Results 131 to 140 of about 273,096 (313)
Mesoporous Silica Nanoparticles in Biomedicine: Advances and Prospects
Mesoporous silica nanoparticles offer unique properties like high surface area, tunable pores, and functionalization. They excel in drug delivery, tissue engineering, and stimuli‐responsive therapies, enabling targeted and controlled treatments. With roles in cancer therapy and diagnostics, their clinical translation requires addressing challenges in ...
Miguel Manzano, María Vallet‐Regí
wiley +1 more source
Neural network-based analysis for radiative entropy induced rheological material
Attention here is focused to address the artificial neural networks study for magnetohydrodynamic flow of second grade material by stretched surface. Furthermore, employing advanced artificial neural networks based computational techniques such as multi ...
Tasawar Hayat +3 more
doaj +1 more source
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Basic problems and the bottleneck of current approaches for objective assessment of product sensuous quality (PSQ) are discussed. As a solution, a new approach, an expert system (ES) based on artificial neural networks (ANNs) is proposed, in which the ES
Su, Z, Su, D
core
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang +20 more
wiley +1 more source
Measuring efficiency with neural networks. An application to the public sector [PDF]
In this note we propose the artificial neural networks for measuring efficiency as a complementary tool to the common techniques of the efficiency literature. In the application to the public sector we find that the neural network allows to conclude more
Francisco J. Delgado
core
A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho +3 more
wiley +1 more source
Regime Switching and Artificial Neural Network Forecasting [PDF]
This paper provides an analysis of regime switching in volatility and out-of-sample forecasting of the Cyprus Stock Exchange using daily data for the period 1996-2002.
Robert Georgiades +3 more
core
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Application of a Modified Generalized Regression Neural Networks Algorithm in Economics and Finance
In this paper we propose an alternative and modified Generalized Regression Neural Networks Autoregressive model (GRNN-AR) in S&P 500 and FTSE 100 index returns, as also in Gross domestic product growth rate of Italy, USA and UK. We compare the forecasts
Giovanis, Eleftherios
core

