Abstract: A method for optimizing network parameters of a network includes receiving, via a network probe in communication with the network, a service type, key performance indicators associated with the service type, and network parameter information of the network. A customer satisfaction score associated with the service type and the associated key performance indicators is determined. When the customer satisfaction score is determined to be below a threshold, one or more network parameters leading to the customer satisfaction score being below the threshold are determined from the network parameter information. The one or more network parameters are adjusted, via a network configuration interface in communication with the network, to thereby increase the customer satisfaction score.

Abstract: A rapid application developer system is disclosed that provides a development platform configured to generate an application manifest document for developing a new target application within a certain industry. The application manifest is generated based on components identified from previously developed applications within the same industry as the target application.

Abstract: A device may receive a plurality of data items related to an entity to be analyzed. The device may store the plurality of data items using a storage device based on receiving the plurality of data items. The device may analyze the plurality of data items to identify complexity factors related to the entity based on storing the plurality of data items. The complexity factors may positively impact the entity or negatively impact the entity. The device may generate a set of action items associated with modifying operations of the entity to impact the complexity factors related to the entity. The set of action items may be associated with positively impacting the entity. The device may perform a set of actions based on the set of action items to positively impact the entity.

Abstract: A device may process application data or historical data to identify a set of metrics to be used to analyze a set of applications or to identify baseline values for the set of metrics. The device may determine a score, for each application of the set of applications, based on values for the set of metrics for the each application of the set of applications. The device may determine a refined classification for the each application of the set of applications based on the historical data or information related to the classification or the score. The device may generate a set of recommendations related to optimizing a current deployment of the set of applications. The device may perform an action to implement the set of recommendations related to optimizing the current deployment of the set of applications.

Abstract: A device may receive information identifying a development project. The device may determine a set of scripts to assess program code of the development project. The device may execute the set of scripts to perform a project assessment of the development project after determining the set of scripts. The device may generate a user interface including information identifying a result of executing the set of scripts. The result may include information associated with detecting an execution type of error or information associated with detecting a non-execution type of error. The device may communicate with a client device to provide the user interface for display via the client device.

Abstract: A system may provide a smart contract interface for blockchain interoperability. The system receive selection parameters indicative of a furnisher blockchain and a receiver blockchain. The system may obtain, based on the selection parameters, furnisher synchronization logic and receiver synchronization logic. The furnisher synchronization logic may include instructions to lock token data on the furnisher blockchain. The receiver synchronization logic may include instructions to commit token data to the receiver blockchain. The system may generate an interoperability smart contract comprising the furnisher synchronization logic and the receiver synchronization logic. The system may deploy the interoperability smart contract to a furnisher blockchain and the receiver blockchain.

Abstract: A system may receive a request to perform a token exchange between a first account and a second account. A selected token for the token exchange may be associated with the first account. A hash of the selected token may be stored on a furnisher blockchain of a first distributed ledger. The system may generate a new token and a hash of the new token. The system may generate a shielded exchange instruction, the shielded exchange instruction comprising the hash of the new token and a zero-knowledge proof, wherein the zero-knowledge proof is indicative of the selected token being associated with the first account. The system may submit the shielded exchange instruction to a distributed ledger technology platform to cause execution of a furnisher smart contract and a receiver smart contract. Each of the smart contracts are configured to separately verify the zero-knowledge proof and update corresponding blockchains to consummate and record the token exchange.

Abstract: Techniques are described for iteratively adjusting data processing decision results in accordance with rules. In some implementations, the applied rules may be data ethics rules associated with particular demographic groups, such as users in a particular geographic location, users in a particular age range, and so forth. The rules may describe the manner in which data, such as data that describes or identifies individuals, is collected, stored, analyzed, applied, manipulated, and/or destroyed. The various stages of data handling may be described as a data supply chain, and a set of rules may apply to the handling of data at one or more stages of the data supply chain. The rules may enforce data privacy considerations and/or other types of constraints on data handling.

Abstract: Techniques are described for aggregating data generated by multiple platforms of different types. A particular user (e.g., end-user) may interact with multiple individual (e.g., siloed) platforms of different types and/or that support different business purposes or industries. The individual platforms may generate data describing and/or resulting from these interactions. The data may be received, ingested, and processed by a super-platform. The super-platform may generate aggregate data by aggregating the data received from different individual platforms. Data aggregation may be performed on data that is generated by different individual platforms and that is associated with a particular user or multiple users. Aggregation may also be performed on data that is independent of any particular user, such as sensor data that describes an environment in proximity to the platform.

Abstract: Systems, apparatuses, and methods directed to one or more sensors configured to detect data related to at least one of a patient, an environment to which the patient is exposed, and an environmental resource, obtain the detected data, and transmit the detected data. The system also comprises a server configured to receive the detected data, the server comprising: a receiver configured to receive the detected data; and a processor coupled to a memory, the processor configured to: calculate a risk score for the detected data; calculate an overall risk score based on the risk score for the detected data; and determine one or more actions to be performed based on at least the overall risk score, the one or more actions reducing risk value, the risk value identifying the likelihood that the patient will contract a hospital acquired condition (HAC) or a hospital acquired infection (HAI).

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing performance engineering are disclosed. In one aspect, a method includes the actions of providing, to a cloud computing system that is configured to implement multiple different types of virtual computing nodes, an instruction to execute an application on a virtual computing node that is a first type of virtual computing node of the multiple different types of virtual computing nodes. The actions further include determining computing performance parameters of the virtual computing node. The actions further include determining to execute the application on both the virtual computing node and an additional virtual computing node. The actions further include selecting, from among the multiple different types of virtual computing nodes, a second type of virtual computing node.

Abstract: A device obtains prescription information relating to a medication in a container. The device causes a camera device of the device to obtain image data relating to the medication and a weighing device of the device to obtain weight data relating the medication. The device sends the prescription information, the image data, and the weight data to a different device to cause the different device to verify the medication using a machine learning model. The device receives information concerning the medication and automatically generates, based on the information concerning the medication, a message concerning the medication, wherein the message includes instructions on how much of the medication a user of the device is to take. The device causes the device or an additional device to present the message.

Abstract: This document describes systems, methods, devices, and other techniques for accessing a first video showing a first two-dimensional scene of an environment and captured by a first camera located in the environment having a first field of view; detecting one or more objects shown in the first video; analyzing the first video to determine one or more features of each of the detected objects shown in the first video; accessing a second video showing a second 2D scene of the environment and captured by a second camera located in the environment having a second field of view; detecting one or more objects shown in the second video; analyzing the second video to determine one or more features of each of the detected objects shown in the second video; and correlating one or more objects shown in the first video with one or more objects shown in the second video.

Abstract: A device may select an enterprise content management (ECM) system for monitoring. The ECM system may include a set of subsystems. The device may monitor the set of subsystems of the ECM system based on selecting the ECM system for monitoring. The device may perform a set of health checks on the set of subsystems based on monitoring the set of subsystems. The set of health checks may include a validation of a set of network addresses associated with the set of subsystems, an analysis of a set of log files associated with the set of subsystems, and a determination of a set of metrics associated with the set of subsystems. The device may generate a health check report based on the set of health checks. The device may provide the health check report.

Abstract: A device may instrument a codebase associated with a software application. The device may execute a test on the instrumented codebase as the instrumented codebase executes, wherein the instrumented codebase generates test data based on the test being executed. The device may generate, based on the test data, a live graphical model of the codebase from a composite graphical model of the codebase, wherein the composite graphical model includes historical information, associated with the codebase, mapped to a graphical model of the codebase. The device may generate an extended reality rendered view of the live graphical model. The device may provide, to an extended reality device, the extended reality rendered view of the live graphical model for display by the extended reality device.

Abstract: A device may determine probabilities for test scripts associated with a test to be executed on a software element, where a respective probability is associated with a respective test script, indicates a likelihood that the respective test script will be unsuccessful in a test cycle, and is determined based on historical test results, associated with the software element, for the respective test script. The device may generate, based on the probabilities, a test script execution order, of the test scripts, for the test cycle, and may execute, based on the test script execution order, the test on the software element in the test cycle. The device may dynamically generate, based on results for the test in the test cycle, an updated test script execution order, and may execute, based on the updated test script execution order, the test on the software element in the test cycle.

Abstract: Methods, systems, and apparatus for improving exchange systems. In one aspect, a method includes receiving data representing an exchange problem; determining, from the received data, an integer programming formulation of the exchange problem; mapping the integer programming formulation of the exchange problem to a quadratic unconstrained binary optimization (QUBO) formulation of the exchange problem; obtaining data representing a solution to the exchange problem from a quantum computing resource; and initiating an action based on the obtained data representing a solution to the exchange problem.

Abstract: A device may receive, from sources, data objects identifying values relating to entities for which a risk indicator is to be determined, and may process the data objects to generate an analytical record that identifies relationships between values of different data objects. The device may determine, based on the analytical record, the risk indicator corresponding to one or more entities. The risk indicator may be determined based on at least one of: a comparison between the analytical record and a data structure that identifies expected values of one or more of the data objects; an identification of a group of the entities, and an outlier from the group of the entities based on the analytical record; or an identification of a change in behavior of the one or more entities based on the analytical record. The device may perform an action based on determining the risk indicator.

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: A distributed ledger technology (DLT) network may include a plurality of participant nodes. The participant nodes may respectively validate a distributed ledger based on a consensus protocol. A blockchain export system may send, to a data receiver not included in the DLT network, a participant public key for a participant node of the DLT network. The blockchain export system may receive, from the data receiver, a request to share token data stored in a blockchain of the distributed ledger. The blockchain export system may generate a certification that the token data is stored on the blockchain. The certification may include a digital signature based on a participant private key paired to the participant public key. The blockchain system may transmit the certification to the data receiver. The data receiver may verify the certification based on the participant public key.