Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Application of Continuous Wavelet Transform to the Analysis of the Modulus of the Fractional Fourier Transform Bands for Resolving Two Component Mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Flow-injection potentiometric method for the routine determination of chloride: application to bread analysis

Bread is consumed worldwide by man, thus contributing to the regular ingestion of certain inorganic species such as chloride. It controls the blood pressure if associated to a sodium intake and may increase the incidence of stomach ulcer. Its routine control should thus be established by means of quick and low cost procedures. This work reports a double- channel flow injection analysis (FIA) system with a new chloride sensor for the analysis of bread. All solutions are prepared in water and necessary ionic strength adjustments are made on-line. The body of the indicating electrode is made from a silver needle of 0.8 mm i.d. with an external layer of silver chloride. These devices were constructed with different lengths. Electrodes of 1.0 to 3.0 cm presented better analytical performance. The calibration curves under optimum conditions displayed Nernstian behaviour, with average slopes of 56 mV decade-1, with sampling rates of 60 samples h-1. The method was applied to analyze several kinds of bread, namely pão de trigo, pão integral, pão de centeio, pão de mistura, broa de milho, pão sem sal, pão meio sal, pão-de-leite, and pão de água. The accuracy and precision of the potentiometric method were ascertained by comparison to a spectrophotometric method of continuous segmented flow. These methods were validated against ion-chromatography procedures.

On local fractional continuous wavelet transform

We introduce a new wavelet transform within the framework of the local fractional calculus. An illustrative example of local fractional wavelet transform is also presented.

Analysis of stock market indices with multidimensional scaling and wavelets

Stock market indices SMIs are important measures of financial and economical performance. Considerable research efforts during the last years demonstrated that these signals have a chaotic nature and require sophisticated mathematical tools for analyzing their characteristics. Classical methods, such as the Fourier transform, reveal considerable limitations in discriminating different periods of time. This paper studies the dynamics of SMI by combining the wavelet transform and the multidimensional scaling MDS . Six continuous wavelets are tested for analyzing the information content of the stock signals. In a first phase, the real Shannon wavelet is adopted for performing the evaluation of the SMI dynamics, while their comparison is visualized by means of the MDS. In a second phase, the other wavelets are also tested, and the corresponding MDS plots are analyzed.