Results 61 to 70 of about 723,870 (293)

Magnetoactive Metamaterials: A State‐of‐the‐Art Review

Advanced Engineering Materials, EarlyView.
Magnetoactive metamaterials combine magnetoactive composites with architected metastructures to enable contactless, tunable control of mechanical, acoustic, and elastic properties. This review highlights recent advances in their design, fabrication, and applications in soft robotics, biomedical devices, and adaptive structures and outlines future ...
Seyyedmohammad Aghamiri, Ramin Sedaghati
wiley   +1 more source

A case of in-streaming-learning: how to program with Z-tree software to design experiments on economic decision making

Eduser, 2019
In this paper, we present a real in-streaming case of learning about how to program with the z-tree software to design experiments on economic decision making for the members of the NECE Research Unit in Business Sciences, in Portugal.This
Nuria Hernández-León, Ricardo Rodrigues, Mario Diogo   +2 more
doaj   +1 more source

Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery

Advanced Functional Materials, EarlyView.
This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer, Min Jiang, Adrian Kromer, Anny Nguyen, Müge Molbay, Simone Pinto Carneiro, David Jürgens, Gerald Burgstaller, Bastian Popper, Benjamin Winkeljann, Olivia Monika Merkel   +10 more
wiley   +1 more source

Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning [PDF]

, 2014
A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and
Kurbatsky, Victor, Leahy, Paul, Sidorov, Denis, Spiryaev, Vadim, Tomin, Nikita, Zhukov, Alexei   +5 more
core   +2 more sources

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset

Energies, 2018
Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using a Raspberry Pi computer with camera.
Ariana Moncada, Walter Richardson, Rolando Vega-Avila   +2 more
doaj   +1 more source

Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-Agent Trajectories

, 2018
With the explosion in the availability of spatio-temporal tracking data in modern sports, there is an enormous opportunity to better analyse, learn and predict important events in adversarial group environments.
Denman, Simon, Fernando, Tharindu, Fookes, Clinton, Sridharan, Sridha   +3 more
core   +1 more source

Bimetallic Nanoparticles as Cocatalysts for Photocatalytic Hydrogen Production

Advanced Functional Materials, EarlyView.
Recent developments have introduced bimetallic nanoparticles as effective cocatalysts for photocatalytic systems. This review explores the rapidly expanding research on bimetallic cocatalysts for photocatalytic production of hydrogen, emphasizing the creation of carrier‐selective contacts, localized surface plasmon resonance effects, methodologies for ...
Yufen Chen, Asier Agrelo‐Lestón, Ignasi Burgués‐Ceballos, Jordi Llorca, Lluís Soler   +4 more
wiley   +1 more source

Аргументи „за” и „против” държавната намеса в аграрния сектор

Икономика и управление на селското стопанство, 2012
Целта на настоящата статия е да представи някои от основните аргументи в подкрепа или против субсидирането на аграрния сектор. Анализът ще изложи накратко ролята на държавното подпомагане за земеделието според икономическата теория.
СТАНИМИР АНДОНОВ
doaj  

Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization

, 2019
One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability. In this work, a practicable approach of gaining explainability of deep artificial neural networks (NN) using an ...
Huber, Marco F., Maucher, Johannes, Schaaf, Nina   +2 more
core   +1 more source