A hybrid scatter search. Electromagnetism meta-heuristic for project scheduling. [PDF]
In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the ...
Debels, D +3 more
core
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang +9 more
wiley +1 more source
A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung +10 more
wiley +1 more source
Testing the Generalizability of the Priority Heuristic to Two-Stage Decision Making Tasks: A Comparison to Quantum Cognition and Prospect Theory. [PDF]
Fisher CR, Larue O, Schmidt K.
europepmc +1 more source
A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti +6 more
wiley +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
Path programmability recovery under multiple controller failures in Software-Defined WAN
The path programmability recovery mechanism is an effective strategy for ensuring the quality of service under controller failure in a Software-Defined Wide Area Network (SD-WAN).To address the problem of improving the recovery capability of offline ...
WANG Kun +5 more
doaj
Energy-aware priority-based task scheduling in cloud data centers using bacterial foraging optimization. [PDF]
Hosseinlou F +3 more
europepmc +1 more source
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou +5 more
wiley +1 more source
Dual-Loop Resilient Scheduling with Predictive Path Reconfiguration for Deterministic Industrial Wireless Networks. [PDF]
Huang KF.
europepmc +1 more source

