Results 71 to 80 of about 35,631 (308)

Intrinsic Photoactive Star ZnPc–Poly(glutamate) Nanoplatforms for Multimodal Glioblastoma Therapy and Brain‐Targeted Delivery

Advanced Functional Materials, EarlyView.
An intrinsic photoactive star‐shaped zinc phtalocyanine‐poly(L‐glutamic acid) (ZnPc‐PGA) nanoplatform for multimodal glioblastoma (GBM) therapy and brain‐targeted elivery. A ZnPc‐PGA‐based multifunctional theranostic nanocarrier platform enables image‐guided, multimodal GBM therapy. ZnPc‐PGA nanocarriers support the integration of fluorescence imaging,
Amina Benaicha‐Fernández, Teodora Ranđelović, Ana Armiñán, Víctor Sebastián, Manuel Fuentes, Cristián Huck‐Iriart, Esther Masiá, Paula Carrascosa‐Marco, Pablo Juanes‐Velasco, Snežana Đorđević, Clara Bayona, Ignacio Ochoa, Maria Medel, Inmaculada Conejos‐Sánchez, María J. Vicent   +14 more
wiley   +1 more source

Neural Network Models for Predicting Magnetization Surface Switched Reluctance Motor: Classical, Radial Basis Function, and Physics-Informed Techniques

IEEE Access
Neural networks have increasingly been utilized in electric drive systems to enhance modeling, control, and optimization. These data-driven techniques enable accurate predictions of complex nonlinear behaviors, including the magnetization characteristics
Galina Demidova, Jackson J. Justo, Dmitry Lukichev, Nikolai Poliakov, Alecksey Anuchin   +4 more
doaj   +1 more source

Combined genetic algorithm optimization and regularized orthogonal least squares learning for radial basis function networks

, 1999
The paper presents a two-level learning method for radial basis function (RBF) networks. A regularized orthogonal least squares (ROLS) algorithm is employed at the lower level to construct RBF networks while the two key learning parameters, the ...
Luk, B.L., Wu, Y., Chen, S.
core  

Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks [PDF]

, 2001
. Radial Basis Neural (RBN) network has the power of the universal approximation function and the convergence of those networks is very fast compared to multilayer feedforward neural networks.
Leal, Andrés, Molina López, José Manuel, Galván, Inés M., Molina, José M., Valls, José M., Leal, A.   +5 more
core  

Resolving the Cu(bdc) Conundrum: Identifying Non‐Porous Packing of Prototypical Coordination‐Network Thin Films Combining Advanced Diffraction Techniques and Computational Modelling

Advanced Functional Materials, EarlyView.
Solution‐processed Cu(bdc) forms prototypical MOF thin films for which a multitude of not fully satisfactory structural models have been suggested. Combining rotating grazing‐incidence diffraction and X‐ray reflectivity on two complementary samples with density‐functional theory, we first discard the previously suggested models and then identify a non ...
Narges Taghizade, Mario Fratschko, Robbin Steentjes, Mercedes Linares‐Moreau, Paolo Falcaro, Christof Wöll, Roland Resel, Egbert Zojer   +7 more
wiley   +1 more source

Modeling Marine Electromagnetic Survey with Radial Basis Function Networks

Journal of ICT Research and Applications, 2014
A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record ...
Agus Arif, Vijanth S. Asirvadam, M.N. Karsiti   +2 more
doaj  

Noise Reduction Technique for Images using Radial Basis Function Neural Networks [PDF]

Mehran University Research Journal of Engineering and Technology, 2014
This paper presents a NN (Neural Network) based model for reducing the noise from images. This is a RBF (Radial Basis Function) network which is used to reduce the effect of noise and blurring from the captured images. The proposed network calculates the
Sander Ali Khowaja, Syed Zafi Sherhan Shah, Muhammad Usman Memon   +2 more
doaj  

Designed Lewis Acid–Base Passivation for High Performance Perovskite Solar Cells

Advanced Functional Materials, EarlyView.
ABSTRACT Silicon's high cost and long energy payback time remain major barriers to the global expansion of solar power. In contrast, metal–halide perovskites offer abundant, solution‐processable absorbers, and have achieved efficiencies of 25%–30%, positioning them as strong competitors to silicon.
Afna Manaf, Hiba Shahulhameed, Bhabani Sankar Swain, Shengzhong (Frank) Liu, Adel Najar   +4 more
wiley   +1 more source

On Comparison between Radial Basis Function and Wavelet Basis Functions Neural Networks

Ibn Al-Haitham Journal for Pure and Applied Sciences, 2017
      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space.
L.N.M. Tawfiq, T.A.M. Rashid
doaj  

The use of radial basis function and non-linear autoregressive exogenous neural networks to forecast multi-step ahead of time flood water level

IJAIN (International Journal of Advances in Intelligent Informatics), 2019
Many different Artificial Neural Networks (ANN) models of flood have been developed for forecast updating. However, the model performance, and error prediction in which forecast outputs are adjusted directly based on models calibrated to the time series ...
Amrul Faruq, Shahrum Shah Abdullah, Aminaton Marto, Mohd Anuar Abu Bakar, Shamsul Faisal Mohd Hussein, Che Munira Che Razali   +5 more
doaj   +1 more source