Results 41 to 50 of about 6,534,602 (244)
PERMODELAN INVERSI PEREDAM MAGNET-REOLOGI BERBASIS JARINGAN SARAF TIRUAN UNTUK SISTEM KENDALI
Rekayasa Mesin, 2022 The application of artificial neural network (ANN) models in magnet-rheological damper modeling is of great interest in recently challenges. Therefore, this study aims to propose a solution to overcome this problem by conducting inverse modeling using an
Rafly Asprilla Alwi +4 more
doaj +1 more source
A wavelet neural network approach to predict daily river discharge using meteorological data
Measurement + Control, 2019 This paper reports some part of modelling and data analysis work carried out within the frame of a comprehensive project on the web-based development of watershed information system.
Ömer Gürsoy, Seref Naci Engin
doaj +1 more source
Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Electrophysiological approaches to informing therapeutic interventions with deep brain stimulation
npj Parkinson's DiseaseNeuromodulation therapy comprises a range of non-destructive and adjustable methods for modulating neural activity using electrical stimulations, chemical agents, or mechanical interventions.
Atefeh Asadi +5 more
doaj +1 more source
Sensors, 2022 Structural anomaly diagnosis, such as damage identification, is a continuously interesting issue. Artificial neural networks have an excellent ability to model complex structure dynamics.
Zhi-Gang Ruan, Zu-Guang Ying
doaj +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
Guiding AlphaFold to predict how Munc13‐1 opens Syntaxin‐1
FEBS Open Bio, EarlyView.The syntaxin‐1 Habc‐domain (orange), linker (pink) and SNARE motif (yellow) form a closed conformation that binds to Munc18‐1 (violet) and is opened by the Munc13‐1 MUN domain (cyan) to form the SNARE complex that triggers neurotransmitter release.
Madhurima Chattopadhyay +2 more
wiley +1 more source
Removing Unclassified Hand Tremor Motion from Computer Mouse Input with Neural Networks
International Journal of Interactive Multimedia and Artificial Intelligence, 2018 An artificial neural network based filter to remove unwanted tremor-induced motion in computer mouse input is presented and tested. A method to efficiently capture appropriate training data is shown to be important in the operation and training of the ...
Stephen Mack
doaj +1 more source
Artificial neural networks training acceleration through network science strategies [PDF]
, 2020 The development of deep learning has led to a dramatic increase in the number of applications of artificial intelligence. However, the training of deeper neural networks for stable and accurate models translates into artificial neural networks (ANNs ...
Liotta, Antonio +9 more
core +1 more source
Adenosine triphosphate as a modulator of protein interactions and stability
FEBS Open Bio, EarlyView.ATP is best known as the cell's energy currency, but it also shapes how proteins fold, interact, aggregate and form biomolecular condensates. This review explains the emerging physical principles behind these effects, including weak binding to charged protein regions, magnesium‐dependent behaviour and concentration‐dependent control of protein ...
Shuyuan Tan, Robin Curtis
wiley +1 more source