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Wood

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Deep learning-aided preparation and mechanism revaluation of waste wood lignocellulose-based flame-retardant composites.

International journal of biological macromolecules
Wood and its derivatives play a decisive role in traditional Chinese architecture. Waste wood as a major source of garbage in the construction industry represents a valuable source. The efficient recycling of waste wood has become an urgent technical...

Combating trade in illegal wood and forest products with machine learning.

PloS one
Trade in wood and forest products spans the global supply chain. Illegal logging and associated trade in forest products present a persistent threat to vulnerable ecosystems and communities. Illegal timber trade has been linked to violations of tax a...

Assessment of fuzzy logic to enhance species distribution modelling of two cryptic wood boring beetle species in Australia.

Scientific reports
Fuzzy logic presents a promising approach for Species Distribution Modelling by generating a value that can be used for comparative purposes termed 'environmental favourability'. In contrast to 'presence probability', 'environmental favourability' re...

Performance of convolutional neural network (CNN) and performance influencing factors for wood species classification of Lepidobalanus growing in Korea.

Scientific reports
This study aimed to investigate the performance and factors affecting the species classification of convolutional neural network (CNN) architecture using whole-part and earlywood-part cross-sectional datasets of six Korean Quercus species. The accura...

Random forest machine-learning algorithm classifies white- and brown-rot fungi according to the number of the genes encoding Carbohydrate-Active enZyme families.

Applied and environmental microbiology
UNLABELLED: Wood-rotting fungi play an important role in the global carbon cycle because they are the only known organisms that digest wood, the largest carbon stock in nature. In the present study, we used linear discriminant analysis and random for...

Higher heating value estimation of wastes and fuels from ultimate and proximate analysis by using artificial neural networks.

Waste management (New York, N.Y.)
Higher heating value (HHV) is one of the most important parameters in determining the quality of the fuels. In this study, comparatively large datasets of ultimate and proximate analysis are constructed to be used in HHV estimation of several classes...

Predictive modeling of copper (II) adsorption from aqueous solutions by sawdust: a comparative analysis of adaptive neuro-fuzzy interference system (ANFIS) and artificial neural network (ANN) approaches.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Heavy metal ions are considered to be the most prevalent and toxic water contaminants. The objective of thois work was to investigate the effectiveness of employing the adsorption technique in a laboratory-size reactor to remove copper (II) ions from...

Wood identification based on macroscopic images using deep and transfer learning approaches.

PeerJ
Identifying forest types is vital for evaluating the ecological, economic, and social benefits provided by forests, and for protecting, managing, and sustaining them. Although traditionally based on expert observation, recent developments have increa...

Assessment of the effects of the biotic and abiotic harmful factors on the amount of industrial wood production with deep learning.

Environmental science and pollution research international
The protection and sustainability of forest assets is possible with planned production of forest products to lead to minimum loss. One of the products obtained from forests is the industrial wood, which is the most important raw material for many sec...

Acoustic Denoising Using Artificial Intelligence for Wood-Boring Pests Larvae Early Monitoring.

Sensors (Basel, Switzerland)
Acoustic detection technology is a new method for early monitoring of wood-boring pests, and the effective denoising methods are the premise of acoustic detection in forests. This paper used sensors to record larval feeding sounds and various enviro...