Search results for "Smoothing"
showing 10 items of 135 documents
First‐Derivative Fourier‐Transform Infrared Determination of Oxadiazon in Commercial Herbicide Formulations
2008
Abstract A Fourier‐transform infrared (FTIR) method has been developed for the quantification of oxadiazon in herbicide formulations. The method involves the extraction of the active ingredient by sonication of the samples with CHCl3 and direct measurement of the peak area values in first‐order derivate spectra from 1770 cm−1 to 1774 cm−1 corrected with a baseline point located at 1950 cm−1 and after a 5‐point smoothing. A limit of detection (3 s) of 0.03 mg g−1 and a typical relative standard deviation (RSD) of 1.3% were found. Results obtained were comparable with those found by liquid chromatography with UV detection. The proposed method involves a 7‐times reduction in solvent consumptio…
An Enhanced Detector of Blurred and Noisy Edges
2007
Detecting edges in digital images is a tricky operation in image processing since images may contain areas with different degrees of noise, blurring and sharpness. Such operation represents an important step of the whole process of similarity shape analysis and retrieval.
Polynomial Smoothing Splines
2014
Interpolating splines is a perfect tool for approximation of a continuous-time signal \(f(t)\) in the case when samples \(x[k]=f(k),\;k\in \mathbb {Z}\) are available. However, frequently, the samples are corrupted by random noise. In such case, the so-called smoothing splines provide better approximation. In this chapter we describe periodic smoothing splines in one and two dimensions. The SHA technique provides explicit expression of such splines and enables us to derive optimal values of the regularization parameters.
Batch Methods for Resolution Enhancement of TIR Image Sequences
2015
Thermal infrared (TIR) time series are exploited by many methods based on Earth observation (EO), for such applications as agriculture, forest management, and meteorology. However, due to physical limitations, data acquired by a single sensor are often unsatisfactory in terms of spatial or temporal resolution. This issue can be tackled by using remotely sensed data acquired by multiple sensors with complementary features. When nonreal-time functioning or at least near real-time functioning is admitted, the measurements can be profitably fed to a sequential Bayesian algorithm, which allows to account for the correlation embedded in the successive acquisitions. In this work, we focus on appli…
Probabilistic Forecast for Northern New Zealand Seismic Process Based on a Forward Predictive Kernel Estimator
2011
In seismology predictive properties of the estimated intensity function are often pursued. For this purpose, we propose an estimation procedure in time, longitude, latitude and depth domains, based on the subsequent increments of likelihood obtained adding an observation one at a time. On the basis of this estimation approach a forecast of earthquakes of a given area of Northern New Zealand is provided, assuming that future earthquakes activity may be based on the smoothing of past earthquakes.
The Random-Time Binomial Model
1999
In this paper we study Binomial Models with random time steps. We explain, how calculating values for European and American Call and Put options is straightforward for the Random-Time Binomial Model. We present the conditions to ensure weak-convergence to the Black-Scholes setup and convergence of the values for European and American put options. Differently to the CRR-model the convergence behaviour is extremely smooth in our model. By using extrapolation we therefore achieve order of convergence two. This way it is an efficient tool for pricing purposes in the Black-Scholes setup, since the CRR model and its extrapolations typically achieve order one. Moreover our model allows in a straig…
Prudential supervisors' independence and income smoothing in European banks
2019
[EN] We investigate the role of prudential supervisors' independence in affecting income smoothing behavior in European banks. Powerful national supervisors are predicted to influence the accounting practices of their supervised entities, shaping the properties of the accounting numbers they prepare. In particular, we study whether greater independence of powerful supervisors from the government and from the industry is associated with lower income smoothing. We use the mandatory adoption of a single set of accounting standards in Europe as a shock to the influence of prudential supervisors over national banks' accounting practice. Our results confirm that political and industry independenc…
Hand Held 3D Scanning for Cultural Heritage: Experimenting Low Cost Structure Sensor Scan
2017
In the last years 3D scanning has become an important resource in many fields, in particular it has played a key role in study and preservation of Cultural Heritage. Moreover today, thanks to the miniaturization of electronic components, it has been possible produce a new category of 3D scanners, also known as handheld scanners. Handheld scanners combine a relatively low cost with the advantage of the portability. The aim of this chapter is two-fold: first, a survey about the most recent 3D handheld scanners is presented. As second, a study about the possibility to employ the handheld scanners in the field of Cultural Heritage is conducted. In this investigation, a doorway of the Benedictin…
Enhancing TIR Image Resolution via Bayesian Smoothing for IRRISAT Irrigation Management Project
2013
Accurate estimation of physical quantities depends on the availability of High Resolution (HR) observations of the Earth surface. However, due to the unavoidable tradeoff between spatial and time resolution, the acquisition instants of HR data hardly coincides with those required by the estimation algorithms. A possible solution consists in constructing a synthetic HR observation at a given time k by exploiting Low Resolution (LR) and HR data acquired at different instants. In this work we recast this issue as a smoothing problem, thus focusing on cases in which observations acquired both before and after time k are available. The proposed approach is validated on a region of interest for t…
Exponential smoothing with covariates applied to electricity demand forecast
2013
Exponential smoothing methods are widely used as forecasting techniques in industry and business. Their usual formulation, however, does not allow covariates to be used for introducing extra information into the forecasting process. In this paper, we analyse an extension of the exponential smoothing formulation that allows the use of covariates and the joint estimation of all the unknowns in the model, which improves the forecasting results. The whole procedure is detailed with a real example on forecasting the daily demand for electricity in Spain. The time series of daily electricity demand contains two seasonal patterns: here the within-week seasonal cycle is modelled as usual in exponen…