Abstract: A method, system, and computer-readable storage medium for implementing a location-based electronic transaction service are provided. The method includes: receiving a request for a first electronic transaction associated with a first transaction account; obtaining a geographic location associated with the request; transmitting a query for an identification of transaction accounts that are registered to conduct location-based electronic transactions at the geographic location; receiving the identification of transaction accounts; and utilizing the transaction account database to determine whether the first transaction account is registered to conduct the location-based electronic transactions.

Abstract: A mainframe workflow method manages workflow tasks in a mainframe workflow management system. The method includes selecting, by a user terminal, a target mainframe computing system from a plurality of target mainframe computing systems for execution of a mainframe workflow process having a plurality of workflow tasks, and transmitting the plurality of workflow tasks to the selected target mainframe computing system over a communication network. The method also includes storing the plurality of workflow tasks, in a workflow file repository at the target mainframe computing system, and checking the plurality of workflow tasks for inter-task dependencies.

Abstract: Various systems, methods, and media for facilitating selection of a transaction mode are provided. User identification information, that identifies a user of a user device that performs an electronic transaction, is obtained. User accounts are determined based on the user identification information. Location information of the user device is also obtained, and a merchant is determined based on the location information of the user device. The user accounts are analyzed and a recommended user account is determined based on a result of the analyzing and the merchant. A notification to be displayed on the user device is generated, with the notification being configured to be used to complete the electronic transaction using the recommended user account.

Abstract: A method for distributing data process according to technical resource capacity availability and constraints across a network is disclosed. The method includes receiving, at a database, a feed request for processing by a computing resource, among a network of computing resources that are geographically dispersed. Further, the method includes identifying, among the network of computing resources, a computing resource for processing the feed request based on the at least one attribute and processing capacity of the computing resources, and assigning the feed request for processing to the identified computing resource in real-time and without predetermined assignment to process increase in data volume by leveraging remotely located and/or underutilized computing resources.

Abstract: Systems and methods for uniquely identifying and regularly authenticating users at login are disclosed. A method may include an authentication computer program receiving a user identifier for a user as part of a login attempt from a workstation computer program; communicating a multifactor authentication request to an authenticator application executed on a user mobile electronic device; receiving a response to the multifactor authentication request from the authenticator application; verifying that the response to the multifactor authentication request matches an expected value; and saving user activity data associated with the login attempt, and a user trust computer program calculating a user trust score based on the user activity data; determining that the user trust score is above a threshold; and authorizing the login attempt to the workstation and a user session on the workstation.

Abstract: An electronic device for automated image-based auditing of equipment cabinets may include a memory storing an imaging computer program; and a computer processor. The imaging computer program, when executed by the computer processor, may cause the computer processor to perform the following: receive a plurality images from an image capture device on a carriage, wherein the image capture device is configured to traverse an equipment cabinet and capture the plurality of images of equipment in the equipment cabinet; generate a single image by stitching the plurality of images together; receive data from a sensor on the carriage, wherein the sensor is configured to capture data from the equipment in the equipment cabinet; associate the data with a location in the equipment cabinet; compare the single image and the data to an expected image and expected data; and output a result of the comparison.

Abstract: Systems and methods for detecting code duplication are disclosed. In one embodiment, a method for detecting exact code snippet duplicates may include: (1) representing, by a code duplication detection computer program, each of a plurality of code snippets in a codebase as an abstract syntax trees; (2) featurizing, by the code duplication detection computer program, the abstract syntax trees into corpus feature vectors by converting the abstract syntax tree into vector representations; (3) generating, by the code duplication detection computer program, dense feature vectors from the corpus feature vectors using a dimension reduction technique; (4) identifying, by the code duplication detection computer program, exact duplicate code snippet matches by apply density-based clustering to the dense feature vectors; and (5) tagging, by the code duplication detection computer program, the exact duplicate code snippets.

Abstract: Various methods, apparatuses/systems, and media for understanding the recovery of business services due to loss of availability that occur in information technology infrastructure are provided. The system and method automatically predict or detect the probability of an availability incident, determine associated risk and impact using a machine learning model to enhance the determination of severity of an incident based upon technology component attributes data, incident history data or other metadata. The machine learning model also alerts and determines capacity requirements/availability of alternate infrastructure impacted to begin orchestrating recovery and the overall recovery time and potential data loss.

Abstract: In some aspects, the techniques described herein relate to a method including: defining a user experience based on one or more software services provided by a platform; defining a service level indicator based on service metrics data; tracking an execution of the user experience, wherein the tracking includes recording of metadata that is output by each software service, wherein the metadata is defined as a parameter of the service level indicator; calculating a value of the services level indicator; and determining whether the value of the service level indicator is lower than a threshold value of a service level objective associated with the service level indicator.

Abstract: A method for providing an artificial intelligence model to facilitate automated sentiment analysis is disclosed. The method includes receiving, via a graphical user interface, a seed term, the seed term relating to a language element that represents a theme; determining, by using a model, thematic terms that relate to the seed term; aggregating, via an application programming interface, data from sources based on a predetermined parameter, the predetermined parameter including a time parameter; identifying, by using the model, thematic mentions in the aggregated data, the thematic mentions corresponding to terms from among the thematic terms; linking, by using the model, the thematic mentions with a corresponding target; and determining, by using the model, a score for each of the linked thematic mentions.

Abstract: A method and a system for providing database resiliency are disclosed. The method includes receiving a set of data from one or more sources at a primary database. Next, the method includes continuously monitoring for a potential detection of at least one anomaly in the set of data based on at least one activity performed on the set of data. Next, the method includes transmitting a plurality of data logs associated with the set of data from the primary database to an intermediate log storage location. Next, the method includes introducing a predefined delay to the plurality of data logs at the intermediate log storage location prior to a transmission of the plurality of data logs to a recovery database. Thereafter, the method includes performing a standby switchover to the recovery database in an event the at least one anomaly is detected at the primary database.

Abstract: A method for automated data driven configuration management is provided. The method includes: receiving a set of data from a plurality of sources; automatically processing the received data into service data using at least one trained model; and routing the service data for configuration management.

Abstract: Various methods, apparatuses/systems, and media for mediating traffic between an APCR and a TPS. A processor intercepts all traffic between a plurality of APCR and a plurality of TPS; halts a TCP connection from an incoming transaction request; determines that the incoming transaction request has been originated from a particular APCR among the plurality of APCR; checks, based on determining, which TPS or its siblings the incoming transaction request should be routed to; executes, based on checking, a new TCP connection with either the TPS or its siblings; receives, based on the new TCP connection, a response from the connected TPS or its siblings; attaches the response to the halted TCP connection after intercepting the response; resumes the halted TCP connection; and receives the response by an APCR node of the particular APCR in a manner as if directly received from the TPS or its siblings.

Abstract: Various methods, apparatuses/systems, and media for generating platform and database agnostic queries are disclosed. A processor implements an object relational model to build a system as a query generator, and causes the query generator to: receive a configuration file that includes instructions to perform certain operations; interpret the configuration file; invoke, in response to interpreting the configuration file, a predefined API; and automatically generate, in response to invoking the API, a set of platform and database agnostic queries.

Abstract: Various methods, apparatuses/systems, and media for generating a data model are disclosed. A processor receives data from a plurality of data sources; displays, onto a graphical user interface (GUI), a plurality of selectable icons for receiving user input in selecting a set of attributes data related to generating a desired data model; receives user input of the selected set of attributes data; automatically creates an executable custom code based on the received data from the plurality of data sources and the selected set of attributes data; executes the custom code; calls, in response to executing, a backend platform for processing the received data from the plurality of data sources and the selected set of attributes data; and automatically generates, in response to calling, the desired data model based on the processed received data and the selected set of attributes data.

Abstract: Systems and methods for cloud federated token just in time authorization are disclosed. A method may include: (1) receiving, by a cloud authentication services computer program, authenticating information for a user from an active directory federation service computer program; (2) querying, by the cloud authentication services computer program, a plurality of backend services to validate the authenticating information; (3) communicating, by the cloud authentication services computer program, validation to the active directory federation service computer program, wherein the active directory federation service computer program is configured to generate a security token comprising one or more assertion, wherein the assertion comprises a limit on a session with the user at a cloud platform, and wherein the cloud platform is configured to receive the security token and a trusted federated endpoint executed by the cloud platform is configured to enforce the limit on the session.

Abstract: A method for removing uninterested attributes from multi-modality data may include: receiving, by a multi-modality attribute removal computer program executed by an electronic device, multi-modality data comprising a plurality of modalities from a data source, wherein data in each modality are related; receiving, by the multi-modality attribute removal computer program, an uninterested attribute in the multi-modality data to remove; training, by the multi-modality attribute removal computer program, a modality-focused encoder for each modality of the multi-modality data to remove the uninterested attribute using a removal loss and a retention loss for the respective modality; receiving, by the multi-modality attribute removal computer program, a multi-modality data set for processing; and processing, by the multi-modality attribute removal computer program, the multi-modality data set using the modality-focused encoders, wherein the processing results in a processed multi-modality data set with the uninterest

Abstract: Systems and methods for distributed ledger-based settlement are disclosed. In one embodiment, a method may include: receiving settlement instructions from a first party providing a commodity and a second party providing cash; matching the settlement instructions; affirming the matched settlement instructions with the parties; a smart contact sending the affirmed settlement instructions to a commodity clearing bank; the smart contract receiving confirmation of a blockage of the commodity from the commodity clearing bank; the smart contact sending the affirmed settlement instructions to a cash clearing bank; the smart contract receiving confirmation of a blockage of the cash from the cash clearing bank; the smart contract executing the exchange of tokens for the commodity for tokens for the cash; and the smart contract writing the tokens for the cash to a wallet for the first party, and writing tokens for the commodity to a wallet for the second party.