Abstract: Techniques and solutions are provided for determining elements of a routing. A set of inputs is obtained, where the set of inputs includes sets of one or more characteristics for respective inputs of the set of inputs. At least a portion of values for the one or more characteristics are submitted along with a set of labels to train a machine learning model. A set of inference data that includes input values for a set of one or more characteristics for inputs of the set of inference data is analyzed using the machine learning model to provide an inference result. The inference result provides a predicted set of labels associated with a routing element of a routing involving the set of inference data. Using characteristics values can provide more accurate inference results and can allow a greater portion of data to be used as training data.

Abstract: Fairness and output authenticity for secure distributed machine learning is provided by way of an encrypted output of a garbled circuit which is simultaneously provided to a garbler and an evaluator by an output discloser. Related systems, methods and articles of manufacture are also disclosed.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives, from a client device, a request for information associated with a category. In response to the request, the program further accesses a storage to retrieve a first value associated with the category. The program also determines a set of values associated with the category based on a plurality of transactions. The program further determines an optimization level value associated with the category. The program also determines a second value associated with the category based on the first value, the set of values, and the optimization level value. The program further provides, by an application operating on the device, a graphical user interface (GUI) to the client device, the GUI comprising the second value.

Abstract: Disclosed herein are system, method, and computer program product embodiments selectively saving draft attributes. In some embodiments, a server generates a form comprising data fields. The server defines associated with the form. The server detects an event associated with the form. Each of the of data fields includes a respective attribute. The server identifies one or more of data fields that are to be draft-enabled in response to the event based on a definition of the event. The server further identifies at least one data field of the plurality of data fields for which draft-enablement is to be removed. The server generates metadata for the at least one data field removing the draft-enablement and stores a draft of each respective attribute for each of the plurality of data fields, excluding an attribute for the at least one data field in a data storage device.

Abstract: A software-based process modeling tool is provided that labels and links a plurality of activities forming part of a process that is being modeled include a recommendation engine. With the modeling tool, the activities are each represented as a node in the graphical user interface. A recommendation engine is polled with information characterizing the labeled activities and their corresponding links to obtain a plurality of ranked recommendations for an unlabeled node representing a next activity in the process for selection by a user. The recommendation engine applies the information characterizing the labeled activities and their corresponding links to a plurality of rules each having a corresponding confidence value. The plurality of rules is generated using a plurality of rule templates as applied to a plurality of historical processes each comprising a plurality of labeled and linked activities.

Abstract: Methods, systems, and computer-readable storage media for selective use of Internet-of-Things (IoT) data in data analytics systems. Implementations include receiving IoT data from an IoT device, determining that hardening is to be applied to the IoT data, comparing a timestamp of the IoT data to a hardening value, and in response to comparing, selectively using the IoT data in one or more uses by the data analytics system.

Abstract: A container group is created using a database deployment infrastructure (DI) administrator (HA). API privileges for the container group are granted, using the HA, to a container group administrator (GA). API privileges for a container created in the container group using the GA are granted, using the GA, to a container administrator (CA). API privileges for the container are granted, using the CA, to a container developer (CD). Schema privileges for the container are granted, using the CA, to a container consumer (CC). API privileges for the container group are revoked, using the HA, from the GA. The container group is dropped using the HA.

Abstract: The present disclosure provides techniques for encoding and decoding characters for optical character recognition. The techniques involve determining sets of numbers for encoding a character set where each number in a particular set of numbers for encoding a particular character is mapped to a graphical unit (e.g., radical) of the particular character. A mapping between each set of numbers in the possible encodings and the character set may be determined based the closest character already encoded. A machine learning model may be trained to perform optical character recognition using training data labeled using the set of encodings and the mappings.

Abstract: According to some embodiments, a user vector generator may access information about a user (e.g., a software deployment developer or operator) in a user data store that contains electronic records each associated with different user. Each record may include, for example, a user identifier and user characteristics. Based on the user characteristics, the system may automatically generate a user vector indicating a computing environment skillset level for that user (e.g., beginner, intermediate, or expert). A machine learning privilege assignment platform may receive an indication of the user vector for the user and, based on the user vector and a machine learning algorithm, generate a privilege decision for that user (e.g., when the user attempts to update the system). An indication of the privilege decision may be output, according to some embodiments, to an SMT solver to review the privilege decision before granting the user access to the computing environment.

Abstract: Some embodiments may be associated with a cloud-based actor framework. A dispatcher platform may determine that a first tenant actor is to be created for a first tenant in connection with a workload associated with a plurality of tenant identifiers. The first tenant may be, for example, associated with a first tenant identifier. The dispatch platform may then select a first thread for the first tenant actor from a pool of available threads and spin a first web assembly module such that execution of the first web assembly module is associated with a first web assembly browser sandbox. The dispatcher platform can then securely create the first tenant actor within the first web assembly browser sandbox to execute the workflow for the first tenant identifier. Similarly, a second web assembly browser sandbox may execute a second tenant actor for a second tenant identifier.

Abstract: A machine learning model may be trained based on a training set including training images depicting various base objects. Each training images may be associated with a ground-truth segmentation corresponding to one or more pixel-wise labels. The machine learning model may be trained to learn base class prototypes corresponding to segmentations of classes of similar base objects. The machine learning model may be further trained based on a support image depicting a novel object. The support image may be associated with an image-level label corresponding to the novel object. The machine learning model may be trained to learn, based on a base class prototype identified as being similar to the support image, a novel class prototype corresponding to the novel object. The trained machine learning model to may be applied to segment a query image. Related systems and computer program products are also provided.

Abstract: A system and method are disclosed associated with a cloud platform as a service provider. A monitoring agent, associated with a database service instance running on a client database virtual machine, periodically executes a performance throttling detection engine. The performance throttling detection engine gathers database statistics based on metrics and features of the database service using a rule-based approach. When it is determined that a pre-determined condition is met, the system may transmit the gathered database statistics to an external application. For example, the external application might comprise a database tuning service and the pre-determined condition may be associated with a decision that the database service may potentially need to tune knob configuration parameters (associated with memory knobs, background writer knobs, asynchronous knobs, etc.).

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program retrieves an assembly and inspection plan for a product. The assembly and inspection plan includes a three-dimensional (3D) model of the product to be assembled. The program further creates an inspection task for an inspection operation in the assembly and inspection plan for the product. The program also associates the 3D model with the inspection task for the inspection operation.

Abstract: A method for accessing data stored in a database may include receiving a query to generate, based on blended data, a visualization. The blended data may include a first set of data from a first data source and a second set of data from a second data source. The query may also include a payload. The method may also include accessing the first set of data by injecting, into the payload, the first permission, and transmitting, to the first data source, the payload including the first permission. The method may also include accessing the second set of data by injecting, into the payload, the second permission, and transmitting, to the second data source, the payload including the first permission, the first set of data, and the second permission. The method may also include causing, using the blended data, presentation of the visualization. Related systems and articles of manufacture are provided.

Abstract: In an example embodiment, machine learning is utilized to automatically present and explain analysis of multidimensional objects categorized based on context in an enterprise data warehouse. The system is capable of handling dependencies to provide clear insights demonstrated in a native language of an end user. The system is multilingual and capable of framing explanations based on natural language processing (NLP), artificial intelligence (AI), and machine learning. It converts the textual predictions into speech synthesis in the user-understandable native format and then dictates the analysis using the speech synthesis.

Abstract: Computer-readable media, methods, and systems are disclosed for validating data associated with schemas. A user defines the object model of at least one asset and a first schema is generated in accordance with the defined object model, and a unique fingerprint is generated. Data is collected from one or more devices in accordance with the object model. The collected data is serialized, and a second schema is generated. The second schema is ordered in accordance with the first schema and a unique fingerprint is generated. The fingerprint of the first schema is compared to the fingerprint of the second schema to provide an efficient review process for determining whether the schemas are equal, and the associated data may be validated. A fingerprint cache may be updated with fingerprints associated with a plurality of schemas, as well as version history of each schema, to provide an efficient review process.

Abstract: Provided are a system and method that use machine learning to identify documents to be excluded from a report or included in a report of a software application. In one example, the method may include receiving document data of a set of documents assigned to a report, executing the machine learning model on the received document data which identifies a document assigned to the set of documents that is to be excluded from the report, displaying, via a user interface, a set of line items corresponding to the set of documents, respectively, activating a user interface element of the identified document within a line item of the identified document, and in response to detecting a selection of the activated user interface element via the user interface, accepting the exclusion of the identified document from the report and move the identified document to a different report.

Abstract: Provided are systems and methods for converting user interface events that occur in a software application developed via a WebGUI framework into activity descriptions and into a bot software program. In one example, a method may include recording events transmitted between a user interface of a web application open within a web browser on a client device and a back-end of the web application on a server, identifying codes associated with user interface elements which are assigned to the recorded events, converting the identified codes assigned to the recorded events into a human-readable descriptions of the recorded events based on a predefined mapping between the codes and the human-readable descriptions stored in the predefined mapping, and displaying the human-readable descriptions of the recorded events based on the identified order among the recorded events.

Abstract: Various examples are directed to systems and methods for executing an enterprise resource planning solution using a database management system (DBMS). An order-to-cash process executing at the at least one processor accesses an indication of waste material for disposal and generates a waste disposal order, where the waste disposal order comprises a material description field including a description of the waste material, regulatory reporting data describing at least one report of the waste material to be provided to a regulatory agency, and a price field indicating a negative price.

Abstract: A method, a system, and a computer program product for accessing data. A data stream including a plurality of data elements is received. A mapping of the plurality of data elements is generated. Each data element is represented by a data node in the mapping. A linked list of the data nodes with starting and ending elements is generated. Each node is linked to at least another node and stores a count of a data element and the corresponding data element. The count represents a number of times the data element is present in the data stream. Each node is positioned in the generated linked list using the count of each data element. Data elements with a highest count are positioned proximate to the starting element and data elements with a lowest count are positioned proximate to the ending element. Data elements are accessed using the generated mapping.