Results 111 to 120 of about 5,861,579 (291)

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

open access: yesAdvanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora   +4 more
wiley   +1 more source

Implementation with state dependent feasible sets and preferences: a renegotiation approach [PDF]

open access: yes, 2005
In this paper we present a model of implementation based on the idea that agents renegotiate unfeasible allocations. We characterize the maximal set of Social Choice Correspondences that can be implemented in Nash Equilibrium with a class of ...
Triossi, Matteo, Corchón, Luis C.
core   +1 more source

Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy

open access: yesAdvanced Engineering Materials, EarlyView.
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang   +6 more
wiley   +1 more source

"Role of Honesty in Full Implementation" [PDF]

open access: yes
This paper introduces a new concept of full implementation that takes into account agents' preferences for understanding how the process works. We assume that the agents have intrinsic preferences for honesty in the sense that they dislike the idea of ...
Hitoshi Matsushima
core   +2 more sources

Understanding Inclusion, Diversity, Equity, and Accessibility in a Distributed Data Network: Environmental Scan Within Health Data Research Network Canada

open access: yesInternational Journal of Population Data Science
Inclusion, Diversity, Equity, and Accessibility (IDEA) are critical in addressing systemic bias and advancing equitable data practices. Health Data Research Network Canada (HDRN Canada) initiated an environmental scan to understand IDEA activities ...
Amy Freier   +9 more
doaj   +1 more source

Investigating the Low‐Temperature Phase Stability of the Binary Ta–W System

open access: yesAdvanced Engineering Materials, EarlyView.
Atomistic simulations show that the binary Ta–W system forms ordered intermetallic phases, B2‐TaW and D03‐TaW3, as 0 K ground states. Configurational entropy, however, lowers the free energy of the disordered bcc solid solution, which becomes the stable phase above about 400 K.
Klemens Lechner   +7 more
wiley   +1 more source

Generating, evaluating, endorsing, and implementing malevolent creativity: a malevolent idea journey

open access: yesFrontiers in Psychology
Over the last years, malevolent creativity research has delved into creative ideas that intend to harm both on the smaller and larger scale (from creative bullying or deception to terrorism and warfare) in different settings (personal revenge ...
Corinna Perchtold-Stefan   +2 more
doaj   +1 more source

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad   +8 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

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