Results 191 to 200 of about 200,066 (302)

NF-MORL: a neuro-fuzzy multi-objective reinforcement learning framework for task scheduling in fog computing environments. [PDF]

Sci Rep
Yu X, Tang L, Mi J, Long L, Qin X, Li X, Mo Q.   +6 more
europepmc   +1 more source

Mapping the Innovation DNA of Agribusiness Firms: A Multi‐Method Analysis of Strategic Capabilities and Performance

Agribusiness, EarlyView.
ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary ...
Beatriz Corchuelo Martínez‐Azúa, Alvaro Dias   +1 more
wiley   +1 more source

Infrared and visible image fusion using GAN with fuzzy logic and Harris Hawks optimization. [PDF]

Sci Rep
Zarimeidani M, Amirabadi A, Amiri N, Ahanian I, Es'haghi S.   +4 more
europepmc   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Assessment of genetically modified cotton GHB614 × T304-40 × GHB119 × COT102 (application EFSA-GMO-ES-2017-147). [PDF]

EFSA J
EFSA Panel on Genetically Modified Organisms (GMO), Casacuberta J, Barro F, Braeuning A, de Maagd R, Epstein MM, Frenzel T, Gallois JL, Koning F, Messéan A, Moreno FJ, Nogué F, Savoini G, Schulman AH, Tebbe C, Veromann E, Ardizzone M, De Sanctis G, Dumont AF, Gennaro A, Gómez Ruiz JÁ, Goumperis T, Kagkli DM, Lenzi P, Camargo AM, Neri FM, Piffanelli P, Raffaello T.   +27 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Fuzzy based priority aware task scheduling optimization for mobile edge computing environments. [PDF]

Sci Rep
Lin P.
europepmc   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Event-triggered self-regulating integrated PID extreme optimization and fault-tolerant strategy for floating offshore platforms driven by TBG-EDF dual finite-time learning mechanism. [PDF]

PLoS One
Chao C, Liu Y, Wang Z.
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source