Results 121 to 130 of about 40,126 (265)

Enhanced biogas production via dual‐layer model predictive control for thermophilic anaerobic digesters

AIChE Journal, EarlyView.
Abstract Thermophilic anaerobic digestion (AD) is an attractive process due to its higher biogas yield compared to mesophilic digestion. To mitigate its higher heating demand and potential process instability, a dual‐layer control architecture comprising a decision‐making layer and an adaptive model predictive control (MPC) system is proposed.
Ali Moradvandi, Mohammad Amin Ghanavati, Merle de Kreuk, Ralph E. F. Lindeboom   +3 more
wiley   +1 more source

Solving Bi-harmonic Cauchy problem using a meshless collocation method

Academic Science Journal
In this article a fourth order differential boundary value problem is solved using a mesh less collocation method. The efficiency of the proposed methods is illustrated by solving problems with some examples of a polynomial and Non polynomial exact ...
Baydaa Khaleel Mostafa, Duaa Jasim , Athraa Falih Hasan , Ibtihal Thabit Jameel, Fatima M. ABOUD   +4 more
doaj   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Limitations of noisy quantum devices in computing and entangling power

npj Quantum Information
Finding solid and practical quantum advantages via noisy quantum devices without error correction is a critical but challenging problem. Conversely, comprehending the fundamental limitations of the state-of-the-art is equally crucial.
Yuxuan Yan, Zhenyu Du, Junjie Chen, Xiongfeng Ma   +3 more
doaj   +1 more source

Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns

Advanced Intelligent Discovery, EarlyView.
Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer, André Orth, Robert Wang, Ben Breitung, Simon Schweidler, Jasmin Aghassi‐Hagmann, Markus Reischl   +6 more
wiley   +1 more source

MINIMIZING THE NUMBER OF PROCESSING UNITS IN DISTRIBUTED COMPUTATIONS

Informatika, 2016
Polynomial algorithms for finding the minimum number of processing units in the problem of scheduling heterogeneous competing processes on parallel processors are developed.
N. S. Kovalenko, V. N. Vengherov, V. M. Metelyskij   +2 more
doaj  

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Abstracts of Doctor Habilitatus Thesis [PDF]

Computer Science Journal of Moldova, 2012
Cotelea Vitalie
doaj  

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source