Abstract: A dynamic tagging system facilitates the control, monitoring, and operation of technical components, such as virtual machines, in cloud environments. The dynamic tagging system performs an analysis on unstructured metadata tags linked to the technical components. The unstructured metadata tags may be created for technical components by authorized operators of the technical components, for instance. The dynamic tagging system may analyze an individual unstructured metadata tag or a combination of unstructured metadata tags assigned to a technical component to automatically trigger any pre-configured control, monitoring or operational actions for the technical component. As one example, the dynamic tagging system detects a trigger condition for an action trigger to perform automated electronic communications between any selected entities to convey information about the technical component.

Abstract: The present specification is related to analysis of digital circuits for assessing a fault sensitivity of a digital logic circuit. An example method includes: obtaining a set of input vectors that represent possible inputs to the digital logic circuit; for each output gate of the plurality of digital logic gates: (i) for each input vector of the set of input vectors, determining a cumulative output delay for the output gate, and (ii) determining an averaged cumulative output delay for the output gate by averaging the cumulative output delays for the output gate that were determined for multiple input vectors of the set of input vectors; generating a fault sensitivity score for the digital logic circuit based on the averaged cumulative output delays for the output gates of the digital logic circuit; and providing the fault sensitivity score.

Abstract: A system may obtain a test utterance sample configured to test a virtual agent. The system may tokenize the test utterance sample into a sample tokens. The system may determine, based on a natural language processing framework, a synonymous set (synset) for at least one of the sample tokens. The synset may include a lemma tokens. The system may obtain a contextual corpus relevant to a natural language context of the virtual agent. The system may select a lemma token that is included in the corpus tokens. The system may generate a new test utterance comprising the selected lemma token. The system may insert the new test utterance in a test repository. The system may communicate the new test utterance to the virtual agent to test the virtual agent based on the new test utterance. If the virtual agent fails a test in respect to the new test utterance, the corpus of the virtual agent can be retrained.

Abstract: Systems and methods for entitlement tracking and control with blockchain technology are provided. A server node may receive usage information indicating usage of a licensed component by a remote device. The server node may generate a datablock that includes the usage information and append the datablock to a blockchain. The server node may acquire, from the blockchain, a license smart contract. The license smart contract may include control logic to control access to the license component. The server node may control access to the license component by the remote device based on the usage information and the control logic.

Abstract: According to an example, product test orchestration may include accessing user-defined information of a product to be tested and identifying, based upon the accessed user-defined information, a set of devices on which the product is to be tested and a set of testing tools to be implemented on the identified set of devices to test the product. Product test orchestration may further include generating test operations for the identified set of testing tools to be implemented on the identified set of devices, executing the generated test operations on the identified set of devices, tracking results of the executed test operations, and generating a report of the tracked results.

Abstract: A system for detecting and preventing execution of malware on a target system includes an interface for receiving training data. The training data includes domain names known to be legitimate and domain names known to be associated with malware. The system is configured to train a first model to classify the domain names in the training data as being legitimate domain names or malware-associated domain names using a supervised learning methodology. The system configured to train a second model to predict a correct domain name associated with domain names in the training data using an unsupervised learning methodology. The system configured to train a third model to classify the domain names in the training data as being legitimate domain names or malware-associated domain names based on an output of the first learning model and an output of the second learning model.

Abstract: A multi-layer storage class placement stack may generate a token containing storage class placement prescriptions for controlling the placement of stored items within a selection of classes for storage. An input layer of the storage class placement stack may generate time-collated activity data based on historical access data, volume metric data, and/or tagging data. The time-collated activity data may include data groupings using timestamps or other timing indicators. A transformation layer may further process the time-collated activity data to generate defined-period summation data that provides summary detail for defined durations across a period of analysis. The defined-period summation data may be used by a prescriptive engine layer to generate prescriptions for placement of individual stored items by associating the prescriptions with storage identifiers for the individual items.

Abstract: A system for generating a document includes a user interface processing subsystem configured to generate an interface configured to receive one or more commands. The commands are provided in at least one of an audio format and a textual format. The user interface processing subsystem is configured to provide at least one response to the commands in at least one of: a graphical, audio, and textual format. A natural language processing subsystem of the system is configured to receive and convert the one or more commands into annotated structured text. A search engine of the system is configured to receive the annotated structured text and search a document database for one or more documents related to the annotated structured text.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for predictive modeling for adjusting initial values are disclosed. In one aspect, a method includes the actions of accessing transaction history data that indicates one or more transaction details associated with the transaction, a predicted value, and a final value. The actions further include determining a difference value between the predicted value and the final value. The actions further include generating a predictive model that is trained to estimate. The actions further include receiving one or more transaction details and a predicted value associated with a subsequently received transaction. The actions further include providing the one or more transaction details as input to the predictive model. The actions further include receiving an adjustment value to apply to the predicted value. The actions further include providing, for output, data indicating the adjustment value.

Abstract: Hardware acceleration supports complex software processes. In particular, a hardware security module provides encryption support for transaction chains. In one implementation, the security module circuitry provides high-speed security features and acceleration of the security features for blockchain processing.

Abstract: Systems, methods, devices, and other techniques for placing and rendering virtual objects in three-dimensional environments. The techniques include providing, by a device, a view of an environment of a first user. A first computing system associated with the first user receives an instruction to display, within the view of the environment of the first user, a virtual marker at a specified position of the environment of the first user, the specified position derived from a second user's interaction with a three-dimensional (3D) model of at least a portion of the environment of the first user. The device displays, within the view of the environment of the first user, the virtual marker at the specified position of the environment of the first user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for combining biometric data are disclosed. In one aspect, a method includes the actions of accessing one or more synthetic biometric data samples. The actions further include identifying data that indicates characteristics of each of the one or more biometric data samples and data that indicates a quality score of each of the one or more biometric data samples. The actions further include identifying target parameters of a synthetic biometric database. The actions further include comparing the target parameters of the synthetic biometric database to the characteristics of each of the one or more biometric data samples and to the quality score of each of the one or more biometric data samples. The actions further include selecting, for the synthetic biometric database, a subset of the synthetic biometric data samples.

Abstract: A device may receive one or more data models that have been trained on a set of historical network performance indicators. The set of historical network performance indicators may include metrics associated with measuring network performance for one or more data centers. The device may receive network data for a group of user devices that are actively using the one or more data centers for network services. The device may determine a set of network performance indicators for the one or more data centers. The device may generate, by providing the set of network performance indicators as input to the one or more data models, one or more recommendations associated with improving network performance. The device may perform, after generating the one or more recommendations, one or more actions associated with improving network performance.

Abstract: Embodiments provide systems and methods for identifying and mitigating outlier network activity. In embodiments, network activity by a plurality of users may be monitored and, based on the monitoring, a plurality of data sets may be compiled. Each of the plurality data sets may include information representative of activity by the plurality of users. A network model representative of at least a portion of the network activity may be constructed based on one or more of the plurality of data sets. The network model may be evaluated against a set of rules to produce outputs that include at least one of: a set of classifications, a set of link metrics, and a set of communities. Decision engine logic may be executed against the outputs to identify outlier network activity. In response to identifying outlier network activity, operations to mitigate the identified outlier network activity may be executed.

Abstract: Complex computer system architectures are described for utilizing a knowledge data graph comprised of elements, and selecting a discovery element to replace an existing element of a formulation depicted in the knowledge data graph. The substitution process takes advantage of the knowledge data graph structure to improve the computing capabilities of a computing device executing a substitution calculation by translating the knowledge data graph into an embedding space, and determining a discovery element from within the embedding space.

Abstract: Implementations include actions of receiving consumer-specific data and ID-specific data from an identification presented by a consumer to a vending machine, processing at least a portion of the ID-specific data to determine one or more of whether the identification is unexpired and whether the identification is authentic, and serving the consumer from the vending machine at least partially in response to determining that the identification is unexpired and that the identification is authentic and determining that the consumer is authentic relative to the identification.

Abstract: A device may receive data from a data source and identify attributes included in the received data. The device may provide, to a user device, a user interface providing user interface elements that enable, by interaction with the user interface elements, selection of at least one attribute, of the attributes, for use by a data module. In addition, the device may receive, from the user device, information identifying the data module, the data module: being configured to process the at least one attribute and defining a function to be performed by a data processing pipeline. Further, the device may activate the data module for use by the data processing pipeline implemented by the device and perform an action on incoming data using the data processing pipeline and the data module.

Abstract: A method for tracking components of equipment. The method includes generating a first record in a component tracking data store of a component tracking system for storing original constituent component identification information that specifies original constituent components of the equipment, and a second record in the component tracking data store of the component tracking system for storing replacement component identification information that specifies a replacement component that replaces a component of the original constituent components of the equipment. The method further includes receiving a request for a current listing of components in the equipment and locating records in the component tracking data store of the component tracking system associated with the equipment.

Abstract: Implementations directed to reducing data flow between an AP, and a RPA platform include receiving, by a platform-specific adapter, a set of data records, providing a data change tuple including an identifier, and a hash value, providing a sub-set of data records from the second set of data records based on comparing hash values of data change tuples to a set of stored hash values, the sub-set of data records including fewer data records than the second set of data records, and each data record in the sub-set of data records including a change indicator, determining, by the platform-specific adapter, a tag for each data record in the sub-set of data records based on a respective change indicator, and transmitting a set of messages to the AP, the set of messages communicating tagged data records of the first set of data records, and the sub-set of data records.

Abstract: A system for providing secure access to digital resources is provided that utilizes a blockchain platform. Using this blockchain platform, digital resource vendors create new digital tracking ledgers for their digital resource products such that updates to the digital resource products are accessible directly from a blockchain. Accordingly, these updates are deliverable in a protected and secure manner to consumers of the digital resources.