Abstract: The disclosed technology relates to analyzing report infrastructure health to determine based on lineage the downstream tables and reports that may be impacted by an infrastructure failure to thereby improve reporting accuracy. An exemplary report management device may extract database table names identified in SQL queries. The SQL queries and report metadata are analyzed to identify driver and required tables, respectively. The database table names are stored in a table inventory and the database table names associated with one of the driver or required tables is marked. For each of the SQL queries comprising a target table, elements and source table names are extracted for source tables of the target table and an association is stored. Lineage data is generated based on the association when the report was not executed successfully. A graphical representation of the report lineage including a failed table and associated source table(s) is then output.

Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.

Abstract: An intelligent door lock system for a door at a dwelling. The intelligent door lock system includes a door status device is at the dwelling, an engine, an energy source, a memory, and a camera. The door status device is coupled to a drive shaft of a lock device to assist in locking and unlocking a lock of a lock device at the door. The lock device is coupled to the door status device and includes a bolt. The engine, the energy source, and the memory are coupled together. The camera is configured to record in response to door lock status.

Abstract: A computer-implemented method of identifying an individual independently of the individual's personally identifying information includes providing independent data stores for elements of personal identifying information for a population and fuzzy searching the data stores independently for the elements. Each data store associates each element value and its known variations with a unique static code. The search returns the unique static code associated with each of the elements found and a new independent code is generated if no code is found. The returned 10 codes are concatenated to form a person code. The person codes link information to produce a relationship between disparate data without a master database of people and PII.

Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.

Abstract: An intelligent door lock system for a door at a dwelling. The intelligent door lock system includes a door status device is at the dwelling, an engine, an energy source, a memory, and a camera. The door status device is coupled to a drive shaft of a lock device to assist in locking and unlocking a lock of a lock device at the door. The lock device is coupled to the door status device and includes a bolt. The engine, the energy source, and the memory are coupled together. The camera is configured to record in response to door lock status.

Abstract: The disclosed technology relates to analyzing report infrastructure health to determine based on lineage the downstream tables and reports that may be impacted by an infrastructure failure to thereby improve reporting accuracy. An exemplary report management device may extract database table names identified in SQL queries. The SQL queries and report metadata are analyzed to identify driver and required tables, respectively. The database table names are stored in a table inventory and the database table names associated with one of the driver or required tables is marked. For each of the SQL queries comprising a target table, elements and source table names are extracted for source tables of the target table and an association is stored. Lineage data is generated based on the association when the report was not executed successfully. A graphical representation of the report lineage including a failed table and associated source table(s) is then output.

Abstract: An intelligent door lock system coupled to a door at a dwelling. a door status device is at the dwelling. The door status device is coupled to a drive shaft of a lock device to assist in locking and unlocking a lock of a lock device at the door. The lock device is coupled to the door status device and includes a bolt. An engine, an energy source and a memory are coupled together. A camera is coupled to or part of the intelligent door lock system. The camera is configured to record in response to door lock status.

Abstract: A method performed by a processing system including at least one processor includes detecting that new data has been added to a repository of reusable machine learning models and machine learning model features, applying data protection to the new data, testing the new data for bias, merging at least a portion of the new data with stored data from the repository to build a new machine learning model in which the data protection is preserved, and publishing the new machine learning model in the repository.

Abstract: A computer-implemented method of identifying an individual independently of the individual’s personally identifying information includes providing independent data stores for elements of personal identifying information for a population and fuzzy searching the data stores independently for the elements. Each data store associates each element value and its known variations with a unique static code. The search returns the unique static code associated with each of the elements found and a new independent code is generated if no code is found. The returned codes are concatenated to form a person code. The person codes link information to produce a relationship between disparate data without a master database of people and PII.

Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.

Abstract: An intelligent door lock system is coupled to a door at a dwelling. A first sensor is at the dwelling. The first sensor is coupled to a drive shaft of a lock device to assist in locking and unlocking a lock of a lock device at a door. The lock device is coupled to the first sensor and the lock device includes a bolt. An engine, an energy source and a memory are coupled together. A magnetic sensor provides a reading or measurement used to determine a door open or closed status.

Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.

Abstract: A wireless access control system is provided to lock or unlock a first door at a dwelling of a user. A user remote access device accepts input based on haptic feedback or motion. The user remote access device includes a vibration mode provides an alert to the user of the remote access device. The user remote access device is configured to be in communication with an intelligent door lock system at the dwelling with the first door. The intelligent door lock system includes: a drive shaft, a circuit coupled to an engine configured to cause a rotation of the drive shaft, and an energy source coupled to the drive shaft. In response to the user remote access device accepting input based on haptic feedback or motion the bolt is caused to move and the first lock is locked or unlocked.

Abstract: An intelligent door lock system coupled to a door at a dwelling. a door status device is at the dwelling. The door status device is coupled to a drive shaft of a lock device to assist in locking and unlocking a lock of a lock device at the door. The lock device is coupled to the door status device and includes a bolt. An engine, an energy source and a memory are coupled together. A camera is coupled to or part of the intelligent door lock system. The camera is configured to record in response to door lock status.

Abstract: An intelligent door lock system coupled to a door at a dwelling. a door status device is at the dwelling. The door status device is coupled to a drive shaft of a lock device to assist in locking and unlocking a lock of a lock device at the door. The lock device is coupled to the door status device and includes a bolt. An engine, an energy source and a memory are coupled together. A camera is coupled to or part of the intelligent door lock system. The camera is configured to record in response to door lock status.

Abstract: An intelligent door lock system is coupled to a door at a dwelling. A first sensor is at the dwelling. The first sensor is coupled to a drive shaft of a lock device to assist in locking and unlocking a lock of a lock device at a door. The lock device is coupled to the first sensor and the lock device includes a bolt. An engine, an energy source and a memory are coupled together. A magnetic sensor provides a reading or measurement used to determine a door open or closed status.

Abstract: Systems and methods are provided for enhancing the terahertz power output of a terahertz beam while increasing its stability and its beam polarity by implementing a pair of pinched ripple electrodes and a small flat section in the middle of each electrode. By using tight control over the design parameters and by exploiting the plasmonic effect and the superradiance effect, systems and methods according to embodiments of the present disclosure can achieve a dramatic improvement in the terahertz output power and beam quality as well as the beam stability.

Abstract: A processing system including at least one processor may obtain at least one of a first machine learning model or a second machine learning model, deploy the at least one of the first machine learning model or the second machine learning model to a plurality of trained machine learning models for operating in parallel with respect to a same prediction task, obtain at least one data set, apply the at least one data set to the plurality of trained machine learning models, obtain the first result of the first machine learning model and a second result of the second machine learning model in accordance with the applying, store the first result of the first machine learning model and the second result of the second machine learning model, and provide an output in accordance with at least one of the first result or the second result.