Results 111 to 120 of about 7,605,221 (315)

Mining Heterogeneous Multivariate Time-Series for Learning Meaningful Patterns: Application to Home Health Telecare

open access: yes, 2004
For the last years, time-series mining has become a challenging issue for researchers. An important application lies in most monitoring purposes, which require analyzing large sets of time-series for learning usual patterns.
Duchene, Florence   +2 more
core   +1 more source

Toward a Semiotic Framework for Using Technology in Mathematics Education: The Case of Learning 3D Geometry [PDF]

open access: yes, 2004
This paper proposes and examines a semiotic framework to inform the use of technology in mathematics education. Semiotics asserts that all cognition is irreducibly triadic, of the nature of a sign, fallible, and thoroughly immersed in a continuing ...
Nason, Rodney, Yeh, Andy
core   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

open access: yesAdvanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha   +18 more
wiley   +1 more source

Development of Learning Models Based on Problem Solving and Meaningful Learning Standards by Expert Validity for Animal Development Course

open access: yes, 2018
The purpose of this study is to produce a learning model based on problem solving and meaningful learning standards by expert assessment or validation for the course of Animal Development.
L. Lufri, R. Fitri, R. Yogica
semanticscholar   +1 more source

A technology training protocol for meeting QSEN goals: Focusing on meaningful learning

open access: yesNursing Forum, 2018
The purpose of this paper is to describe and discuss how we designed and developed a 12-step technology training protocol. The protocol is meant to improve meaningful learning in technology education so that nursing students are able to meet the ...
Shuhong Luo, M. Kalman
semanticscholar   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

open access: yesAdvanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu   +3 more
wiley   +1 more source

Joyful And Meaningful Learning In Mathematics Classroom Through Internet Activities

open access: yesSoutheast Asian Mathematics Education Journal, 2013
This paper arises from the author experiences over the last eight years with regards to investigating how the Internet could be used as a tool for mathematics learning, mathematics teaching as well as for professional development.
Sitti Maesuri Patahuddin
doaj   +1 more source

Meaningful learning: motivations of older adults in serious games. [PDF]

open access: yesUnivers Access Inf Soc, 2023
Cardona JS   +3 more
europepmc   +1 more source

Designing and integrating reusable learning objects for meaningful learning: Cases from a graduate programme

open access: yes, 2017
E-learning quality depends on sound pedagogical integration between the content resources and lesson activities within an e-learning system. This study proposes that a meaningful learning with technology framework can be used to guide the design and ...
J. Koh
semanticscholar   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

open access: yesAdvanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee   +17 more
wiley   +1 more source

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