Results 61 to 70 of about 45,239 (216)

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

Learning-based predictive control for linear systems: a unitary approach

, 2018
A comprehensive approach addressing identification and control for learningbased Model Predictive Control (MPC) for linear systems is presented. The design technique yields a data-driven MPC law, based on a dataset collected from the working plant.
Fagiano, Lorenzo, Farina, Marcello, Scattolini, Riccardo, Terzi, Enrico   +3 more
core   +1 more source

Identification of Exhaled Volatile Organic Compounds Biomarkers for Lung Cancer Under Data‐Limited Conditions Using Data Augmentation and Multi‐View Feature Selection

Advanced Intelligent Discovery, EarlyView.
This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren, Bohao Liu, Zhiyuan Qu, Xue Jiang, Heng Zhao, Danyao Qu, Ruizhi Ning, Chen Su, Taoping Liu, Guangjian Zhang, Weiwei Wu   +10 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

Non-Turing computations via Malament-Hogarth space-times [PDF]

, 2001
We investigate the Church-Kalm\'ar-Kreisel-Turing Theses concerning theoretical (necessary) limitations of future computers and of deductive sciences, in view of recent results of classical general relativity theory. We argue that (i) there are several
Etesi, Gabor, Nemeti, Istvan
core   +4 more sources

Evolution of superbubbles in a self-gravitating disk

, 2012
The expansion of a superbubble is investigated both analytically and numerically. Our model implements the thin layer approximation in a vertical profile of density as given by an isothermal self-gravitating disk. A precise comparison with the results of
Baek, Bell, Bell, Bertin, Bisnovatyi-Kogan, Butt, Chu, De Young, Dickey, Dyson, English, Fermi, Fermi, Ferrand, Goldstein, Higdon, Higdon, Hill, Hjellming, Jaskot, Kim, Kompaneets, Koo, L. Zaninetti, Lang, Lewin, Lockman, Longair, Lozinskaya, Mac Low, Mac Low, Maddox, McCray, McCray, Melioli, Ntormousi, Oey, Olano, Olver, Opsenica, Padmanabhan, Padmanabhan, Press, Rafikov, Rodríguez-González, Rohlfs, Rybicki, Smith, Spitzer, Tomisaka, Tomisaka, Wouterloot, Zaninetti, Zaninetti, Zaninetti, Zaninetti, Zaninetti   +56 more
core   +1 more source

Machine Learning‐Driven Digital Twin of a Field‐Effect Transistor‐Based Hormone Biosensor for Real‐Time Estradiol Monitoring

Advanced Intelligent Systems, EarlyView.
A machine learning‐driven digital twin simulates an aptamer‐functionalized BioFET measuring 17β‐estradiol. Real‐time Isd signals are processed, features are extracted, and trained models estimate hormone concentration. In parallel, a one‐step‐ahead forward model learns biosensor dynamics and generates realistic synthetic signals, enabling in silico ...
Anastasiia Gorelova, Alexandra Parichenko, Shirong Huang, Santiago Melia, Gianaurelio Cuniberti   +4 more
wiley   +1 more source

Data‐Driven Review and Machine Learning Prediction of Diamond Vacancy Center Synthesis

Advanced Intelligent Systems, EarlyView.
A machine learning framework is applied to photoluminescence spectra to extract linewidths and uncover how NV, SiV, GeV, and SnV centers evolve with growth and processing conditions. Unified normalization and k‐fold validation reveal cross‐method trends and enable rapid prediction of defect size and fabrication parameters, offering a data‐driven route ...
Zhi Jiang, Marco Peres, Carlo Bradac, Gil Gonçalves   +3 more
wiley   +1 more source

Representation-free description of light-pulse atom interferometry including non-inertial effects

, 2015
Light-pulse atom interferometers rely on the wave nature of matter and its manipulation with coherent laser pulses. They are used for precise gravimetry and inertial sensing as well as for accurate measurements of fundamental constants.
Kajari, Endre, Kleinert, Stephan, Roura, Albert, Schleich, Wolfgang P.   +3 more
core   +1 more source