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Abstract Introduction: Suicide is the cause of death of almost 800 thousand people worldwide every year. In Brazil, Rio Grande do Sul is one of the states with the highest suicide rates. This study aimed to assess wheth...

"Complex networks theory have gained wider applicability since methods for transformation of time series to networks were proposed and successfully tested. In the last few years, horizontal visibility graph has become a ...

In the last few years, neural networks have found interesting applications in the field of time series modeling and forecasting. Some recent results show the ability of these models to approximate the dynamical behavior ...

BackgroundMeteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the...

"In this paper, we propose a formalism to query transportation networks that are equipped with sensors that produce time-series data. The core of the proposed query mechanism is a logic based language that is capable to...

Abstract Understanding and controlling the marine degradation of biodegradable polymers is crucial for sustainable materials engineering and pollution prevention. However, a unified interpretive method that links multisc...

Subjects / keywords: Economía y Comercio; Gestión Industrial

In recent years a couple of methods aimed at time series symbolic representation have been introduced or developed. This activity is mainly justified by practical considerations such memory savings or fast data base sear...

Abstract The integration of large-scale distributed power sources complicates grid topology and intensifies spatiotemporal coupling in power data. This complicates the analysis of intrinsic correlations and makes predict...

The growth of variable renewable energy sources has increased the occurrence of curtailment in power systems, particularly in regions affected by transmission constraints and limited operational flexibility. Reliable for...

A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in...

Multivariate time series forecasting is pivotal in real-world applications, ranging from energy consumption management and financial market trend analysis to traffic flow prediction and climate monitoring. Yet, it is cri...

Time series analysis is essential for finance, transportation, energy, healthcare, and climate research. While time-frequency domain representation underpins effective time series modeling, its holistic utilization and i...

The aim of this paper is to present and validate rain attenuation time series synthesizers relying on the Maseng-Bakken principle for terrestrial links in tropical areas. Data obtained in experimental measurements at fou...

"In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been...

"In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from...

"A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities i...

Abstract Groundwater is a central component of the Earth system. However, our understanding of how it is dynamically interlinked with the atmosphere, hydrosphere, cryosphere, biosphere, geosphere, and anthroposphere rema...

Importance: Medical time series constitute the largest data type in electronic health records and are often irregularly sampled in real-world clinical settings. Such irregularly sampled medical time series exhibit uneven...

This study examines whether active learning activities based on time series forecasting for engineering students yield statistically significant improvements with respect to performance and engagement. In this context, a...

Since its inception at the end of the XX century, VaR risk measure has gained massive popularity. It is synthetic, easy in interpretation and offers comparability of risk levels reported by different institutions. Howeve...

Analyzing time series data with remote sensing provides a better understanding of vegetation dynamics, since previous conditions and changes that have occurred over a given period are known. The objective of this paper w...

This study analyzes five years of 1-min solar global horizontal irradiance (GHI) and direct normal irradiance (DNI) observations obtained at Petrolina (northeast Brazil). Quality-assured hourly and daily averages are obt...

Subjects / keywords: GRANGER, C.W.J; PRINCETON UNIVERSITY PRESS; 519.232 G758s