Results 111 to 120 of about 6,614,549 (286)

The Relationship Between Learning Environment Perception, Achievement Goals, and the Undergraduate Deep Learning Approach: A Longitudinal Mediation Model

Journal of Intelligence
This study examines the relationship between undergraduates’ learning environment perception, achievement goals, and the deep learning approach in a research-oriented Chinese university with a longitudinal mediation model.
Tingzhi Han, Guoxing Xu
doaj   +1 more source

Increasingly cautious sampling, not the black colouration of unpalatable prey, is used by fish in avoidance learning. [PDF]

Anim Cogn, 2023
Kaczmarski M, Kaczmarek JM, Kowalski K, Borowski K, Kęsy J, Kloskowski J.   +5 more
europepmc   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

An Integrated Strategy for Intelligent Evasion and Navigation of Unmanned Aerial Vehicles in Multi-Obstacle Environments

Aerospace
To enhance the navigation accuracy and obstacle avoidance capability of Unmanned Aerial Vehicles (UAVs) operating in dynamic multi-obstacle environments, this paper proposes an intelligent navigation and avoidance strategy based on deep reinforcement ...
Tianya Liu, Fengshuo Wang, Peng Li
doaj   +1 more source

Paternal Aggression in Early-life Impairs the Spatial Memory and Passive Avoidance Learning in Adulthood of Male Rats: The Possible Role of DRD2. [PDF]

Basic Clin Neurosci, 2023
Khalifeh S, Tirbakhsh Goura S, Asadi S, Asadi E, Maleki A, Khodagholi F, Zarrindast MR, Nasehi M, Kheradmand A.   +8 more
europepmc   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Different brain systems support learning from received and avoided pain during human pain-avoidance learning. [PDF]

Elife, 2022
Jepma M, Roy M, Ramlakhan K, van Velzen M, Dahan A.   +4 more
europepmc   +1 more source

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Optimized protocol for conditioned place avoidance learning in juvenile zebrafish. [PDF]

STAR Protoc, 2021
Palumbo F, Serneels B, Yaksi E.
europepmc   +1 more source

OntOMat: Toward Ontology‐Based Product and Process Design Engineering and Optimization Solutions Fueling Circular Value Chains

Advanced Engineering Materials, EarlyView.
The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ, Jörg Hohe, Martin Kördel, Michael Giese, Niklas Toffert, Christian Seidel, Olaf Rehme, Patrik Schneider, Oliver Focke, Elie Abi Aoun, Claas Falldorf, Beñat Gutierrez, Alexandra Kühn, Sven Torstrick-von der Lieth, Christoph Herden, Erik Johannsen, Jan‐Uwe R. Schmidt, Felix Winkelmann, Andreas Schott, Daniel Schott   +19 more
wiley   +1 more source