Search results for "Time serie"
showing 10 items of 261 documents
Use of CORS Time Series for Geodynamics Applications in Western Sicily (Italy)
2020
In the last few decades, the use of GNSS Continuously Operating Reference Station (CORS) networks allowed improving the accuracy of real-time positioning and post-processing positioning. In this way, several applications have been performed including remote sensing, agriculture, cultural heritage and geodynamics studies. The latter have been developed analysing CORS time-series and consistent data over long periods were needed to validate the results. In Italy, specifically in Sicily, two CORS networks were be used to monitor the geodynamics motions: the Istituto Nazionale di Geofisica e Vulcanologia (INGV) GNSS CORS network in the eastern part and the University of Palermo (UNIPA) GNSS COR…
Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999
2006
Abstract We used land surface temperature (LST) algorithms and NDVI values to estimate changes in vegetation in the European continent between 1982 and 1999 from the Pathfinder AVHRR Land (PAL) dataset. These two parameters are monitored through HANTS (Harmonic ANalysis of Time Series) software, which allows the simultaneous observation of mean value, first harmonic amplitude and phase behaviors in the same image. These results for each complete year of data show the effect of volcanic aerosols and orbital drift on PAL data. Comparison of time series of HANTS cloud-free time series with the original time series for various land cover proves that this software is useful for LST analysis, alt…
Deep learning for agricultural land use classification from Sentinel-2
2020
[ES] En el campo de la teledetección se ha producido recientemente un incremento del uso de técnicas de aprendizaje profundo (deep learning). Estos algoritmos se utilizan con éxito principalmente en la estimación de parámetros y en la clasificación de imágenes. Sin embargo, se han realizado pocos esfuerzos encaminados a su comprensión, lo que lleva a ejecutarlos como si fueran “cajas negras”. Este trabajo pretende evaluar el rendimiento y acercarnos al entendimiento de un algoritmo de aprendizaje profundo, basado en una red recurrente bidireccional de memoria corta a largo plazo (2-BiLSTM), a través de un ejemplo de clasificación de usos de suelo agrícola de la Comunidad Valenciana dentro d…
Predicting service request in support centers based on nonlinear dynamics, ARMA modeling and neural networks
2008
In this paper, we present the use of different mathematical models to forecast service requests in support centers (SCs). A successful prediction of service request can help in the efficient management of both human and technological resources that are used to solve these eventualities. A nonlinear analysis of the time series indicates the convenience of nonlinear modeling. Neural models based on the time delay neural network (TDNN) are benchmarked with classical models, such as auto-regressive moving average (ARMA) models. Models achieved high values for the correlation coefficient between the desired signal and that predicted by the models (values between 0.88 and 0.97 were obtained in th…
Testing Independence: A New Approach
2000
In time series analysis and modelling, testing for independence allows us to determine if the estimated model is correctly specified. In this work, we present a very simple method to test for serial independence, based on the two-dimensional embedding vectors (the so-called “2-histories”), and we analyse the power and size of such a procedure against a wide set of linear and nonlinear alternatives.
How a traditional agricultural protection structure acts in conditioning the internal microclimate: a statistical analytical approach to Giardino Pan…
2014
This work aims to analyze the traditional agricultural technique of the Giardino Pantesco, typical of the isle of Pantelleria (Sicily, Italy). With this particular technique a single citrus tree is encircled by a drywall of volcanic rocks allowing it to grow even in the island's unfavorable meteorological conditions. This technique has been analyzed by placing one instrumental array inside the Giardino and one outside and by measuring different environmental variables. The aim of the work is therefore to understand what is the drywall's effect on the tree by analyzing the time series produced by the sensors, using cross-correlation techniques and reducing the series' autocorrelation, so tha…
A Quantum-Inspired Classifier for Early Web Bot Detection
2022
This paper introduces a novel approach, inspired by the principles of Quantum Computing, to address web bot detection in terms of real-time classification of an incoming data stream of HTTP request headers, in order to ensure the shortest decision time with the highest accuracy. The proposed approach exploits the analogy between the intrinsic correlation of two or more particles and the dependence of each HTTP request on the preceding ones. Starting from the a-posteriori probability of each request to belong to a particular class, it is possible to assign a Qubit state representing a combination of the aforementioned probabilities for all available observations of the time series. By levera…
A Novel Time Series Kernel for Sequences Generated by LTI Systems
2017
The recent introduction of Hankelets to describe time series relies on the assumption that the time series has been generated by a vector autoregressive model (VAR) of order p. The success of Hankelet-based time series representations prevalently in nearest neighbor classifiers poses questions about if and how this representation can be used in kernel machines without the usual adoption of mid-level representations (such as codebook-based representations). It is also of interest to investigate how this representation relates to probabilistic approaches for time series modeling, and which characteristics of the VAR model a Hankelet can capture. This paper aims at filling these gaps by: deriv…
Spectral analysis of the beat-to-beat variability of arterial compliance
2022
Arterial compliance is an important parameter influencing ventricular-arterial coupling, depending on structural and functional mechanics of arteries. In this study, the spontaneous beat-to-beat variability of arterial compliance was investigated in time and frequency domains in thirty-nine young and healthy subjects monitored in the supine resting state and during head-up tilt. Spectral decomposition was applied to retrieve the spectral content of the time series associated to low (LF) and high frequency (HF) oscillatory components. Our results highlight: (i) a decrease of arterial compliance with tilt, in agreement with previous studies; (ii) an increase of the LF power content concurrent…
Assessment of Cardiorespiratory Interactions During Spontaneous and Controlled Breathing: Non-linear Model-free Analysis
2022
In this work, nonlinear model-free methods for bivariate time series analysis have been applied to study cardiorespiratory interactions. Specifically, entropy-based (i.e. Transfer Entropy and Cross Entropy) and Convergent Cross Mapping asymmetric coupling measures have been computed on heart rate and breathing time series extracted from electrocardiographic (ECG) and respiratory signals acquired on 19 young healthy subjects during an experimental protocol including spontaneous and controlled breathing conditions. Results evidence a bidirectional nature of cardiorespiratory interactions, and highlight clear similarities and differences among the three considered measures.