Results 211 to 220 of about 237,731 (274)
Six artificial intelligence strategies advance autism research from tool optimization to paradigm shift: causal modeling, spatiotemporal networks, multimodal integration, digital twins, social cognition mapping, collaborative learning, and context‐aware interventions for precision care.
Ting Zhang +3 more
wiley +1 more source
Super-resolution reconstruction of industrial PET images using a prior-knowledge-based generative adversarial network. [PDF]
Zhu M, Zhao M, Yao M.
europepmc +1 more source
Advancing Extracellular Vesicle Research: A Review of Systems Biology and Multiomics Perspectives
ABSTRACT Extracellular vesicles (EVs) are membrane‐bound vesicles secreted by various cell types into the extracellular space and play a role in intercellular communication. Their molecular cargo varies depending on the cell of origin and its functional state.
Gloria Kemunto +2 more
wiley +1 more source
The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley +1 more source
Remaining Useful Life Prediction for Bearings Across Domains via a Subdomain Adaptation Network Driven by Spectral Clustering. [PDF]
Xu Z +4 more
europepmc +1 more source
Accreditation Against Limited Adversarial Noise
An upgraded accreditation (a variant of quantum verification) scheme is presented, significantly relaxing the assumptions, to allow adversarial noise, while preserving the suitability for near‐term / immediate usage. Abstract An accreditation protocol (a variety of quantum verification) is presented, where error is assumed to be adversarial (in ...
Andrew Jackson
wiley +1 more source
Hybrid framework for image forgery detection and robustness against adversarial attacks using vision transformer and SVM. [PDF]
Abdelmaksoud M +3 more
europepmc +1 more source
Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures
ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño +6 more
wiley +1 more source
OntoSecAI: Ontology-driven security automation for AI-enabled systems. [PDF]
Ullah U, Haleem M, Ullah A.
europepmc +1 more source
ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong +13 more
wiley +1 more source

