Results 71 to 80 of about 38,801 (275)

Maximin Analysis of Message Passing Algorithms for Recovering Block Sparse Signals [PDF]

, 2013
We consider the problem of recovering a block (or group) sparse signal from an underdetermined set of random linear measurements, which appear in compressed sensing applications such as radar and imaging.
Baraniuk, Richard, Maleki, Arian, Studer, Christoph, Taeb, Armeen   +3 more
core   +1 more source

Bridging Theory and Prediction: A Hybrid SEM and Machine Learning Approach to Optimize Lean Construction for Megaproject Sustainability in China

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Construction megaprojects, large‐scale, complex, and capital‐intensive, are particularly prone to inefficiencies, cost overruns, delays, and environmental degradation due to fragmented workflows, stakeholder misalignment, and resource intensity.
Abdelazim Ibrahim, Tarek Zayed, Zoubeir Lafhaj, Ahmed Maged, Ahmed Farouk Kineber, Jingchao Yang   +5 more
wiley   +1 more source

An Efficient and Robust Frequency Estimator Dealing With Short-Observation Under-Sampled Waveforms

IEEE Access, 2018
Frequency estimation of a noisy signal in under-sampled conditions is a challenging problem, which has proved to be effectively solved by Chinese remainder theorem (CRT).
Xiangdong Huang, Mengkai Yang, Mingzhuo Liu, Lin Yang   +3 more
doaj   +1 more source

Reweighting Scheme for the Calculation of Grand‐Canonical Expectation Values in Quantum Monte Carlo Simulations With a Fermion Sign Problem

Contributions to Plasma Physics, EarlyView.
ABSTRACT Ab initio path integral Monte Carlo (PIMC) simulations constitute the gold standard for the estimation of a broad range of equilibrium properties of a host of interacting quantum many‐body systems spanning a broad range of conditions from ultracold atoms to warm dense quantum plasmas.
Paul Hamann, Jan Vorberger, Tobias Dornheim   +2 more
wiley   +1 more source

An Empirical Analysis of Crash Injury Severity Among Young Drivers in England: Accounting for Data Imbalance

Applied Sciences
Crash data analysis is key to improving road safety, but imbalanced data challenges accurate predictions for severe crashes, often leading to biased outcomes. This study investigates crash severity among young drivers (aged 17–24) in England, using crash
Amirhossein Taheri, Kevin Switala, Grigorios Fountas, Abbas Sheykhfard, Nima Dadashzadeh, Steffen Müller   +5 more
doaj   +1 more source

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

IEEE Access, 2019
Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient.
Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed, Mingyi Zhou, Yipeng Liu   +5 more
doaj   +1 more source

Radar-based Feature Design and Multiclass Classification for Road User Recognition

, 2019
The classification of individual traffic participants is a complex task, especially for challenging scenarios with multiple road users or under bad weather conditions.
Appenrodt, Nils, Dickmann, Jürgen, Scheiner, Nicolas, Sick, Bernhard   +3 more
core   +1 more source

Intracranial electroencephalographic approaches in the intensive care unit: Safety, feasibility, and coverage

Epilepsia, EarlyView.
Abstract Objective Nonconvulsive epileptic activity is common after acute brain injury and contributes to neuronal injury and poor outcomes. Although intracranial electroencephalography (iEEG) improves detection compared with surface EEG (suEEG), it currently relies on focal recordings of epileptic dynamics.
Steven Smeijers, Mariella Segreti, Anaïs Van Hoylandt, Jeroen Gijs, Johannes van Loon, Lauranne Scheldeman, Bart Depreitere, Tom Theys   +7 more
wiley   +1 more source

Reconstruction of Self-Sparse 2D NMR Spectra from Undersampled Data in the Indirect Dimension

Sensors, 2011
Reducing the acquisition time for two-dimensional nuclear magnetic resonance (2D NMR) spectra is important. One way to achieve this goal is reducing the acquired data.
Zhong Chen, Shuhui Cai, Xue Cao, Di Guo, Xiaobo Qu   +4 more
doaj   +1 more source

Identifying Venous Insufficiency in Head and Neck Reconstruction Flaps Using Machine Learning and Deep Learning Methods

Head &Neck, EarlyView.
ABSTRACT Background Venous insufficiency is a major cause of flap failure in head and neck reconstruction. AI provides a reliable, convenient solution for early detection. Methods Clinical data and postoperative flap photos of head and neck cancer patients (2018–2024) at our center were retrospectively collected, categorized into normal and venous ...
Yurong He, Jugao Fang, Lizhen Hou, Zufei Li, Shizhi He, Yanming Zhao, Qijia Li, Rongjia Li, Xiaoyu Shi, Jiayi Yang, Qi Zhong   +10 more
wiley   +1 more source