Results 221 to 230 of about 21,724,319 (311)

Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions

Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley   +1 more source

Use of machine learning and voice for multiclass classification of Parkinson's disease, chronic obstructive pulmonary disease, and healthy controls. [PDF]

Sci Rep
Idrisoglu A, Behrens A.
europepmc   +1 more source

Random forest regression for catalyst performance prediction and validation of tri‐reforming of methane (TRM)

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza, Raja Muhammad Afzal, Felipe Gomes Camacho, Nader Mahinpey   +3 more
wiley   +1 more source

Biochip-simulated genotype signals enable accurate and interpretable AMR prediction via machine learning. [PDF]

Front Med (Lausanne)
Fu Z.
europepmc   +1 more source

E-Voting with Aadhar

International Journal for Research in Applied Science and Engineering Technology, 2018
openaire   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

The Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan, Ryan Gosselin, Nicolas Abatzoglou   +2 more
wiley   +1 more source

Nanopore-m⁶A-finder, a novel m⁶A site caller for Nanopore DRS data. [PDF]

Front Genet
Yang Y, Yu L, Mo L, Qi C, Song W, Jin H.
europepmc   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

Reliable ECG classification using parallel hybrid models with limited resources. [PDF]

Sci Rep
Alyahya S, Malik AN, Amir M, Alharbi F, Habib S, Islam M.   +5 more
europepmc   +1 more source

TutorBots im Chemieunterricht: Nutzung, Akzeptanz und Hürden aus Sicht von Lehrkräften

CHEMKON, EarlyView.
Der Einsatz von Künstlicher Intelligenz (KI) bietet großes Potenzial für einen adaptiven Naturwissenschaftsunterricht. In einer explorativen Studie wurde untersucht, wie Chemielehrkräfte zum Einsatz von TutorBots im Unterricht eingestellt sind. Dabei wurde sowohl die aktuelle Nutzungserfahrung im Bereich der Erstellung und Anwendung von TutorBots ...
Mathea Brückner, Christoph Thyssen, Johannes Huwer   +2 more
wiley   +1 more source