The invention relates to a method for identifying workpieces, which preferably consist at least partly of wood, wood materials or the like, in a machining process, having the steps of: detecting at least one workpiece property prior to a machining step, uniquely assigning a workpiece category to the workpiece using the at least one detected workpiece property, and machining the workpiece in the machining step which is determined by the assigned workpiece category of the workpiece.

The invention relates to a method for identifying workpieces, which preferably consist at least partly of wood, wood materials or the like, in a machining process, having the steps of: detecting at least one workpiece property prior to a machining step, uniquely assigning a workpiece category to the workpiece using the at least one detected workpiece property, and machining the workpiece in the machining step which is determined by the assigned workpiece category of the workpiece.

A method for identifying a log of origin of a first board, comprising an identification step, during which a second board (12) is identified which was obtained from the same log (2) as the first board (11) was obtained from, a studying step, during which identifying features of the second board (12) are identified, and a recognition step during which the log (2) of origin of the first board (11) is recognised, among a plurality of known logs (2) about which saved information is available, and this is done by identifying the log of origin of the second board (12), using the identifying features of the second board (12) itself.

The technology disclosed relates to systems, methods, and devices for non-destructive evaluation (NDE) of a wooden specimen. A computer-implemented method for non-destructive evaluation of a wooden specimen comprises receiving acoustic wave signal data from NDE of the wooden specimen; processing the acoustic wave signal data to determine signal characteristics, such as an arrival velocity and amplitude attenuation of an AW2 mode; determining, based in part on a characteristic of the AW2 wave, an estimated strength metric of the wooden specimen; and displaying, on a graphical user interface associated with the computing device, an indication of the estimated strength metric of the wooden specimen.

The technology disclosed relates to systems, methods, and devices for non-destructive evaluation (NDE) of a wooden specimen. A computer-implemented method for non-destructive evaluation of a wooden specimen comprises receiving acoustic wave signal data from NDE of the wooden specimen; processing the acoustic wave signal data to determine signal characteristics, such as an arrival velocity and amplitude attenuation of an AW2 mode; determining, based in part on a characteristic of the AW2 wave, an estimated strength metric of the wooden specimen; and displaying, on a graphical user interface associated with the computing device, an indication of the estimated strength metric of the wooden specimen.

A filler material is applied to a plurality of wood elements. The plurality of wood elements is bonded into a composite wood product, where the bonding includes delivering ultrasound energy to the plurality of wood elements. The ultrasound energy has a frequency within a frequency range of 10 kHz-20 MHz.

A filler material is applied to a plurality of wood elements. The plurality of wood elements is bonded into a composite wood product, where the bonding includes delivering ultrasound energy to the plurality of wood elements. The ultrasound energy has a frequency within a frequency range of 10 kHz-20 MHz.

Computer implemented method for training a software infrastructure based on machine learning techniques and intended for analysis of data obtained from a three-dimensional tomographic inspection of objects of a predetermined type, such as logs, with the aim of determining information about internal characteristics of interest of the self-same objects, wherein, once a training set comprising a plurality of objects of the same predetermined type has been selected, for each object the software infrastructure is supplied with training input data and corresponding training output data, which are processed by the software infrastructure for setting internal processing parameters of the software infrastructure which correlate the training input data with the training output data; where the training input data comprise data obtained from a three-dimensional tomographic inspection of the object, and the training output data comprise information about internal characteristics of interest assessed at internal points of the object, and where the information about the internal characteristics of interest is at least partly assessed at real internal points of the object, previously made accessible by cutting or breaking the object.

A first ethylene-based interpolymer comprising, in polymerized form, monomer units derived from ethylene and from a benzocyclobutene (VBCB) structure of Structure 1; wherein n is from 3 to 10; and wherein the ethylene-based polymer comprises, in polymerized form, from 0.02 to 0.70 wt % of the Structure 1, based on the weight of the first ethylene-based interpolymer, as determined by .sup.1H NMR is provided. Further provided is a composition which comprises a second ethylene-based inter-polymer formed by thermally treating a first ethylene-based interpolymer.

Provided is a novel plant body comprising a plant tissue of a plant belonging to the family Solanaceae, Brassicaceae, Lamiaceae, or Orobanchaceae, wherein graft incompatibility is avoided or suppressed by using a graft medium between different-family plants.