Search results for "Data analysis."
showing 10 items of 377 documents
From time series to complex networks: the visibility graph
2008
In this work we present a simple and fast computational method, the visibility algorithm , that converts a time series into a graph. The constructed graph inherits several properties of the series in its structure. Thereby, periodic series convert into regular graphs, and random series do so into random graphs. Moreover, fractal series convert into scale-free networks, enhancing the fact that power law degree distributions are related to fractality, something highly discussed recently. Some remarkable examples and analytical tools are outlined to test the method's reliability. Many different measures, recently developed in the complex network theory, could by means of this new approach cha…
Second-order tensorial calibration for kinetic spectrophotometric determination
1996
Abstract Kinetic-diode array spectrophotometric detection, as well as other multichannel techniques when used in non-equilibrium conditions, constitute second-order instrumentation. The second-order response provided will be bilinear, under certain conditions even trilinear, thus allowing the use of the generalized rank annihilation method (GRAM) and the trilinear decomposition method (TLD). Both numerically simulated and experimental data were used to evaluate the performance of these calibration techniques. The conditions in which the ‘second-order advantage’ (the possibility of quantifying the analytes in the presence of unknown reactions or interferences) is preserved were investigated.…
Effects of reversible lane implementation, a case study simulation
2019
In a modern society, transport is a necessity for carrying out certain activities that human communities are involved in. This need for mobility is on a continuous rise and can be characterized by the possibility of moving from one point to another, using different means of transport, in order to facilitate the performed activities. The purpose of this research is to design and evaluate the implementation of a system of reversible lanes using simulation. As methodology, it starts from an analysis of data collected from real traffic condition through implementation and simulation with the Synchro application. The analysis proposes solutions to decongest traffic through the implementation of …
"Table 3" of "Measurement of the $W+b$-jet and $W+c$-jet differential production cross sections in $p\bar{p}$ collisions at $\sqrt{s}=1.96$ TeV"
2016
The $\sigma(W+c)/\sigma(W+b)$ cross section ratio in bins of $c(b)$-jet $p_T$.
"Table 2" of "Measurement of the differential photon+ c-jet cross section and the ratio of differential photon+ c and photon+ b cross sections in pro…
2013
The ratio of the (GAMMA+ CJET) to (GAMMA+ BJET) cross section in bins of the GAMMA PT.
Bayesian Analysis of a Future Beta Decay Experiment's Sensitivity to Neutrino Mass Scale and Ordering
2021
Bayesian modeling techniques enable sensitivity analyses that incorporate detailed expectations regarding future experiments. A model-based approach also allows one to evaluate inferences and predicted outcomes, by calibrating (or measuring) the consequences incurred when certain results are reported. We present procedures for calibrating predictions of an experiment's sensitivity to both continuous and discrete parameters. Using these procedures and a new Bayesian model of the $\beta$-decay spectrum, we assess a high-precision $\beta$-decay experiment's sensitivity to the neutrino mass scale and ordering, for one assumed design scenario. We find that such an experiment could measure the el…
Explicit Granger causality in kernel Hilbert spaces
2020
Granger causality (GC) is undoubtedly the most widely used method to infer cause-effect relations from observational time series. Several nonlinear alternatives to GC have been proposed based on kernel methods. We generalize kernel Granger causality by considering the variables cross-relations explicitly in Hilbert spaces. The framework is shown to generalize the linear and kernel GC methods, and comes with tighter bounds of performance based on Rademacher complexity. We successfully evaluate its performance in standard dynamical systems, as well as to identify the arrow of time in coupled R\"ossler systems, and is exploited to disclose the El Ni\~no-Southern Oscillation (ENSO) phenomenon f…
Universal freezing of quantum correlations within the geometric approach
2015
Quantum correlations in a composite system can be measured by resorting to a geometric approach, according to which the distance from the state of the system to a suitable set of classically correlated states is considered. Here we show that all distance functions, which respect natural assumptions of invariance under transposition, convexity, and contractivity under quantum channels, give rise to geometric quantifiers of quantum correlations which exhibit the peculiar freezing phenomenon, i.e., remain constant during the evolution of a paradigmatic class of states of two qubits each independently interacting with a non-dissipative decohering environment. Our results demonstrate from first …
Modelling and Simulation in Science, Proceedings of the 6th International Workshop on Data Analysis in Astronomy >
2007
Probabilistic Anomaly Detection for Wireless Sensor Networks
2011
Wireless Sensor Networks (WSN) are increasingly gaining popularity as a tool for environmental monitoring, however ensuring the reliability of their operation is not trivial, and faulty sensors are not uncommon; moreover, the deployment environment may influence the correct functioning of a sensor node, which might thus be mistakenly classified as damaged. In this paper we propose a probabilistic algorithm to detect a faulty node considering its sensed data, and the surrounding environmental conditions. The algorithm was tested with a real dataset acquired in a work environment, characterized by the presence of actuators that also affect the actual trend of the monitored physical quantities.