Results 101 to 110 of about 153,055 (297)

Technological Turbulence, Circular Economy Practices, and Digitalization as Determinants of Innovative Culture in High‐Growth Firms

Business Strategy and the Environment, EarlyView.
ABSTRACT In a business environment characterized by technological turbulence and an increasing societal demand for greater sustainability, companies seeking to enhance their growth are compelled to foster organizational cultures that promote continuous innovation.
José Bocoya‐Maline, Salustiano Martínez‐Fierro, José Aurelio Medina‐Garrido   +2 more
wiley   +1 more source

Innovation Pathways to Carbon Efficiency: Disentangling the Effects of AI, R&D, and Clean Energy Blessings on U.S. Environmental Sustainability

Business Strategy and the Environment, EarlyView.
ABSTRACT The United States (U.S.) faces challenges in achieving its ambitious net‐zero carbon emissions target by 2050, with current emissions having fallen by less than 1% in 2024. Despite an investment of $500 billion in low‐carbon resources while holding the second‐largest green technology patent portfolio globally, it is further imperative to ...
Md Zubair Ahmad, Jewel Rana, Mohammad Fakhrul Islam, Md Nazmul Islam Jihad, Md. Rashed, Md. Kamal Uddin   +5 more
wiley   +1 more source

Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems [PDF]

, 2011
The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input ...
Alaa Abdulameer Hassan
core  

Hierarchic Kernel Recursive Least-Squares

, 2017
We present a new kernel-based algorithm for modeling evenly distributed multidimensional datasets that does not rely on input space sparsification. The presented method reorganizes the typical single-layer kernel-based model into a deep hierarchical structure, such that the weights of a kernel model over each dimension are modeled over its adjacent ...
Mohamadipanah, Hossein, Heydari, Mahdi, Chowdhary, Girish   +2 more
openaire   +2 more sources

Green Hydrogen for Public Transportation: Insights From an ABM and From Palma de Mallorca Case Study

Business Strategy and the Environment, EarlyView.
ABSTRACT The development of green hydrogen (GH2) value chains is crucial for decarbonizing sectors such as transport and industry. Their emergence, however, requires coordination among diverse actors, technologies, and regulations, which traditional analytical approaches struggle to capture.
Roberta De Cristofaro, Cristina Ponsiglione, Simonetta Primario   +2 more
wiley   +1 more source

Machine Learning‐Driven Prediction and Optimization of Cu‐Based Catalysts for CO2 Hydrogenation to Methanol

Carbon and Hydrogen, EarlyView.
A machine‐learning framework integrating multimodel prediction, feature selection, and SHAP interpretability is developed to uncover structure–performance relationships of Cu‐based CO2‐to‐methanol catalysts. The optimized XGBoost model and an online prediction platform enable accurate selectivity prediction and data‐driven catalyst design.
Conglong Su, Zhangkai Jing, Qiuming Zhou, Yuan Zhu, Sishi Ye, Tianye Wang, Kuo Chen, Xuebin Luan, Zhigang Tang, Run Xu, Chaopeng Hou, Hongwei Li   +11 more
wiley   +1 more source

A Robust Nonlinear Beamforming Assisted Receiver for BPSK Signalling

, 2005
Nonlinear beamforming designed for wireless communications is investigated. We derive the optimal nonlinear beamforming assisted receiver designed for binary phase shift keying (BPSK) signalling.
Chen, S., Hanzo, L., Wolfgang, A.
core  

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley   +1 more source

A novel construction approach for the pore structure model principally focuses on the controllable roundness of rock particles

Deep Underground Science and Engineering, EarlyView.
Particle rounding effects comparison of different methods: (a), (b), and (c) are the rounding results using the B‐spline curve method with different R; (d), (e), and (f) are the results of vertex rounding substitution method with different rounding radii.
Jiabin Dong, Ning Yang, Yi Jin, Ying Wu, Dandan Liu, Junling Zheng, Jingyan Zhao   +6 more
wiley   +1 more source