Search results for "Component analysis"

Multivariate analysis of historical data (2004-2013) in assessing the possible environmental impact of the Bellolampo landfill (Palermo).

2017

Multivariate analysis was performed on a large data set of groundwater and leachate samples collected during 9 years of operation of the Bellolampo municipal solid waste landfill (located above Palermo, Italy). The aim was to obtain the most likely correlations among the data. The analysis results are presented. Groundwater samples were collected in the period 2004–2013, whereas the leachate analysis refers to the period 2006–2013. For groundwater, statistical data evaluation revealed notable differences among the samples taken from the numerous wells located around the landfill. Characteristic parameters revealed by principal component analysis (PCA) were more deeply investigated, and corr…

Distribution of Heavy Metals in Marine Sediments of Palermo Gulf (Sicily, Italy)

2008

Concentrations of Cr, Cu, Hg, Pb and Zn have been measured, by atomic absorption spectrophotometry, in the fine fraction (<63 μm) of surface sediments collected in 30 sites in the Palermo Gulf (Sicily, Italy) in order to assess the levels and the spatial distribution of these elements. Enrichment factors calculated with respect to clean areas have been considered to discriminate between levels due to background or to pollution contributions. The sampling stations, which form a grid inside these areas, are characterized by geographic proximity and by the presence of pollution sources. Ratio matching technique along with hierarchical clustering, minimum spanning tree and principal component a…

Principal polynomial analysis for remote sensing data processing

2011

Inspired by the concept of Principal Curves, in this paper, we define Principal Polynomials as a non-linear generalization of Principal Components to overcome the conditional mean independence restriction of PCA. Principal Polynomials deform the straight Principal Components by minimizing the regression error (or variance) in the corresponding orthogonal subspaces. We propose to use a projection on a series of these polynomials to set a new nonlinear data representation: the Principal Polynomial Analysis (PPA). We prove that the dimensionality reduction error in PPA is always lower than in PCA. Lower truncation error and increased independence suggest that unsupervised PPA features can be b…

Minimal learning machine in hyperspectral imaging classification

2020

A hyperspectral (HS) image is typically a stack of frames, where each frame represents the intensity of a different wavelength of light. Each spatial pixel has a spectrum. In the classification of the HS image, each spectrum is classified pixel-by-pixel. In some of the real-time applications, the amount of the HS image data causes performance challenges. Those issues relate to the platforms (e.g. drones) payload restrictions, the issues of the available energy and to the complexity of the machine learning models. In this study, we introduce the minimal learning machine (MLM) as a computationally cheap training and classification machine learning method for the hyperspectral imaging classificatio…

Multivariate denoising methods combining wavelets and principal component analysis for mass spectrometry data

2010

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years, there has been a growing interest in using mass spectrometry for the detection of such biomarkers. The MS signal resulting from MALDI-TOF measurements is contaminated by different sources of technical variations that can be removed by a prior pre-processing step. In particular, denoising makes it possible to remove the random noise contained in the signal. Wavelet methodology associated with thresholding is usually used for this purpose. In this study, we adapted two multivariate denoising methods that combine wavelets and PCA to MS data. The objective was to o…

Fruit physical, chemical and aromatic attributes of early, intermediate and late apricot cultivars.

2010

BACKGROUND: In order to reach good fruit quality, apricots require a balance of sugars and acids as well as a strong apricot aroma. In this study, fruit quality of early, intermediate and late apricot cultivars was evaluated by measuring physical, chemical and olfactory attributes. Multivariate analysis of quality and aroma attributes was used to identify groups of similar cultivars and association with ripening season. RESULTS: Physical, chemical and aromatic attributes showed great variation amongcultivars but no relation to ripening season. Aromatic profiles (34 volatiles) of fruit tissues indicated qualitative and quantitative differences among cultivars. Ninfa and Mandorlon were riches…

Metabolic flux understanding of Pichia pastoris grown on heterogenous culture media

2014

[EN] Within the emergent field of Systems Biology, mathematical models obtained from physical chemical laws (the so-called first principles-based models) of microbial systems are employed to discern the principles that govern cellular behaviour and achieve a predictive understanding of cellular functions. The reliance on this biochemical knowledge has the drawback that some of the assumptions (specific kinetics of the reaction system, unknown dynamics and values of the model parameters) may not be valid for all the metabolic possible states of the network. In this uncertainty context, the combined use of fundamental knowledge and data measured in the fermentation that describe the behaviour…

Eggshell types and their evolutionary correlation with life-history strategies in squamates

2015

The eggshell is an important physiological structure for the embryo. It enables gas exchange, physical protection and is a calcium reserve. Most squamates (lizards, snakes, worm lizards) lay parchment-shelled eggs, whereas only some gekkotan species, a subgroup of lizards, have strongly calcified eggshells. In viviparous (live-bearing) squamates the eggshell is reduced or completely missing (hereafter “shell-less”). Recent studies showed that life-history strategies of gekkotan species differ between species with parchment- and rigid-shelled eggshells. Here we test if the three different eggshell types found in the squamates are also associated with different life-history strategies. We fir…

Two-step principal component analysis (PCA) as a method for separating auditory N1 and N250 elicited from 9-year-old children using a dense electrode…

2008

Detection of damage in civil engineering structures by PCA on enviromental vibration data

2018

The dynamic behavior of civil engineering structures are usually studied by means of ambient vibration observations and their performance is analyzed by Peak Picking and/or Operational Modal Analysis methods. This paper reports the first results of a statistical multivariate approach, specifically Principal Component Analysis, to detect a suspected structural damage on a sicilian highway bridge. Furthermore, the damage simulated in a simple structural model made it possible to understand the characteristics of the method consisting in comparing the observed data on an undamaged structure with those coming from a damaged one.