Search results for "Data analysis."
showing 10 items of 377 documents
Renewable energy growth and the financial performance of electric utilities: A panel data study
2017
Electric utilities are under pressure to increase clean energy production. Although the adoption of renewable energy can improve the utilities' environmental performance, a fundamental question is if it also pays in economic terms. Building on the natural-resource-based view of the firm, we answer this question using two data analysis methods. First, we carry out a regression analysis of panel data from 66 large electric utilities covering the period 2005–2014, applying both a fixed and random effects estimator. Subsequently, we use the Granger causality test to explore possible causality links. Our results show a negative correlation at the firm level between renewable energy increase and …
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…
Design of a modular Autonomous Underwater Vehicle for archaeological investigations
2015
MARTA (MARine Tool for Archaeology) is a modular AUV (Autonomous Underwater Vehicle) designed and developed by the University of Florence in the framework of the ARROWS (ARchaeological RObot systems for the World's Seas) FP7 European project. The ARROWS project challenge is to provide the underwater archaeologists with technological tools for cost affordable campaigns: i.e. ARROWS adapts and develops low cost AUV technologies to significantly reduce the cost of archaeological operations, covering the full extent of an archaeological campaign (underwater mapping, diagnosis and cleaning tasks). The tools and methodologies developed within ARROWS comply with the "Annex" of the 2001 UNESCO Conv…
Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics
2016
To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This pape…
Principal components analysis: theory and application to gene expression data analysis
2018
Advances in computational power have enabled research to generate significant amounts of data related to complex biological problems. Consequently, applying appropriate data analysis techniques has become paramount to tackle this complexity. However, theoretical understanding of statistical methods is necessary to ensure that the correct method is used and that sound inferences are made based on the analysis. In this article, we elaborate on the theory behind principal components analysis (PCA), which has become a favoured multivariate statistical tool in the field of omics-data analysis. We discuss the necessary prerequisites and steps to produce statistically valid results and provide gui…
A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model.
2018
International audience; In this article, a new Python package for nucleotide sequences clustering is proposed. This package, freely available on-line, implements a Laplacian eigenmap embedding and a Gaussian Mixture Model for DNA clustering. It takes nucleotide sequences as input, and produces the optimal number of clusters along with a relevant visualization. Despite the fact that we did not optimise the computational speed, our method still performs reasonably well in practice. Our focus was mainly on data analytics and accuracy and as a result, our approach outperforms the state of the art, even in the case of divergent sequences. Furthermore, an a priori knowledge on the number of clust…
Sublimation of icy aggregates in the coma of comet 67P/Churyumov–Gerasimenko detected with the OSIRIS cameras on board Rosetta
2016
Beginning in 2014 March, the OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System) cameras began capturing images of the nucleus and coma (gas and dust) of comet 67P/Churyumov¿Gerasimenko using both the wide angle camera (WAC) and the narrow angle camera (NAC). The many observations taken since July of 2014 have been used to study the morphology, location, and temporal variation of the comet's dust jets. We analysed the dust monitoring observations shortly after the southern vernal equinox on 2015 May 30 and 31 with the WAC at the heliocentric distance Rh = 1.53 AU, where it is possible to observe that the jet rotates with the nucleus. We found that the decline of brightness a…
"Table 7" of "Measurement of the differential cross-section of highly boosted top quarks as a function of their transverse momentum in $\sqrt{s}$ = 8…
2016
Correlation matrix between the bins of the particle-level differential cross-section as a function of $p_{T,ptcl}$.
Particle identification in ALICE: a Bayesian approach
2016
We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss ($\mathrm{d}E/\mathrm{d}x$) and time-of-flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high-purity samples of identified particles in the decay channels ${\rm K}^0_S \righta…
Gaia -ESO Survey: Analysis of pre-main sequence stellar spectra
2015
This paper describes the analysis of UVES and GIRAFFE spectra acquired by the Gaia-ESO Public Spectroscopic Survey in the fields of young clusters whose population includes pre-main sequence (PMS) stars. Both methods that have been extensively used in the past and new ones developed in the contest of the Gaia-ESO survey enterprise are available and used. The internal precision of these quantities is estimated by inter-comparing the results obtained by such different methods, while the accuracy is estimated by comparison with independent external data, like effective temperature and surface gravity derived from angular diameter measurements, on a sample of benchmarks stars. Specific strategi…