Abstract: A system includes a memory and a processor coupled to the memory. The processor receives a user credential associated with a first user and authorizes an avatar of the first user to enter a virtual environment. When the first user is registered with a first entity, the processor obtains a user profile of the first user. Based on the user profile, the processor determines and indicates to the first user in the virtual environment that a first type of data file of the first user qualifies the first user to obtain a product or service for a first amount of data objects. The processor receives a selection of the product of service from the first user, receives a command to transfer the first amount of data objects from the first type of data file to a second data file, and transfers the first amount to the second data file.

Abstract: Systems, computer program products, and methods are described herein for developers to initiate development operations from within a development environment of a user application. This can also be extendable dynamically for different user groups (e.g., testers, support, internal associates or employees, or the like), and environments (e.g., lower-level environments, production environments, or the like). As such, the invention offers a dynamic debug mode feature for virtual assistants based on different sections of users and environments.

Abstract: Systems, devices, and methods for user authentication are described. A security platform may authenticate a user based on a machine learning model created using historical user behavior. The user behavior may correspond to user interaction with and/or operation of a computing device. The user behavior may correspond to, for example, historical user purchase patterns. Applications include user authentication for online and offline purchases, access to computing resources, and/or access to physical locations.

Abstract: Systems, devices, and methods for user authentication are described. A security platform may authenticate a user based on a machine learning model created using historical user behavior. The user behavior may correspond to user interaction with and/or operation of a computing device. The user behavior may correspond to, for example, historical user purchase patterns. Applications include user authentication for online and offline purchases, access to computing resources, and/or access to physical locations.

Abstract: Arrangements for providing dynamic user authentication are provided. In some aspects, a user may initiate a transaction at a merchant point-of-sale (POS) system, via a merchant website, or the like. In response, user data from one or more pre-registered user devices may be retrieved. The data may be analyzed to identify one or more data points for use as a correct answer to an authentication question. An authentication question may be dynamically generated and transmitted to the merchant system for display and the user may provide authentication response data. The authentication response data may be received and compared to the data points providing the basis for the authentication question. If the data matches, the user may be authenticated and the transaction may be processed. If not, additional user authentication data may be requested. The system may then delete the received user data.

Abstract: A system and method for computer aided design includes constructing, by an engineering software tool for a current project, a design of a circuit or a subsystem of an industrial system comprising a plurality of hardware elements. A project knowledge graph is constructed for the current project representing an ontology for a set of elements and element relationships, wherein the set of elements include the plurality of hardware elements. A feature extraction module extracts features of the project knowledge graph related to the plurality of hardware elements. An AI-based advisor runs integrated with the engineering tool during a current project and queries one or more reference knowledge graphs for common features extracted by the feature extraction module, and responsive to identifying additional information related to hardware constraints, generates and displays recommendations to the user for the design.

Abstract: Enforcing data ownership may include receiving a request to register an application programming interface (API) endpoint. A plurality of elements of the API endpoint and a target API endpoint may be preprocessed. A distance may be computed for each of element of the API endpoint relative to at least one of the elements of the target API endpoint. A distance score for the API endpoint may be computed based on the distance scores. A term frequency-inverse document frequency (TF-IDF) value may be computed for a plurality of metadata terms of the API endpoint and the target API endpoint. A similarity score between the TF-IDF values of the metadata terms may be computed. An adjusted score may be computed for the API endpoint based on the distance score and the similarity scores. The API endpoint may be registered based on the adjusted score being below a permissions threshold.

Abstract: Various embodiments described herein relate to an anomaly detection framework adaptable to different asset types. In this regard, a data stream associated with a first asset is received. The data stream is then processed to generate output data by encoding the data stream based on historical data associated with the first asset, the historical data comprising clustered data representative of fault states and one or more non-fault states. Furthermore, in accordance with a determination that the generated output data is indicative of a potential fault of the first asset, fault data indicative of the potential fault is generated and caused to be transmitted to an administrative device for display.

Abstract: A system including: a processor; and a memory storing computer program code that controls the processor to: collect real-time business process metrics; collect real-time cluster metrics for a plurality of application clusters indicative of a required allotment of infrastructure resources for a given business process level; estimate a predicted future business process level; based on the estimated predicted future business process level and the real-time cluster metrics, predict a future infrastructure resource requirement of each of the plurality of application clusters; compare the predicted future infrastructure resource requirement of each of the plurality of application clusters to a current dedication of each of the plurality of application clusters; automatically adjust, in real-time and based on the comparison, respective allotments of infrastructure resources for each of the plurality of application clusters; receive an actual business process; and process the business process across the plurality of

Abstract: Methods and systems are presented for providing automated online chat assistance in multiple languages. A query in a first language is received via a chat robot from a user device. The query is machine-translated into a second language and transmitted to an artificial intelligence system that includes a dialog tree configured in the second language. The artificial intelligence system determines a response in the second language to the query by locating a node corresponding to an intent based on the query in the dialog tree. The node includes a node ID and response text in the second language. The artificial intelligence system transmits the second-language response including the node ID to the chat robot. The second-language response is intercepted, and first-language response text corresponding to the second-language response text is determined based on the node ID. The second-language response text is then provided to the user device by the chat robot.

Abstract: Provided is a computer-implemented deep-learning-based method for extracting minutiae from a latent friction ridge image. The method comprises training a minutiae extraction model though a deep-learning network with ground truth latent friction ridge images as training samples, and, inputting a latent friction ridge image into the minutiae extraction model to extract minutiae of the latent friction ridge image, wherein the model outputs locations and directions for the extracted minutiae. The deep-learning network includes a base network configured to generate a minutiae feature map from a latent friction ridge image, a Region Proposal Network (RPN) configured to propose minutiae locations and directions from the minutiae feature map, and a Region-Based Convolutional Neural Network (RCNN) configured to definitely decide minutiae locations and directions from RPN's proposal.

Abstract: A system including: a processor; and a memory storing computer program code that controls the processor to: collect real-time business process metrics; collect real-time cluster metrics for a plurality of application clusters indicative of a required allotment of infrastructure resources for a given business process level; estimate a predicted future business process level; based on the estimated predicted future business process level and the real-time cluster metrics, predict a future infrastructure resource requirement of each of the plurality of application clusters; compare the predicted future infrastructure resource requirement of each of the plurality of application clusters to a current dedication of each of the plurality of application clusters; automatically adjust, in real-time and based on the comparison, respective allotments of infrastructure resources for each of the plurality of application clusters; receive an actual business process; and process the business process across the plurality of

Abstract: Enforcing data ownership may include receiving a request to register an application programming interface (API) endpoint. A plurality of elements of the API endpoint and a target API endpoint may be preprocessed. A distance may be computed for each of element of the API endpoint relative to at least one of the elements of the target API endpoint. A distance score for the API endpoint may be computed based on the distance scores. A term frequency-inverse document frequency (TF-IDF) value may be computed for a plurality of metadata terms of the API endpoint and the target API endpoint. A similarity score between the TF-IDF values of the metadata terms may be computed. An adjusted score may be computed for the API endpoint based on the distance score and the similarity scores. The API endpoint may be registered based on the adjusted score being below a permissions threshold.

Abstract: The present invention relates to a method of fusing at least two different candidate lists into a single candidate list, said at least two different candidate lists being generated by matching biometric data captured from an individual to be identified and biometric data enrolled from candidates to calculate match scores of candidates and ranking said match scores, the method comprising steps of: normalizing the match scores of the candidates of said at least two different candidate lists; ranking at least part of the candidates of said at least two different candidate lists in a single candidate list according to said normalized match scores to fuse said at least two different candidate lists; identifying at least one candidate belonging to multiple lists of said at least two different candidate lists; and raising said identified at least one candidate's rank in said single candidate list.

Abstract: There are provided systems and methods for automated generation of conversational workflows for automation chatbots. A service provider, such as an electronic transaction processor for digital transactions, may provide self-service channels for assistance through chatbot and other automated computing processes. In order to facilitate deployment of new automated skills, a conversational workflow generator may be provided to internal users of the service provider that allows for automated construction of conversational workflows. The generator may process input REST endpoints, request and response parameters, and workflow diagram to generate Java classes and code. The generator may then connect to a conversational AI platform using the code, which may generate the conversational workflow through dialog and a dialog tree that is mapped to the workflow diagram. The conversational workflow may then be implemented in a chatbot to provide automated services through conversational dialog.

Abstract: A transaction processing system capable of processing transactions and implementing a flexible circuit breaker process during a cyber event. A circuit breaker module initiates a circuit breaker event (CBE), an account identification module identifies one or more affected accounts, and a rule generation module generates conditional rules for evaluating each transaction presented to a transaction processing module. If a transaction presented to the transaction processing module satisfies the conditional rule, the transaction is not processed. Transactions not processed are stored in memory and groups of impacted transactions are assigned to resource modules based on common characteristics. The resource module determines if impacted transactions should be allowed to process. A message notification module monitors and receives notifications and updates a dashboard display to allow users to visualize the impact of a cyber event.

Abstract: Disclosed herein are various embodiments for a performance metric monitoring and feedback system. An embodiment operates by determining a first performance metric for a first application available to a plurality of users of the first application operating first user devices. A second performance metric for a second application available to a plurality of users of the second application operating second user devices is determined. A real-time performance of both the first application and the second application is monitored across the set of computing devices. A user interface that simultaneously displays both the first performance metric for the first application and the second performance metric for the second application accessible to one or more members of the organization in accordance with the display format of the metric template is generated.

Abstract: The present disclosure describes a system and method for profiling and predicting customer behavior using machine learning. The system for profiling and predicting customer behavior uses all available signals from each individual customer across digital channels to build predictive artificial intelligence algorithms to create customer genome markers that predict the likelihood that specific customer will respond to digital actions.

Abstract: Various embodiments described herein relate to an anomaly detection framework adaptable to different asset types. In this regard, a data stream associated with a first asset is received. The data stream is then processed to generate output data by encoding the data stream based on historical data associated with the first asset, the historical data comprising clustered data representative of fault states and one or more non-fault states. Furthermore, in accordance with a determination that the generated output data is indicative of a potential fault of the first asset, fault data indicative of the potential fault is generated and caused to be transmitted to an administrative device for display.

Abstract: A system including: a processor; and a memory storing computer program code that controls the processor to: collect real-time business process metrics; collect real-time cluster metrics for a plurality of application clusters indicative of a required allotment of infrastructure resources for a given business process level; estimate a predicted future business process level; based on the estimated predicted future business process level and the real-time cluster metrics, predict a future infrastructure resource requirement of each of the plurality of application clusters; compare the predicted future infrastructure resource requirement of each of the plurality of application clusters to a current dedication of each of the plurality of application clusters; automatically adjust, in real-time and based on the comparison, respective allotments of infrastructure resources for each of the plurality of application clusters; receive an actual business process; and process the business process across the plurality of