Results 141 to 150 of about 1,648,241 (310)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

A voyage to Mars: A challenge to collaboration between man and machines [PDF]

A speech addressing the design of man machine systems for exploration of space beyond Earth orbit from the human factors perspective is presented.
Statler, Irving C.
core   +1 more source

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Advanced Intelligent Discovery, EarlyView.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki, Bassam Bachour Junior, Marcelo Mulato, José Ilton de Oliveira Filho   +3 more
wiley   +1 more source

Conceptualising quality early childhood education: Learning from young children in Brazil and South Africa through creative and play‐based methods

British Educational Research Journal, EarlyView., 2023
Abstract Early childhood has increasingly been acknowledged as a vital time for all children. Inclusive and quality education is part of the United Nations Sustainable Development Goals, with the further specification that all children have access to quality pre‐primary education.
Laura H. V. Wright, Irene Rizzini, Malibongwe Gwele, Lynn McNair, Cristina Laclette Porto, Marsha Orgill, E. Kay M. Tisdall, Malcolm Bush, Linda Biersteker   +8 more
wiley   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

V/STOL lift fan commercial short haul transports: Continuing conceptual design study [PDF]

A design study of commercial V/STOL transport airplanes for a 1985 operational time period has been made. The baseline mission considered was 400 nmi at a cruise speed of M = 0.75 and a 100-passenger payload with VTOL.
Bohn, J. G., Derbyshire, T., Mcbarron, J. P., Middlebrooks, J. E., Miller, C. W., Minkler, W. F., Williams, B., Zabinsky, J. M.   +7 more
core   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

How the next billion users are challenging global tech assessment: Interview by Julia Hahn

TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis, 2022
Julia Hahn, Arora Payal
doaj   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

QUICK-GEOMETRY, a rapid response method for mathematically modeling configuration geometry [PDF]

The philosophy, development, and various applications of the QUICK-GEOMETRY system were outlined. This system provides a practical method for developing the geometry models that are essential to the operation of computer-based design and manufacturing ...
Vachris, A. F., Jr., Yaeger, L. S.
core   +1 more source