1,253 research outputs found
A plug-in approach to sparse and robust principal component analysis
We propose a method for sparse and robust principal component analysis.
The methodology is structured in two steps: first, a robust estimate of the covariance
matrix is obtained, then this estimate is plugged-in into an elastic-net regression which
enforces sparseness. Our approach provides an intuitive, general and flexible extension
of sparse principal component analysis to the robust setting. We also show how to
implement the algorithm when the dimensionality exceeds the number of observations
by adapting the approach to the use of robust loadings from ROBPCA. The proposed
technique is seen to compare well for simulated and real datasets
S-estimation of hidden Markov models
A method for robust estimation of dynamic mixtures of multivariate distributions is proposed. The EM algorithm is modified by replacing the classical M-step
with high breakdown S-estimation of location and scatter, performed by using the
bisquare multivariate S-estimator. Estimates are obtained by solving a system of estimating equations that are characterized by component specific sets of weights, based on
robust Mahalanobis-type distances. Convergence of the resulting algorithm is proved
and its finite sample behavior is investigated by means of a brief simulation study and
n application to a multivariate time series of daily returns for seven stock markets
Robust methods for data reduction
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant anal
Il 'donax' di Apuleio fra epigramma erotico e poesia bucolica: intertestualità e critica testuale in Apul. fr. 4 Courtney/Blänsdorf
Starting from the discussion of a textual problem in the final couplet of a pederastic epigram composed by Apuleius, and quoted by the author in the Apologia (Apul. fr. 4 Courtney/Blänsdorf), this article provides further exploration of the intertextual relationships in Apuleian poetry with the Greco-Roman literary tradition, focusing in particular on bucolic poetry (Virgil’s Eclogue 2; Calpurnius Siculus’ Eclogue 3) and erotic epigrams (Meleager, already a model for Verg. ecl. 2; [ps.-]Plato)
Shielding performances of ITO transparent windows: Theoretical and experimental characterization
The shielding performance of Indium-Titanium-Oxide (ITO) thin film depends on the characteristics of the impinging electromagnetic field, on the geometry of the shield, on the frequency range. In this paper, a complete experimental characterization of the shielding effectiveness of ITO transparent windows is performed by using three different approaches. The obtained results are compared in order to define the limit of applicability of each technique. In addition, numerical simulations are performed by applying the finite-difference time-domain method in order to assess the effects of the geometry of the test configuration on the obtained results
Development of a method for determining the charcoal calorific value variability as integration of the UNI EN ISO 18125:2018 standard
Geolocation of Internet hosts: Accuracy limits through Cramer-Rao lower bound
With active IP geolocation, the position of an Internet host is estimated by measuring the network delay from a number of other hosts with known position (usually called landmarks). In particular, after having converted delays into distances, geometrical techniques like trilateration are used to provide the estimated position on a global reference system. In this paper, we derive the Cramer-Rao lower bound (CRLB) of IP geolocation. The CRLB defines a bound on the minimum mean squared error that affects any unbiased estimator. From a practical point of view, the CRLB provides insights about the maximal theoretical accuracy that can be achieved by IP geolocalization methods. The CRLB also provides conceptual tools useful to understand how the position of landmarks and their distribution affect localization performance. Results show that to obtain accuracy levels in the order of a few tens of kilometers, the number of landmarks to be involved can be relevant and/or their distance from the target cannot be too large
Il progetto MEDITA. La documentazione non letteraria mediolatina e la lessicografia storico-etimologica italo-romanza
Questo articolo si concentra sul progetto PRIN 2022 MEDITA, frutto della collaborazione tra l'Università di Napoli Federico II, l'Università Ca’ Foscari di Venezia e l'Opera del Vocabolario Italiano (CNR, Firenze). Il progetto mira a costruire una base di conoscenza testuale di testi latini medievali non letterari di area italiana. Nel primo paragrafo descriviamo le caratteristiche fondamentali e gli obiettivi principali del progetto, per poi soffermarci sulla struttura della piattaforma digitale (§ 2) e sull'articolazione del progetto e delle sue unità (§ 3). La conclusione (§ 4) si concentra sul duplice scopo della base di conoscenza integrata nella piattaforma digitale MED.ITA, evidenziando sia la rilevanza dei testi pratici del latino medievale per la lessicografia romanza, sia il loro valore linguistico come oggetto di analisi in sé
Grilling and air pollution: how charcoal quality affects emissions
Cooking with charcoal is widely popular worldwide. Several types of lump charcoal and charcoal briquettes are available
on the market, presenting distinct characteristics based on raw materials and production methods. Charcoal quality can
significantly impact combustion properties and pollutant emissions. This study aims to: (1) assess the qualitative characteristics
of commercial lump charcoal and charcoal briquettes, (2) evaluate the emission factors (EFs) associated with
their combustion, and (3) investigate how different characteristics of charcoal affect air pollutant emissions. Significant
differences in quality were observed among the charcoal samples analyzed. Lump charcoal generally exhibited superior
characteristics, including a higher carbon content (> 75% d.b.), fixed carbon (> 75% d.b.), heating value (> 29 MJ/kg),
and fuel ratio (> 4.5). In contrast, charcoal briquettes showed higher levels of volatile matter (> 20% d.b.), ash (> 15%
d.b.), and moisture content (> 6% w.b.). Furthermore, charcoal briquettes exhibited higher EFs for carbon monoxide (CO)
(> 250 g/kg), volatile organic compounds (VOC) (> 1.5 g/kg), and total suspended particulates (TSP) (> 7.5 g/kg) than
lump charcoal. Principal component analysis (PCA) demonstrated a strong influence of qualitative characteristics on emission
factors. Volatile matter, ash yield, moisture, and nitrogen content were positively correlated with higher emissions,
while carbon content, fixed carbon, and fuel ratio were negatively correlated. As lump charcoal aligns more closely with
the latter parameters, it releases lower emissions than briquettes. Improving charcoal production techniques and reinforcing
international standards are crucial to ensure product quality, reduce emissions, and minimize environmental and health
risks
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