Abstract: A system and method for machine learning architecture for prospective resource allocations are described. The method may include: receiving data records representing historical resource allocations from a user account associated with a first identifier to a resource account associated with a second identifier; deriving input features based on the data records; computing, using a trained neural network architecture, a predicted resource allocation amount and a predicted resource allocation date for the predicted resource allocation amount based on the derived input features; determining, using the trained neural network architecture, a first selection score associated with the predicted resource allocation amount and a second selection score associated with the predicted resource allocation date; and when the first or second selection score is above a minimum threshold, causing to display, at a display device, the associated resource allocation amount or date corresponding to the second identifier.

Abstract: A system for the inspection of the optical quality of a part, object or product having a portion comprising transparent material such as ophthalmologic lenses, protective eyewear, visors, eyewear shield and the like is provided. A liquid crystal display (LCD) screen emits variable patterns of light through the transparent part under inspection to a charged coupled device (CCD) camera that captures the image and transmits the image data to an image processing module. The processed image data are then transmitted to an analysis module which then generally measures the dimensions of the part, the transparency, the colour and the optical strength. The analysis module also advantageously detects and measures the presence of dots, stains, scratches, optical distortions, fingerprints, cloudiness and other optical artefacts and/or defects in the transparent material. Accordingly, the patterns emitted by the LCD screen are designed to measure the optical specifications and highlight potential optical defects.

Abstract: Disclosed is a bipolar electrolyzer having individual bipolar units. Each of the bipolar units has a steel cathodic member and a valve metal anodic member in back-to-back configuration. The bipolar electrolyzer is characterized in that the cathodic member is spaced from the anodic member defining an electrolyte tight compartment therebetween, and that the bipolar unit further has conduit means extending outwardly from between the anodic member and the cathodic member. Also disclosed is a method of electrolysis in a bipolar electrolyzer which method is characterized by collecting hydrogen between the anodic and cathodic members of the bipolar unit and removing the hydrogen so collected through hydrogen removal means.