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Time Series Data Mining
This section introduces time series data mining tasks in the sport domain. One of the aspects that are described is the discovering of events or...
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Temporal classification of short time series data
MotivationWithin the frame of their genetic capacity, organisms are able to modify their molecular state to cope with changing environmental...
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Biodiversity time series are biased towards increasing species richness in changing environments
The discrepancy between global loss and local constant species richness has led to debates over data quality, systematic biases in monitoring...
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Tail-dependence clustering of time series with spatial constraints
We introduce a clustering method for time series based on tail dependence. Such a method also considers spatial constraints by means of a suitable...
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Assessing cumulative uncertainties of remote sensing time series and telemetry data in animal-environment studies
ContextRemote sensing time series (hereafter called time series) and telemetry data are widely used to study animal-environment relationships....
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Real-time cucurbit fruit detection in greenhouse using improved YOLO series algorithm
The real-time cucurbit fruit detection algorithm in complex environment of greenhouse is associated with challenges. Leaves occlusion, overlap**...
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A Dictionary-Based Approach to Time Series Ordinal Classification
Time Series Classification (TSC) is an extensively researched field from which a broad range of real-world problems can be addressed obtaining...
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Time series-based hybrid ensemble learning model with multivariate multidimensional feature coding for DNA methylation prediction
BackgroundDNA methylation is a form of epigenetic modification that impacts gene expression without modifying the DNA sequence, thereby exerting...
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RENGE infers gene regulatory networks using time-series single-cell RNA-seq data with CRISPR perturbations
Single-cell RNA-seq analysis coupled with CRISPR-based perturbation has enabled the inference of gene regulatory networks with causal relationships....
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Level of kayakers’ skills influence their boat acceleration time series
Paddler ability in kayaking is reflected through boat motion. Through the application of accelerometers, an easy to use and readily available...
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Biclustering fMRI time series: a comparative study
BackgroundThe effectiveness of biclustering, simultaneous clustering of rows and columns in a data matrix, was shown in gene expression data...
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Modeling deficit irrigation water demand of maize and potato in Eastern Germany using ERA5-Land reanalysis climate time series
ERA5-Land reanalysis (ELR) climate time series has proven useful in (hydro)meteorological studies, however, its adoption for local studies is limited...
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Gramian Angular and Markov Transition Fields Applied to Time Series Ordinal Classification
This work presents a novel ordinal Deep Learning (DL) approach to Time Series Ordinal Classification (TSOC) field. TSOC consists in classifying time...
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Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning
Traditional time series forecasting models often use all available variables, including potentially irrelevant or noisy features, which can lead to...
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Forecasting Potato Production in Major South Asian Countries: a Comparative Study of Machine Learning and Time Series Models
This study analyzed and forecasted potato production in eight major South Asian countries from 1961 to 2028 using advanced time series and machine...
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Four-dimensional measurement of root system development using time-series three-dimensional volumetric data analysis by backward prediction
BackgroundRoot system architecture (RSA) is an essential characteristic for efficient water and nutrient absorption in terrestrial plants; its...
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Biclustering analysis on tree-shaped time-series single cell gene expression data of Caenorhabditis elegans
BackgroundIn recent years, gene clustering analysis has become a widely used tool for studying gene functions, efficiently categorizing genes with...
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Did Covid-19 Impacted Market Arrivals and Prices of Major Food Commodities in India: Evidence from Extended Time Series Analysis
The COVID-19 pandemic and subsequent lockdown policy significantly impacted all sectors of the economy, including agriculture. It disrupted the...
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Modeling Global Monkeypox Infection Spread Data: A Comparative Study of Time Series Regression and Machine Learning Models
The global impact of COVID-19 has heightened concerns about emerging viral infections, among which monkeypox (MPOX) has become a significant public...
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Time series clustering using trend, seasonal and autoregressive components to identify maximum temperature patterns in the Iberian Peninsula
Time series (TS) clustering is a crucial area of data mining that can be used to identify interesting patterns. This study introduces a novel...
