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This research focuses on the estimation of a non-parametric regression function designed for data with simultaneous time and space dependencies. In such a context, we study the Trend Filtering, a nonparametric estimator introduced by…

Methodology · Statistics 2023-09-14 Carlos Misael Madrid Padilla , Oscar Hernan Madrid Padilla , Daren Wang

Electrocardiogram (ECG) is one of the non-invasive and low-risk methods to monitor the condition of the human heart. Any abnormal pattern(s) in the ECG signal is an indicative measure of malfunctioning of the heart, termed as arrhythmia.…

Signal Processing · Electrical Eng. & Systems 2018-10-10 Sai Manoj Pudukotai Dinakarrao , Matthias Wess

Non-invasive at-home monitoring of lung and lung airways health enables the early detection and tracking of respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD). Various proposed approaches estimate the…

Signal Processing · Electrical Eng. & Systems 2021-10-12 Maria Nyamukuru , Kofi Odame

Ocean microbes are critical to both ocean ecosystems and the global climate. Flow cytometry, which measures cell optical properties in fluid samples, is routinely used in oceanographic research. Despite decades of accumulated data,…

Methodology · Statistics 2025-04-17 Sangwon Hyun , Tim Coleman , Francois Ribalet , Jacob Bien

The temporal behaviour of segmentation clock oscillations show phase synchrony via mean field like coupling of delta protein restricting to nearest neighbours only, in a configuration of cells arranged in a regular three dimensional array.…

We present a time-domain method to detect and correct spectral alterations of signals by employing statistical characterization of waveforms and a pattern-recognition procedure using simple Artificial Neural Networks. The proposed strategy…

Signal Processing · Electrical Eng. & Systems 2022-12-29 Guillermo H. Bustos , Héctor H. Segnorile

The automated segmentation and tracking of macrophages during their migration are challenging tasks due to their dynamically changing shapes and motions. This paper proposes a new algorithm to achieve automatic cell tracking in time-lapse…

Image and Video Processing · Electrical Eng. & Systems 2023-01-03 Seol Ah Park , Tamara Sipka , Zuzana Kriva , George Lutfalla , Mai Nguyen-Chi , Karol Mikula

Interactions between neighboring cells are essential for generating or refining patterns in a number of biological systems. We propose a discrete filtering approach to predict how networks of cells modulate spatially varying input signals…

Tissues and Organs · Quantitative Biology 2019-02-14 Melinda Liu Perkins , Murat Arcak

A sequential estimator based on the Ensemble Kalman Filter for Data Assimilation of fluid flows is presented in this research work. The main feature of this estimator is that the Kalman filter update, which relies on the determination of…

Computational Engineering, Finance, and Science · Computer Science 2021-07-28 Gabriel Moldovan , Guillame Lehnasch , Laurent Cordier , Marcello Meldi

This work presents an algorithm for determining the parameters of a nonlinear dynamic model of the respiratory system in patients undergoing assisted ventilation. Using the pressure and flow signals measured at the mouth, the model's…

Systems and Control · Electrical Eng. & Systems 2024-03-01 Diego A. Riva , Carolina A. Evangelista , Paul F. Puleston , Luis Corsiglia , Nahuel Dargains

We propose a novel approach for change-point detection and parameter learning in multivariate non-stationary time series exhibiting oscillatory behaviour. We approximate the process through a piecewise function defined by a sum of…

Methodology · Statistics 2026-02-02 Nicolas Bianco , Lorenzo Cappello

Quantum phase estimation plays a central role in quantum simulation as it enables the study of spectral properties of many-body quantum systems. Most variants of the phase estimation algorithm require the application of the global unitary…

Gene expression levels, hormone secretion, and internal body temperature each oscillate over an approximately 24-hour cycle, or display circadian rhythms. Many circadian biology studies have investigated how these rhythms vary across…

We present online prediction methods for time series that let us explicitly handle nonstationary artifacts (e.g. trend and seasonality) present in most real time series. Specifically, we show that applying appropriate transformations to…

Machine Learning · Statistics 2018-08-28 Christopher Xie , Avleen Bijral , Juan Lavista Ferres

The ocean is filled with microscopic microalgae called phytoplankton, which together are responsible for as much photosynthesis as all plants on land combined. Our ability to predict their response to the warming ocean relies on…

Applications · Statistics 2022-08-05 Sangwon Hyun , Mattias Rolf Cape , Francois Ribalet , Jacob Bien

We investigate methods to calibrate the non-common path aberrations at an adaptive optics system having a wavefront-correcting device working at an extremely high resolution (larger than 150x150). We use focal-plane images collected…

Instrumentation and Methods for Astrophysics · Physics 2015-06-22 Visa Korkiakoski , Christoph U. Keller , Niek Doelman , Matthew Kenworthy , Gilles Otten , Michel Verhaegen

Signals with varying periodicity frequently appear in real-world phenomena, necessitating the development of efficient modelling techniques to map the measured nonlinear timeline to linear time. Here we propose a regression model that…

Objectives: The main objective of this review article is to evaluate the usability of Computational Fluid Dynamics (CFD) as a supporting clinical tool for respiratory system. Data Source: The English articles referred for this review paper…

Fluid Dynamics · Physics 2023-10-24 Rajneesh Kashyap , R. Thundil Karuppa Raj

In this article I recommend a better point estimator for Krippendorff's Alpha agreement coefficient, and develop a jackknife variance estimator that leads to much better interval estimation than does the customary bootstrap procedure or an…

Methodology · Statistics 2022-10-25 John Hughes

Threshold networks are used as models for neural or gene regulatory networks. They show a rich dynamical behaviour with a transition between a frozen and a chaotic phase. We investigate the phase diagram of randomly connected threshold…

Statistical Mechanics · Physics 2009-11-13 Agnes Szejka , Tamara Mihaljev , Barbara Drossel
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