Results 191 to 200 of about 1,907,337 (239)

Fully Characterizing Lossy Catalytic Computation. [PDF]

Algorithmica
Folkertsma M, Mertz I, Speelman F, Tupker Q.   +3 more
europepmc   +1 more source

Dynamic Behavioral Profiling for User Authentication Using Binary Pressure Sequences and Grip Patterns via a Soft Stacking Ensemble

Advanced Intelligent Systems, EarlyView.
A smartphone‐embedded fabric‐strip sensing interface captures side‐pressure sequences and grip‐position patterns for behavioral authentication. Probability‐based soft stacking integrates class‐wise predictive probabilities from multiple learners to improve verification‐style discrimination, supporting a sensor‐integrated mobile‐security framework that ...
Wonki Hong
wiley   +1 more source

Accelerated Multisecret Sharing Scheme Using Fast Matrix Spectral Factorization. [PDF]

Entropy (Basel)
Çalkavur S, Solé P, Ephremidze L.
europepmc   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source

Elevation-dependent classification of outdoor thermal stress in a tropical Andean country: a case study of Colombia. [PDF]

Int J Biometeorol
Mejía-Parada C, Mora-Ruiz V, Otero-Meneses L, Mieles H, Soto-Paz J, Parra-Orobio BA.   +5 more
europepmc   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Polynomial Perceptrons for Compact, Robust, and Interpretable Machine Learning Models. [PDF]

Entropy (Basel)
Aldana-Bobadilla E, Molina-Villegas A, Cesar-Hernandez J, Garza-Fabre M.   +3 more
europepmc   +1 more source

Revealing Hidden Raman Signatures Through Attention‐Based Spectral Unmixing

Advanced Intelligent Systems, EarlyView.
Weak Raman signatures are recovered from background‐dominated spectra using a transformer‐based, reference‐free spectral unmixing AI framework. Self‐attention reconstructs substrate contribution directly from mixed data, enabling reliable extraction of previously inaccessible vibrational features.
Dmitriy A. Poteryayev, Pietro Novelli, Annalisa Coriolano, Riccardo Dettori, Valentina Tozzini, Fabio Beltram, Massimiliano Pontil, Antonio Rossi, Stiven Forti, Camilla Coletti   +9 more
wiley   +1 more source

Machine learning-driven adaptive parameter selection for homomorphic encryption in edge computing. [PDF]

Sci Rep
Bouabidi HE, Ghmary ME, Hebabaze SE, Amnai M.   +3 more
europepmc   +1 more source

A Multidimensional Perspective on Network Conditions in Telesurgery

Advanced Intelligent Systems, EarlyView.
A multidimensional framework systematically evaluates how combined network impairments influence telesurgical performance. By jointly analyzing latency, jitter, bandwidth, and packet loss, the proposed methodology identifies relevant network condition parameters and their interactions, supporting the design of reliable and safe telesurgical systems ...
Florian Heemeyer, Marco Cina, Ege Cem Kirci, Laurent Vanbever, Quentin Boehler   +4 more
wiley   +1 more source