Results 161 to 170 of about 117,918 (260)
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas +6 more
wiley +1 more source
An intelligent IoT-machine learning framework for wildfire detection and prediction using a hybrid RF-XGB model. [PDF]
Radhi AA, Ibrahim AA.
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
Prediction of unconfined compressive strength of fly ash and waste paper sludge stabilized clayey soil using explainable machine learning. [PDF]
Aggarwal V +9 more
europepmc +1 more source
Forest Engineering Department in Bologna Process
S A Kilpelyaynen, V M Kostukevich
openaire +1 more source
Adult Sex Ratio as a Demographic Feedback Linking Mating Systems, Parental Care, and Evolution
Breeding systems are some of the most diverse social behavior, and our team is investigation the evolutionary causes of this diversity. This review summarises our research carried out at the University of Bath. We argue that demographic components of wild populations, especially the adult sex ratio, plays a key role driving breeding system variation ...
Tamás Székely, Oscar G. Miranda
wiley +1 more source
New journal - Croatian Journal of Forest Engineering
Tibor Pentek
doaj
Enhanced diagnosis of diabetic retinopathy: integrating advanced algorithms for automated detection and classification. [PDF]
Murali E +4 more
europepmc +1 more source
THE TRAINING AND QUALIFICATIONS OF THE FOREST ENGINEER IN QUEBEC [PDF]
openaire +1 more source

