Abstract: Various examples are directed to cloud platform systems that implement a plurality of cloud components. A first cloud component may receive a zone token. The zone token may comprise a first user identifier indicating a first user and a first zone identifier (ID) indicating a first zone. The first cloud component may receive from a user computing system associated with the zone token a task request indicating a first task. The first cloud component may execute the first task. Executing the first task may include determining a first data unit at the first cloud component associated with the first zone ID, accessing the first data unit, and sending a request message to a second cloud component, the request message comprising the first zone ID, wherein the second cloud component comprises at least one second data unit associated with the first zone ID.

Abstract: A service descriptor file is retrieved from a remote database by a server, where the service descriptor file describes a service corresponding to a service-specific chatbot requested by a user. The received service descriptor is parsed to obtain a capability and relevant service data associated with the service. The service-specific chatbot is generated with at least one object that is based on the obtained capability and relevant service data, where the at least one object includes intents, expressions, and skills that correspond to the service. The generated service-specific chatbot is provided to the user through at least one channel to enable an interaction with the service-specific chatbot with a graphical user interface.

Abstract: The present disclosure involves systems, software, and computer implemented methods for a efficient distributed secret shuffle protocol for encrypted database entries using dependent shufflers. Each of multiple clients provides an encrypted client-specific secret input value. A subset of clients are shuffling clients who participate with a service provider in a secret shuffling of the encrypted client-specific secret input values. The protocol includes generation and exchange of random numbers, random permutations and different blinding values. A last protocol step includes using homomorphism, for each client, to perform computations on intermediate encrypted data to homomorphically remove a first blinding value and a second blinding value, to generate a client-specific rerandomized encrypted secret input value.

Abstract: The present disclosure is directed to systems and methods including generating image data and audio data during a collaborative work using a stereoscopic camera system and a binaural microphone system, determining that physical media have been affixed to a work surface and, for each physical medium, providing a digital object including data representative of the physical medium, and determining that a session has ended, and in response, automatically: processing at least a portion of data of the digital objects using one or more clustering algorithms to provide two or more groups of digital objects, and providing an affinity diagram including the two or more groups of diagrams, the affinity diagram being displayed as digital representations of the physical media, the digital representations being grouped in the two or more groups.

Abstract: Various examples are directed to systems and methods for detecting training data for a generative model. A computer system may access generative model sample data and a first test sample. The computer system may determine whether a first generative model sample of the plurality of generative model samples is within a threshold distance of the first test sample and whether a second generative model sample of the plurality of generative model samples is within the threshold distance of the first test sample. The computer system may determine that a probability that the generative model was trained with the first test sample is greater than or equal to a threshold probability based at least in part on whether the first generative model sample is within the threshold distance of the first test sample, the determining also based at least in part on whether the second generative model sample is within the threshold distance of the first test sample.

Abstract: Techniques and solutions are described that can be used to determine data subsets of a data set that may be responsive to a query. In one aspect, imprints are created for the data subsets, where an imprint indicates whether, for a plurality of bins, a data subset contains values within respective bins. The bins are defined at least in part using data for a set of queries. In another aspect, at least one bin of a plurality of bins is designated to be associated with values of the data set satisfying a threshold frequency. In a further aspect, imprints are created for a plurality of bins, where an imprint indicates whether the plurality of data subsets comprise a value for a given bin. A query imprint can be compared with the data subset imprints or bin imprints to determine data subsets that may be responsive to an associated query.

Abstract: Briefly, embodiments of a system, method, and article for receiving data from one or more clients, where the data indicates user interactions with one or more user interfaces (UIs) of an application. The data may be analyzed with machine learning to identify how users of the one or more clients interact with the UIs of the application. One or more parameters may be generated based, at least in part, on the identification of how the users of the one or more clients interact with the UIs of the application. One or more objects of the application may be modified based, at least in part, on the parameters to reduce user interactions with the one or more UIs.

Abstract: The present disclosure involves systems, software, and computer implemented methods for ensuring seamless lifecycle stability for extensions to standard software products. One example method includes determining a requested change to a software feature of a software object. The software feature has been designated as an extensible software feature and is associated with a lifecycle stability contract that identifies aspects of the extensible software feature that are designated to remain stable across different releases of the software object. The lifecycle stability contract is used to perform a compatibility check for the requested change to determine whether the requested change complies with the lifecycle stability contract. The requested change is permitted in response to determining that the requested change complies with the lifecycle stability contract and the requested change is denied in response to determining that the requested change violates the lifecycle stability contract.

Abstract: A producer may supply amounts xi of a good to a plurality of consumers Ci in a series of transactions and be subject to a mass balancing verification protocol after every K transactions. A producer platform may compute K random shares (r1 through rK) of a random value r, publish blinded amounts ti representing xi+ri to a secure, distributed transaction ledger, and transmit an encrypted ri to consumer Ci using an asymmetric cryptosystem. A consumer platform may receive and decrypt ri (while the consumer Ci actually receives an amount {circumflex over (x)}i of the good from the producer), compute {circumflex over (x)}i+ri and generate a fraud alert signal if it differs from the published ti. The consumer platform may also transmit an encrypted rolling sum value to a next consumer Ci+1. A verifier platform may, after K transactions, execute the mass balance verification protocol to determine a total amount of the good that the producer had collectively supplied to the consumers Ci.

Abstract: The present disclosure involves systems, software, and computer implemented methods for a communication-efficient secret shuffle protocol for encrypted data based on homomorphic encryption and oblivious transfer. A service provider and multiple clients participate in a secret shuffle protocol of randomly shuffling encrypted client-specific secret input values. The protocol includes generation and exchange of random numbers, random permutations and different blinding values, including use of an oblivious transfer mechanism. A last protocol step includes using homomorphism, for each client, to perform computations on intermediate encrypted data to homomorphically remove a first blinding value and a second blinding value, to generate a client-specific rerandomized encrypted secret input value. As a result, the client-specific rerandomized encrypted secret input values are generated in an order that is unmapped to an order of receipt, at the service provider, of the encrypted secret input values.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program executable by at least one processing unit of a device. The program provides a display area for viewing a 3D model that includes a plurality of three-dimensional (3D) objects. The program further provides a tool for viewing 3D objects in the 3D model. The program also determines a 3D object in the plurality of 3D objects in the 3D model to hide. The program further hides the determined 3D object in the 3D model.

Abstract: Embodiments relate to a platform offering configurable analytics facilitating performance analysis between multiple Application Programming Interfaces (APIs)—e.g., APIs of individual microservices invoked by a cloud application as part of an end-to-end process flow. For purposes of performance monitoring, a visualization framework according to embodiments permits user configuration of end points of the cloud application. A library parses that configuration, storing analytics data in a schema provided by the application. The library can store metadata generated by the monitoring configuration, allowing generation of analytical reports based upon that metadata. Configuration options permit creating visualizations (e.g., charts) for individual microservice APIs, and co-relating data between APIs by providing contextual navigation from visualization of one API metric to another.

Abstract: The present disclosure involves systems, software, and computer implemented methods for principal propagation. One example method includes deploying a token service to a first cloud platform. A first token request is received from an integration component for a token to be included in a message sent from the first cloud platform to a second cloud platform. A user information request is generated and sent to an identity provider associated with the first cloud platform. User information is received from the identity provider in response to the user information request. A second token request is generated and sent to a token service provider associated with the second cloud platform. The second token request includes the received user information. The requested token is received from the token service provider. The received token is sent to the integration component to enable the integration component to send the message to the second cloud platform.

Abstract: A computer system includes one or more database search models configured to search data contained in a plurality of database tables. The one or more database search models can include a plurality of structural containers and one or more search enabling containers. The plurality of structural containers can represent objects having a structural relationship and contain property data of the objects. The property data of the objects can be obtained from the plurality of database tables. The plurality of structural containers can be shared by the one or more database search models. The one or more search enabling containers can correspond to the one or more database search models and specify a scope for searching data and a format for presenting search results.

Abstract: A request for an inference from a customer is received at a machine learning (ML) decentralized application (DAPP) platform, where the request includes a data record associated with a user that is associated with the customer. The data record is distributed by the ML DAPP platform among a number of service providers. An inference is received at the ML DAPP platform from each service provider. The received inferences are returned to the customer by the ML DAPP platform.

Abstract: A synchronization protocol is provided that can be used to resolve synchronization errors encountered while trying to synchronize versions of data objects between a client device and a remote computing system. The protocol includes a client device, in an offline processing mode, handling user interface (“UI”) manipulation actions on one or more UI elements of one or more UI screens. The handling of the UI manipulation actions modifies or creates a local version of a data object stored on the client device. The UI manipulation actions are stored by the client device and sent to the remote computing system. The client device receives a synchronization error notification from the remote computing system. After receiving the notification, the client device displays, in one of the UI screens, the local version of the data object and one or more indications of a synchronization error.

Abstract: Implementations of the present disclosure include receiving a view command for creating a view to display anonymized data in response to one or more queries, the view command including a view name, a table, a set of columns of the table, an anonymization type, a set of static parameters, and, for a sub-set of columns of the table, one or more sets of column-specific parameters, each set of column-specific parameters being specific to anonymization of data of a respective column of the table included in the sub-set of columns, storing the view command within the database system, and receiving a query referencing the view, and in response, providing a data set including data from each column in the sub-set of columns, receiving an anonymized data set including anonymized data that is generated from the data set using the anonymization type, the static parameters, and the sets of column-specific parameters.

Abstract: A system can receive an identifier for a query used by a query service of one or more query services and an identifier for the query used by an issuing computer system. The query service and the computer system that issued the query can use different schemas for query results. A mapping can be established that maps elements of one schema to the other schema. This mapping, and a mapping of the query identifiers, can be used to convert query results to a format useable by the computing system that issued the query. By converting query results from multiple query services, which may have different formats, to a common format of the issuing computing system, the use of multiple query services is facilitated.

Abstract: Implementations of the present disclosure include receiving, by a query processing server, a first query, the first query including a syntax indicating that precision loss is allowed, processing, by the query processing server, the first query to provide a first QEP, optimization of which would result in precision loss in a generated query result, determining that the syntax is provided, and in response, optimizing the first QEP to provide an optimized QEP, executing the optimized QEP to generate a query result that includes data stored within a database system, the query result having reduced accuracy relative to a query result that would be generated based on the first QEP, and providing the query result as output from the database system.

Abstract: Methods and systems for expense management, comprising: retrieving at least one electronic feed of charges for multiple expense receipt records directly from at least one lodging and/or transportation vendor, the at least one feed of charges including computer-readable electronic transaction data; detecting that at least one expense receipt record from the multiple expense receipt records from the at least one feed of charges is comprised of two or more line items; mapping the two or more line items to at least one transportation and/or lodging good and/or service that is chargeable to at least one account identifier, the mapping utilizing vendor expense codes and/or keyword searches; and pre-populating the at least one transportation and/or lodging good and/or service mapped to each of the two or more line items from the at least one expense receipt record in at least one expense report in at least one expense management system as two or more expense itemizations.