Results 71 to 80 of about 17,625 (278)

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

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 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

Undersampling Multisine Signals

Undersampling Multisine Signals is a tool for selecting frequencies of a multisine signal that do not overlap in the frequency domain in undersampling ...
Blömeke, Alexander, Sauer, Dirk Uwe
core   +1 more source

Evolutionary undersampling for imbalanced big data classification

, 2015
Classification techniques in the big data scenario are in high demand in a wide variety of applications. The huge increment of available data may limit the applicability of most of the standard techniques.
Triguero, Isaac, F. Herrera, Galar, Mikel, Y. Saeys, Cornelis, Chris, Bustince, Humberto, Vluymans, Sarah, I. Triguero, C. Cornelis, M. Galar, S. Vluymans, Saeys, Yvan, Herrera, Francisco, H. Bustince   +13 more
core   +1 more source

Hashing-based undersampling for large scale histopathology image classification

, 2023
The early diagnosis of cancer based on histopathology images plays an important role in medical science. Existing techniques generally partition the original histopathology image into small pieces for further classification. However, due to the fact that
Qiu, Lin, Yu, Honghua, Liu, Baoyi, Zhang, Jianjun, Wang, Hui; id_orcid, Tian, Xing, Li, Qihua, Dong, Xinran, Kwong, Sam, Ng, Wing W.Y., Hu, Yijun   +10 more
core   +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

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

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