Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for correlating security policy inputs and outputs. A server system can obtain a system input comprising two versions of a policy input and corresponding versions of a policy output. The system can compute differences between the versions of the policy input and the versions of the policy output. The system can then correlate input differences to output differences. The system can generate and store a database record identifying the correlation.

Abstract: Example implementations described herein involve systems and methods that can include, responsive to a request to deploy an application using a storage of a storage system, managing a storage configuration for the application; managing data information and storage configuration information associated with a copy relationship between data used by the application and the storage configuration for the storage system; extracting and evaluating possible configuration patterns from the data information and the storage configuration information; and providing ones of the possible configuration patterns that satisfy specified requirements for the application.

Abstract: A method and system for adaptive video streaming receives inputs by a deep learning neural network engine. The inputs may include a previous lookahead buffer size, previous download time(s), a current buffer size, next available stream size(s), a last chuck quality, a current buffer size, previous download speed(s), a previous lookahead buffer size, a number of chunks remaining, and/or network condition statistics based upon geolocation information. The inputs are processed by the deep learning neural network engine using a neural network machine learning model to adjust a capacity of a buffer lookahead.

Abstract: A method includes receiving a query directed to a first data model that specifies base data fields. The method includes determining extension bindings for the first data model. A binding specifies an extension to the first data model and specifies one of the base data fields as a node at which the specified extension is added. The extension specifies a non-empty set of data fields. The method includes retrieving base data values according to the base data fields and extension data values according to, for a first binding, the set of data fields. The method includes generating a data object from the base and extension data values according to a second data model. The second data model is based on the first data model extended by adding the data fields from the extension specified by the first binding to the first data model at the specified node.

Abstract: Embodiments of a multitenant content server that employs embodiments of a database architecture for use in multitenant environments that include a global partition and a tenant partition for each tenant. These partitions can be accessed using sessions corresponding to the partitions and interfaces associated with the tenants.

Abstract: A query that includes one or more variables is received. The one or more variables correspond to one or more specific web elements associated with a webpage. Webpage content associated with the webpage that identifies a plurality of web elements associated with the webpage is processed. A script utilizing a query response that maps the one or more variables to a subset of the plurality of web elements associated with the webpage is generated.

Abstract: Methods, non-transitory computer readable media, and model evaluations systems for understanding diverse machine learning models (MLMs) are disclosed. In some examples, a feature contribution value is determined for features included in a reference or evaluation input data set. The evaluation input data set represents a protected class population and each feature contribution value identifies a contribution by a feature to a difference in output generated by an MLM for the evaluation input data set. Model explanation information is generated using the feature contribution values and execution of the MLM is monitored. The model explanation information explains the difference in output generated by the MLM for the evaluation input data set and includes information relating to a model-based decision. A report is generated from a knowledge graph for the MLM and output via a GUI to an operator device that includes the model explanation information.

Abstract: A vehicle includes a sensor and a transmitter. The vehicle further includes a non-transitory computer readable medium configured to store instructions thereon. The vehicle further includes a processor connected to the non-transitory computer readable medium. The processor is configured to execute the instructions for receiving or generating a data collection command, wherein the data collection command includes processing instructions for processing data collected from at least one of the sensor, an application log, or a system log, the processing information includes a number of processing operations to be performed, and a type of processing for each of the processing operations. The processor is further configured to execute the instructions for collecting sensor information based on the data collection command.

Abstract: Described herein are embodiments for machine-generating and naming ontologies for for-sale items. A neural network may be used to train information describing for-sale items into feature vectors that describe the for-sale items. These feature vectors may be sorted into clusters based on their relative proximity using clustering algorithms. The resulting clusters may be sub-divided into smaller clusters depending on the precision used in the clustering algorithm. The set of clusters may form a hierarchical data structure where each level has clusters determined at a certain precision and each lower level sub-divides those clusters. The clusters may be named based on the most salient facets that describe the for-sale items in the clusters.

Abstract: One or more aerial images of a construct (e.g., a utility construct, a utility asset, a power pole, a telephone pole, etc.) may be used to determine a location of the construct. The images may be used to identify adverse conditions affecting the construct such as wood rot, arc damage, flashing, tracking, floating conductors, loose tie-wires, loose hardware, and/or the like. The images may be used to prioritize actions to address the adverse conditions and identify and/or verify the location of the construct. aggregating the inspection data.

Abstract: Described is a content mining system comprising a crawler configured to retrieve a plurality of files from a data storage system. The content mining system further comprises a plurality of converters configured to extract data from the plurality of files retrieved by the crawler from the data storage system, where each of the plurality of converters is configured to process a respective type of data. The content mining system further comprises a plurality of queues interposed between the crawler and the plurality of converters, where each queue is associated with a single converter.

Abstract: Systems and methods for predicting yearly performance improvement rates for nearly all definable technologies for the first time are provided. In one embodiment, a correspondence of all patents within the U.S. patent system to a set of technology domains is created. From the identified patent sets, the invention may calculate average centrality of the patents in each domain to predict improvement rates, following a patent network-based methodology. Also disclosed is a system to intake a user technology search query and match user intent with the technology domain as well as the corresponding improvement rate.

Abstract: A system and method is presented that extracts snippets form web pages according to specially designed logic. The extracted snippets might be made relevant to, i.e., indexed by, a location and time/day applicability. Such snippets may be thought of as apps or services that are defined only when a mobile terminal is in a pre-defined geographical area at a certain time and day (e.g., as defined by a calendar of events). Extracted snippets are stored and made searchable. Methods and a system are described to control the display of snippet search results. Snippets may be selected by user or by programmed logic and executed on the mobile terminal or in remote servers without the need to download the app or source code associated with the snippet.

Abstract: A computer-implemented method, system and computer program product for improving performance of a distributed database. A query is received to store version data in the distributed database. Upon receiving the query to store the version data, the version data is stored in a row of a data page of a main table of a heap organized table/index organized table of the distributed database, where the row of the data page of the main table of the heap organized table/index organized table of the distributed database contains a pointer pointing to a later/previous version of the version data if the later/previous version of the version data is stored in the data page thereby chaining version data bi-directionally.

Abstract: A method services competing updates from multiple servicing instances. An update message is received by a class of a plurality of classes that service an object. The update message includes an update to the object and an expected version for the object. A version match is determined between the expected version and a current version of the object. When the version match is successful, the update is applied to the object. A response message including the current version of the object is generated. The response message is transmitted. When the update is successfully applied, the response message is transmitted as a success message. When the update is not successfully applied, the response message is transmitted as a failure message.

Abstract: A computer can connect with a middleware computing system. The middleware computing system may use application programming interfaces (APIs), webhooks, file-based integration, database replication, message queues, websockets, or direct integration to establish connections with different computing devices. The computer may request an account classification for an external account stored in a remote computing device. The middleware computing system can receive the request, identify the connection that the middleware computing device has with the remote computing device, and retrieve transaction records for transactions performed by the external account from the remote computing device. The middleware computing system can use metadata in the transaction records to automatically determine an account type of the account. The middleware computing system can generate instructions that cause the computer to link the external account with the profile.

Abstract: Systems and methods for improved data conversion and distribution are provided. A data subscription unit is configured to receive data and information from a plurality of data source devices. The data subscription unit is in communication with a virtual machine that includes backtesting utility configured to generate backtesting data using one or more statistical models and one or more non-statistical models. The backtesting utility may translate the backtesting results into one or more interactive visuals, and generate a graphical user interface (GUI) for displaying the backtesting results and the one or more interactive visuals on a user device. The backtesting utility may update one or more of the displayed backtesting results and the one or more interactive visuals without re-running the modeling steps.

Abstract: A method for dynamically creating and validating a predictive analytics model to transform data into actionable insights the method comprising: identifying an event, selectively tagging, based on analytics expertise, at least one time series data area (data area), where the identified event occurred, comparing data area where the identified event is tagged with the data area where the identified event is not tagged, building, based on analytics expertise, the predictive analytics model embodying the classification generated by selective tagging, displaying the visual indicia generated by executing the predictive analytics model, and validating the predictive model based on a feedback from at least one domain expert.

Abstract: User interface responsiveness is improved using batch interface calls and response processing. To do this, a selection, via a user interface, is obtained of nodes of a hierarchy corresponding to a hierarchical data structure containing information to be presented in the user interface based on the selection. A separate request is sent to a database to obtain information corresponding to each of the nodes. Responses corresponding to a particular request are received from the database. Each response is processed to obtain parsed data in separate threads such that the responses are executable in parallel. The processing of the responses outputs parsed data for the corresponding response. The parsed data is obtained and the parsed data for a particular response is incrementally presented in the user interface as it is obtained.

Abstract: In an embodiment a method is provided. The method includes receiving forecast information in a computer from a first group of users. The method also includes integrating the forecast information into a database and corresponding OLAP cube accessible by the computer. The method further includes receiving comments on specific entries of the forecast information in the computer from a second group of users. The method also includes receiving changes of the forecast information in the computer from a second group of users The method further includes integrating comments and changes into the database and OLAP cube. Moreover, the method includes providing a display of the comments and the changes to the first group of users in an interface to the computer.