Abstract: The present invention is directed to the development of novel photocrosslinking activity based probes (ABPs) and their uses. Specifically, ubiquitin-charged E2 conjugating enzymes are engineered and shown to be effective ABPs of RING ubiquitin E1 and E3 ligases as well as deubiquitination enzymes.

Abstract: Systems and methods for token and transaction management are disclosed. According to one embodiment, in an issuer wallet server comprising at least one computer processor, a method for token and transaction management may include: (1) receiving a update for an attribute for a Device WalletID or an issuer wallet application executed by an electronic device; (2) providing the update to the issuer wallet application; (3) providing the update to a third party wallet server associated with a third party wallet application executed by the electronic device, wherein the third party wallet server communicates the update to the third party wallet application; and (4) updating the attribute in the Device WalletID.

Abstract: Systems and methods for automated fraud-type identification and decisioning are disclosed. In one embodiment, a method may include: (1) receiving, from a fraud detection system, an identification of a fraudulent transaction with a merchant; (2) determining that the fraudulent transaction was conducted using a digital wallet; (3) determining that the fraudulent transaction is associated with a linked merchant account; (4) retrieving a transaction history with the merchant and determining that the fraudulent transaction is a result of merchant account take over by: (a) determining that the transaction history only includes valid transactions with the merchant prior to the fraudulent transaction; (b) determining that the transaction history includes only valid digital wallet transactions with the merchant prior to the fraudulent transaction; and (c) determining that the transaction history includes a digital wallet transaction. with the linked merchant account.

Abstract: Systems and methods for token and transaction management are disclosed. According to one embodiment, in an issuer wallet server comprising at least one computer processor, a method for token and transaction management may include: (1) receiving a update for an attribute for a Device WalletID or an issuer wallet application executed by an electronic device; (2) providing the update to the issuer wallet application; (3) providing the update to a third party wallet server associated with a third party wallet application executed by the electronic device, wherein the third party wallet server communicates the update to the third party wallet application; and (4) updating the attribute in the Device WalletID.

Abstract: Systems and methods for identifying and processing person-to-person payments are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for processing a transaction may include: (1) receiving, from a third-party payment platform and via a card association and an acquirer, a transaction request comprising a person-to-person payment indicator in a pass-through field in the transaction request; (2) updating a token transaction characteristic value to contain a person-to-person payment flag; and (3) applying a business rule to the transaction request based on the person-to-person payment flag.

Abstract: Embodiments of the invention relate to systems, methods, and computer program products for a high performance data copy utility that is operable to dynamically copy data from a source database to a target database in an object-relational database environment. High performance is realized by defining, prior to copying the data, performance boundaries of the source and target environment, such as the quantity of data (i.e., commit points) and quantity of parallel processes (i.e., parallel threads) applicable to a copy job. Moreover, the copying schema of the present invention allows for data to be copied from one database to another database without the need higher level privileges, such as database administrator (DBA) or data definition language (DDL), which would otherwise require changing the structure of the database. In this regard, embodiments of the present invention rely solely on lower-level data manipulation language (DML) privileges configured for inserting, updating and deleting data structures.

Abstract: A system for storing time series data includes an ingester that prepares metadata indices associated with blocks of incoming time series data and stores the blocks of data in a time series database and the indices in a separate index database. The time series database distributes storage of the data blocks among multiple data nodes. A query layer receives queries and uses the index database to determine which data blocks are needed to process the query, and then requests only those data blocks from the time series database. Processing of the query is performed within the time series database only on those data nodes that contain relevant data, and partial results are passed to an output layer for formation into a final query result.

Abstract: Time series data is received from a time series data repository and the time series data includes a plurality of sub-portions. The sub-portions of data are first sorted in chronological order to appear as if the data is being generated in real time and are then sent for analysis. The received sorted time series data is then analyzed to detect one or more predefined events or patterns in the data. When the predefined events or patterns are detected in the time series data by the analysis, a user or downstream analysis component is informed that the one or more predefined events or patterns have been found.

Abstract: A system for predicting events by associating time series data with other types of non-time series data can include a processor configured to receive a data stream including time series data transmitted from a sensor configured to measure an operating parameter of a component being monitored. The processor identifies sequences of interest in the time series data having predictive value. The processor compares the real-time data stream to a set of known historical patterns that act as effective leading indicators of different alarms and events. The processor extracts any identified sequences of interest from the time series data as an extracted event. The processor quantifies the relationship between the data of the extracted event and the known historical pattern by calculating a confidence level to denote a probability of occurrence of the event by comparing how closely the new time series data matches the data patterns associated with known events.

Abstract: A system for predicting events by associating time series data with other types of non-time series data can include a processor configured to receive a data stream including time series data transmitted from a sensor configured to measure an operating parameter of a component being monitored. The processor identifies sequences of interest in the time series data having predictive value. The processor compares the real-time data stream to a set of pre-existing event data that act as effective leading indicators of different alarms and events. The processor extracts any identified sequences of interest from the time series data as an extracted event. The processor quantifies the relationship between the data of the extracted event and the known historical pattern by calculating a confidence level to denote a probability of occurrence of the event by comparing how closely the new time series data matches the data patterns associated with known events.

Abstract: A method of performing data management in a high-speed data environment. The method includes collecting time-series information including multiple data types captured concurrently, and storing the collected time-series information in a process historian with organization, the organization occurring when the multiple data types are captured.

Abstract: Approaches are provided where, at a local computing device, time series data is received from an industrial component in a first format. This time series data additionally has a tag or identifier appended thereto and a quality setting. The tag is automatically converted to a descriptor used by an analytic system, and the time series data is converted to a format readable by the analytic system. This format is specified by at least a portion of an analytic system blueprint. The time series data is then transmitted to the analytic system such that the time series data and the descriptor are in a format that do not require additional conversions in order to be processed by the analytic system.

Abstract: Provided is a method and system for detecting changes in models applied to analyze time series data. A method includes receiving at a processor a data stream transmitted from a sensor configured to measure an operating parameter of a component being monitored, wherein the data stream comprises at least time series data. The method also includes analyzing the data stream to identify a sequence of interest in the time series data, searching metadata stored separately for an appropriate model to apply to the time series data, and selecting the appropriate model. Information about the selected appropriate model is carried forward with the time series data.

Abstract: Embodiments of the invention relate to systems, methods, and computer program products for a high performance data copy utility that is operable to dynamically copy data from a source database to a target database in an object-relational database environment. High performance is realized by defining, prior to copying the data, performance boundaries of the source and target environment, such as the quantity of data (i.e., commit points) and quantity of parallel processes (i.e., parallel threads) applicable to a copy job. Moreover, the copying schema of the present invention allows for data to be copied from one database to another database without the need higher level privileges, such as database administrator (DBA) or data definition language (DDL), which would otherwise require changing the structure of the database. In this regard, embodiments of the present invention rely solely on lower-level data manipulation language (DML) privileges configured for inserting, updating and deleting data structures.

Abstract: A first attribute is associated with a first data storage device and a second attribute is associated with a second data storage device. The first data storage device stores first time series data and the second data storage device stores second time series data. In parallel, the first attribute is applied to the first time series data and the second attribute is applied to the second time series data. The application is effective to cause an alteration of one or more of the first time series data or the second time series data. The alteration may be a thinning or reduction of the time series data.

Abstract: Characterization information related to time series data is obtained. A data storage rule is automatically determined based upon the characterization information. The rule defines at least one of a location for the storage of the time series data and a format for storage of the time series data. The rule is applied to the time series data and the time series data is stored according to the rule.

Abstract: Time series data is identified that is related to a predetermined characteristic and the predetermined characteristic being at least one of an identity of a sensor or a time range. Based upon the identified time series data, the time series data is moved to selected ones of the plurality of separate data storage devices, and the movement is temporary for processing purposes. In parallel, queries are performed on the time series data on each of the selected ones of the plurality of separate data storage devices to obtain a plurality of results. The plurality of results are aggregated.

Abstract: A first query and a second query are received. The first query and the second query are evaluated and, based upon the evaluating, identifying first time series data required to fulfill the first query and second time series data required to fulfill the second query. An extent of overlap of the first time series data and the second time series data is determined. When the extent of overlap exceeds a predetermined threshold, the overlapping data is retrieved from a plurality of data storage devices in parallel, the data retrieved across all of the plurality of storage devices via a single read operation.

Abstract: A user query or analytic user is received. The user query or analytic requires one or more portions of time series data from a plurality of transient memories. The time series data is linked together across the transient memories devices. A location of one or more portions of the time series data is identified at the plurality of transient memories. One or more portions of the time series data is automatically retrieved from the transient memories.

Abstract: A data storage policy is determined. Time series data is received and a score for the time series data is determined. The score prioritizes the time series data according to a likelihood the time series data will be needed for future use. Based upon the data storage policy and the score, the time series data is stored at one or more data storage devices. The score is updated over time to reflect changing priorities regarding the use of the data.