A Training-Free Foreground-Background Separation-Based Wire Extraction Method for Large-Format Transmission Line Images. [PDF]
Liu N +6 more
europepmc +1 more source
A Guide to Bayesian Optimization in Bioprocess Engineering
ABSTRACT Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small data sets, and provide adaptive suggestions for sequential experimentation.
Maximilian Siska +5 more
wiley +1 more source
Impact of rain on transmission lines’ ampacity: Scotland as a case study [PDF]
Abdael Baset, Abdallah +2 more
core +1 more source
Joint Coherent/Non-Coherent Detection for Distributed Massive MIMO: Enabling Cooperation Under Mixed Channel State Information. [PDF]
Gunasekara S +3 more
europepmc +1 more source
ABSTRACT The critical role of small and medium‐sized enterprises (SMEs) in driving economic growth through employment generation and innovation cannot go unseen, especially the efforts of small firms in promoting sustainable entrepreneurship. With more market and consumer focus on sustainability and the shift toward eco‐friendly products, SMEs can ...
Nasser Hadi Alajmi
wiley +1 more source
Partitioned cache architectures for reduced NBTI-induced aging [PDF]
Calimera, Andrea +3 more
core +1 more source
Maximum Shoulder Torque and Muscle Activation During Standing Arm Flexion: Reference Data for Biomechanical and Ergonomic Applications. [PDF]
Aronis G +5 more
europepmc +1 more source
Solvent washing of coffee‐ground hydrochars produces activated carbons with tunable pore sizes while maintaining surface area. Removing non‐polar contaminants enhances microporosity, increasing CO2 uptake by 40%. Moderate pore sizes (9–12 Å) yield optimal CO2:N2 selectivity, whereas smaller pores reduce selectivity due to stronger interactions between ...
Muhammad Irfan Maulana Kusdhany +4 more
wiley +1 more source
Distributed Multi-Agent Deep Reinforcement Learning-Based Transmit Power Control in Cellular Networks. [PDF]
Kim H, So J.
europepmc +1 more source
Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches
Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Bidhan Chandra Garain +3 more
wiley +1 more source

