Abstract: A method and a system control the water production for a water distribution network. The method includes collecting field sensor data from a water distribution network, using the received data to model the water distribution network and determining an optimal water flow, and generating the optimal water production plan for controlling the water production in the water distribution network based on received data including the sensor data and the historical data. The system includes a process and memory and processor executable instructions to carry out the above method.

Abstract: A certification management system helps an organization develop and maintain a repository of current certification status of employees. The system may integrate multiple learning management systems and other enterprise level systems across the organization. The system facilitates identifying and enrolling targeted employees for any number and type of certification programs. The system may also implement and support reconfiguring certification programs, for example, during training, and enforcing recertification requirements according to maturing business needs. The system provides automated workflows that facilitate a formal, structured approach to the development and recognition of specific specialized skills at scale by infusing more consistency, rigor, and objectivity.

Abstract: Implementations are directed to receiving, by a security data exchange platform, security data from an enterprise of a plurality of enterprises, the security data representative of a data security threat against the enterprise, processing the security data to determine a score assigned to the security data, the score being determined based on baseline threat data, providing a data summary to a distributed ledger platform having a private distributed ledger, the data summary being stored to the private distributed ledger, being representative of the security data, and having a smaller memory footprint than the security data, determining, a token value to be associated with the security data, the token value being determined using a smart contract executed on the distributed ledger platform, and being based on the data summary of the security data, and updating, by the distributed ledger platform, a wallet associated with the enterprise to include the token value.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a touchless testing platform employed to, for example, create automated testing scripts, sequence test cases, and implement defect solutions. In one aspect, a method includes receiving a log file and testing results generated from a code base for an application; processing the log file through a pattern-mining algorithm to determine a usage pattern of code modules within the code base; clustering defects from the testing results based on a respective functionality of the application reported within each of the defects; generating testing prioritizations for test cases for the application by assigning weightages to the test cases based on the clusters of defects and the usage pattern of the code modules within the code base; sequencing a set of the test cases based on the test prioritizations; and transmitting the sequence to a test execution engine.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for engineering a data analytics platform using machine learning are disclosed. In one aspect, a method includes the actions of receiving data indicating characteristics of data for analysis, analysis techniques to apply to the data, and requirements of users accessing the analyzed data. The actions further include accessing provider information that indicates computing capabilities of a respective data analysis provider, analysis techniques provided by the respective data analysis provider, and real-time data analysis loads of the respective data analysis provider. The actions further include applying the characteristics of the data, the analysis techniques, the requirements of the users, and the provider information, the analysis techniques, and the real-time data analysis loads to a model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing video recommendations. For each video in a set of videos, a set of images included in the video are obtained. For each respective image in the set of images for a video, a set of one or more keywords that describe visual content depicted by the respective image is generated. Based at least on the sets of one or more keywords for at least some of the images, a set of keywords that describe the video is generated. The videos are assigned to groups based on the set of keywords generated for each video. A request is received for a video recommendation based on a first video. Data identifying a second video are provided as the video recommendation based on the second video being assigned to a same group as the first video.

Abstract: A device may receive, from a user device, a request for one or more code quality assessments of a program. The device may obtain authorization to access one or more environments associated with the program. The device may obtain one or more tokens that are associated with the one or more environments. The device may obtain a set of test classes for the program. The device may determine one or more code quality assessment scores by performing, for the program, a code quality assessment of the one or more code quality assessments. The device may perform the code quality assessment by accessing the one or more environments using the one or more tokens, executing the set of test classes in each environment, and determining the one or more code quality assessment scores. The device may provide the one or more code quality assessment scores to the user device.

Abstract: A device may receive a first command, included in a set of commands, to set a configuration parameter associated with performing feature extraction. The device may receive a second command, included in the set of commands, to set a corresponding value for the configuration parameter. The configuration parameter and the corresponding value may correspond to a particular feature metric that is to be extracted. The device may configure, based on the configuration parameter and the corresponding value, feature extraction for a corpus of documents. The device may perform, based on configuring feature extraction for the corpus, feature extraction on the corpus to determine the particular feature metric. The device may generate a feature vector based on performing the feature extraction. The feature vector may include the particular feature metric. The feature vector may include a feature identifier identifying the particular feature metric. The device may provide the feature vector.

Abstract: A computer-implemented method that includes a computing system receiving a plurality of data items that include content data. The system then generates a first inference model based on the received content data. The system also receives metadata associated with respective data items and then generates a second inference model based on the received metadata data. The system further determines, based on the first inference model, a first weight parameter associated with the content data, and determines, based on the second inference model, a second weight parameter associated with the metadata. The system then generates a classification model for determining a classification of at least one data item of the plurality of data items. The classification model is generated based on at least one of the first weight parameter or the second weight parameter.

Abstract: A device may receive information associated with an application to be tested. The device may identify test data associated with the application to be tested based on the received information. The device may associate the test data with a plurality of test cases. The device may associate the plurality of test cases with a test set. The device may associate the test set with a release. The device may provide the plurality of test cases and the test data, associated with the release, to the application to be tested. The device may receive a plurality of first results, and may compare the plurality of first results and a plurality of second results. The device may provide information for display based on comparing the plurality of first results and the plurality of second results.

Abstract: A device receives images of a video stream, models for objects in the images, and physical property data for the objects, and maps the models and the physical property data to the objects in the images to generate augmented data sequences. The device applies different physical properties to the objects in the augmented data sequences to generate augmented data sequences with different applied physical properties, and trains a machine learning (ML) model based on the images to generate a first trained ML model. The device trains the ML model, based on the augmented data sequences with the different applied physical properties, to generate a second trained ML model, and compares the first trained ML model and the second trained ML model. The device determines whether the second trained ML model is optimized based on the comparison, and provides the second trained ML model when optimized.

Abstract: Knowledge graph systems are disclosed for implementing multiple approaches, including stand alone or combined approaches, for knowledge graph pruning. The approaches are based on graph sampling work such as, for example, information gain theory. The approaches are applied by a knowledge graph system to perform schema pruning, automatic graph pruning, and query correlation for improving query performance.

Abstract: Knowledge graph systems are disclosed for implementing multiple approaches, including stand alone or combined approaches, for knowledge graph pruning. The approaches are based on graph sampling work such as, for example, information gain theory. The approaches are applied by a knowledge graph system to perform schema pruning, automatic graph pruning, and query correlation for improving query performance.

Abstract: A method for anonymously communicating data that defines a token from a source system to a destination system via a block-chain distributed database includes receiving, at a token distribution system, request information from a source system. The request information specifies source identifying information and an address for receiving one or more tokens. The token distribution system determines one or more tokens for allocation to the source system and communicates the allocated tokens to the address defined in the request information via a zero-knowledge transaction. The source system moves the tokens to a different address for communicating a block-chain transaction and communicates the tokens at the different address to a destination address associated with the destination system via a block-chain transaction.

Abstract: A device may receive first information associated with an emergence area. The first information may include imagery data of the emergence area. The device may determine an expected commodity quantity value based on the first information. The device may determine an actual commodity quantity value based on the imagery data. The device may determine an emergence value, associated with the emergence area, based on the expected commodity quantity value and the actual commodity quantity value. The device may receive second information associated with a commodity, and may determine one or more conditions based on the second information and the emergence value. The device may determine a recommendation based on the one or more conditions, and may provide the recommendation to permit and/or cause an action to be performed in association with the emergence area.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for incident response are disclosed. In one aspect, a computer-implemented method includes receiving data identifying two or more groups of actions performed to remediate a computer security threat. The method includes determining first unique paths from a first action of each of the two or more groups of actions to a second action of each of the two or more groups of actions, and determining second unique paths from the second action of each of the two or more groups of actions to a third action of each of the two or more groups of actions. The method also includes combining common paths among the first unique paths and the second unique paths, identifying one of the common paths that appears most frequently, and determining a core path that includes a subset of the actions of the two or more groups of actions based on the one of the common paths that appears most frequently.

Abstract: A device may receive first data that identifies operations of an organization. The operations may be associated with a first manner in which the organization stores second data or a second manner in which the organization generates a contract. The device may process the first data to identify the operations of the organization. The device may perform a first analysis of the first data to determine whether the operations of the organization satisfy a set of rules. The set of rules may indicate the first manner in which the organization is to store the second data. The device may perform a second analysis of the second data to identify an error associated with the second data. The device may perform an action to modify the operations of the organization or to facilitate fixing of the error based on a result of the first analysis or the second analysis.

Abstract: A task transformation architecture meets the technical challenges of geographically distributed task assignment and completion, e.g., by crowd-sourced workers who are external to any given enterprise that needs the task completed. The architecture delivers task information to the workers while maintaining confidentiality. In one aspect, the architecture determines when task descriptions include confidential information, transforms the task to remove the confidential information, and delivers the transformed task to the worker. When the worker responds with a completed project, e.g., source code for executing the transformed task, the architecture transforms the completed project into a form that restores the confidential information.

Abstract: A knowledge graph virtualization system (KGVS) implements data virtualization techniques using semantic knowledge when parsing a knowledge graph to return results to a query. The data virtualization using semantic knowledge enable end users and applications to describe desired output without detailed knowledge of underlying data storage, schema, and relationships.

Abstract: A system for elastic volume type selection and optimization is provided. The system may detect that a block storage volume was provisioned by a public cloud computing platform based on a first volume type identifier of a first volume type. The system may determine, based on a normalization model, a baseline operation rate and a baseline throughput rate for the provisioned block storage volume. The system may determine, based on a selected transition mode and historical performance measurements, a simulated operation rate and a simulated throughput rate. The system may communicate, in response to the simulated throughput being greater than the baseline throughput rate or the simulated operation rate being greater than the baseline operation rate, a provisioning instruction to re-provision the provisioned block storage volume on the cloud computing platform.