Results 251 to 260 of about 4,311,294 (371)

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

VN-EGNN: E(3)- and SE(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification. [PDF]

J Cheminform
Sestak F, Schneckenreiter L, Brandstetter J, Hochreiter S, Mayr A, Klambauer G.   +5 more
europepmc   +1 more source

Piezoelectric Origami Metamaterials for Enhanced Handwriting Recognition and Trajectory Tracking

Advanced Intelligent Discovery, EarlyView.
This study introduces origami metamaterials inspired by Kresling piezoelectric generators to enhance biometric authentication and handwriting trajectory recognition. Overcoming sensor limitations in conventional devices, the design enables multichannel data acquisition with fewer sensors, utilizing machine learning to accurately identify content ...
Yinzhi Jin, Ting Tan, Zhimiao Yan
wiley   +1 more source

The use of fully immersive virtual reality for screening neurodegenerative diseases: A systematic review of behavioral and diagnostic outcomes. [PDF]

Alzheimers Dement (Amst)
Liu Z, Soria D, Lai DJ, Zhang J, Shergill S, Ang CS.   +5 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Optimized CatBoost machine learning (OCML) for DDoS detection in cloud virtual machines with time-series and adversarial robustness. [PDF]

Sci Rep
Samy H, Bahaa-Eldin AM, Sobh MA, Taha A.
europepmc   +1 more source

Transient power stabiliser for a virtual synchronous machine control in doubly-fed induction generators

Jesús Castro Martínez, Francisco González-Longatt, Santiago Arnaltes, José Luis Rodríguez-Amenedo   +3 more
openalex   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Kademlia hash snow ablation resource optimized stride scheduling for mobile computing services in healthcare sector. [PDF]

Sci Rep
Sivakumar NR.
europepmc   +1 more source

Glowworm Swarm Optimisation Algorithm for Virtual Machine Placement in Cloud Computing

, 2016
Dabiah Alboaneen, Huaglory Tianfield, Yan Zhang   +2 more
openalex   +2 more sources