Results 101 to 110 of about 10,758 (305)

Artificial Intelligence as the Next Visionary in Liquid Crystal Research

Advanced Functional Materials, EarlyView.
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam, Ouassim L'Karkouri, Danqing Liu   +2 more
wiley   +1 more source

A model-based velocity controller for chaotization of flexible joint robot manipulators

International Journal of Advanced Robotic Systems, 2018
This article presents a model-based velocity controller able to induce a chaotic motion on n -degrees of freedom flexible joint robot manipulators. The proposed controller allows the velocity link vector of a robot manipulator to track an arbitrary ...
Roger Miranda-Colorado, Luis T Aguilar, J Moreno-Valenzuela   +2 more
doaj   +1 more source

Upper bounds on the error probabilities and asymptotic error exponents in quantum multiple state discrimination [PDF]

, 2014
Koenraad M. R. Audenaert, Milán Mosonyi
openalex   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Generalized Random Gilbert-Varshamov Codes: Typical Error Exponent and Concentration Properties [PDF]

, 2022
Lan V. Truong, Albert Guillén Fàbregas
openalex   +1 more source

From Bug to Feature: Harnessing Cross‐Sensitivity for Multiparametric Luminescence Sensing

Advanced Functional Materials, EarlyView.
Cross‐sensitivity in luminescence sensing is reframed from a limitation into a resource for multiparametric detection. Using ruby microspheres as a model system, cross‐sensitivity is quantitatively assessed and exploited through linear discriminant analysis, enabling simultaneous, correction‐free pressure and temperature sensing with a single ...
Nikita Panov, Liyan Ming, Stanislav Sinogeikin, Erving Ximendes, Daniel Jaque, Riccardo Marin   +5 more
wiley   +1 more source

Self‐Hybridized Exciton‐Polariton Photodetectors From Layered Metal‐Organic Chalcogenolates

Advanced Functional Materials, EarlyView.
Self‐hybridized exciton‐polariton photodetectors are demonstrated using high refractive index mithrene, eliminating the need for top mirrors. This simplified architecture enables tunable sub‐bandgap photodetection via lower exciton‐polariton states and enhanced carrier transport through ultrafast polariton group velocities.
Bongjun Choi, Adam D. Alfieri, Wangleong Chen, Deep Jariwala   +3 more
wiley   +1 more source

Asymptotic Behavior of Error Exponents in the Wideband Regime [PDF]

, 2005
Xiaobin Wu, R. Srikant
openalex   +1 more source

Adaptive Hydrogels With Spatiotemporal Stiffening Using pH‐Modulating Enzymes

Advanced Functional Materials, EarlyView.
The chemomechanical coupling in an adaptive hydrogel is studied to further the development of adaptive hydrogels. This coupling is achieved by embedding a pH‐modulating enzyme in a pH‐responsive hydrogel. The enzymatic reaction can be triggered locally, which generates a pH‐decreasing wave throughout the system, increasing the crosslinking density and ...
Natascha Gray, Zoe Grämiger, André R. Studart, Rafael Libanori   +3 more
wiley   +1 more source

How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression

Applied Sciences
This study uses Artificial Neural Networks (ANNs) and multiple linear regression (MLR) models to explore the relationship between gait dynamics and the metabolic cost.
Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield   +2 more
doaj   +1 more source