Results 41 to 50 of about 18,233,102 (295)

Network structure of multivariate time series [PDF]

Scientific Reports, 2015
AbstractOur understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing.
Lacasa L, Nicosia V, LATORA, Vito Claudio   +2 more
openaire   +4 more sources

Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA

FEBS Open Bio, EarlyView.
Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley   +1 more source

Eigen-entropy based time series signatures to support multivariate time series classification

Scientific Reports
Most current algorithms for multivariate time series classification tend to overlook the correlations between time series of different variables. In this research, we propose a framework that leverages Eigen-entropy along with a cumulative moving window ...
Abhidnya Patharkar, Jiajing Huang, Teresa Wu, Erica Forzani, Leslie Thomas, Marylaura Lind, Naomi Gades   +6 more
doaj   +1 more source

Data-Adaptive Dynamic Time Warping-Based Multivariate Time Series Fuzzy Clustering

IEEE Access
Multivariate time series (MTS) clustering has become a critical research area. Current methods typically rely on space projection or representation learning for clustering but tend to overlook the significance and contribution of MTS dimensions, leading ...
Qinglin Cai, Leiying Chen, Jian Shao, Ling Chen   +3 more
doaj   +1 more source

Relationship Between Neurologic Symptoms and Signs and FMR1 Genotype in Premutation Carriers

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Fragile X‐associated Tremor/Ataxia Syndrome (FXTAS) is the most severe late‐onset condition caused by a premutation in the FMR1 gene, characterized by expanded CGG triplet repeats of 55–200. Clinical presentations of FXTAS, including gait ataxia, kinetic tremor, cognitive decline, and rare Parkinsonism, are linked to ...
Flora Tassone, Freddy Chafota, Miguel E. Rentería, Randi J. Hagerman, Ellery Santos, Anna Atkinson, Nicholas G. Martin, Elsdon Storey, Danuta Z. Loesch   +8 more
wiley   +1 more source

Variance changes detection in multivariate time series [PDF]

, 2004
This paper studies the detection of step changes in the variances and in the correlation structure of the components of a vector of time series. Two procedures are considered.
Peña, Daniel, Daniel Peña, Pedro Galeano, Galeano, Pedro   +3 more
core   +1 more source

Multi-Granular Embedding and Hybrid Encoder–Decoder Architecture with Temporal Linear Regression Bypass for Sensor-Based Time Series Forecasting in Smart Infrastructure

Sensors
In this work, we propose a robust deep encoder–decoder neural network that integrates multiple deep sequence models for time series forecasting in sensor-based applications.
Hsu-Yung Cheng, Huan-Hsuan Lin, Chi-Lun Jiang, Chih-Chang Yu   +3 more
doaj   +1 more source

Exploring Dynamic Structures in Matrix-Valued Time Series via Principal Component Analysis

Axioms, 2023
Time-series data are widespread and have inspired numerous research works in machine learning and data analysis fields for the classification and clustering of temporal data. While there are several clustering methods for univariate time series and a few
Lynne Billard, Ahlame Douzal-Chouakria, S. Yaser Samadi   +2 more
doaj   +1 more source

Online Clustering of Multivariate Time-series [PDF]

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016
Copyright © by SIAM. The intrinsic nature of streaming data requires algorithms that are capable of fast data analysis to extract knowledge. Most current unsupervised data analysis techniques rely on the implementation of known batch techniques over a sliding window, which can hinder their utility for the analysis of evolving structure in applications ...
Masud Moshtaghi, Christopher Leckie, James C. Bezdek   +2 more
openaire   +2 more sources

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source