Sustainability in wood products: a new perspective for handling natural diversity

M Schubert, G Panzarasa, I Burgert - Chemical Reviews, 2022 - ACS Publications
Wood is a renewable resource with excellent qualities and the potential to become a key
element of a future bioeconomy. The increasing environmental awareness and drive to …

Detection of fungal infections in strawberry fruit by VNIR/SWIR hyperspectral imaging

A Siedliska, P Baranowski, M Zubik, W Mazurek… - Postharvest Biology and …, 2018 - Elsevier
Early stages of fungal infections in strawberry fruit are difficult to detect by the majority of
commonly used manual and automatic sorting methods In this study, hyperspectral imaging …

An ANN-based ensemble model for change point estimation in control charts

A Yeganeh, F Pourpanah, A Shadman - Applied Soft Computing, 2021 - Elsevier
Signaling in the control charts is usually followed by a substantial amount of delay, in which
precise identification of the time when a change has occurred in a process simplifies the …

Artificial neural network and partial least square regressions for rapid estimation of cellulose pulp dryness based on near infrared spectroscopic data

LR Costa, GHD Tonoli, FR Milagres, PRG Hein - Carbohydrate polymers, 2019 - Elsevier
The content of water in fiber suspension and affects pulp refining, bleaching and draining
operations. Cellulose pulp dryness estimate through near infrared (NIR) spectroscopy …

The role of drying schedule and conditioning in moisture uniformity in wood: A machine learning approach

S Rahimi, V Nasir, S Avramidis, F Sassani - Polymers, 2023 - mdpi.com
Monitoring the moisture content (MC) of wood and avoiding large MC variation is a crucial
task as a large moisture spread after drying significantly devalues the product, especially in …

Experimental analysis and prediction of strength of adhesive-bonded single-lap composite joints: Taguchi and artificial neural network approaches

H Rangaswamy, I Sogalad, S Basavarajappa… - SN Applied …, 2020 - Springer
Adhesive-bonded joints made up of composite materials offer complex structures with the
ease of joining similar or dissimilar materials. The failure behavior of adhesive-bonded joints …

Failure load prediction of adhesively bonded GFRP composite joints using artificial neural networks

B Birecikli, ÖA Karaman, SB Çelebi… - Journal of Mechanical …, 2020 - Springer
There are different process parameters of bonding joints in the literature. The main objective
of the paper was to investigate the effects of bonding angle, composite lay-up sequences …

Estimation of flexural tensile strength as a function of shear of timber structures

FN Arroyo, JF Borges, WMP Junior, HF Santos… - Forests, 2023 - mdpi.com
To avoid the intrinsic difficulties regarding the characterization of wood (ie, different
applications in different directions), various normative documents present the relationships …

Modeling the bending strength of MDF faced, polyurethane foam-cored sandwich panels using response surface methodology (RSM) and artificial neural network …

M Nazerian, F Naderi, A Partovinia, AN Papadopoulos… - Forests, 2021 - mdpi.com
The present study evaluates and compares predictions on the performance and the
approaches of the response surface methodology (RSM) and the artificial neural network …

Prediction of the Effect of CO2 Laser Cutting Conditions on Spruce Wood Cut Characteristics Using an Artificial Neural Network

I Ružiak, R Igaz, I Kubovský, M Gajtanska, A Jankech - Applied Sciences, 2022 - mdpi.com
In addition to traditional chip methods, performance lasers are often used in the field of wood
processing. When cutting wood with CO2 lasers, it is primarily the area of optimization of …