Search results for "Principal component"

Biological mineral content in Iberian skeletal cremains for control of diagenetic factors employing multivariate statistics

2013

Abstract The aim of this study was to define a strategy for a correct selection of bone samples by employing inductively coupled plasma optical emission spectroscopy (ICP-OES) for reconstructing the biological mineral content in bones through the determination of major elements, trace elements and Rare Earth Elements (REE, lanthanides) in skeletal cremains of ancient Iberians (III–II B.C), discovered in the Necropolis of Corral de Saus (Moixent, Valencia) between 1972 and 1979. The biological mineral content was determined taking into account diagenetic factors. A control method for a better reading of results was applied. To explore large geochemical datasets and to reduce the number of va…

Using machine learning to disentangle LHC signatures of Dark Matter candidates

2019

We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical WIMP Dark Matter candidate in the form of a SUSY neutralino, a pseudo-Goldstone impostor in the shape of an Axion-Like Particle, and a light Dark Matter impostor whose interactions are mediated by a heavy particle. All these benchmarks are tensioned against each other, and against the main SM background ($Z$+jets). Our analysis uses both the leading-order kinematic features as well as the information of an additional hard jet. We explore different representa…

DATE FRUIT SORTING USING APPEARANCE-BASED INFORMATION AND NEURAL NETWORK CLASSIFIER

2014

Retrieval of atmospheric CH4profiles from Fourier transform infrared data using dimension reduction and MCMC

2016

We introduce an inversion method that uses dimension reduction for the retrieval of atmospheric methane (CH4) profiles. Uncertainty analysis is performed using the Markov chain Monte Carlo (MCMC) statistical estimation. These techniques are used to retrieve CH4 profiles from the ground-based spectral measurements by the Fourier Transform Spectrometer (FTS) instrument at Sodankyla (67.4 degrees N, 26.6 degrees E), Northern Finland. The Sodankyla FTS is part of the Total Carbon Column Observing Network (TCCON), a global network that observes solar spectra in near-infrared wavelengths. The high spectral resolution of the data provides approximately 3 degrees of freedom about the vertical struc…

Landslide susceptibility mapping using precipitation data, Mazandaran Province, north of Iran

2017

Precipitation is a nonlinear and complex phenomenon and varies in time and space. It is also evident that there is a link between precipitation and shallow landslides, and precipitation is always considered as a landslide-triggering factor. This study aims to investigate the relationship between the characteristics of precipitation and the historical shallow landslides in Mazandaran Province, north of Iran. For this purpose, the spatial variability of rainfall was analyzed using monthly rainfall data collected at 15 synoptic stations distributed over the region between 1981 and 2014. Monthly precipitation and other derived parameters were used, and a hybrid model combining principal compone…

2016

Abstract. Scanning spectrometer networks using scattered solar radiation in the ultraviolet spectral region have become an increasingly important tool for monitoring volcanic sulfur dioxide (SO2) emissions. Often measured spectra are evaluated using the differential optical absorption spectroscopy (DOAS) technique. In order to obtain absolute column densities (CDs), the DOAS evaluation requires a Fraunhofer reference spectrum (FRS) that is free of absorption structures of the trace gas of interest. For measurements at volcanoes such a FRS can be readily obtained if the scan (i.e. series of measurements at different elevation angles) includes viewing directions where the plume is not seen. I…

Regional frequency analysis of extreme rainfall in Sicily (Italy)

2018

Heavy daily precipitation distribution in east-central Franceand west European meteorological patterns

2000

Principal Component Analysis is used to link the spatial distribution of Heavy Daily Precipitation (HDP) in East-Central France with meteorological patterns of the Meteo-France automatic classification, which takes into account 15 different meteorological parameters (e.g. geopotential heights at different levels, humidities, pseudo-adiabatic temperatures) over Western Europe. Every parameter is classified in 10 classes, or synoptic patterns. The annual PCA shows 3 dominant modes of HDP distribution, explaining more than 90% of the total variance. Associated atmospheric situations are obtained by using the scores of the 150 classes (10 per meteorological parameter). Other PCAs (i.e., half-an…

Detection of homogeneous precipitation regions at seasonal and annual time scales, northwest Iran

2017

Abstract Detection of homogeneous climate areas is a challenging issue, which can be affected by different criteria. One of the most prominent factors is choosing the time scale, which can lead to different spatial and temporal patterns. Total precipitation is a key factor in climatological studies, and studying its distribution is of utmost importance. The combination of principal components analysis and cluster analysis is used for homogeneous precipitation areas' detection. Hence, the spatial pattern of total precipitation was investigated in northwestern Iran during the past two decades (1991–2010) on seasonal and annual time scales. The results of clustering on each time scale were val…

Temporal variability of airborne bacterial community structure in an urban area

2006

International audience; Temporal airborne bacterial genetic community structure and meteorological factors were analysed above an urban area in the northwest of France from December 2003 to April 2004 with a sampling strategy considering different time intervals (from an hour to a month). Principal component analysis (PCA) of B-ARISA (Bacterial-Automated Ribosomal Intergenic Spacer Analysis) profiles revealed a hierarchy in the temporal variability of bacterial community: daily<weekly<seasonal. Co-inertia analysis between B-ARISA data and meteorological factors demonstrated the correlation between the seasonal variability in the bacterial community and climatic conditions such as temperatur…