Abstract: A set of resource requests that each includes authorization-supporting data for receiving a requested resource can be received. For each request, augmenting data associated with part of the data is retrieved, and it is determined whether access is authorized based on the augmenting data and the authorization-supporting data. A machine-learning model is trained using representations of the set of resource requests and the authorization determinations. Additional requests are processed by the trained model to generate corresponding authorization outputs. One or more identifiers to flag for inhibition of resource access are determined based on the authorization outputs. Upon detecting that a new resource request to access a particular resource includes an identifier of the one or more identifiers, a new authorization output is generated to inhibit access to the particular resource.

Abstract: Provided is a process including: receiving a data token to be passed from a first node to a second node; retrieving machine learning model attributes from a collection of one or more of the sub-models of a federated machine-learning model; determining based on the machine learning model attributes, that the data token is learning relevant to members of the collection of one or more of the sub-models and, in response, adding the data toke to a training set to be used by at least some members of the collection of one or more of the sub-models; determining a collection of data tokens to transmit from the second node to a third node of the set of nodes participating in a federated machine-learning model; and transmitting the collection of data tokens.

Abstract: A set of resource requests that each includes authorization-supporting data for receiving a requested resource can be received. For each request, augmenting data associated with part of the data is retrieved, and it is determined whether access is authorized based on the augmenting data and the authorization-supporting data. A machine-learning model is trained using representations of the set of resource requests and the authorization determinations. Additional requests are processed by the trained model to generate corresponding authorization outputs. One or more identifiers to flag for inhibition of resource access are determined based on the authorization outputs. Upon detecting that a new resource request to access a particular resource includes an identifier of the one or more identifiers, a new authorization output is generated to inhibit access to the particular resource.

Abstract: An example system can include: at least one processor; and non-transitory computer-readable storage storing instructions that, when executed by the at least one processor, cause the system to: generate an ingestion manager programmed to ingest data associated with a job; and generate a logging manager programmed to capture metadata associated with the job; wherein the ingestion manager is programmed to automatically retry the job based upon the metadata captured by the logging manager.

Abstract: A method may include receiving, at a listener channel, an event described by a message, determining, using the message, a subscriber of the listener channel, determining, using a delivery preference of the subscriber, an adapter to deliver the message, and dispatching, via the adapter, the message to the subscriber.

Abstract: Computer-automated systems and methods that retain requests for information until documents containing the information are released at a later date. Release of the documents can trigger natural language understanding of the documents to be automatically performed and responses to the requests to be generated. In some examples, the responses include recommendations for taking or not taking financial actions relating to the request and the information.

Abstract: A set of resource requests that each includes authorization-supporting data for receiving a requested resource can be received. For each request, augmenting data associated with part of the data is retrieved, and it is determined whether access is authorized based on the augmenting data and the authorization-supporting data. A machine-learning model is trained using representations of the set of resource requests and the authorization determinations. Additional requests are processed by the trained model to generate corresponding authorization outputs. One or more identifiers to flag for inhibition of resource access are determined based on the authorization outputs. Upon detecting that a new resource request to access a particular resource includes an identifier of the one or more identifiers, a new authorization output is generated to inhibit access to the particular resource.

Abstract: This disclosure relates generally to a method and system for real time monitoring and forecasting of fouling of an air preheater (APH) in a thermal power plant. The system is deploying a digital replica or digital twin that works in tandem with the real APH of the thermal power plant. The system receives real-time data from one or more sources and provides real-time soft sensing of intrinsic parameters as well as that of health, fouling related parameters of APH. The system is also configured to diagnose the current class of fouling regime and the reasons behind a specific class of fouling regime of the APH. The system is also configured to be used as advisory system that alerts and recommends corrective actions in terms of either APH parameters or parameters controlled through other equipment such as selective catalytic reduction or boiler or changes in operation or design.

Abstract: According to some embodiments, methods and systems may include a package manager chart file repository storing charts associated with a container orchestration system. A package manager platform, coupled to the package manager chart file repository, may access a first parent chart from the package manager chart file repository and determine that the first parent chart includes a dependency manifest. The package manager platform may then construct a Directed Acyclic Graph (“DAG”) based on the dependency manifest. Container orchestration system objects, including those associated with sub-charts of the first parent chart, may then be deployed in accordance with a topological ordering of the DAG.

Abstract: Various embodiments discussed herein are directed to improving existing technologies by extracting or detecting identifiers from a page, regardless of the device or platform a user is using, and then anonymizing such identifiers to determine if the same user accessed different pages or if the current user of a current computer session is a same user as in past computer sessions.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Certain aspects of the present inventive concept are directed towards a data analysis system. The data analysis system includes a memory and one or more processors coupled to the memory, the one or more processors being configured to: obtain health information associated with at least one patient of a health facility; analyze the health information to determine a rate of health decline associated with one or more health parameters of the patient; generate at least one interface indicating whether the rate of health decline meets a threshold for each of the one or more health parameters, and output the at least one interface for display on a display device.

Abstract: Provided is a process including: writing, with a computing system, a first plurality of classes using object-oriented modelling of modelling methods; writing, with the computing system, a second plurality of classes using object-oriented modelling of governance; scanning, with the computing system, a set of libraries collectively containing both modelling object classes among the first plurality of classes and governance classes among the second plurality of classes to determine class definition information; using, with the computing system, at least some of the class definition information to produce object manipulation functions, wherein the object manipulation functions allow a governance system to access methods and attributes of classes among first plurality of classes or the second plurality of classes to manipulate objects of at least some of the modelling object classes; and using at least some of the class definition information to effectuate access to the object manipulation functions.

Abstract: According to some embodiments, methods and systems may include a package manager chart file repository storing charts associated with a container orchestration system. A package manager platform, coupled to the package manager chart file repository, may access a first parent chart from the package manager chart file repository and determine that the first parent chart includes a dependency manifest. The package manager platform may then construct a Directed Acyclic Graph (“DAG”) based on the dependency manifest. Container orchestration system objects, including those associated with sub-charts of the first parent chart, may then be deployed in accordance with a topological ordering of the DAG.

Abstract: Provided is a process including: writing, with a computing system, a first plurality of classes using object-oriented modelling of modelling methods; writing, with the computing system, a second plurality of classes using object-oriented modelling of governance; scanning, with the computing system, a set of libraries collectively containing both modelling object classes among the first plurality of classes and governance classes among the second plurality of classes to determine class definition information; using, with the computing system, at least some of the class definition information to produce object manipulation functions, wherein the object manipulation functions allow a governance system to access methods and attributes of classes among first plurality of classes or the second plurality of classes to manipulate objects of at least some of the modelling object classes; and using at least some of the class definition information to effectuate access to the object manipulation functions.

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: Provided is a process of modeling methods organized in racks of a machine learning pipeline to facilitate optimization of performance using modelling methods for implementation of machine learning design in an object-oriented modeling (OOM) framework, the process including: writing classes using object-oriented modelling of optimization methods, modelling methods, and modelling racks; writing parameters and hyper-parameters of the modeling methods as attributes as the modeling methods; scanning modelling racks classes to determine first class definition information; selecting a collection of rack and selecting modeling method objects; scanning modelling method classes to determine second class definition information; assigning racks and locations within the racks to modeling method objects; and invoking the class definition information to produce object manipulation functions that allow access the methods and attributes of at least some of the modeling method objects, the manipulation functions being configur

Abstract: Provided is a process that includes sharing information among two or more parties or systems for modeling and decision-making purposes, while limiting the exposure of details either too sensitive to share, or whose sharing is controlled by laws, regulations, or business needs.

Abstract: A method for automated booking of an on-demand service in a multimodal journey includes receiving information related to a multimodal trip plan for a commuter trip. The multimodal trip plan includes a plurality of segments, and the plurality of segments include an on-demand service segment that requires an on-demand service vehicle as the mode of transport. The method also includes receiving real-time information relating to a location of the commuter from one or more location tracking sensors, determining an estimated time of arrival of the commuter at a transfer point for transfer to the on-demand service segment by analyzing the real-time information, identifying a time of availability of an on-demand service vehicle at the transfer point (as a function of a time of booking), and determining an optimal time of booking of the on-demand service vehicle based on the estimated time of arrival and the time of availability.