Search results for "Data analysi"
showing 10 items of 391 documents
The Role of Big Data in Addressing Societal Challenges: A Systematic Mapping Study
2019
Part 2: Big Data Analytics; International audience; Big data has recently become the focus of academic and corporate investigation due to its high potential in generating business and social value. We have done a systematic mapping of the literature related to big data and its applications leading to social change through the lens of social innovation. The search strategy initially resulted in 593 papers, and after applying inclusion exclusion criteria a total of 156 papers were mapped; 59% of which were identified as empirical studies. This mapping investigated the publication frequency of the studies, research approach and contributions, research areas and article distribution per journal…
The Potsdam Open Source Radio Interferometry Tool (PORT)
2021
The Potsdam Open Source Radio Interferometry Tool (PORT) is the very long baseline interferometry (VLBI) analysis software developed and maintained at the GFZ German Research Centre for Geosciences. Chiefly, PORT is tasked with the timely processing of VLBI sessions and post-processing activities supporting the generation of celestial and terrestrial reference frames. In addition, it serves as a framework for research and development within the GFZ's VLBI working group and is part of the tool set employed in educating young researchers. Starting out from VLBI group delays, PORT estimates station and radio sources positions, as well as Earth orientation parameters, tropospheric parameters, a…
Effective field theory search for high-energy nuclear recoils using the XENON100 dark matter detector
2017
International audience; We report on weakly interacting massive particles (WIMPs) search results in the XENON100 detector using a nonrelativistic effective field theory approach. The data from science run II (34 kg×224.6 live days) were reanalyzed, with an increased recoil energy interval compared to previous analyses, ranging from (6.6–240) keVnr. The data are found to be compatible with the background-only hypothesis. We present 90% confidence level exclusion limits on the coupling constants of WIMP-nucleon effective operators using a binned profile likelihood method. We also consider the case of inelastic WIMP scattering, where incident WIMPs may up-scatter to a higher mass state, and …
Projected WIMP sensitivity of the XENONnT dark matter experiment
2020
XENONnT is a dark matter direct detection experiment, utilizing 5.9 t of instrumented liquid xenon, located at the INFN Laboratori Nazionali del Gran Sasso. In this work, we predict the experimental background and project the sensitivity of XENONnT to the detection of weakly interacting massive particles (WIMPs). The expected average differential background rate in the energy region of interest, corresponding to (1, 13) keV and (4, 50) keV for electronic and nuclear recoils, amounts to 12.3 ± 0.6 (keV t y)-1 and (2.2± 0.5)× 10−3 (keV t y)-1, respectively, in a 4 t fiducial mass. We compute unified confidence intervals using the profile construction method, in order to ensure proper coverage…
High precision mass measurements for wine metabolomics
2014
An overview of the critical steps for the non-targeted Ultra-High Performance Liquid Chromatography coupled with Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-ToF-MS) analysis of wine chemistry is given, ranging from the study design, data preprocessing and statistical analyses, to markers identification. UPLC-Q-ToF-MS data was enhanced by the alignment of exact mass data from FTICR-MS, and marker peaks were identified using UPLC-Q-ToF-MS(2). In combination with multivariate statistical tools and the annotation of peaks with metabolites from relevant databases, this analytical process provides a fine description of the chemical complexity of wines, as exemplified in the case of red (P…
Resolution of the ATLAS muon spectrometer monitored drift tubes in LHC Run 2
2019
The momentum measurement capability of the ATLAS muon spectrometer relies fundamentally on the intrinsic single-hit spatial resolution of the monitored drift tube precision tracking chambers. Optimal resolution is achieved with a dedicated calibration program that addresses the specific operating conditions of the 354 000 high-pressure drift tubes in the spectrometer. The calibrations consist of a set of timing offsets and drift time to drift distance transfer relations, and result in chamber resolution functions. This paper describes novel algorithms to obtain precision calibrations from data collected by ATLAS in LHC Run 2 and from a gas monitoring chamber, deployed in a dedicated gas fac…
Missing Observations and Evolutionary Spectrum for Random Fields
2012
International audience
Convergence Rates for Persistence Diagram Estimation in Topological Data Analysis
2014
International audience; Computational topology has recently seen an important development toward data analysis, giving birth to the field of topological data analysis. Topological persistence, or persistent homology, appears as a fundamental tool in this field. In this paper, we study topological persistence in general metric spaces, with a statistical approach. We show that the use of persistent homology can be naturally considered in general statistical frameworks and that persistence diagrams can be used as statistics with interesting convergence properties. Some numerical experiments are performed in various contexts to illustrate our results.
A Neural Network Meta-Model and its Application for Manufacturing
2015
International audience; Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to increase a manufacturer's competitive advantage through improved sustainability, productivity, and flexibility of their operations. Manufacturers, as well as other industries, have successfully applied a promising statistical learning technique, called neural networks (NNs), to extract meaningful information from large data sets, so called big data. However, the application of NN to manufacturing problems remains limited because it involves the specialized skills of a data scientist. This paper introduces an appr…
Semantic User Profiling for Digital Advertising
2015
International audience; With the emergence of real-time distribution of online advertising space (“real-time bidding”), user profiling from web navigation traces becomes crucial. Indeed, it allows online advertisers to target customers without interfering with their activities. Current techniques apply traditional methods as statistics and machine learning, but suffer from their limitations. As an answer, the proposed approach aims to develop and evaluate a semantic-based user profiling system for digital advertising.