Search results for "Time-serie"
showing 10 items of 41 documents
Effects of density, species interactions, and environmental stochasticity on the dynamics of British bird communities
2022
Our knowledge of the factors affecting species abundances is mainly based on time-series analyses of a few well-studied species at single or few localities, but we know little about whether results from such analyses can be extrapolated to the community level. We apply a joint species distribution model to long-term time-series data on British bird communities to examine the relative contribution of intra- and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatiotemporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, envi…
Empirical analysis of daily cash flow time-series and its implications for forecasting
2019
Usual assumptions on the statistical properties of daily net cash flows include normality, absence of correlation and stationarity. We provide a comprehensive study based on a real-world cash flow data set showing that: (i) the usual assumption of normality, absence of correlation and stationarity hardly appear; (ii) non-linearity is often relevant for forecasting; and (iii) typical data transformations have little impact on linearity and normality. This evidence may lead to consider a more data-driven approach such as time-series forecasting in an attempt to provide cash managers with expert systems in cash management.
Feasibility of Ultra-Short-Term Analysis of Heart Rate and Systolic Arterial Pressure Variability at Rest and during Stress via Time-Domain and Entro…
2022
Heart Rate Variability (HRV) and Blood Pressure Variability (BPV) are widely employed tools for characterizing the complex behavior of cardiovascular dynamics. Usually, HRV and BPV analyses are carried out through short-term (ST) measurements, which exploit ~five-minute-long recordings. Recent research efforts are focused on reducing the time series length, assessing whether and to what extent Ultra-Short-Term (UST) analysis is capable of extracting information about cardiovascular variability from very short recordings. In this work, we compare ST and UST measures computed on electrocardiographic R-R intervals and systolic arterial pressure time series obtained at rest and during both post…
Persistence in complex systems
2022
Persistence is an important characteristic of many complex systems in nature, related to how long the system remains at a certain state before changing to a different one. The study of complex systems' persistence involves different definitions and uses different techniques, depending on whether short-term or long-term persistence is considered. In this paper we discuss the most important definitions, concepts, methods, literature and latest results on persistence in complex systems. Firstly, the most used definitions of persistence in short-term and long-term cases are presented. The most relevant methods to characterize persistence are then discussed in both cases. A complete literature r…
WATCHING PEOPLE: ALGORITHMS TO STUDY HUMAN MOTION AND ACTIVITIES
2020
Nowadays human motion analysis is one of the most active research topics in Computer Vision and it is receiving an increasing attention from both the industrial and scientific communities. The growing interest in human motion analysis is motivated by the increasing number of promising applications, ranging from surveillance, human–computer interaction, virtual reality to healthcare, sports, computer games and video conferencing, just to name a few. The aim of this thesis is to give an overview of the various tasks involved in visual motion analysis of the human body and to present the issues and possible solutions related to it. In this thesis, visual motion analysis is categorized into thr…
Seasonal Modulation of the $^7$Be Solar Neutrino Rate in Borexino
2017
We detected the seasonal modulation of the $^7$Be neutrino interaction rate with the Borexino detector at the Laboratori Nazionali del Gran Sasso in Italy. The period, amplitude, and phase of the observed time evolution of the signal are consistent with its solar origin, and the absence of an annual modulation is rejected at 99.99\% C.L. The data are analyzed using three methods: the sinusoidal fit, the Lomb-Scargle and the Empirical Mode Decomposition techniques, which all yield results in excellent agreement.
Motivic Pattern Extraction in Music, and Application to the Study of Tunisian Modal Music
2007
A new methodology for automated extraction of repeated patterns in time-series data is presented, aimed in particular at the analysis of musical sequences. The basic principles consists in a search for closed patterns in a multi-dimensional parametric space. It is shown that this basic mechanism needs to be articulated with a periodic pattern discovery system, implying therefore a strict chronological scanning of the time-series data. Thanks to this modelling global pattern filtering may be avoided and rich and highly pertinent results can be obtained. The modelling has been integrated in a collaborative pro ject between ethnomusicology, cognitive sciences and computer science, aimed at the…
Prediction and interpolation of time series by state space models
2015
Artikkeliväitöskirja. Sisältää yhteenveto-osan ja neljä artikkelia. Article dissertation. Contains an introduction part and four articles. A large amount of data collected today is in the form of a time series. In order to make realistic inferences based on time series forecasts, in addition to point predictions, prediction intervals or other measures of uncertainty should be presented. Multiple sources of uncertainty are often ignored due to the complexities involved in accounting them correctly. In this dissertation, some of these problems are reviewed and some new solutions are presented. A state space approach is also advocated for an e cient and exible framework for time series forecas…
Data from: Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models
2018
Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypoth…
Optical turbulence measurements and channel modeling of an indoor Free Space Optics link (Versione estesa)
2014
In this work, we propose an indoor experimental set-up able to generate several optical turbulence conditions in a Free Space Optics link. Using this set-up, we prove the effectiveness of an irradiance time-series generator based on the Gamma-Gamma model and able to predict the irradiance fluctuations at the receiver, under both weak and moderate turbulence conditions.