1,721,186 research outputs found
Analog and digital worlds: Part 1. Signal sampling and Fourier Transform
No full textProper data sampling of a continuously varying quantity that describes the proceeding of a natural process leads to a simpler equivalent representation. This representation consists of a sequence of discrete data, which is more suitable to be mathematically handled and allows one not to lose essential information provided by the original signal. The discrete values of the sequence obtained by sampling differ from one another by finite quantities. In the ideal case, the original representation should be perfectly reconstructed by a backward procedure. The rules that should be respected in order to satisfy this basic condition are very simple, but require the decomposition of the signal into a suitable set of elementary components. This may be performed by applying to the sequence the algorithm called Discrete Fourier Transform (DFT). The direct result of the transformation consists of the spectrum of the signal, which can be analysed in many ways. The mathematics to make the FT algorithm work, eventually in an as fast as possible way (FFT – Fast Fourier Transform) is perhaps of less interest to the chemists and will not be treated here. Rather, the aim is to address the reader about what FT allows to obtain
Transform Methods in the Synthesis and Elaboration of Signals
No full textDifferent transform methods, from Fourier Transform to Wavelet Transform, are discussed and exemplifie
Colourgrams: an alternative, fast and inexpensive way for characterising inhomogeneous food matrices through multivariate image analysis
No full textColorigrammi: impiego di fotocamere digitali come sensori ottici per l’analisi del colore di matrici alimentari disomogenee
No full textData dimensionality reduction and data fusion for fast characterization of green coffee samples using hyperspectral sensors
Full text linkHyperspectral sensors represent a powerful tool for chemical mapping of solid-state samples, since they provide spectral information localized in the image domain in very short times and without the need of sample pretreatment. However, due to the large data size of each hyperspectral image, data dimensionality reduction (DR) is necessary in order to develop hyperspectral sensors for real-time monitoring of large sets of samples with different characteristics. In particular, in this work, we focused on DR methods to convert the three-dimensional data array corresponding to each hyperspectral image into a one-dimensional signal (1D-DR), which retains spectral and/or spatial information. In this way, large datasets of hyperspectral images can be converted into matrices of signals, which in turn can be easily processed using suitable multivariate statistical methods. Obviously, different 1D-DR methods highlight different aspects of the hyperspectral image dataset. Therefore, in order to investigate their advantages and disadvantages, in this work, we compared three different 1D-DR methods: average spectrum (AS), single space hyperspectrogram (SSH) and common space hyperspectrogram (CSH). In particular, we have considered 370 NIR-hyperspectral images of a set of green coffee samples, and the three 1D-DR methods were tested for their effectiveness in sensor fault detection, data structure exploration and sample classification according to coffee variety and to coffee processing method. Principal component analysis and partial least squares-discriminant analysis were used to compare the three separate DR methods. Furthermore, low-level and mid-level data fusion was also employed to test the advantages of using AS, SSH and CSH altogether. [Figure not available: see fulltext.
Density and volumetric behavior of 1,2-dimethoxyethane plus water binary mixtures from -10 to 80 degrees C
No full textThe densities (rho) and excess molar volumes (V-E) for 1,2-dimethoxyethane + water binary mixtures were determined, when possible, at 19 different temperatures ranging from -10 up to +80 degrees C. The experimental measurements were used to test some empirical relations giving the dependence of the density on the temperature and binary composition: rho = rho(t), rho = rho(X-1), and rho = rho(t,X-1). Furthermore, the results of V-E calculations are discussed in terms of the influence of interactions between the components, of the order and degree of packing in the mixtures, and of the free-volume differences
Elaboration and Application of Algorithms Performing Feature Selection in the Wavelet Domain
No full textAnalog and digital worlds: Part 2. Fourier analysis in signals and data treatment
Full text linkThe most direct scope of Fourier Transform (FT) is to give an alternative representation of a signal: from the original domain to the corresponding frequency domain. The original domain can be time, space or any other independent variable that can be used as the domain of the function. This subject has been treated in Part 1 [1]. In particular, the FT of a signal, also referred to as the frequency spectrum of a signal, has been used to calculate the lowest sampling frequency that provides a correct representation of the signal itself. At the beginning of this contribution, it is illustrated how to implement the so-called windowing process to periodic sequences. Then, the meaning of the operations denominated convolution and deconvolution is discussed. It is shown how FT provides a very effective path to the execution of these operations in the alternative domain by employing the convolution theorem. Finally, the application of convolution and deconvolution operations to experimental signals associated with the 'spontaneous' convolution of two concurrent events is analysed by different examples
Extraction and quantification of main pigments in pesto sauces
No full textPesto is a widely diffused Italian pasta sauce, whose main ingredient is basil. Since its appearance is a key factor for marketing, the determination of its pigment content is of fundamental interest. To this aim, a method for the determination of pesto pigments by C18-HPLC is proposed. Only b-carotene was determined directly by Vis-spectrophotometry, as a consequenceof sample purification over a silica cartridge.The proposed method is reliable allowing, for the first time, an easy determination of chlorophylls, pheophytins, lutein and b-carotene in a complex matrix such as pesto. The results show great differences in pigment composition among the samples, with pheophytins as the main components. Only non-thermally processed product show appreciable chlorophyll content as aconsequence of the different production technique.Principal Component Analysis performed on thepigment contents showed great variability among thedifferent samples
Determinazione di pigmenti e attributi sensoriali mediante analisi multivariata del colore di immagini digitali
No full textRecentemente è stato presentato un nuovo metodo automatizzato per la classificazione di matrici alimentari disomogenee sulla base delle comuni fotografie digitali RGB che, rappresentando il contenuto in colore di ogni immagine digitale sotto forma di un segnale (colorigramma) dato dalla sequenza di curve di distribuzione di vari descrittori del colore dei pixel, permette di selezionare le regioni più significative con opportuni algoritmi di feature selection/classificazione. I risultati ottenuti su una serie di campioni di pesto alla genovese, ci hanno spinto a valutare la possibilità di impiegare lo stesso approccio a scopi di calibrazione, utilizzando i colorigrammi ottenuti da fotografie di campioni di pesto per prevederne il contenuto in pigmenti (clorofille, feofitine, caroteni) ed alcune caratteristiche legate all’aspetto, valutate per mezzo di un panel test. Per molte delle proprietà studiate sono stati ottenuti modelli di calibrazione PLS con soddisfacente capacità predittiva, e risultati ancora migliori sono stati raggiunti impiegando un algoritmo di feature selection/calibrazione basato sulla Trasformata Wavelet
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