Results 151 to 160 of about 114,074 (272)

Developing Sustainable Innovations for Planet, Profits—And People: Mixed‐Methods Insights From the Textile Industry

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Sustainable innovations are increasingly recognized as promising avenues for businesses to tackle global sustainability challenges, expected to deliver ecological, social, and economic benefits. Yet social outcomes at the individual level remain underexplored, raising questions about whether such innovations fully realize their sustainability ...
Lisa Hollands, Celine Bökemeyer, Luca Haensse, Nick Lin‐Hi   +3 more
wiley   +1 more source

Probability prediction of true‐triaxial compressive strength of intact rocks based on the improved PSO‐RVM model

Deep Underground Science and Engineering, EarlyView.
In this work, we propose an improved particle swarm optimization (PSO) algorithm and develop an improved PSO‐relevance vector machine (RVM) model as a substitute for traditional true‐triaxial testing. The model's high prediction accuracy was validated through comparisons with two other machine learning methods and five three‐dimensional Hoek–Brown type
Qi Zhang, Maohui Wang, Ning Wang, Yixin Shen, Xuzhen He   +4 more
wiley   +1 more source

Integrated single marker scanning and sparse Bayesian learning improves performance of detection for GWAS. [PDF]

Plant Methods
Zhang J, Wu Z, Cai M, Liu K, Han X, Liu C, Han G, Wen Y.   +7 more
europepmc   +1 more source

Robust Sparse Bayesian Learning-Based Off-Grid DOA Estimation Method for Vehicle Localization. [PDF]

Sensors (Basel), 2020
Ling Y, Gao H, Zhou S, Yang L, Ren F.
europepmc   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Hierarchical sparse Bayesian learning with adaptive Laplacian prior for single image super-resolution. [PDF]

Sci Rep
Qi M, Zhou Y, Hu Y, Xie C, Xu S.
europepmc   +1 more source

Harnessing the power of machine and deep learning for transferring joint species distribution models considering the structure of biotic interactions

Ecography, EarlyView.
The transferability of single or joint species distribution models ((j)SDMs) depends on their ability to predict beyond the observed environmental range and to remain consistent despite shifts in biotic interactions. Transfer accuracy may be improved by recent advances in the application of deep learning that provide greater flexibility and potentially
Marco Basile, Maximilian Pichler, Francesco Valerio, Lorenzo Balducci, Francesco Chianucci, Sérgio Godinho, Francesco Rota, Frédéric Archaux, Christophe Bouget, Gediminas Brazaitis, Thomas Campagnaro, Ettore D'Andrea, Luc De Keersmaeker, Wouter Dekoninck, Pallieter De Smedt, Zoltán Elek, Itziar García‐ Mijangos, Frédéric Gosselin, Marion Gosselin, Andrin Gross, Elena Haeler, Sebastian Kepfer‐ Rojas, Nathalie Korboulewsky, Daniel Kozák, Thibault Lachat, Carlos Miguel Landivar Albis, Anja Leyman, Xiang Liu, Anders Mårell, Radim Matula, Martin Mikoláš, Péter Ódor, Yoan Paillet, Kastytis Šimkevičius, Tommaso Sitzia, Silvia Stofer, Nicolas Strebel, Miroslav Svoboda, Flóra Tinya, Mariana Ujházyová, Kris Vandekerkhove, Kris Verheyen, Michael Wohlwend, Fotios Xystrakis, Sabina Burrascano   +44 more
wiley   +1 more source

Physiological swelling imaging in human calf under stocking compression by sparse Bayesian learning implemented into electrical impedance tomography (SBL-EIT). [PDF]

Biomed Eng Lett
Asano K, Ogawa R, Sejati PA, Akita S, Takei M.   +4 more
europepmc   +1 more source

Toward a Paradigm Shift in Low‐Temperature SCR Catalyst Design: Defect Engineering and Data‐Driven Integration

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This work systematically reviews the key factors influencing the performance of low‐temperature NH3‐SCR. The mechanism and challenges of defect engineering strategies, such as oxygen vacancies, heteroatom doping, crystal facet exposure, and surface reconstruction, in controlling both activity and selectivity were analyzed.
Rongrong Kan, Pinjing He, Fan Lü, Hua Zhang   +3 more
wiley   +1 more source

Off-Grid Sparse Bayesian Learning for Channel Estimation and Localization in RIS-Assisted MIMO-OFDM Under NLoS. [PDF]

Sensors (Basel)
Mutlu U, Kabalci Y.
europepmc   +1 more source