Results 211 to 220 of about 51,507 (261)

Experimental methods in chemical engineering: The scientific method versus engineering design methodology

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Engineering graduate students confuse the scientific method and problem solving when presenting their pre‐doctoral exams and theses: Science discourse adopts question and hypotheses to assert and establish a study's rationale, while it is problem and objectives in engineering design.
Gregory S. Patience, Alexander R. P. Harrison, Nicolas A. Patience, Paul A. Patience, Robert S. Weber   +4 more
wiley   +1 more source

Intelligent predictive neural network analysis on LTNE impacts on thermophoretic particle deposition in HFE 7100 nanofluid with Co₃O₄ nanoparticle. [PDF]

Discov Nano
Liaqat S, Dammak B, Khan MS, Abdelfattah W, Djuansjah J, Khan I, Abbas M, Khedher NB.   +7 more
europepmc   +1 more source

AI‐Enabled Precision Dosing in Pediatrics: Enhancing Model‐Informed Decision Making

Clinical Pharmacology &Therapeutics, EarlyView.
Ensuring safe and effective pharmacotherapy for children remains a central challenge in clinical pharmacology, yet rapid advances in AI have not translated into clinical practice. This Perspective highlights how AI‐enabled approaches can enhance model‐informed decision making for precision dosing.
Kei Irie, Tomoyuki Mizuno
wiley   +1 more source

Fractional-order epidemic modeling with a deep neural network framework. [PDF]

Sci Rep
Jangir P, Agarwal G, Nisar KS.
europepmc   +1 more source

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Optimization of Exoskeleton Assistance Function Based on Physics-Guided Dynamic Fusion Model. [PDF]

Bioengineering (Basel)
Tian H, Wang J, Guo S, Cao F, Liu L.
europepmc   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

Deep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +1 more source

Regime shift detection and neurocomputational substrates for under and overreactions to change. [PDF]

Elife
Wang MC, Wu G, Wu SW.
europepmc   +1 more source

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

Deep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source

Bilevel Optimized Implicit Neural Representation for Scan-Specific Accelerated MRI Reconstruction. [PDF]

IEEE Trans Med Imaging
Yu H, Fessler JA, Jiang Y.
europepmc   +1 more source