Results 101 to 110 of about 883,011 (303)

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

open access: yesAdvanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto   +8 more
wiley   +1 more source

Evolution of Decision Trees

open access: yes, 2001
This paper addresses the issue of the induction of orthogonal, oblique and mul­tivariate decision trees. Algorithms pro­posed by other researchers use heuristic, usually based on the information gain con­cept, to induce decision trees greedily. These algorithms are often tailored for a given tree type ( e.g orthogonal), not be­ing able to induce other ...
Llorà Fàbrega, Xavier   +1 more
openaire   +2 more sources

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

open access: yesAdvanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu   +5 more
wiley   +1 more source

Data Mining Decision Trees in Economy [PDF]

open access: yes
Data Mining represents the extraction previously unknown, and potentially useful information from data. Using Data Mining Decision Trees techniques our investigation tries to illustrate how to extract meaningful socio-economical knowledge from large data
Badulescu, Laviniu-Aurelian   +1 more
core   +1 more source

Recycling of Thermoplastics with Machine Learning: A Review

open access: yesAdvanced Functional Materials, EarlyView.
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque   +5 more
wiley   +1 more source

Hardware Acceleration of Sparse Oblique Decision Trees for Edge Computing

open access: yesElektronika ir Elektrotechnika, 2019
This paper presents a hardware accelerator for sparse decision trees intended for FPGA applications. To the best of authors’ knowledge, this is the first accelerator of this type. Beside the hardware accelerator itself, a novel algorithm for induction of
Predrag Teodorovic   +1 more
doaj   +1 more source

Alginate‐Sludge Derived Biochar‐Calcium Hydrogel for Phosphate Removal and Slow‐Release Fertilizer: A Sustainable and Multifunctional Solution

open access: yesAdvanced Functional Materials, EarlyView.
An alginate‐based biochar hydrogel (ABC‐hydrogel), derived from sewage sludge, is developed for simultaneous phosphate removal and agricultural reuse. It captures phosphorus from water and gradually releases it as fertilizer, enhancing lettuce growth.
Yu Zhang   +4 more
wiley   +1 more source

Unlock the Walnut: How a Pectin‐Rich Suture Tissue and Moisture‐Driven Crack Formation Induce Shell Splitting and Facilitate Seed Germination

open access: yesAdvanced Functional Materials, EarlyView.
Walnut seeds are enclosed in a remarkably strong shell made of sclerenchyma, separated by a pectin‐rich suture tissue. Different cell shapes and chemical composition of this tissue point to an opening mechanism, which is triggered by cyclic humidity changes.
Sebastian J. Antreich   +3 more
wiley   +1 more source

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