Abstract: Systems and methods are provided for associating confirmed user (CU) indications to network-initiated transactions. An example method includes receiving network details for a transaction between a user and a first party and storing the network details in a data repository in association with an transaction identifier for the transaction. The method also includes accessing, from the data repository, network details for multiple prior transactions between the user and the first party and comparing the network details for said transaction and the network details for the multiple prior transactions. The method then includes, based on a match between the network details for said transaction and the network details for the multiple prior transactions, appending a confirmed user flag in an authorization message for the transaction, whereby an issuer relies on the confirmed user flag in deciding to approve or decline the transaction.

Abstract: Systems and Methods are disclosed herein for automatically indexing multiple informational fields in digital data records, the method comprising: identifying, based on rules defining target information fields, for each target field of the target information fields, at least one page in a digital data record comprising content related to the target field; extracting, for each target field, from the identified at least one page, at least one portion of text comprising the content; feeding, for each target field, a pre-processed version of the at least one portion of text into a machine learning (ML) model, wherein the ML model is trained on the target field; determining, for each target field, via the ML model trained on the target field, at least one candidate text comprising the content; and extracting, for each target field, the at least one candidate text.

Abstract: Systems and methods for automated indexing and extraction of information in digital documents are disclosed. A method may comprise identifying a page containing targeted information; inputting an image of the page into a visual machine learning network (visual ML), wherein the visual ML is trained to recognize text associated with the targeted information in an image; identifying by the visual ML, a section of the image that contains the targeted information; inputting the digital document, and coordinates of the section into an extraction module; and extracting the targeted information by the extraction module from the section.

Abstract: Systems and Methods are disclosed herein for automatically indexing multiple informational fields in digital data records, the method comprising: identifying, based on rules defining target information fields, for each target field of the target information fields, at least one page in a digital data record comprising content related to the target field; extracting, for each target field, from the identified at least one page, at least one portion of text comprising the content; feeding, for each target field, a pre-processed version of the at least one portion of text into a machine learning (ML) model, wherein the ML model is trained on the target field; determining, for each target field, via the ML model trained on the target field, at least one candidate text comprising the content; and extracting, for each target field, the at least one candidate text.

Abstract: Systems and methods for automated indexing and extraction of information in digital documents are disclosed. A method may comprise selecting a page number of a digital document to identify a page containing targeted information; inputting an image of the page into a visual machine learning network (visual ML), wherein the visual ML is trained to recognize text associated with the targeted information in an image; identifying by the visual ML, a section of the image that contains the targeted information; inputting the page number, the digital document, and coordinates of the section into an extraction module; and extracting the targeted information by the extraction module from the section.

Abstract: A computer-implemented method for authenticating an online user includes steps including receiving, from a requestor server in communication with a merchant website, an authentication request message including authentication data collected from a user computing device during an online interaction with the merchant website. The steps also include extracting the authentication data from the authentication request message, and applying a risk-based authentication (RBA) engine to the authentication data to obtain RBA result data including a reason code that includes no more than three bytes of data. The steps further include causing the reason code to be embedded in an authorization request message generated during the online interaction and routed to a decisioning server via a payment network.

Abstract: An apparatus for determining a bit index for a parity bit of a polar codeword is disclosed. Each index of a polar codeword may have an associated weight and an associated reliability value. The apparatus may compare the weights and reliability values of a group of bit indices in parallel to determine a bit index of the group associated with the lowest weight and highest reliability value. Additional groups may be processed until all of the bit indices of the polar codeword have been examined and the bit index with the lowest weight and highest reliability value is identified.

Abstract: Embodiments described herein provide a code generation mechanism (FIG. 3, 301) in a Polar encoder (FIG. 2, 204) to determine a bit type (FIG. 3, 312) corresponding to each coded bit in the Polar code before sending the data bits for encoding (FIG. 3, 303). For example, each bit in the Polar code is determined to have a bit type of a frozen bit, parity bit, an information bit, or a cyclic redundancy check (CRC) bit based at least on the respective reliability index of the bit from a pre-computed reliability index lookup table (FIG. 4A, 411). In this way, the bit type determination can be completed in one loop by iterating the list of entries in the pre-computed reliability index lookup table.

Abstract: Low-density parity check (LDPC) decoder circuitry is configured to decode an input codeword using a plurality of circulant matrices of a parity check matrix for an LDPC code. Multiple memory banks are configured to store elements of the input codeword. A memory circuit is configured for storage of an instruction sequence. Each instruction describes for one of the circulant matrices, a corresponding layer and column of the parity check matrix and a rotation. Each instruction includes packing factor bits having a value indicative of a number of instructions of the instruction sequence to be assembled in a bundle of instructions. A bundler circuit is configured to assemble the number of instructions from the memory circuit in a bundle. The bundler circuit specifies one or more no-operation codes (NOPs) in the bundle in response to the value of the packing factor bits and provides the bundle to the decoder circuitry.

Abstract: An apparatus and method for selectively capturing substantially separate phases from a multiphase fluid mixture flowing through a flowline. The apparatus is preferably substantially aerofoil shaped, and includes sample ports which are positioned on the apparatus in such an orientation that takes advantage of the low density and high density flow around the aerofoil shape, as well as the pressure distribution around the aerofoil shape.

Abstract: An apparatus and method for selectively capturing substantially separate phases from a multiphase fluid mixture flowing through a flowline. The apparatus is preferably substantially aerofoil shaped, and includes sample ports which are positioned on the apparatus in such an orientation that takes advantage of the low density and high density flow around the aerofoil shape, as well as the pressure distribution around the aerofoil shape.