and oil seed rape. The greatest level of risk is generally found at the beginning of the growing season for annual crops and later in June–July for permanent crops.

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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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A new mild method has been devised for generating o-(naphtho)quinone methides via fluoride-induced desilylation of silyl derivatives of o-hydroxybenzyl(or 1-naphthylmethyl) nitrate. The reactive o-(naphtho)quinone methide intermediates were trapped by C, O, N and S nucleophiles and underwent “inverse electron-demand” hetero Diels- Alder reaction with dienophiles to give stable adducts. The method has useful potential application in natural product synthesis and drug research

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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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This paper describes an experimental application of constrained predictive control and feedback linearisation based on dynamic neural networks. It also verifies experimentally a method for handling input constraints, which are transformed by the feedback linearisation mappings. A performance comparison with a PID controller is also provided. The experimental system consists of a laboratory based single link manipulator arm, which is controlled in real time using MATLAB/SIMULINK together with data acquisition equipment.