Abstract: A lightweight construction element is disclosed comprising a first and a second flange member 10, 20 each having front face 13, 23 facing each other and back face 14, 24 non-facing each other. The first flange member and the second flange member 10, 20 are aligned alongside each other at a distance X. Further, the lightweight construction element comprises a plurality of web members 50, whereby, the length of the plate portion 51 of web members 50 defines the spacing between the first flange member 10 and the second flange member 20. The plurality of web members 50 are physically coupled to the first and second flange members 10, 20 by attaching to either the front surface 13, 23, or the back surface 14, 24 of each flange member 10, 20, and are bent at an angle ranging between 90-110 degrees to the plate portion 51 along the attachment line 60. The plurality of web members 50 eliminate the need of a full length web and which results in reduction of metal usage and thus in turn reduced CO2 emission.

Abstract: A stiffener 50 for construction elements for providing resistance against deflection and cracking is disclosed comprising a U-shaped cross-section with a web 10 and two flanges 20a, 20b extending transversely from the web 10 and having ribs 30 rising parallel, perpendicular or diagonal from the flanges 20a, 20b. The stiffener 50 is configured to be fixed within the construction element. A drywall stud and a ceiling section provided with a plurality of stiffeners 50 of the present disclosure spaced at desired locations along their length is also disclosed. Such drywall studs and ceiling sections comprising stiffeners 50 of the present disclosure reduce deflection of drywall partition and suspended ceiling system, respectively by up to 50%.

Abstract: Systems and methods for extracting parameters from invoice files are provided, including techniques to determine suppliers of invoice files using machine learning models. The system can identify an invoice file in a message, determine an analysis process, such as optical character recognition, for the invoice file based on the invoice file type, and perform an extraction process on the invoice file via a cloud computing system to extract objects from the invoice file. The system can extract invoice parameters from the objects using a first analysis process, and if the first analysis process fails to extract a predetermined set of invoice parameters, perform subsequent analysis processes to extract parameters that the first analysis process failed to extract. The system can then transmit the invoice parameters and the invoice file to a node server.