Results 111 to 120 of about 14,401 (279)

Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter

open access: yesAdvanced Intelligent Discovery, EarlyView.
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon   +3 more
wiley   +1 more source

Heuristics Influence on Investment Decision Making at Pakistan Stock Exchange: Mediation of Digital Financial Literacy and Moderation of AI Adoption

open access: yesJournal of Accounting and Finance in Emerging Economies
Purpose: The objective of this inquiry is to evaluate the role of cognitive biases such as the availability heuristic, ostrich heuristic, gambler’s fallacy, herding heuristic played.
Akbar Saeed, Azam Anwar Khan
doaj   +1 more source

In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs

open access: yesAdvanced Intelligent Discovery, EarlyView.
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley   +1 more source

Subjective Moral Biases & Fallacies: Developing Scientifically & Practically Adequate Moral Analogues of Cognitive Heuristics & Biases [PDF]

open access: yes, 2019
In this dissertation, I construct scientifically and practically adequate moral analogs of cognitive heuristics and biases. Cognitive heuristics are reasoning “shortcuts” that are efficient but flawed.
Herman, Mark H.
core   +1 more source

Heuristics and Biases

open access: yes, 2021
Klaus Fiedler   +2 more
openaire   +1 more source

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

Cognition, heuristics, and biases behind environment-related behaviours

open access: yesThe Lancet Planetary Health, 2018
Silvia Riva   +2 more
doaj   +1 more source

A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

open access: yesAdvanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison   +4 more
wiley   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

open access: yesAdvanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source

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