1,721,073 research outputs found
Tests of correlation among wavelet based estimates for long memory processes
No full textLong memory models have received a significant amount of attention in the theoretical literature as they cover a wide range of applications, including economics and telecommunications. In recent years, a semiparametric estimator of the long memory parameter of stationary processes with long-range dependence, based on wavelet decomposition, has been proposed and studied by Veitch and Abry (1999) under the idealized assumption of decorrelation among wavelet coefficients. The asymptotic statistical analysis of the wavelet-based estimator has been recently complemented taking into account the correlations among wavelet coefficients, at fixed scales as well as among different scales (Bardet et al., 2000). The goal of the present article is to study the statistical properties of the wavelet-based estimator for a finite sample size and the correlation among the wavelet-based long memory estimates. The analysis is conducted by simulation, through the use of the circulant matrix method and shows that the correlation among wavelet coefficients has an impact on the moments of the wavelet-based estimator and on the correlation among the wavelet-based long memory estimates computed on non overlapping blocks of the original process
Identification of long range dependence in telecommunication networks
No full textIn this paper a statistical analysis of real ATM traffic is considered to validate the presence of long range dependence (LRD) in a set of telecommunication networks and protocols wider than those examined so far in the literature. The data come from a measurement campaign conducted in Italy by Telecom Italia in the framework of the European ATM Pilot Project. The notions of self similarity, LRD, second order self similarity are revised thoroughly, and the criteria for identifying the presence of LRD are presented. The available measurements (the applications considered are videoconference and transport of routing information between IP network routers) are processed through heuristic (R/S statistic, sampling variance plot, correlogram) as well as semiparametric (the Whittle estimator) techniques. The analysis shows that (i) evidence of LRD is statistically significant in the IP routing protocol application; (ii) the heuristic methods currently considered to detect LRD may not be able to capture the nature of the available data. These findings suggest to investigate further the impact of LRD in engineering and performance evaluation of ATM and IP networks, and to explore deeply the use of other semiparametric methods for the analysis of long memory sequences
Comparative evaluation of semiparametric long memory estimators
No full textMeasurements of data traffic in telecommunication networks show that the packet arrival process exhibits long-range dependence (LRD or long-memory) increments, whose parameters (namely the Hurst parameter) can be estimated and employed in statistical inference methods to evaluate the network performance (adversely affected by LRD). In the class of the semiparametric methods used for the estimation of the Hurst parameter, the more prominent ones, the local Whittle estimator and the linear wavelet estimator by Abry and Veitch, have been validated only through an asymptotic analysis, while in a more realistic setting just finite sample sizes are available. In this article, these two semiparametric estimators are evaluated for finite sample size, by employing the Cholesky decomposition method for the simulation of the long-memory process, and the related performances are analysed on a methodological basis. In both cases, a major impact on the performances is due to choices made for the parameters of the two methods, specifically the number of vanishing moments of the wavelet used in the wavelet-based estimator and the number of frequencies used in both the local Whittle and the wavelet-based estimator. Moreover, the performances of the wavelet-based estimator could be adversely affected by the failure of some assumptions that are at the basis of its statistical properties
Two dimensional electrical imaging for detection of hydrocarbon contaminants
No full textThe effects of a long-term diesel oil pollution due to leakage from buried tanks have been
investigated using electrical resistivity tomography. The reliability of 2D electrical resistivity
imaging of the subsoil was assessed using a numerical modelling approach that simulated the
different behaviour of the contaminated zone. The effects of inversion parameters, such as
the damping factor and smoothing matrix, have been studied in order to evaluate the optimal parameters to process real data.
The results of the field test indicated that highly conductive anomalies can be related to
the biological degradation of hydrocarbons: geochemical analysis performed on several
groundwater samples confirmed the presence of biodegradation activity. Chemical analysis
pointed out an anomalous concentration of iron and manganese cations dissolved in the
groundwater. Very low values of resistivity can be associated with a marked modification of
the cation exchange capacity of the soil mixture due to degradation of these hydrocarbons.
Chemical and physical interactions due to hydrocarbon pollution affect the electrical properties of soils and groundwater
Confronto delle diverse tecnologie geofisiche applicabili nella caratterizzazione di siti contaminati
No full text
STABILITY OF ASCORBIC ACID IN COSMETIC FORMULATION: PROTECTIVE ROLE OF RESVERATROL AND MELATONIN
No full textThe degradation of ascorbic acid (AA) has been considered one of the causes of quality and color changes during processing and storage of cosmetic products. The degradation process of AA is very complex and proceeds toward a number of oxidation/reduction and intermolecular rearrangement reactions [1]. In particular, AA is highly unstable in aqueous solution with the formation of degradation products such as dehydroascorbic acid, 2-furoic acid, 3-hydroxy-2-pyrone, furfural, etc. The nature of the degradation products depends on the reaction conditions. In the presence of oxygen (aerobic) the oxidation of ascorbic acid leads to the formation of several intermediates [2] and the final formation of various five carbons compounds such as 2-furoic acid and 3-hydroxy-2-pyrone. Under anaerobic conditions ascorbic acid was found to degrade via several steps to furfural [3].
The aims of our study was to investigate the AA stability in an aqueous cosmetic formulation, containing resveratrol (R), melatonin (M). The degradation kinetics of AA have been studied in single solutions, in the presence of resveratrol and melatonin, and in the commercial sample at different temperature (25, 40 and 60 °C). A reverse phase chromatographic method with gradient elution was developed by using both UV and mass spectrometric detection (HPLC-UV, LC-ESI-MS). The separation of the components of the cosmetic solution and the main degradation products (2-furoic acid, 3-hydroxy-2-pyrone, furfural, dehydroascorbic acid) was achieved on a Phenomenex LUNA C18 (4,6 x 150 mm ID; 5m) column.
It was found that the main degradation products were deriving from the degradation of AA, and that their relative abundance and formation rates were influenced by the presence of M and R. In particular, in the absence of melatonin and resveratrol the degradation led to the preferential formation of dehydroascorbic acid, 2-furoic acid and 3-hydroxy-2-pyrone, representative aerobic degradation products. On the other hand, M and R presence in solution caused a slower AA degradation rate and the preferential formation of furfural, typical anaerobic reaction product.
In aqueous solution at 40°C, the contemporary presence of R and M decreased AA degradation rate to t1/2 =267 days, instead of 66 days when AA was alone, demonstrating a protective role in AA degradation .
Since R and M are potent antioxidant and free radical scavenger [4,5], it can be hypothesized that they protect AA from oxidation process and promote AA anaerobic degradation to furfural
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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