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We consider the problem of sampling continuous-time auto-regressive processes on a uniform grid. We investigate whether a given sampled process originates from a single continuous-time model, and address this uniqueness problem by introducing an alternativ ...
Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables lik ...
Provenance is often used to validate data, by verifying its origin and explaining its derivation. When searching for “causes” of tuples in the query results or in general observations, the analysis of lineage becomes an essential tool for providing such ju ...
Nowadays, physiological monitoring is imperative for the safety of medical operations. However, systems which monitor the depth of anaesthesia are still far from reliable, such that still some patients may experience the trauma of remaining conscious under ...
An analytical method for the quantification of the widely used herbicide, glyphosate, its main by-product, aminomethylphosphonic acid (AMPA) and the herbicide glufosinate at trace level was developed and tested in different aqueous matrices. Their derivati ...
This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propose a novel topic model that accounts for the two main factors that affect thes ...
This paper proposes a robust semiparametric bootstrap method to estimate predictive distributions of GARCH-type models. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH residuals that contr ...
In this paper we modeled the effects that dominant people might induce on the nonverbal behavior (speech energy and body motion) of the other meeting participants using Granger causality technique. Our initial hypothesis that more dominant people have gene ...
Neurons in the brain form complicated networks through synaptic connections. Traditionally, functional connectivity between neurons has been analyzed using simple metrics such as correlation, which do not provide direction of influence. Recently, an inform ...
Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference systems and genetic programming are used in this chapter for the modeling of the nonlinear behavior of composite laminates subjected to constant amplitude loadin ...