Offline processing of biometrically-enabled payment transactions are disclosed. A method may include a biometric processor computer program: receiving a biometric payment request from a user electronic device comprising transaction information for a transaction at a payment terminal for a merchant that does not have an active connection with the biometric processor computer program or with an acquirer for the merchant; receiving, from the user electronic device, a user biometric; retrieving a financial instrument associated with the user biometric; providing the financial instrument and the transaction information to the acquirer that decisions the transaction and returns an approval for the transaction; and returning the approval and the financial instrument to the user electronic device. The user electronic device generates a code comprising the financial instrument and the approval and presents the code to the payment terminal, and the payment terminal processes the transaction as an offline approval.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
Systems and methods for digital document exchange are disclosed. According to an embodiment, a method for digital document exchange may include: (1) receiving, by a document exchange computer program, a document; (2) ingesting, by the document exchange computer program, the document; (3) identifying, by the document exchange computer program, a folder for the document; (4) storing, by the document exchange computer program, the document in the folder; (5) identifying, by the document exchange computer program, a target for the document; and (6) notifying, by the document exchange computer program, the target that the document was received.
Systems and methods for throttled sharing of personal information are disclosed. A method for throttled sharing of personal information may include: (1) receiving, by a computer program at a trusted entity and from a customer, customer personal information; (2) receiving, by the computer program at the trusted entity and from a third party system, an identification of personal information fields required for a transaction; (3) receiving, by the computer program at the trusted entity and from the third party system, a request for personal information verification for a transaction involving the customer; (4) retrieving, by the computer program, the personal information fields required by the third party system; (5) creating, by the computer program, a payload comprising the customer personal information for the personal information fields required by the third party system; and (6) returning, by the computer program, the payload to the third party system.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/42 - Confirmation, p. ex. contrôle ou autorisation de paiement par le débiteur légal
4.
METHODS AND SYSTEMS FOR ACTIVITY FRAMEWORK GENERATION
There are provided systems and methods for generating, configuring, or reconfiguring activity frameworks. For instance, there is provided a method for configuring an activity framework. The method can reside as instructions on a non-transitory computer-readable medium, the instructions being configured to cause a processor to perform certain operations. The operations may include receiving a set of requirements and constructing a set of computational steps required to meet the set of requirements. The operations can further include generating the activity framework and the activity framework can include a workflow of activities. The operations can further include generating a configuration file.
A system and method for optimized asset allocation recommendations based on socio-economic trends are disclosed. The method includes receiving first information associated with a set of assets, and a set of beneficiary entities associated with a user. Further, the method includes retrieving second information associated with the set of assets and a testament from at least one external resource. Further, the method includes analyzing, using a recommendation engine, the first information and the second information to determine an optimized allocation of the set of assets to the set of beneficiary entities. Further, the method includes generating a preliminary testament draft based on the optimized asset allocation recommendation. Further, the method includes rendering, via a display, the generated preliminary testament draft to the user to prompt the user to provide a user input. Thereafter, the method includes generating a final testament draft based on the user input.
Systems and methods for determining performance-based pricing are disclosed. A method may include: creating a borrower entry based on borrower loans for a borrower and a borrower rating; polling a plurality of rating agencies for agency borrower ratings; receiving agency borrower ratings from the plurality of rating agencies; determining that one of the agency borrower ratings has changed from a previous agency borrower rating; predicting, using a machine learning engine that is trained with historic agency rating changes, a recommended change to a pricing grid for the borrower based on the change in the agency borrower rating; updating the pricing grid for the borrower based on the recommendation; and providing the updated pricing grid to a loan platform. The loan platform is configured to implement the pricing grid, and the implementation of the pricing grid changes a payment for at least one of the plurality of borrower loans.
In some aspects, the techniques described herein relate to a method including: receiving, as input to a binary search process, a subject vector embedding and a class vector embedding, wherein the subject vector embedding is generated from a plurality of subject text strings and wherein the class vector embedding is generated from a class text string; generating a similarity score; determining that the similarity score is below a threshold value; splitting the plurality of subject text strings into a first new plurality of subject text strings and a second new plurality of subject text strings; receiving a new subject vector embedding, wherein the new subject vector embedding is generated from the first new plurality of subject text strings; and calling the binary search process recursively using the new subject vector embedding and the class vector embedding as input to the binary search process.
A system and method for regulatory compliance management are disclosed. The method includes receiving, by the at least one processor, at least one regulatory document from at least one regulatory source. Further, the method includes analyzing, by the at least one processor using a trained model, the at least one regulatory document. Further, the method includes drafting, by the at least one processor, an obligation for at least one entity based on the analysis of the at least one regulatory document. Further, the method includes mapping, by the at least one processor, an information in the obligation to at least one of a set of internal procedures and policies of the at least one entity. Further, the method includes updating, by the at least one processor, the internal procedures and policies of the at least one entity to maintain a legal compliance with the obligation.
In some aspects, the techniques described herein relate to a method including: providing a machine unlearning algorithm, wherein the machine unlearning algorithm is configured to: approximate a final training state of model parameters trained with an unfiltered dataset; approximate a final training state of model parameters trained with a retain dataset; and compute a vector for shifting parameter weights from the final training state of model parameters trained with the unfiltered dataset to the final training state of model parameters trained with the retain dataset; tuning a batch normalization layer of a convolutional neural network included in a machine learning model with the machine unlearning algorithm, wherein parameters of a convolution layer of the convolutional neural network remain fixed; and tuning prompt parameters of a transformer model included in the machine learning model with the machine unlearning algorithm, wherein other parameters of the transformer model remain fixed.
Various methods and processes, apparatuses/systems, and media for automating cloud financial operations management optimizations are disclosed. A processor implements a cloud financial operations management module (CFOMM) and establishes a communication link among the CFOMM, a plurality of infrastructure observability systems, and a plurality of Infrastructure as a Code (Iaac) systems of record (SOR) via a communication interface. The processors triggers the CFOMM through events from the infrastructure observability systems on cloud financial operations management based metrics and alerts data identifying environments to be corrected associated with a cloud; identifies IaaC code's originating code repository and related materials through corresponding SOR; implements an AI LLM to automatically generate new code specific to the environments to be corrected based on predefined rules received from a rule database and the code received from the originating code repository; and automatically corrects the environments associated with the cloud by implementing the new code.
Systems and methods for identity verification using identity tokens are disclosed. In one embodiment, a method for throttled sharing of personal information may include: (1) receiving, by a personal identity verification computer program and from a third party system for a third party, an identity token for a customer, wherein the third party system received the identity token from a customer electronic device; (2) retrieving, by the personal identity verification computer program, customer personal information for the customer associated with the identity token; (3) retrieving, by the personal identity verification computer program, third party identity verification requirements for the third party; (4) confirming, by the personal identity verification computer program, that the customer personal information meets the third party identity verification requirements; and (5) returning, a result of the confirmation to the third party system.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
12.
SYSTEMS AND METHODS FOR PROVIDING MODEL-GENERATED CONTENT BASED ON PRIVATE DATA
In some embodiments, the techniques described herein relate to a method including: receiving, at a query management platform and from a client device, a query, wherein the query includes an application identifier of an application to be migrated from the client device to a cloud based platform; retrieving, by the query management platform and from a context data store, context data; generating, by the query management platform, a prompt including the query and a migration profile including the context data as an embedding and provide the prompt to the machine learning model; receiving a request to search a vector database for a stored term similar to a query term and providing the stored term and a vector to the machine learning model; receiving an executable script in response to the migration profile; and executing the executable script to migrate the application from the client device to the cloud based platform.
In some aspects, the techniques described herein relate to a method including: receiving, at an entitlement service and from a client application, a request for an entitlement token; signing, by the entitlement service, a permission file with a private key from a public-private key pair; generating, by the entitlement service, a composite key using a public key from the public-private key pair; encrypting, by the entitlement service, the permission file using the composite key as an encryption key in a symmetric encryption function, wherein encrypting the permission file generates the entitlement token; and sending the entitlement token to the client application.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
45 - Services juridiques; services de sécurité; services personnels pour individus
39 - Services de transport, emballage et entreposage; organisation de voyages
43 - Services de restauration (alimentation); hébergement temporaire
Produits et services
Concierge services for elite members comprising making requested personal arrangements and reservations and providing customer-specific information to meet individual needs for elite members rendered together in an airport lounge; all the foregoing provided to credit card members Airport services, namely, transit lounge facilities for elite passenger relaxation featuring access to the Internet provided by others; providing transit lounge facilities for elite passenger relaxation featuring enhanced and expedited customer service responses for elite passengers; booking and arranging of access to airport lounges for elite passengers; airport services, namely, transit lounge facilities for elite passenger relaxation and also including shower facilities; all the foregoing provided to credit card members Providing premium food and beverage services for elite air travelers in transit lounges; providing bar and cocktail lounges also featuring related amenities being temporary accommodations in the nature of conference rooms, shower facilities, and work stations for relaxation to elite air travelers in transit lounges; and providing conference and meeting room facilities for elite air travelers in transit lounges and airport terminals; all the foregoing provided to credit card members
(1) Airport services, namely, transit lounge facilities for elite passenger relaxation featuring access to the Internet provided by others; providing transit lounge facilities for elite passenger relaxation featuring enhanced and expedited customer service responses for elite passengers; booking and arranging of access to airport lounges for elite passengers; airport services, namely, transit lounge facilities for elite passenger relaxation and also including shower facilities; all the foregoing provided to credit card members
(2) Providing premium food and beverage services for elite air travelers in transit lounges; providing bar and cocktail lounges also featuring related amenities being temporary accommodations in the nature of conference rooms, shower facilities, and work stations for relaxation to elite air travelers in transit lounges; and providing conference and meeting room facilities for elite air travelers in transit lounges and airport terminals; all the foregoing provided to credit card members
(3) Concierge services for elite members comprising making requested personal arrangements and reservations and providing customer-specific information to meet individual needs for elite members rendered together in an airport lounge; all the foregoing provided to credit card members
16.
METHOD AND SYSTEM FOR RECOMMENDING AGILE SOFTWARE FRAMEWORK METHODOLOGY
A method and a system for recommending agile software framework methodology are disclosed. The method includes receiving at least one input from a user. The method further includes analyzing the at least one input to authenticate and authorize the at least one input. Further, the method includes recommending at least one agile software framework methodology with an associated confidence score. The method further includes receiving a response input from the user on the recommended agile software framework methodology. Further, the method includes creating a set of tasks for the recommended agile software framework methodology based on a positive response from the user on the recommended agile software framework. Thereafter, the method includes executing the set of tasks associated with the recommended agile software frame methodology for development of a software.
In some aspects, the techniques described herein relate to a method including: determining, by an embedding engine, a first plurality of nodes in a graph database; generating, by the embedding engine, a property-level vector embedding for each node of the first plurality of nodes, wherein each property-level vector embedding is based on a node property defined by each node of the first plurality of nodes; determining, by the embedding engine, a second plurality of nodes; generating, by the embedding engine, a node-level vector embedding for each node in the second plurality of nodes, wherein each node-level vector embedding is based on a type of each node in the second plurality of nodes; and persisting, by the embedding engine, each property-level vector embedding and each node-level vector embedding in a vector database with an association to an index key.
Systems and methods for metadata driven data reconciliation are disclosed. A method may include: (1) identifying origin dataset metadata for an origin dataset; (2) identifying new dataset metadata for a new dataset; (3) comparing the origin dataset metadata to the new dataset metadata; (4) identifying a sample size for the origin dataset, wherein the sample size comprises a number of cells; (5) extracting an origin dataset sample of the sample size of random cells from the origin dataset; (6) generating origin dataset features for the origin dataset sample; (7) generating new dataset features for the new dataset; (8) searching for the origin dataset features in the new dataset features; and (9) returning a matching result in response to the origin dataset features being found in the new dataset features.
In some aspects, the techniques described herein relate to a method including: receiving a first list entity vector embedding, wherein the first list entity vector embedding is of a categorical type and is associated with a list entity; generating a first similarity score between the first list entity vector embedding and a stored vector embedding of a plurality of stored vector embeddings, wherein the stored vector embedding of the plurality of stored vector embeddings is of the categorical type and is associated with a stored entity; adding the first similarity score to a second similarity score, wherein the sum of the first similarity score and the second similarity score is an overall similarity score associated with the stored entity; querying a datastore to retrieve data associated with the stored entity; and returning, as output of the list expansion module, the data associated with the stored entity.
A system and a method for allocating indivisible resources to agents over a finite horizon in a manner that balances resource utilization and fairness are provided. The method includes: receiving first information that relates to a number of agents included in a set of agents; receiving second information that relates to whether each respective agent is requesting an allocation of an indivisible resource during a particular allocation round; assigning, to each respective agent, a respective weight that relates to an importance of the respective agent; calculating, for each respective agent, a respective agent-specific allocation probability; and determining an allocation of the indivisible resource for the particular allocation round based on the agent-specific allocation probabilities. The determination of the allocation may be adjusted based on a budget that indicates an availability of the resource during the particular allocation round.
An external data storage device, without a battery, provides a user-selectable low power mode. The external data storage device includes storage media for storing data and a data port for receiving power and transmitting data to a host device. The external storage data device includes control circuitry configured to negotiate delivery of a first amount of power from the host device in response to connecting the external data storage device to the host device, receive the first amount of power from the host device, receive a selection, via an input device, of a reduced power mode from a user, and reduce power consumption from the host device to a second amount of power lower than the first amount of power in response to receiving the selection of the reduced power mode.
Systems and methods for enabling real-time graph machine learning models using bitwise transaction graph frameworks are disclosed. According to one embodiment, a method may include: (1) receiving, by a bitwise transaction graph computer program, a plurality of historical transactions, wherein each historical transaction comprises a customer identifier for a customer, a card number or card reference number, a merchant identifier for a merchant, a transaction authorization time, a transaction risk score, and a set of real-time fraud risk attributes; (2) converting, by the bitwise transaction graph computer program, the historical transactions to a fixed length data structure; and (3) loading, by the bitwise transaction graph computer program, the fixed length data structure onto edges of a transaction graph, wherein each vertex of the transaction graph represents one of the customers or one of the merchants.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 30/018 - Certification d’entreprises ou de produits
23.
SYSTEMS AND METHODS FOR AUTOMATED IDENTIFICATION OF EMERGING TRENDS
Systems and methods for automated identification of emerging trends are disclosed. A method may include: (1) receiving, by a computer program executed on an electronic device, a plurality of documents; (2) training, by the computer program, a proximity model to identify word pairs in each of the plurality of documents, wherein the word pairs comprise two words within a predetermined distance of each other at a predetermined frequency in the plurality of documents; (3) identifying, by the computer program and using the proximity model, trends involving the word pairs, wherein the trends are based on a frequency that the word pairs appear in the plurality of documents and/or a velocity at which the word pairs appear in the plurality of documents over a period of time; and (4) outputting, by the computer program, the word pairs and the trends to a downstream system.
A method and a system for migrating a computing environment from a first platform to a second platform are disclosed. The method includes identifying a first set of components associated with the first platform and a second set of components associated with the second platform. The method further includes comparing the first set of components with the second set of components. Further, the method includes mapping the first set of components with the second set of components based on the comparison. The method further includes introducing the first set of components in the second platform based on the mapping. Further, the method includes updating at least one interface associated with the second platform for interaction with at least one entity. Thereafter, the method includes enriching, using a trained model, the second set of components associated with the second platform.
A data storage device may include an enclosure and a metal organic framework (MOF) container situated within an enclosure interior. The MOF container contains a MOF configured to store captive molecular units and to release the captive molecular units in gaseous form into the enclosure interior. A method of manufacturing the data storage device may include charging the MOF, attaching the MOF container to the enclosure interior, and sealing the enclosure after attaching the MOF container to the interior of the enclosure. A method of adjusting an amount of gas in a sealed data storage device may comprise including a MOF container within an interior of the sealed data storage device, the MOF container containing a MOF, charging the MOF, and, after the sealed data storage device has been placed into service, the MOF releasing captive molecular units into the interior of the sealed data storage device.
G11B 33/12 - Disposition des éléments de structure dans les appareils, p. ex. d'alimentation, des modules
B01D 53/04 - Séparation de gaz ou de vapeursRécupération de vapeurs de solvants volatils dans les gazÉpuration chimique ou biologique des gaz résiduaires, p. ex. gaz d'échappement des moteurs à combustion, fumées, vapeurs, gaz de combustion ou aérosols par adsorption, p. ex. chromatographie préparatoire en phase gazeuse avec adsorbants fixes
G11B 25/04 - Appareils caractérisés par la forme du support d'enregistrement employé mais non spécifiques du procédé d'enregistrement ou de reproduction utilisant des supports d'enregistrement plats, p. ex. disques, cartes
G11B 33/14 - Diminution de l'influence des paramètres physiques, p. ex. changements de température, humidité, poussière
26.
INCREASED VCM CURRENT RESOLUTION DURING TRACK FOLLOW TO DECREASE NRRO
A data storage device may include one or more disks; a voice coil motor (VCM) driver for driving a VCM and having a programmable transconductance (Gm); an actuator arm assembly comprising one or more disk heads and the VCM, wherein the VCM is configured to operate in a first mode and a second mode; and one or more processing devices configured to control the actuator arm assembly to actuate the disk heads over corresponding disk surfaces of the disks, and further configured to: determine a current mode of operation of the VCM, the current mode of operation comprising the first mode; and transition the VCM from the current mode of operation to a new mode of operation, the new mode of operation comprising the second mode, wherein the transitioning comprises tuning the Gm from a first transconductance value to a second, different transconductance value.
G11B 5/55 - Changement, sélection ou acquisition de la piste par déplacement de la tête
G11B 5/00 - Enregistrement par magnétisation ou démagnétisation d'un support d'enregistrementReproduction par des moyens magnétiquesSupports d'enregistrement correspondants
27.
SYSTEM AND METHOD FOR QUESTIONNAIRE DATA DIGITIZATION AND RECONCILIATION
Various methods and processes, apparatuses/systems, and media for questionnaire data digitization and reconciliation are disclosed. A processor generates an autonomous program for continuously monitoring shared mailbox for unread emails having questionnaire data containing a plurality of line items filled out by a client; converts, by utilizing an OCR tool, the questionnaire data containing the plurality of line items into a machine-readable format data; reads, by utilizing an automated reconciliation tool, the machine-readable format data for each line item; compares, by utilizing the automated reconciliation tool, data for each line item against a corresponding predefined guidance data; identifies, based on comparing, missing response data, negative response data, and insufficient response data corresponding to the questionnaire data filled out by the client by applying predefined rules; and automatically reconciles the missing response data, negative response data, and insufficient response data.
A method for using machine learning models to automatically cluster data into meaningful populations and groups and to identify hidden patterns and structures in such data is provided. The method includes: receiving first information that relates to a group of entities; analyzing the first information with respect to a predetermined set of parameters and a predetermined set of data types; selecting, based on a result of the analysis, a first machine learning (ML) model from among a predetermined set of ML models; and using the selected first ML model to generate a report that includes second information that relates to at least one data cluster identified by the first ML model from the first information.
A method for facilitating supervised generative optimization for synthetic data generation is disclosed. The method includes receiving, via an application programming interface, inputs that include input data and parameters; partitioning the input data to generate data sets, the data sets including training data sets, validation data sets, and test data sets; tuning hyperparameters of synthesizers by using the data sets and supervised optimization that is based on downstream performance metrics; determining a mixture distribution from among the tuned synthesizers; training machine learning models based on the mixture distribution; and generating, by using the trained machine learning models, sets of synthetic data based on the input data.
A method for facilitating automated scoring of software development tasks by using predictive analytics is disclosed. The method includes receiving, via a graphical user interface, search requests for various tasks; aggregating raw data that corresponds to the tasks, the raw data including information in a natural language format; generating structured data sets from the raw data based on predetermined parameters; determining, by using a first model, a task score for each of the tasks based on the structured data sets; determining, by using a second model, a confidence score for the task score; and computing predictive outputs for the tasks based on the corresponding task score and the corresponding confidence score.
A method and system for performing information-directed pessimism in offline learning for reduction of distribution mismatch are disclosed. The method includes determining a first and second distribution for the ML model based on different datasets, and determining a presence of a distribution mismatch between the first distribution and the second distribution. The method further includes calculating a value for an individual state-action pair in a training dataset and comparing the calculated value against a reference data distribution, determining a difference between the calculated value and the reference data distribution and comparing the difference against a reference threshold. When the determined difference is greater than the reference threshold, removing the individual state-action pair from the training dataset as a pessimistic penalty, determining an offset value based on the modified training dataset, and generating a modified ML model based on the determined offset value without retraining the ML model.
Various apparatuses, systems, methods, and media are disclosed to provide a heat-assisted magnetic recording (HAMR) medium that has a magnetic recording layer on a MgO—TiO (MTO) underlayer, where the MTO underlayer is formed using pulsed DC sputtering and has less than 50 mol % of TiO. By providing an MTO layer with less than 50 mol % of TiO, smaller grain sizes may be achieved in the magnetic recording layer, providing for higher areal densities. In some embodiments, a second MTO underlayer is provided, which is formed using non-pulsed DC sputtering and has 50 mol % of TiO. That is, a dual-layer MTO underlayer may be provided with, e.g., an MgO-30TiO layer atop an MgO-50TiO layer.
G11B 5/66 - Supports d'enregistrement caractérisés par l'emploi d'un matériau spécifié comportant uniquement le matériau magnétique, sans produit de liaison les supports d'enregistrement étant constitués par plusieurs couches magnétiques
G11B 5/00 - Enregistrement par magnétisation ou démagnétisation d'un support d'enregistrementReproduction par des moyens magnétiquesSupports d'enregistrement correspondants
A system for optimizing shut-down and restart of an Open Radio Access Network (O-RAN) radio unit (O-RU) deployed in an O-RAN Citizens Broadband Radio Service (CBRS) network includes: spectrum access system (SAS); CBRS Domain Proxy (DP) located in a Centralized Data Center (CDC); Cloud Management Service (CMS) located in the CDC; a first CBRS Interface Monitoring and Alert (CIMA) located in the CDC; a second CIMA located in a Distributed Data Center (DDC); at least one O-RAN Distributed Unit (O-DU) located in the DDC; a plurality of O-RAN Radio Units (O-RUs) located in the DDC; and an O1 interface connecting the CDC and DDC. The second CIMA located in the DDC monitors the O1 interface connection to the DDC, and if a failure of the O1 interface lasts longer than a specified time duration Sd, alerts the at least one O-DU regarding the failure of the O1 interface.
H04L 41/0659 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant la reprise sur incident de réseau en isolant ou en reconfigurant les entités défectueuses
34.
METHOD AND SYSTEM FOR REMOVING DEFICIENCIES FROM A DATASET
A system for removing deficiencies from a dataset. The system may include a processor and memory that stores instructions that, when executed by the processor, cause the processor to perform operations. The operations may include removing deficiencies from a dataset that may have been obtained via an input of the synthetic training data generation tool. The removing of deficiencies from the dataset may comprise: determining that the dataset includes training deficiencies; retrieving, from one or more data sources, first remediating data that rectifies a first deficiency; rectifying the first deficiency by updating the dataset with the first remediating data; determining that the updated dataset still includes a training deficiency; and synthesizing second remediating data that rectifies the training deficiency.
A method and system for evidencing skills of a developer are disclosed. The method includes extracting, from various databases, a list of terms and definitions for identifying skills, and grouping the identified skills for forming at least one ontology based on similarity. The method further includes acquiring raw data and performing data cleaning on the raw data for identifying at least one domain-specific skill. Subsequently, skill matching is performed by comparing the at least one domain-specific skill against the at least one ontology for determining that the at least one ontology is evidenced for the developer. The method further includes performing analytics to display the evidenced at least ontology and corresponding level, and automatically assigning the at least one task based on the performed analytics.
Systems and methods for providing an automated servicing desktop are disclosed. A method may include: (1) receiving, by a request processing computer program executed on an electronic device, a loan maintenance request from a source system; (2) extracting, by the request processing computer program, data from the loan maintenance request; (3) verifying, by the request processing computer program, that the loan maintenance request is not a duplicate loan maintenance request; (4) executing, by the request processing computer program, a dynamic lookup for data; (5) applying, by the request processing computer program, rules to the loan maintenance request; (6) generating, by the request processing computer program, a dashboard; (7) determining, by the request processing computer program, that a target service level has not been met; and (8) generating, by the request processing computer program, an alert in response to the target service level not being met.
Systems and methods for end-to-end automation of borrowing base calculations are disclosed. A method may include a borrowing basis computer program: (1) receiving documents for collateral, assets, and liabilities from a borrowing system for a borrower; (2) extracting information for the collateral, assets, and liabilities from the documents; (3) calculating, from the information, a borrowing base for the borrower; (4) sending the borrowing base to the borrower system; (5) receiving, by the borrowing basis computer program, acknowledgement from the borrower system; (6) setting a borrowing limit based on the borrowing base; (7) receiving updated documents for the borrower; (8) extracting updated information from the updated documents; (9) calculating, from the updated information, an updated borrowing base for the borrower; and (10) setting an updated borrowing limit based on the borrowing base.
Systems and methods for executing smart payments are disclosed. According to an embodiment, a method for executing smart payments may include: (1) receiving, by a computer program and from a borrower, a bulk payment for a plurality of loans; (2) retrieving, by the computer program, information on each of the loans, wherein the information comprises a payment amount due for the loan; (3) determining, by the computer program and using a machine learning model that is trained with prior payments to the loans by the borrower, a payment allocation of the bulk payment for each of the loans; and (4) providing, by the computer program, the payment allocation to a loan system for each of the loans, wherein the loan system for each of the loans executes a payment to the loan for the payment allocation.
A method and system for generating a unique character string based on attribute information are disclosed. The method includes receiving transaction information of a non-standard transaction, extracting various attributes from the received transaction information, and dynamically generating a character string using a combination of the various attributes. The method further includes identifying a vendor identifier that corresponds with a set of attributes stored at a vendor device that matches with the various attributes of the dynamically generated character string, and consolidating the vendor identifier with the dynamically generated unique identifier for generating a unique consolidated identifier for the non-standard transaction.
A method for using an artificial intelligence (AI) technique to forecast trading behavior and thematic concepts for trade baskets with respect to derivatives and other specific types of financial instruments is provided. The method includes: retrieving, from an internet website, information that relates to at least one form that corresponds to a government filing; using the retrieved information to generate a knowledge graph that relates to a particular entity; generating at least one application programming interface (API) that is configured to analyze the retrieved information and the knowledge graph in order to provide insight into at least one financial instrument that relates to the particular entity; and forecasting, based on an output of the API(s) and by applying an AI algorithm to the knowledge graph, at least one proposed future transaction to be executed with respect to the financial instrument(s) that relate to the particular entity.
A head gimbal assembly (HGA), such as for a hard disk drive (HDD), includes a load beam formed with a deck and side rails extending away from each lateral edge of the deck in a direction away from a corresponding flexure, where each side rail portion includes a limiter structure extending from the side rail in a direction toward the flexure, the limiter structure including a hooking portion positioned on a distal side of the flexure for limiting displacement of the flexure in a direction away from the load beam. As an integral part of the load beam, the limiters do not adversely impact the existing gimbal dynamic performance designed to enable high areal density HDDs.
A method for using graphical model tools to evaluate classification models that are trained by using incomplete data sets for which data is known to be missing and the missing data is known to be non-random is provided. The method includes: receiving first information that relates to first data to be used for training and evaluating a performance of a first classification model; analyzing the first information to determine second information that relates to missing data; generating a missingness graph that relates to a description of how the missing data has come to be missing; decomposing, based on the missingness graph, an expression that relates to a classification metric into recoverable terms and non-recoverable terms; training a second classification model to generate respective weights for the recoverable terms; and calculating, based on the non-recoverable terms, an upper bound and a lower bound on the classification metric.
A method and system for performing a neural level vulnerability detection are disclosed. The method includes receiving a neural network model, performing a bit-level corruption check on the received neural network model indicating a potential presence of an embedded malware in the neural network model, and deploying the neural network model. The method further includes scheduling a periodic anomaly detection on the deployed neural network model, performing the periodic anomaly detection on the deployed neural network model for detecting an anomaly at a scheduled time, and when the anomaly is detected on the neural network model, executing an explainable artificial intelligence based embedded malware exploration to identify an alteration made by the embedded malware at a neuron level of the neural network model.
Systems and methods for redacted statement delivery to third-party institutions are disclosed. A method may include: receiving a request for a statement from a third-party backend; retrieving a list comprising a plurality of available statements; providing the list of the plurality of available statements to the third-party backend; retrieving a selection of one of the plurality of available statements; identifying metadata for data fields in a statement template; generate the selected statement using the statement template and embedding the metadata in data fields of the statement; identifying a redaction reason; identifying redaction metadata associated with the redaction reason; redact data fields in the statement having metadata matching the redaction reason metadata; storing the redacted statement in a temporary store; and returning a path for the temporary store to the third-party backend, wherein the third-party backend may retrieve the redacted statement from the temporary store.
A system for expeditiously de-archiving archived objects. The system may include operations that comprise: configuring a first application programing interface (API) gateway between an auxiliary memory system and a repository of archived objects; receiving, via an application, a first user request for a first archived object that is stored within the repository of archived objects; processing the first user request to retrieve the first archived object; pushing, via the first API gateway, the first archived object into the auxiliary memory system that provides high-speed access to objects within the auxiliary memory system; and updating first metadata for the first archived object to store a first log of the retrieving and the pushing.
A method for using an artificial intelligence (AI) technique to forecast market activities by specific parties with respect to derivatives and other specific types of financial instruments is provided. The method includes: retrieving first information that relates to at least one form that corresponds to a government filing; generating, based on the first information, a first knowledge graph that relates to an entity, such as a commercial concern; retrieving second information that relates to historical actions performed by at least one person that is associated with the entity; and forecasting, based on the first knowledge graph and the second information, at least one proposed future transaction to be executed by the person with respect to the first entity. The forecasting is based on an application of an AI algorithm to the information retrieved from the government filing(s).
A method for evaluating classification models that are trained by using incomplete data sets for which data is known to be missing and the missing data is known to be non-random is provided. The method includes: receiving first information that relates to data to be used for training and evaluating a performance of a classification model that is designed to make a determination with respect to a particular query; analyzing the first information to determine second information that relates to a known portion of the first information and third information that relates to missing data; estimating, based on the third information, an uncertainty that corresponds to the missing data; and calculating, based on the second information and the estimated uncertainty, a first Gaussian approximation to a performance metric that relates to the first classification model.
A method for implementing robust data pipelines through model-driven engineering (MDE) is provided. The method may be implemented by at least one processor. The method may include receiving data at an MDE ecosystem; modelling the data to create a logical data model based on a meta model stored in a data catalog; storing the logical data model in the data catalog; generating a data in motion (DiM) library based on the logical data model; creating an original channel in the data catalog and registering the logical data model as a data contract on the original channel; receiving a transformation data flow into the data catalog in the MDE ecosystem, wherein a transformation process of the transformation data flow is performed outside of the MDE ecosystem; and using a reverse engineering tool to generate a new channel in the data catalog from the transformation data flow.
Various illustrative aspects are directed to a data storage device, method, and one or more processing devices that are configured to: select a seek time model from a plurality of seek time models based at least in part on an operational characteristic of an access command, the operational characteristic relating to an off-track susceptibility of executing the access command; determine an access time for the access command using the selected seek time model; and select a next access command for execution based on the determined access time for the access command and determined access times for other ones of a plurality of access commands.
Systems and methods for improving document readability are disclosed. A method may include: (1) receiving, by a computer program executed on a user electronic device, may receive a document comprising text; (2) identifying, the computer program, a subject for the document; (3) retrieving, by the computer program, a plurality of trigger words and a plurality of skim-through words for the subject; (4) identifying, by the computer program, trigger words in the text of the document and applying a first graphical pattern to the identified trigger words; (5) identifying, by the computer program, skim-through words in the text of the document and applying a second graphical pattern to the identified skim-through words; and (6) causing, by the computer program, the document to be output with the identified trigger words output in the first graphical pattern and the skim-through words being output in the second graphical pattern.
A method and system for accounting for missing not-at-random (MNAR) data in training dataset via Bayesian regularization are disclosed. The method includes acquiring historical data of an organization, the historical data including the MNAR data. The method further includes performing estimation for two of at least three unknown quantities based on the historical data, and injecting quantitative information for remaining one of the at least three unknown quantities based on qualitative information regarding nature of missingness. Lastly, the method reassembles the estimation for two of the at least three unknown quantities and injected quantitative information for the remaining one of the at least three unknown quantities, to provide a modified function.
Systems and methods for space-based transactions are disclosed. A method for conducting a space-based transaction may include: (1) a first space-based device determining that it is incapable or will be incapable of providing the service; (2) the first space-based device identifying a second space-based device; (3) the first space-based device requesting capability information for the second space-based device; (4) the first space-based device that the second space-based device is capable of providing the service based on the capability information; and (5) the first space-based device executing a transaction with the second space-based device, wherein the first space-based device pays the second space-based device for the service by transferring payment from an electronic wallet for the first space-based device to an electronic wallet for the second space-based device on the distributed ledger network, and the second space-based device provides the service to the user.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
53.
METHOD AND SYSTEM FOR PROVIDING SYNTHETIC NEURAL DATA MODELS
A method for providing a synthetic neural data model is disclosed. The method includes generating a model that simulates an electronic communication network; appending agents to the model, the agents relating to a software component that sends orders to the model based on a predetermined timestep; assigning a fixed grid to the model, the fixed grid including a tick size that relates to a fixed granularity; calibrating each of the agents by using a calibration data set; inputting the model and historical book data to a neural network; and training, via the neural network, a neural network extension of the model by using an optimizer.
A method and a system for generating domain-aware captions for time-series images that are capable of adapting to new domains without retraining are provided. The method includes: receiving information that relates to a first time-series image that is associated with a target domain; generating a generic caption for the first time-series image; extracting, from a memory based on the generic caption, a plurality of image-caption pairs; generating, for each respective one of the plurality of image-caption pairs, a corresponding domain-agnostic caption that includes information that describes a shape of the respective image; and adapting the generic caption into a domain-specific caption for the first time-series image that relates to the target domain. The generating of domain-agnostic captions and domain-specific captions may be performed by using models that are respectively trained based on synthetic time series images having captions that correspond to a set of parameters.
Systems and methods for identifying blockchain address owners using test funds are disclosed. According to one embodiment, a method for identifying blockchain address owners using test funds may include: identifying, by an identity identification computer program executed by an electronic device, a room identifier for an application deployed to a test blockchain network for a main blockchain network; fetching, by the identity identification computer program, chat messages for the room identifier; extracting, by the identity identification computer program, identifying information from the chat messages; and outputting, by the identity identification computer program, the identifying information.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for submission, automation, exchange, creation, analysis, protection, and facilitation of orders, invoices, debits, discounts, credits, payments, payment instructions, cross-border payments, electronic funds transfers, accounting data entry, price lists, and business documents; downloadable software used to facilitate the reception, submission, management, coding and approval of invoices; downloadable software for workflow coordination and automation of invoices, including planning, procurement and conducting tasks; computer software for business to business e-commerce and services; downloadable software that automates financial, operational and business workflow and processes; global proprietary digital network for the secure exchange of electronic invoices Financial services, namely, providing electronic bill payment services, electronic payment services involving electronic processing of invoices and subsequent transmission of bill payment data, electronic commerce payment services, namely, clearing and reconciling financial transactions via a global computer network Platform as a service (PAAS) featuring computer software platforms for submission, automation, exchange, creation, analysis, protection, and facilitation of orders, invoices, debits, discounts, credits, payments, payment instructions, cross-border payments, electronic funds transfers, accounting data entry, price lists, and business documents; Platform as a service (PAAS) to facilitate the reception, submission, management, coding and approval of invoices; Platform as a service (PAAS) for workflow coordination and automation of invoices, including planning, procurement and conducting tasks; Platform as a service (PAAS) for facilitating business to business e-commerce and services; Platform as a service (PAAS) that automates financial, operational and business workflow and processes
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for submission, automation, exchange, creation, analysis, protection, and facilitation of orders, invoices, debits, discounts, credits, payments, payment instructions, cross-border payments, electronic funds transfers, accounting data entry, price lists, and business documents; downloadable software used to facilitate the reception, submission, management, coding and approval of invoices; downloadable software for workflow coordination and automation of invoices, including planning, procurement and conducting tasks; computer software for business to business e-commerce and services; downloadable software that automates financial, operational and business workflow and processes; global proprietary digital network for the secure exchange of electronic invoices. Financial services, namely, providing electronic bill payment services, electronic payment services involving electronic processing of invoices and subsequent transmission of bill payment data, electronic commerce payment services, namely, clearing and reconciling financial transactions via a global computer network. Platform as a service (PAAS) featuring computer software platforms for submission, automation, exchange, creation, analysis, protection, and facilitation of orders, invoices, debits, discounts, credits, payments, payment instructions, cross-border payments, electronic funds transfers, accounting data entry, price lists, and business documents; Platform as a service (PAAS) to facilitate the reception, submission, management, coding and approval of invoices; Platform as a service (PAAS) for workflow coordination and automation of invoices, including planning, procurement and conducting tasks; Platform as a service (PAAS) for facilitating business to business e-commerce and services; Platform as a service (PAAS) that automates financial, operational and business workflow and processes.
58.
METHOD AND SYSTEM FOR AUTOMATED MESSAGE GENERATION
A method for automating a process of generating messages that are responsive to client inquiries by using an AI algorithm that implements a machine learning technique to ensure accuracy and timeliness in the responses is provided. The method includes: receiving a first message that includes an inquiry that relates to an account associated with a user; applying an AI algorithm for analyzing the first message in order to extract information that relates to the inquiry; determining, based on a result of the analysis, whether generating a response to the inquiry requires human intervention; when human intervention is not required, retrieving information that is responsive to the inquiry from a memory; generating a second message that includes the information that is responsive to the inquiry; and transmitting the second message to the user.
H04L 51/07 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel caractérisée par l'inclusion de contenus spécifiques
A method for optimizing bandwidth part (BWP) management for 5G wireless network includes: periodically analyzing, by a BWP analytics module located at one of near-real-time radio access network intelligent controller (near-RT RIC) or a distributed unit (DU) of a gNodeB, at least one of physical resource block (PRB) utilization difference, delay violation percentage corresponding to a percentage of logical channels not able to meet delay requirements for quality of service (QOS) profile assigned to the logical channels, throughput, and interference levels of a BWP to classify the BWP; periodically analyzing, by the BWP analytics module, at least one of PRB utilization, throughput, and delay requirements of at least one user equipment (UE); and categorizing, by the BWP analytics module, the at least one UE into one of a plurality of BWP classifications based on the analyzing of the at least one of PRB utilization, throughput, and delay requirements.
H04L 5/00 - Dispositions destinées à permettre l'usage multiple de la voie de transmission
H04L 47/2441 - Trafic caractérisé par des attributs spécifiques, p. ex. la priorité ou QoS en s'appuyant sur la classification des flux, p. ex. en utilisant des services intégrés [IntServ]
60.
METHOD AND SYSTEM FOR MANAGING RESOURCES USING PREDICTIVE ANALYTICS
A method for facilitating resource management by using predictive analytics is disclosed. The method includes aggregating, via an application programming interface, data from various sources, the data including end user data, resource data, and influential factor data; generating data products based on the aggregated data, the data products including a structured data set, an application, and a tool; training a first model by using the generated data products; determining predictive outputs by using the trained first model and the generated data products, each of the predictive outputs corresponding to a recommended action for management of resources; and publishing the predictive outputs to a downstream application.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
61.
SYSTEMS AND METHODS FOR DISTRIBUTED LEDGER-BASED IDENTITY MANAGEMENT
Systems and methods for distributed ledger-based identity management are disclosed. In one embodiment, a computer-based method for managing attestations may include: (1) receiving, by a computer program executed by an electronic device for an identity consumer and from an identity provider, a notification from an identity provider server that an attestation is available, wherein the attestation may be generated by the identity provider based on authorization from a system operator and may include a chain of trust comprising an identification of the system operator and the identity provider; (2) requesting, by the computer program, the attestation from the identity provider; and (3) downloading, by the computer program, the attestation to an identity consumer electronic wallet for the identity consumer. The identity provider may commit the downloading of the attestation to a distributed ledger, wherein the distributed ledger maintains a current status for the attestation.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
62.
SYSTEM AND METHOD FOR PROVIDING LARGE LANGUAGE MODEL FOR SANCTIONS ARTIFICIAL INTELLIGENCE ASSISTED AUTOMATION
A method and system for reducing false-positives using a neural network are disclosed. The method includes receiving a data envelope, scanning the data envelope and detecting a presence of data corresponding to a value in a list of sanctioned entities. The method further includes transforming format of the data envelope into a text format, identifying and extracting target information including the data corresponding to the value in the list of sanctioned entities and surrounding information, and reformatting the extracted target information and surrounding information into a natural language question. Once the natural language question is provided, the natural language question is processed by a neural network model for determining whether a sanctioned entity is included or not based on context provided by the natural language question.
An assembly configured for a hard disk drive includes a head slider having a suspension face and a recording medium face opposing the suspension face, where the slider houses a read-write transducer at or near a trailing edge (TE) face opposing a LE face, and a suspension assembly comprising a flexure having a standoff structure extending from a main planar body of the flexure, to which the suspension face of the slider is adhered. A first portion of the suspension face of the slider is coated with an anti-reflective coating (ARC) extending at least to a farthest portion, in a direction of the LE face, of the standoff structure of the flexure. An adhesive attaches the head slider to the flexure and is positioned to interface in its entirety with at least a portion of the ARC.
There are provided a system and a method for automation as a service (AaaS) workflows. For instance, there is provided a method for configuring a workflow to create or manage a specified environment. The method may be embodied as instructions residing a non-transitory computer-readable medium, and these instructions may be configured to configure a processor to perform certain operations. As configured, the processor embodies an application-specific computing system configured in structure and function to conduct the operations which may include configuring a first set of parameters associated with one or more environments other than the specified environment. The operations may further include configuring set of parameters associated with the specified environment, and they may further include executing an automation service based on the first and second sets of parameters.
Provided are methods and systems for configuring a workflow to create or manage a specified environment. An exemplary method resides as instructions on a non-transitory computer-readable medium and are configured to cause a processor to perform operations including receiving an input including a first set of parameters associated with one or more environments other than the specified environment and a second set of parameters associated with the specified environment. The operations also include generating a payload based on the input, validating the generated payload, and executing, in response to the generated payload being successfully validated, the workflow as an automation-as-a-service workflow using the validated generated payload.
In some aspects, the techniques described herein relate to a method including: providing a first datum to a target model, wherein the first datum is retrieved from a forget dataset; providing a sample drawn from Gaussian noise to an original model; computing a first loss, wherein the first loss is based on target model output from processing the first datum and original model output from processing the sample drawn from Gaussian noise; providing a second datum to the target model, wherein the second datum is retrieved from a retain dataset; providing the second datum to the original model as input to the original model; computing a second loss, wherein the second loss is based on target model output from processing the second datum and original model output from processing the second datum; and combining the first loss and the second loss with an alpha weighting to generate a weighted combination.
In some aspects, the techniques described herein relate to a method including: determining a first cross-entropy loss, wherein the first cross-entropy loss is determined based on a set of predictions, and wherein the set of predictions are based on a classifier head of a machine learning model generating the set of predictions based on a set of feature vectors; updating the classifier head and a prompt of the machine learning model with the first cross-entropy loss; generating outlier samples based on the set of feature vectors; providing, as input to the classifier head, the set of feature vectors and the outlier samples, wherein a second cross-entropy loss and an outlier regularization loss are computed by the classifier head based on the set of feature vectors and the outlier samples; and updating the classifier head with the second cross-entropy loss and the outlier regularization loss.
G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance
68.
METHOD AND APPARATUS FOR ENCODING RAN PARAMETERS OVER E2 INTERFACE USING E2SM-RC FOR TRAFFIC STEERING-BASED SLA OPTIMIZATION UPON CELL SHUTDOWN FOR ENERGY SAVINGS ACTIVATION
A method of implementing an optimal handover of a user equipment (UE) in an Open Radio Access Network (O-RAN) system from a first serving cell subject to a shutdown to an optimal target cell for the UE before executing the shutdown includes: providing an event trigger style for an event trigger used to trigger an event in an E2 node of the O-RAN system when a configuration change is ongoing within the E2 node, wherein the event trigger style is provided as radio intelligent controller (RIC) Event Trigger Definition information element (IE) Style Type 5; sending the event trigger from the E2 node to a near-real time (near-RT) RIC; and sending, by the near-RT RIC, a control message to the E2 node to implement the optimal handover of the UE to the optimal target cell for the UE.
A voice coil motor (VCM) includes a coil, and on a first side a first yoke having a coil-side facing the coil, a first low-coercivity permanent magnet positioned between the coil and the coil-side of the first yoke and having a yoke-side facing the first yoke and a coil-side opposing the yoke-side, and a first high-coercivity permanent magnet adjoining the coil-side of the first low-coercivity magnet. A second side of the VCM on the opposing side of the coil is similarly configured. The permeance coefficient of such a VCM enables magnetic stability of low-coercivity magnetic materials. Additional high-coercivity permanent magnets may be bonded to the coil-sides of each of the first and second yokes and adjoining the yoke-sides of each of the low-coercivity permanent magnets, if the relative thicknesses of the magnet materials so dictate by design.
G11B 5/55 - Changement, sélection ou acquisition de la piste par déplacement de la tête
G11B 5/48 - Disposition ou montage des têtes par rapport aux supports d'enregistrement
H02K 1/02 - Détails du circuit magnétique caractérisés par le matériau magnétique
H02K 15/03 - Procédés ou appareils spécialement adaptés à la fabrication, l'assemblage, l'entretien ou la réparation des machines dynamo-électriques des corps statoriques ou rotoriques comportant des aimants permanents
H02K 41/035 - Moteurs à courant continuMoteurs unipolaires
36 - Services financiers, assurances et affaires immobilières
Produits et services
Banking and financial services, namely, investment banking services; financial planning and management services; financial and investment advisory services; investment brokerage services; securities brokerage services; financial portfolio management and analysis services; mutual fund consultation, brokerage, and investment services; providing information and advice in the field of financial planning and investments
71.
Method and system for migrating database content onto new database infrastructure
A system configured to: determine an optimal migration cache size; interface with a source database; index each respective entry from among the plurality of database record entries based on their respective database record entry dates; respectively prioritize each entry from among the plurality of database record entries for migration based on their plurality of respective database record entry dates and sizes; queue a queue of unmigrated database record entries for migration based on each respective prioritization; initiate a migration of each respective entry from among the queue of unmigrated database record entries; monitor a respective progress of the migration of each respective entry from among the queue; and provide a status of the respective progress of the migration of each respective entry from among the plurality of database record entries.
Systems and methods for efficient test-time prediction of model arbitrariness are disclosed. According to an embodiment, a method for efficient test-time estimation of predictive multiplicity may include: (1) receiving, by arbitrariness prediction computer program, a trained machine learning model, wherein the trained machine learning model comprises a plurality of nodes, and each node has a weight; (2) determining, by the arbitrariness prediction computer program, a number of dropout models for the trained machine learning model to generate; (3) creating, by the arbitrariness prediction computer program, the number of dropout models; (4) providing, by the arbitrariness prediction computer program, sample data to each of the dropout models; (5) receiving, by the arbitrariness prediction computer program, an output from each of the dropout models; and (6) determining, by the arbitrariness prediction computer program, an arbitrariness for the trained machine learning model based on the outputs.
In some embodiments, the techniques described herein relate to a method including: collecting metadata from one or more data sources, the metadata including connections between a plurality of applications and one or more of a plurality of platform services; storing the metadata in a graph structure on a memory, wherein the graph structure includes a node for each application and platform service and an edge for a connection between each application and each platform service; and identifying a plurality of tranches of the graph structure, wherein a first tranche of the plurality of tranches includes a first application of the plurality of applications connected to a first platform service of the plurality of platform services.
A method and a system for generating synthetic time series data that is subject to various types of constraints are provided. The method includes: receiving first information that relates to a sample of a historical time series and second information that relates to constraints; obtaining a set of synthetic time series based on the first information and the second information; calculating a set of distances of respective differences between the historical time series and each of the set of synthetic time series; and selecting, from among the set, a first synthetic time series for which a corresponding distance is a maximum. The set of synthetic time series may be obtained by using a Sequential Least Squares Programming algorithm or by using a diffusion model that is trained according to a defined protocol.
A method and system for reducing context length in processing a codebase using large language model (LLM) are disclosed. The method includes receiving the codebase including multiple files for processing, generating, via the LLM, summaries based on the multiple files, and subsequently organizing the summaries based on a structure of the codebase. The method further includes determining a downstream task, determining whether the downstream task requires a summary of a code or the code itself, and transmitting the summary or the code to the downstream task for executing the downstream task.
Systems and methods for non-human account tracking are disclosed. According to one embodiment, a method may include: retrieving, by a tracing tool computer program executed by a computer processor, a plurality of records for a computer application from an application database, the plurality of records comprising a computer application name, one or more Application Programming Interfaces (APIs) associated with the computer application, and an identification of a plurality of non-human accounts that have access to the computer application; storing, by the tracing tool computer program, the plurality of records as raw data in a relational database; determining, by the tracing tool computer program, that each of the retrieved plurality of non-human accounts is in an account vault; associating, by the tracing tool computer program, the non-human accounts with the retrieved one or more APIs; and storing, by the tracing tool computer program, the association in a relational database.
A method for verifying origin of request for payments may include a financial institution computer program: receiving a request for a payment URL from a merchant, the payment URL provided for a transaction with a customer; generating the payment URL, wherein the payment URL comprises a pointer to a network location for the financial institution; providing the payment URL to a customer electronic device; receiving, from the customer electronic device and at a browsed URL, a stored or pinned certificate of domain for the payment URL; (5) comparing the stored or pinned certificate of domain for the payment URL to a certificate of domain for the browsed URL; presenting a payment page in response to a match; and returning an error in response to a mismatch.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
78.
SYSTEMS AND METHODS FOR COMPUTER APPLICATION AUDIT ORGANIZATION
Systems and methods for computer program audit organization may leverage advanced technologies, including large language models (LLMs) and feedback controllers, to automate and streamline the audit process. The system receives audit requests, auto-populates them with relevant details, and breaks them into parts specifying responsive artifacts. The parts are routed to application owners and developers for review and response. A feedback controller interacts with an LLM to modify suggested responses and evidence based on feedback. The system bundles approved files into a package and sends notifications to audit participants.
Systems and methods for processing checks with machine-readable optical labels are disclosed. In one embodiment, a method for processing checks with machine-readable optical labels may include (1) receiving, by a presenting bank computer program executed by an electronic device, a check comprising a machine-readable optical label printed thereon, wherein the machine-readable optical label comprises a payor bank routing number that is encrypted with a private key for a payor bank; (2) reading, by the presenting bank computer program, the machine-readable optical label; (3) decrypting, by the presenting bank computer program, the machine-readable optical label using a public key corresponding to the private key; (4) identifying, by the presenting bank computer program, the payor bank routing number from the machine-readable optical label; and (5) routing, by the presenting bank computer program, the check to the payor bank associated with the payor bank routing number.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
In some aspects, the techniques described herein relate to a method including: receiving, at a change request service, a request to update contact information data; receiving, at the change request service, from a verification service provider, a raw ownership score; normalizing, by the change request service, the raw ownership score; sending, by the change request service, the contact information data, the customer identifier, and the normalized ownership score to a risk engine; receiving, by the change request service from the risk engine, a confidence score; providing, by the change request service, the confidence score, the normalized ownership score, and historical data associated with the stored customer profile, to a consolidation function; receiving, by the change request service and from the consolidation function, a consolidated trust score; and updating a datastore record associated with a customer represented by the customer identifier with the contact information data.
In some aspects, the techniques described herein relate to a method including: receiving, at an application programming interface (API) of a middle-tier platform, an initial API method call including a request identifier associated with a processing request and a data parameter; writing the data parameter and the request identifier to a record of a datastore, wherein the record of the datastore includes a batch field; writing a value of false to the batch field; executing, by a first intermediary processing procedure, a query of the datastore, wherein the query of the datastore retrieves the record of the datastore; performing, by a second intermediary processing procedure, additional intermediary processing; making a secondary API call to a backend system; receiving a second data parameter from the backend system in response to the secondary API call; and generating a response to the processing request.
The present disclosure generally relates to a magnetic recording head comprising one or more spin-orbit torque (SOT) devices, the SOT devices each comprising a bismuth antimony (BiSb) layer. The magnetic recording head comprises a SOT device comprising a first shield extending to a media facing surface (MFS), a seed layer disposed over the first shield, the seed layer being disposed at the MFS, a free layer disposed on the seed layer, the free layer being disposed at the MFS, a bismuth antimony (BiSb) layer disposed over the free layer, the BiSb layer being recessed from the MFS, a second shield disposed over the BiSb layer, the second shield extending to the MFS, and a shield notch coupled to the second shield, the shield notch being disposed between the first shield and the second shield. The magnetic recording head may be a two-dimensional magnetic recording head comprising two SOT devices.
A method and a system for performing multivariate time series imputation by using a modulated auto-decoding framework that is built upon implicit neural representations are provided. The method includes: receiving information that relates to a latent vector representation of a time series for which there are missing values; using the received information to generate a set of network weights that is usable by a sinusoidal representation network model for obtaining a functional representation of the time series; modulating a set of sine activation amplitudes of the functional representation of the time series; and using the network weights and the modulated sine activation amplitudes to impute the missing values. The method is performable by using three different neural network models for various functions.
A method for facilitating automated information management by using predictive analytics is disclosed. The method includes receiving, via a graphical user interface, a request that includes a question in a natural language format; generating, by using a first model, queries based on the question, each of the queries corresponding to a stand-alone component of the question; identifying, from a data repository, data sections for each of the queries, each of the data sections relating to a page in an electronic document; determining, by using a second model, contextual information for each of the queries from the corresponding data sections; and generating, by using a third model, a response for the request based on the queries and the corresponding contextual information.
A method and a system for providing a secure communication are disclosed. The method includes receiving a request to install an application for the secure communication between a first entity and a second entity. Next, the method includes generating a certificate for the secure communication between the first entity and the second entity. Next, the method includes extracting a first key and a second key from the certificate. Next, the method includes sharing the first key with the second entity for encryption of a message in the secure communication. Next, the method includes receiving the encrypted message from the second entity. Next, the method includes decrypting the encrypted message using the second key. Thereafter, the method includes displaying the decrypted message in the application.
Method and Apparatus to Encode RAN OAM-Related Data Over the R1 and Other O-RAN Open Interfaces Using Generic Data Encoding Model and Information Semantics
A method for providing generic information encoding for RAN OAM-related data by providing semantics of RAN OAM data including CM/PM/Trace data and a generic information encoding model using Information Elements (IE) and/or IE structures that leverage the RAN semantics for encoding RAN OAM-related data using common message structures to encode any number of OAM-related RAN parameters, nested in hierarchical RAN structures to any depths enabling an R1 data consumer via a data customer computer to discover data capabilities of an R1 data producer that produces the RAN OAM-related data over an O-RAN-standardized R1 interface between rApps and Non-RT RIC/SMO platform functions.
A system for providing granular location information for User Equipment (UE) in an Open Radio Access Network (O-RAN) that generates and transmits a Location Report without receiving a Location Reporting Control message. When UE moves either, between sectors or bands of a cell site or the UE is handed over to another cell site, a Location Update message is generated by the cell site responsible for the UE and is transmitted to a controlling Distributed Unit (DU) and onward to a controlling Central Unit (CU). The information is further transmitted to Core equipment that may include Mobility Management Entity/Access and Mobility Management Function (MME/AMF) and Lawful Interception Management System (LIMS) allowing for high granularity for location identification of UE in an O-RAN system.
Systems and methods for predicting and preventing social engineering scams in real time are disclosed. According to one embodiment, a method for predicting social engineering scams in real time may include: (1) receiving, at a computer program executed by a user electronic device for a user, a communication; (2) extracting, by the computer program and using a machine learning engine, a pattern from the communication; (3) comparing, by the computer program, the pattern to scam patterns in a local scam database; (4) and generating, by the computer program, an alert in response to the pattern matching one of the scam patterns.
G06Q 30/018 - Certification d’entreprises ou de produits
G10L 17/26 - Reconnaissance de caractéristiques spéciales de voix, p. ex. pour utilisation dans les détecteurs de mensongeReconnaissance des voix d’animaux
89.
Multi-Tier Error Correction Codes for DNA Data Storage
Example systems and methods for using a multi-tier error correction code distributed among oligos for DNA data storage are described. A data unit may be encoded as a set of codewords where each codeword is distributed as symbols on different oligos. The codewords may include a set of first tier codewords that include CRC and ECC redundancy data and one or more additional tiers of codewords that include permuted data and corresponding ECC redundancy data. Decoding may include a sequence of decoding iterations between the first tier of codewords and additional tiers of codewords.
H03M 13/19 - Correction d'une seule erreur sans utiliser les propriétés particulières des codes cycliques, p. ex. codes de Hamming, codes de Hamming étendus ou généralisés
H03M 13/00 - Codage, décodage ou conversion de code pour détecter ou corriger des erreursHypothèses de base sur la théorie du codageLimites de codageMéthodes d'évaluation de la probabilité d'erreurModèles de canauxSimulation ou test des codes
90.
SYSTEMS AND METHODS FOR NEAR REAL TIME BLOCKCHAIN BASED PAYABLES VERSUS RECEIVABLES RECONCILIATION
A method may include a computer program executed by a financial institution backend: (1) receiving payables data for a plurality of transactions from a merchant, wherein each of the plurality of transactions in the payables data comprises a transaction identifier, a merchant identifier, a payable transaction amount, and a payables currency; (2) writing the payables data to a blockchain; (3) sending the payables data to a payment brand, wherein a payment brand computer program is configured to generate receivables data for the plurality of transactions, and the receivables data for each of the plurality of transactions comprises the transaction identifier, a receivable transaction amount, and a receivable currency; (4) receiving the receivables data; and (5) writing the receivables data to a blockchain, wherein a smart contract on the blockchain is configured to reconcile the transactions in the payables data with the transactions in the receivables data.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
91.
METHOD AND SYSTEM FOR PROVIDING A PRIORITIZATION RECOMMENDATION FOR A SET OF TASKS
A method and a system for providing a task prioritization recommendation for a set of tasks on a set of user devices are disclosed. The method includes: receiving, by a processor, first information related to a failure of the set of tasks; retrieving, by the processor, a set of target parameters related to the failure of the set of tasks; analyzing, by the processor using an artificial intelligence-based module, the first information related to the failure of the set of tasks and the set of target parameters; generating, by the processor, a composite score for the set of tasks based on the analysis; and providing, by the processor on the set of user devices, the task prioritization recommendation based on the composite score.
In some aspects, the techniques described herein relate to a method including: receiving, from a plurality of data channels, client interaction data; preprocessing the client interaction data into a format consumable by one or more machine learning models; ingesting, by a sentiment scorer machine learning model, the client interaction data; generating, by the sentiment scorer machine learning model, a plurality of sentiment scores for a client associated with the client interaction data; ingesting, by a health scorer machine learning model, the plurality of sentiment scores; and outputting, by the health scorer machine learning model and based on the plurality of sentiment scores, a weighted health index score for the client associated with the client interaction data.
In some aspects, the techniques described herein relate to a method including: receiving, from a query interface, a natural language query; encoding the natural language query into tokens; embedding the tokens into a natural language query vector, wherein the natural language query vector represents a semantic meaning of the natural language query; formatting an index query of an index datastore, wherein the index query includes the natural language query vector as a lookup parameter of the index query; receiving, as a response to the index query, a document set; passing the document set and the natural language query to a machine learning model; receiving a response to the natural language query from the machine learning model, wherein the response is based on the document set; and providing the response to the natural language query to the query interface for consumption.
Systems and methods for neurodivergence-driven ambiguity detection and resolution are disclosed. In one embodiment, a method for neurodivergence-driven ambiguity detection and resolution may include: (1) receiving, by an ambiguity detection training computer program executed by an electronic device, a labeled dataset comprising data labeled by one or more neurodivergent individuals, wherein the data is labeled as clear or ambiguous; (2) training, by the ambiguity detection training computer program, an ambiguity detection engine using the labeled dataset to predict ambiguities in new data; and (3) deploying, by the ambiguity detection training computer program, the ambiguity detection engine to a computer program or system, wherein the ambiguity detection engine is configured to receive the new data, predict whether the new data is ambiguous, and present a modification to the new data based on the prediction.
Systems and methods for hybrid classical-quantum optimization using random matrix theory-based subproblem identification on correlation matrices are disclosed. A method may include a classical computer program: receiving a problem to optimize and time series data comprising a plurality of parameters; computing an average and a correlation matrix for the time series data; determining an aspect ratio for the correlation matrix; filtering the correlation matrix based on the aspect ratio and using a denoising solution; redefining the problem into a plurality of subproblems; determining that one of the plurality of subproblems exceeds a limit of a quantum computer; repeatedly dividing the subproblem until the limit of the quantum computer is met; embedding the subproblems on the quantum computer, wherein the quantum computer is configured to execute a quantum optimization routine on each of the subproblems and output a plurality of solution vectors; and recombining the plurality of solution vectors.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
A method may include: receiving a first communication from an ATM; identifying a first processing server of a plurality of processing servers; associating the first processing server to the ATM and returning an association indicator for an association between the ATM and the first processing; routing the first communication to the first processing server; saving a session state of the ATM to a cache; determining that the first processing server is offline; identifying a second processing server; associating the second processing server to the ATM and returning a new association indicator for the association between the ATM and the second processing server to the ATM; receiving a second communication from the ATM to process a transaction comprising the new association indicator; identifying the second processing server from the new association indicator; routing second communication to the second processing server; and retrieving the session state for the ATM from the cache.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
97.
SYSTEM AND METHOD TO IMPLEMENT AI/ML MODELS TO OUTPUT FEEDBACK DATA TO AUTOMATICALLY MITIGATE MICROAGGRESSION
Various methods and processes, apparatuses/systems, and media for generating model-based output feedback data to automatically mitigate microaggression are disclosed. A processor creates a data model based on a diverse dataset encompassing various forms of data corresponding to microaggressions; and trains the data model to identify and respond to microaggressions by implementing artificial intelligence and machine learning techniques with the diverse dataset and corresponding feedback data. The processor also receives a plurality of communication data in connection with various users via a plurality of communication channels; runs the data model to automatically generate feedback data in response to identified microaggression data tailored towards a certain user by analyzing patterns, language nuances, and contextual cues from the communication data; and transmits and displays the feedback data to a computing device via a private communication channel accessed only by the certain user so that the certain user may learn and mitigate identified microaggression.
A method for providing cross-account data distribution management is disclosed. The method includes receiving an indication of a change in an object repository of a producer account, the change including an addition of data sets into the object repository; scheduling computing resources based on the indication and a predetermined guideline; identifying, via an application programming interface, parameters that correspond to a data warehouse of a consumer account; initiating the computing resources based on the scheduling to copy the data sets from the object repository to a producer data lake; transmitting, based on the identified parameters, the data sets from the producer data lake to a consumer data lake by using a managed data lake; and persisting the data sets from the consumer data lake in the data warehouse.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
Various methods and processes, apparatuses/systems, and media for systemically and dynamically onboarding and reporting data with no code or low code data warehouse are disclosed. A processor implements a model driven data WaaS and reporting platform; receives data from a plurality of data source systems; provisions the data received from the plurality of source systems; validates the provisioned data; creates a machine learning data model based on the validated data; onboards the data model onto the model driven data WaaS and reporting platform; and generates an adapter pattern on every field type to treat it as a field. The adapter pattern is generated where fields and their types are entered into data WaaS field types so that a user can define the field once and use across all reports thereby enabling no code approach. The processor then dynamically generates a report corresponding to the adapter pattern for publication and consumption.
In one example, a method for rotating security credentials includes instantiating an execution environment in which to execute instructions of a script. The method also includes executing the instructions of the script within the execution environment to cause the at least one processor to monitor a passage of time to identify an arrival of a time to coordinate a rotation of a security credential between an executable routine and a secrets management service. The at least one processor is also caused, in response to identifying the arrival of the time, perform operations including: providing a first request to the executable routine to communicate with the secrets management service of the processing device to request rotation of the security credential at the secrets management service, and providing a second request to the executable routine to rotate the security credential at the executable routine.
