Concept

Seasonality

Related publications (10)

Spatio-temporal controls of C–N–P dynamics across headwater catchments of a temperate agricultural region from public data analysis

Characterizing and understanding spatial variability in water quality for a variety of chemical elements is an issue for present and future water resource management. However, most studies of spatial variability in water quality focus on a single element a ...

2021

Seasonal hysteresis of surface urban heat islands

Gabriele Manoli, Gabriel George Katul

Temporal dynamics of urban warming have been extensively studied at the diurnal scale, but the impact of background climate on the observed seasonality of surface urban heat islands (SUHIs) remains largely unexplored. On seasonal time scales, the intensity ...

2020

Application of Time Series Methods on Long-Term Structural Monitoring Data for Fatigue Analysis

Eugen Brühwiler, Bartlomiej Wojciech Sawicki, Morteza Ahmadivala

Structural health monitoring (SHM) can be employed to reduce uncertainties in different aspects of structural analysis such as: load modeling, crack development, corrosion rates, etc. Fatigue is one of the main degradation processes of structures that caus ...

2019

Probabilistic Prediction and Forecast of Daily Suspended Sediment Concentration on the Upper Yangtze River

Mário Jorge Rodrigues Pereira Da Franca, José Pedro Gamito de Saldanha Calado Matos

Sediment transport in suspension can represent more than 90% of a river's total annual flux of sediment. In the case of the Yangtze River, more than 99% of the sediment supplied to the sea is suspended load. Suspended sediment is thus an important componen ...

AMER GEOPHYSICAL UNION2018

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia, Carlos Castillo

Applying classical time-series analysis techniques to online content is challenging, as web data tends to have data quality issues and is often incomplete, noisy, or poorly aligned. In this paper, we tackle the problem of predicting the evolution of a time ...

Infrequent Rebalancing, Return Autocorrelation, and Seasonality

Vincent Jean Bogousslavsky

A model of infrequent rebalancing can explain specific predictability patterns in the time series and cross-section of stock returns. First, infrequent rebalancing produces return autocorrelations that are consistent with empirical evidence from intraday r ...

Wiley-Blackwell2016

Demodulation of time series highlights impacts of hydrologic drivers on the Everglades ecosystem

Andrea Rinaldo

In the context of climatic uncertainty and potential climatic change, incorporating climatic variability and change in eco-hydrological analysis, as well as understanding the impact of such variability on ecosystems, is of crucial importance. The latter is ...

Wiley-Blackwell2015

Seasonal variation of municipal solid waste generation and composition in four East European cities

Christian Ludwig

The quality of recyclable and residual municipal solid waste (MSW) is, among other factors, strongly influenced by the seasonal variation in MSW composition. However, a relatively marginal amount of published data on seasonal MSW composition especially in ...

Elsevier2014

Extreme events in total ozone over Arosa---Part 1: Application of extreme value theory

Anthony Christopher Davison

In this study ideas from extreme value theory are for the first time applied in the field of stratospheric ozone research, because statistical analysis showed that previously used concepts assuming a Gaussian distribution (e.g. fixed deviations from mean v ...

Copernicus Publications2010

Nonlinear feature transformations for noise robust speech recognition

Shajith Ikbal

Robustness against external noise is an important requirement for automatic speech recognition (ASR) systems, when it comes to deploying them for practical applications. This thesis proposes and evaluates new feature-based approaches for improving the ASR ...

EPFL2004

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