Abstract: The disclosed embodiments include computerized methods and systems, including computer programs encoded on a computer storage medium, for objectively characterizing an impact of an intervention on individuals or groups. For example, a computing system may obtain, and store in a data lake, intervention data identifying interventions, and objective data characterizing an impact of these interventions on at least one individual. The computer system may also populate a queryable interface with query parameters (e.g., at least one of the interventions and at least a portion of the objective data), which may be presented to a user via a device. The computer system may obtain stored intervention and objective data consistent with a received query, which may be provided to the device for presentation to the user. The disclosed embodiments also provide a visual representation of trends in the stored data and candidate interventions the address the identified trends without user input.

Abstract: A device may receive a plurality of data objects from a plurality of sources; identify text data, image data, and location data of the plurality of data objects; identify relevant data objects, of the plurality of data objects, based on the text data, and/or based on the image data, based on the location data, and/or based on comparing the text data, the image data, and the location data to a predefined element that identifies values relevant to a particular group or subject area; assign scores to the relevant data objects based on the text data, the image data, and the location data; aggregate the scores, as one or more aggregated scores, with regard to one or more users associated with the relevant data objects; and/or perform one or more actions based on the one or more aggregated scores associated with the one or more users.

Abstract: An intelligent automatic license plate recognition (IALPR) system implements technical solutions that improve the accuracy of automatic license plate recognition. The IALPR analyzes an image of a vehicle proximate to a toll collection point using optical character recognition (OCR), and determines candidate license plate identifications based, at least in part, on the corresponding OCR confidence level. The IALPR can also perform fingerprinting for candidate license plate images and matching analysis with a knowledge base, resulting in additional confidence levels. The IALPR can also perform behavioral analysis on the candidate license plate identifications, including trip context analysis, historical behavioral analysis, or other analytics. The IALPR can generate an overall confidence level for the candidate license plate identifications responsive to the OCR and vehicle fingerprint confidence levels and the behavioral analysis.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for recognizing object sub-types in images. One of the methods includes receiving training data; selecting training data for an image; determining whether to randomly permute a value of a property of the selected image; providing, to a deep neural network, the particular training data or the randomly permuted particular training data; receiving, from the deep neural network, output data indicating a predicted label for an object sub-type for an object depicted in the selected image, and a confidence score that represents a likelihood that the object has the object sub-type; updating one or more weights in the deep neural network using an expected output value, the predicted label, and the confidence score; and providing the deep neural network to a mobile device for use detecting whether one or more images depict objects having the particular object sub-type.

Abstract: A system may include a client device. The client device may receive, from a set of vending devices and via a network connecting the set of vending devices with the client device, sensor data relating to a status of the set of vending devices. The client device may generate a user interface associated with providing information identifying the status of the set of vending devices. The client device may provide, for display, the user interface based on generating the user interface. The client device may detect, based on providing the user interface, a selection of an adjustment that is to be performed for a particular vending device of the set of vending devices. The client device may transmit, via the network, an instruction to the particular vending device to cause the adjustment to be performed for the particular vending device.

Abstract: An extensible key management system includes a developer services portal for accessing an application. The system may identify initiation via the developer services portal of an association of the application with an external API of a third party provider service and automatically obtain a sub-key for the external API from the third party provider service on behalf of a developer of the application. The sub-key may be obtained in accordance with authorization provided by a master key previously provided from the third party provider service. The system may map an association between the sub-key, the application and the external API and store the association. Upon receipt of a service call message resulting from a request from a user device executing the application, the system may identify and replace a developer API key included in the service call message with the sub-key based on the stored association.

Abstract: Computerized methods and systems, including computer programs encoded on a computer storage medium, may detect event shown within digital video content captured by one or more video cameras, and correlate these detected events to real-world conditions that may not be captured within the digital video data. For example, a computing system may detect events shown within digital video content captured by one or more video cameras, and may obtain data that identifies at least one external event. The computer system may establish a predictive model that correlates values of event parameters that characterize the detected and external events during a first time period, and may apply the predictive model to an event parameter that characterizes an additional event detected during a second time period. Based on an outcome of the predictive model, the computing system may determine an expected value of the external event parameter during the second time period.

Abstract: According to examples, software integration testing with an unstructured database may include determining a driver class file for an integration testing tool to connect to a specified unstructured database. A connectivity driver may be generated for the specified unstructured database. Dependency files may be determined for retrieval of data from the specified unstructured database and update of the data in the specified unstructured database. The driver class file, the connectivity driver, and the dependency files may be stored in a library of the integration testing tool. A connection may be established between the integration testing tool and the specified unstructured database. A query may be sent to the specified unstructured database for execution, and query results may be received based on performing a function when the query is executed. The query results may be compared to validation data to determine whether the function operates in a determined manner.

Abstract: According to an example, intent and bot based query guidance may include receiving a query associated with a domain, and identifying, based on an analysis of the query, an intent of the query by extracting an action associated with the query and an entity associated with the query. An intent model associated with the query may be generated based on a mapping of the action and the entity with a domain model of the domain. An intent domain specific language representation of the intent model associated with the query may be generated. Based on an analysis of the intent domain specific language representation, a plurality of bots may be identified, and a parameterized bot chain may be generated to respond to the query. A runtime binding of bots of the parameterized bot chain may be performed, and invoked to generate the response to the query.

Abstract: A system may provide hardware acceleration for blockchain-based record entry. Client circuitry may provide record entry information to node circuitry. The node circuitry may compile the record entry information into a record entry for submission to blockchain management circuitry (BMC). The BMC may access a consensus operating procedure. The BMC may apply the consensus operating procedure to the record entry to gain append permissions for a blockchain. After completing the consensus operating procedure, the BMC may append a block generated based on the record entry to the blockchain. Accordingly, the system may ensure that blocks added to the blockchain were generated in compliance with the consensus operating procedure.

Abstract: Computerized methods and systems, including computer programs encoded on a computer storage medium, may detect events shown within digital video content captured by one or more video cameras during a prior time period, and predict an occurrence of an additional event during a future time period based on time-varying patterns among the detected events. For example, a computing system may detect events shown within digital video content captured by one or more video cameras, and may establish a predictive model that identifies one or more time-varying patterns in event parameter values that characterize the detected events within the prior time period. Based on an outcome of the predictive model, the computing system may determine an expected value of one of the event parameters during the second time period.

Abstract: A device may receive a uniform resource identifier that identifies an object source. The object source may include one or more objects organized in a hierarchy of objects. The device may identify an object, of the one or more objects, to permit extraction of one or more properties of the object. The device may extract the one or more properties of the object based on identifying the object. The device may select a subset of properties, of the one or more properties, to use to generate an object locator based on extracting the one or more properties. The object locator may be associated with locating the object in the hierarchy of objects. The device may generate the object locator based on selecting the subset of properties of the object.

Abstract: According to an example, customized visualization based intelligence augmentation may include accessing, based on a user request, a domain model, and mapping the user request to the domain model. Based on the mapping, a guided query that includes a relevant refinement question may be generated. A response may be received to the refinement question. Based on the received response, a refined user request may be generated, and classified into an intelligence augmentation category. Based on the classification, an intelligence augmentation analyzer may be accessed to analyze the refined user request to generate an insight output that is classified to a visualization. Based on the classification of the insight output to the visualization, responsive to the user request, a display of the visualization may be generated.

Abstract: A mobile application portfolio management system that estimates performance of a mobile application portfolio on various metrics and provides suggestions for improvements is disclosed. The mobile application portfolio manager calculates different KPIs for estimating performance of the mobile applications within the mobile application portfolio. The KPIs that underperform their respective thresholds are analyzed to isolate the elements of the KPIs that result in subpar performances by the KPIs. Various corrective actions to improve the performance of the elements of the KPIs can be derived based on the rules configured within the mobile application portfolio management system.

Abstract: There has been exponential growth in the capture and retention of immense quantities of information in a globally distributed manner. A closed-loop unified metadata architecture includes a universal metadata repository and implements data quality and data lineage analyses. The architecture solves significant technical challenges to provide a meaningful, consistent and normalized view of the metadata that describes the information, as well as to determine data lineage and meaningful data quality metrics.

Abstract: According to an example of the present disclosure, a software testing system is operable to test functionalities of a web application across different platforms. The software testing system can interact with different platforms via different drivers to facilitate multiplatform testing of the functionalities. Also, multiplatform test result views may be generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying network security risks. One of the methods includes receiving organizational hierarchy data and receiving access privilege data for a network, generating an adjacency matrix that represents connections between individuals within the organizational hierarchy and various groups, and that represents connections between the individuals and various access privileges, selecting an analytic technique for analyzing the adjacency matrix, determining, for each individual, an individual score that represents a security risk associated with the individual's network account, and in response to determining that the individual score meets a threshold, applying security controls.

Abstract: A signal analysis system matches a mobile device cellular identifier to a mobile device network identifier. The system obtains multiple cellular positioning records (CPRs) and multiple network positioning records (NPRs). These records include different types of information because they are generated by different types of networks. The system performs spatial matching and temporal matching of the CPRs and the NPRs to identify a specific mobile device cellular identifier among the CPRs that belongs to a mobile device identified by a specific mobile device network interface identifier among the NPRs.

Abstract: A device may receive, from another device, an image that depicts one or more events occurring at a location. The device may detect an event of the one or more events depicted in the image. The device may determine a first score that indicates a likelihood that the event is an anomalous event. The first score may be based on first data received from the other device. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the other device. The second data may comprise data from a sensor, a wearable device, a mobile device, and/or a handheld device. The device may perform an action based on the first score or the second score.

Abstract: A system includes circuitry for rewriting blockchains in a non-tamper-evident or tamper-evident operation using a key secret held by a trusted party. The blockchains may include a series of blocks secured by a chameleon hash that may prevent non-tamper-evident rewrites by non-trusted parties that are not in possession of the key secret. Rewrite circuitry of the system may determine randomness data from the chameleon hash and altered data from a rewrite. The randomness data may be written to the randomness field of a block overwritten with the altered data such that the block remains coding-consistent with the chameleon hash and other blocks in the blockchain.