Results 91 to 100 of about 5,002,199 (254)

Sequencing Interval Situations and Related Games [PDF]

open access: yes
In this paper we consider one-machine sequencing situations with interval data. We present different possible scenarioes and extend classical results on well known rules and on sequencing games to the interval setting.cooperative games;interval data ...
Brânzei, R.   +3 more
core  

Controlling Grain Growth in Powder Bed Fusion of Yttria‐Stabilized Zirconia Using Femtosecond Lasers: Challenges and Methodological Insights

open access: yesAdvanced Engineering Materials, EarlyView.
Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn   +5 more
wiley   +1 more source

Coupling Machine Learning and Physically Based Hydrological Models for Reservoir-Based Streamflow Forecasting

open access: yesRemote Sensing
High-accuracy streamflow forecasting with long lead times can help promote the efficient utilization of water resources. However, the construction of cascade reservoirs has allowed the evolution of natural continuous rivers into multi-block rivers.
Benjun Jia, Wei Fang
doaj   +1 more source

Monotonicity Problems of Interval Solutions and the Dutta-Ray Solution for Convex Interval Games [PDF]

open access: yes
This paper examines several monotonicity properties of value-type interval solutions on the class of convex interval games and focuses on the Dutta-Ray (DR) solution for such games.
Brânzei, R., Tijs, S.H., Yanovskaya, E.
core  

Non-constructive interval simulation of dynamic systems [PDF]

open access: yes, 2012
In this report, inspired by non-constructive simulation developed in the qual-itative reasoning eld, we present a non-constructive interval simulation algorithm forthe simulation of dynamic systems.
Pang, Wei; id_orcid   +3 more
core  

Effects of Mg on Microstructure and Solidification of a Hypereutectic Zn–8 wt.%Al Alloy

open access: yesAdvanced Engineering Materials, EarlyView.
An appreciable set of results involving thermal data, microstructure, chemical composition, and microstructural growth laws is reported for ZnAlMg alloys. Such results demonstrate that ZnAlMg alloys have high potential for applications in automotive self‐lubricating components, batteries, and electrical systems.
Raí B. de Sousa   +6 more
wiley   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns   +67 more
wiley   +1 more source

A multivariate soil temperature interval forecasting method for precision regulation of plant growth environment

open access: yesFrontiers in Plant Science
Foliage plants have strict requirements for their growing environment, and timely and accurate soil temperature forecasts are crucial for their growth and health.
Hang Yin   +6 more
doaj   +1 more source

Coupling interval from slow to tachycardiac pacing decides sustained alternans pattern

open access: yes, 2001
We discovered that the coupling beat interval from a slow to a tachycardiac pacing period considerably affected the pattern of the beat-to-beat alternation of the tachycardia-induced sustained contractile alternans.
Waso Fujinaka   +9 more
core   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin   +14 more
wiley   +1 more source

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