980 resultados para ecliptic curve based chameleon hashing


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Due to the high dependence of photovoltaic energy efficiency on environmental conditions (temperature, irradiation...), it is quite important to perform some analysis focusing on the characteristics of photovoltaic devices in order to optimize energy production, even for small-scale users. The use of equivalent circuits is the preferred option to analyze solar cells/panels performance. However, the aforementioned small-scale users rarely have the equipment or expertise to perform large testing/calculation campaigns, the only information available for them being the manufacturer datasheet. The solution to this problem is the development of new and simple methods to define equivalent circuits able to reproduce the behavior of the panel for any working condition, from a very small amount of information. In the present work a direct and completely explicit method to extract solar cell parameters from the manufacturer datasheet is presented and tested. This method is based on analytical formulation which includes the use of the Lambert W-function to turn the series resistor equation explicit. The presented method is used to analyze the performance (i.e., the I - V curve) of a commercial solar panel at different levels of irradiation and temperature. The analysis performed is based only on the information included in the manufacturer's datasheet.

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The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

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Mercury intrusion porosimetry (MIP) has been widely used to evaluate the quality of concrete through the pore size distribution parameters. Two of these parameters are the critical pore diameter (Dcrit) and the percentage of the most interconnected net of pores compared to the total volume of pores. Some researchers consider Dcrit as the diameter obtained from the inflexion point of the cumulative mercury intrusion curve while others consider Dcrit as the diameter obtained from the point of abrupt variation in the same curve. This study aims to analyze two groups of concretes of varying w/c ratios, one cast with pozzolanic cement and another with high initial strength cement, in order to determine which of these diameters feature a better correlation with the quality parameters of the concretes. The concrete quality parameters used for the evaluations were (1) the w/c ratios and (2) chloride diffusion coefficients measured at approximately 90 days. MIP cumulative distributions of the same concretes were also measured at about 90 days, and Dcrit values were determined (1) from the point of abrupt variation and alternatively, (2) from the inflexion point of each of these plots. It was found that Dcrit values measured from the point of abrupt variation were useful indicators of the quality of the concrete, but the Dcrit values based on the inflexion points were not. Hence, it is recommended that Dcrit and the percentage of the most interconnected volume of pores should be obtained considering the point of abrupt variation of the cumulative curve of pore size distribution.

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For non-negative random variables with finite means we introduce an analogous of the equilibrium residual-lifetime distribution based on the quantile function. This allows us to construct new distributions with support (0, 1), and to obtain a new quantile-based version of the probabilistic generalization of Taylor's theorem. Similarly, for pairs of stochastically ordered random variables we come to a new quantile-based form of the probabilistic mean value theorem. The latter involves a distribution that generalizes the Lorenz curve. We investigate the special case of proportional quantile functions and apply the given results to various models based on classes of distributions and measures of risk theory. Motivated by some stochastic comparisons, we also introduce the “expected reversed proportional shortfall order”, and a new characterization of random lifetimes involving the reversed hazard rate function.

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The water retention curve (WRC) is a hydraulic characteristic of concrete required for advanced modeling of water (and thus solute) transport in variably saturated, heterogeneous concrete. Unfortunately, determination by a direct experimental method (for example, measuring equilibrium moisture levels of large samples stored in constant humidity cells) is a lengthy process, taking over 2 years for large samples. A surrogate approach is presented in which the WRC is conveniently estimated from mercury intrusion porosimetry (MIP) and validated by water sorption isotherms: The well-known Barrett, Joyner and Halenda (BJH) method of estimating the pore size distribution (PSD) from the water sorption isotherm is shown to complement the PSD derived from conventional MIP. This provides a basis for predicting the complete WRC from MIP data alone. The van Genuchten equation is used to model the combined water sorption and MIP results. It is a convenient tool for describing water retention characteristics over the full moisture content range. The van Genuchten parameter estimation based solely on MIP is shown to give a satisfactory approximation to the WRC, with a simple restriction on one. of the parameters.

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Background There is limited information regarding the clinical utility of amino-terminal pro-B-type natriuretic pepticle (NT-proBNP) for the detection of left ventricular (LV) dysfunction in the community. We evaluated predictors of circulating NT-proBNP levels and determined the utility of NT-proBNP to detect systolic and diastolic LV dysfunction in older adults. Methods. A population-based sample of 1229 older adults (mean age 69.4 years, 50.1% women) underwent echocardiographic assessment of cardiac structure and function and measurement of circulating NT-proBNP levels. Results Predictors of NT-proBNP included age, female sex, body mass index, and cardiorenal parameters (diastolic dysfunction [DID] severity; LV mass and left atrial volume; right ventricular overload; decreasing ejection fraction [EF] and creatinine clearance). The performance of NT-proBNP to detect any degree of LV dysfunction, including mild DID, was poor (area under the curve 0.56-0.66). In contrast, the performance of NT-proBNP for the detection of EF 0.90 regardless of age and sex; history of hypertension, diabetes, coronary artery disease; or body mass category. The ability of NT-proBNP to detect EF

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A novel algorithm for performing registration of dynamic contrast-enhanced (DCE) MRI data of the breast is presented. It is based on an algorithm known as iterated dynamic programming originally devised to solve the stereo matching problem. Using artificially distorted DCE-MRI breast images it is shown that the proposed algorithm is able to correct for movement and distortions over a larger range than is likely to occur during routine clinical examination. In addition, using a clinical DCE-MRI data set with an expertly labeled suspicious region, it is shown that the proposed algorithm significantly reduces the variability of the enhancement curves at the pixel level yielding more pronounced uptake and washout phases.

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Keyword identification in one of two simultaneous sentences is improved when the sentences differ in F0, particularly when they are almost continuously voiced. Sentences of this kind were recorded, monotonised using PSOLA, and re-synthesised to give a range of harmonic ?F0s (0, 1, 3, and 10 semitones). They were additionally re-synthesised by LPC with the LPC residual frequency shifted by 25% of F0, to give excitation with inharmonic but regularly spaced components. Perceptual identification of frequency-shifted sentences showed a similar large improvement with nominal ?F0 as seen for harmonic sentences, although overall performance was about 10% poorer. We compared performance with that of two autocorrelation-based computational models comprising four stages: (i) peripheral frequency selectivity and half-wave rectification; (ii) within-channel periodicity extraction; (iii) identification of the two major peaks in the summary autocorrelation function (SACF); (iv) a template-based approach to speech recognition using dynamic time warping. One model sampled the correlogram at the target-F0 period and performed spectral matching; the other deselected channels dominated by the interferer and performed matching on the short-lag portion of the residual SACF. Both models reproduced the monotonic increase observed in human performance with increasing ?F0 for the harmonic stimuli, but not for the frequency-shifted stimuli. A revised version of the spectral-matching model, which groups patterns of periodicity that lie on a curve in the frequency-delay plane, showed a closer match to the perceptual data for frequency-shifted sentences. The results extend the range of phenomena originally attributed to harmonic processing to grouping by common spectral pattern.

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We perform numerical simulations on a model describing a Brillouin-based temperature and strain sensor, testing its response when it is probed with relatively short pulses. Experimental results were recently published [e.g., Opt. Lett. 24, 510 (1999)] that showed a broadening of the Brillouin loss curve when the probe pulse duration is reduced, followed by a sudden and rather surprising reduction of the linewidth when the pulse duration gets shorter than the acoustic relaxation time. Our study reveals the processes responsible for this behavior. We give a clear physical insight into the problem, allowing us to define the best experimental conditions required for one to take the advantage of this effect.

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A new family of commercial zinc alloys designated as ZA8, ZA12, and ZA27 and high damping capacity alloys including Cosmal and Supercosmal and aluminium alloy LM25 were investigated for compressive creep and load relaxation behaviour under a series of temperatures and stresses. A compressive creep machine was designed to test the sand cast hollow cylindrical test specimens of these alloys. For each compressive creep experiment the variation of creep strain was presented in the form of graphs plotted as percentage of creep strain () versus time in seconds (s). In all cases, the curves showed the same general form of the creep curve, i.e. a primary creep stage, followed by a linear steady-state region (secondary creep). In general, it was observed that alloy ZA8 had the least primary creep among the commercial zinc-based alloys and ZA27 the greatest. The extent of primary creep increased with aluminium content to that of ZA27 then declined to Supercosmal. The overall creep strength of ZA27 was generally less than ZA8 and ZA12 but it showed better creep strength than ZA8 and ZA12 at high temperature and high stress. In high damping capacity alloys, Supercosmal had less primary creep and longer secondary creep regions and also had the lowest minimum creep rate among all the tested alloys. LM25 exhibited almost no creep at maximum temperature and stress used in this research work. Total creep elongation was shown to be well correlated using an empirical equation. Stress exponent and activation energies were calculated and found to be consistent with the creep mechanism of dislocation climb. The primary α and β phases in the as-cast structures decomposed to lamellar phases on cooling, with some particulates at dendrite edges and grain boundaries. Further breakdown into particulate bodies occurred during creep testing, and zinc bands developed at the highest test temperature of 160°C. The results of load relaxation testing showed that initially load loss proceeded rapidly and then deminished gradually with time. Load loss increased with temperature and almost all the curves approximated to a logarithmic decay of preload with time. ZA alloys exhibited almost the same load loss at lower temperature, but at 120°C ZA27 improved its relative performance with the passage of time. High damping capacity alloys and LM25 had much better resistance to load loss than ZA alloys and LM25 was found to be the best against load loss among these alloys. A preliminary equation was derived to correlate the retained load with time and temperature.

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This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at 2 h following triage. The model was constructed from retrospective patient data abstracted from the ED charts. The original data was preprocessed to eliminate questionable patient records and to normalize values of age-dependent clinical attributes. The model uses attributes routinely collected in the ED and provides predictions even for incomplete observations. Its performance was verified on independent validating data (split-sample validation) where it demonstrated AUC (area under ROC curve) of 0.83, sensitivity of 84%, specificity of 71% and the Brier score of 0.18. The model is intended to supplement an asthma clinical practice guideline, however, it can be also used as a stand-alone decision tool.

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We consider a Cauchy problem for the Laplace equation in a two-dimensional semi-infinite region with a bounded inclusion, i.e. the region is the intersection between a half-plane and the exterior of a bounded closed curve contained in the half-plane. The Cauchy data are given on the unbounded part of the boundary of the region and the aim is to construct the solution on the boundary of the inclusion. In 1989, Kozlov and Maz'ya [10] proposed an alternating iterative method for solving Cauchy problems for general strongly elliptic and formally self-adjoint systems in bounded domains. We extend their approach to our setting and in each iteration step mixed boundary value problems for the Laplace equation in the semi-infinite region are solved. Well-posedness of these mixed problems are investigated and convergence of the alternating procedure is examined. For the numerical implementation an efficient boundary integral equation method is proposed, based on the indirect variant of the boundary integral equation approach. The mixed problems are reduced to integral equations over the (bounded) boundary of the inclusion. Numerical examples are included showing the feasibility of the proposed method.

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We perform numerical simulations on a model describing a Brillouin-based temperature and strain sensor, testing its response when it is probed with relatively short pulses. Experimental results were recently published [e.g., Opt. Lett. 24, 510 (1999)] that showed a broadening of the Brillouin loss curve when the probe pulse duration is reduced, followed by a sudden and rather surprising reduction of the linewidth when the pulse duration gets shorter than the acoustic relaxation time. Our study reveals the processes responsible for this behavior. We give a clear physical insight into the problem, allowing us to define the best experimental conditions required for one to take the advantage of this effect.

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Motivation: In any macromolecular polyprotic system - for example protein, DNA or RNA - the isoelectric point - commonly referred to as the pI - can be defined as the point of singularity in a titration curve, corresponding to the solution pH value at which the net overall surface charge - and thus the electrophoretic mobility - of the ampholyte sums to zero. Different modern analytical biochemistry and proteomics methods depend on the isoelectric point as a principal feature for protein and peptide characterization. Protein separation by isoelectric point is a critical part of 2-D gel electrophoresis, a key precursor of proteomics, where discrete spots can be digested in-gel, and proteins subsequently identified by analytical mass spectrometry. Peptide fractionation according to their pI is also widely used in current proteomics sample preparation procedures previous to the LC-MS/MS analysis. Therefore accurate theoretical prediction of pI would expedite such analysis. While such pI calculation is widely used, it remains largely untested, motivating our efforts to benchmark pI prediction methods. Results: Using data from the database PIP-DB and one publically available dataset as our reference gold standard, we have undertaken the benchmarking of pI calculation methods. We find that methods vary in their accuracy and are highly sensitive to the choice of basis set. The machine-learning algorithms, especially the SVM-based algorithm, showed a superior performance when studying peptide mixtures. In general, learning-based pI prediction methods (such as Cofactor, SVM and Branca) require a large training dataset and their resulting performance will strongly depend of the quality of that data. In contrast with Iterative methods, machine-learning algorithms have the advantage of being able to add new features to improve the accuracy of prediction. Contact: yperez@ebi.ac.uk Availability and Implementation: The software and data are freely available at https://github.com/ypriverol/pIR. Supplementary information: Supplementary data are available at Bioinformatics online.

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The objective of this study was to develop a GIS-based multi-class index overlay model to determine areas susceptible to inland flooding during extreme precipitation events in Broward County, Florida. Data layers used in the method include Airborne Laser Terrain Mapper (ALTM) elevation data, excess precipitation depth determined through performing a Soil Conservation Service (SCS) Curve Number (CN) analysis, and the slope of the terrain. The method includes a calibration procedure that uses "weights and scores" criteria obtained from Hurricane Irene (1999) records, a reported 100-year precipitation event, Doppler radar data and documented flooding locations. Results are displayed in maps of Eastern Broward County depicting types of flooding scenarios for a 100-year, 24-hour storm based on the soil saturation conditions. As expected the results of the multi-class index overlay analysis showed that an increase for the potential of inland flooding could be expected when a higher antecedent moisture condition is experienced. The proposed method proves to have some potential as a predictive tool for flooding susceptibility based on a relatively simple approach.