Abstract: An API reader reads a system application's API specification file and creates a root.yml file containing key:value pairs, in which the keys are objects, and the values are staging_object.yml files. Each staging_object.yml file includes a set of entries, with each entry including a REST operation, a REST endpoint, and a description of the operation to be performed using that entry. An intelligent API converter creates structured object.yml files based on corresponding unstructured staging_object.yml files, and replaces the staging_object.yml files of the root.yml file with the newly created object.yml files. Each object.yml file includes a plurality of entries, corresponding to the entries of the respective staging_object.yml file. Each entry of the object.yml file includes an OPERATION, a JSON payload, and a VALIDATION section. An API builder uses the root.yml file to build a REST API for the system under test which is used to automate testing of the application.

Abstract: Methods, apparatus, and processor-readable storage media for connecting configuration services using blockchain technology are provided herein. An example computer-implemented method includes obtaining at least one user request comprising configuration-related data pertaining to at least one item of hardware and at least one user network; encrypting at least a portion of the configuration-related data using one or more cryptographic hash functions; storing copies of the encrypted configuration-related data across multiple nodes within at least one distributed blockchain technology-based cloud storage system; and performing one or more automated actions, in connection with the at least one user request, using at least a portion of the stored data within the at least one distributed blockchain technology-based cloud storage system.

Abstract: A method includes retrieving information regarding a candidate from a plurality of sources, and analyzing the information regarding the candidate using one or more machine learning techniques. A plurality of questions for the candidate are generated based on the analysis. The method further includes receiving and analyzing a plurality of natural language responses to the plurality of questions from the candidate, and computing a plurality of confidence scores for the plurality of natural language responses using the one or more machine learning techniques. The plurality of questions and the plurality of confidence scores are provided to a user via a user interface.

Abstract: In one aspect, a device may include at least one processor and storage accessible to the at least one processor. The storage may include instructions executable by the at least one processor to receive input from one or more sensors and, based on the input from the one or more sensors, determine that a trigger related to a user moving between viewing a first display location and a second display location is satisfied. Responsive to the determination, the instructions may be executable to move at least one graphical object presented on at least one display from the first display location to a third display location different from the first and second display locations.

Abstract: Method and system for providing ground truth dataset and use thereof for improving data correctness. Datasets comprising data elements are received from different sources, each data element including an identifier and at least one attribute value associated therewith. Data correctness values are determined for the attribute values, each associated with a probability that an attribute value is correct. Data element with single data correctness value is added to the ground truth dataset for each attribute value for each identifier with which a respective attribute value is associated based on the determined data correctness values for the attribute values, whereby the data correctness values in the ground truth dataset define probability distributions of data correctness for the attribute values. Data correctness values for attribute values of data elements of a new dataset can be determined based on overlapping data compared in the ground truth dataset and the new dataset.

Abstract: A cloud marketplace includes a network of data centers that collectively allow users to search and purchase products, including applications and extensions to applications. Each data center supports a marketplace module that executes on computing resources to offer users the products and receive and send product metadata descriptive of the products. The marketplace module in each data center passes the product metadata to a database management system for storage in the data center. The marketplace module also passes the product metadata to an agent module within the data center that is separate from the database management system. The agent module passes the product metadata to agent modules of other data centers via the network so that the product metadata can be synchronized across data centers without having to wait for the database management systems to synchronize the databases.

Abstract: A method and system for intelligent power distribution management. Specifically, the disclosed method and system propose allocating (and deallocating) reserve or supplemental electrical power to host devices dynamically based on intelligent analyses of host device telemetry including, but not limited to, workload criticality, workload computing resource utilization, hardware configuration metadata, various operational parameters describing host device state, and measurements (as well as other information) pertinent to electrical power usage.

Abstract: This disclosure relates to method and system for representing functional simulation performance for a plurality of simulations in real-time using Graphical User Interface (GUI) elements. For each of the plurality of simulations in a verification environment and upon completing each of a plurality of simulation intervals, the method includes determining a simulation performance value for a simulation interval based on wall clock time lapsed during completion of the simulation interval; calculating, in real-time, an average simulation performance value based on a sum of the simulation performance value corresponding to each of completed simulation intervals from the plurality of simulation intervals; estimating an additional wall clock time required to complete remaining of the plurality of simulation intervals using the average simulation performance value; and updating a special log file with a set of simulation parameters.

Abstract: A software process is tested using an instance of a computer system. A first set of data and a second set of data are collected. The first set relates to resources used by the software process during the testing and the second set relates to conditions of the instance during the testing. A machine learning algorithm is trained with the first set of data and the second set of data, thereby generating a model relating to the resources used by the software process under the conditions of the instance. User input is received, the user input relates to expectations of a test plan for the software test. The test plan is created as a function of the model and the user input.

Abstract: In one aspect, a device may include at least one processor and storage accessible to the at least one processor. The storage may include instructions executable by the at least one processor to receive input from one or more sensors and, based on the input from the one or more sensors, determine that a trigger related to a user moving between viewing a first display location and a second display location is satisfied. Responsive to the determination, the instructions may be executable to move at least one graphical object presented on at least one display from the first display location to a third display location different from the first and second display locations.

Abstract: Provided are methods and systems for enabling seamless integration between multiple products as a common layer by using a common visual modeler. An example system may include an application server and a common visual modeler. The common visual modeler may include a visual modeling environment for building an application by an end user. The visual modeling environment may include a modeler for creating the application, wherein the modeler comprises at least one component from at least one enterprise software product, the at least one component comprising at least one UI-based modeling tool for creating at least one artifact and a configuration module for managing settings of the at least one component. The common visual modeler may also include a server runtime environment for executing the application, the server runtime environment comprising at least one runtime engine for the at least one artifact created by the modeler.

Abstract: A durable coating which reduces ice adhesion and minimizes ice accumulation includes a polymeric binder and a film forming lubricant. The polymeric binder is selected from a fluoropolymer or silicone polymer having one or more reactive groups. The film forming lubricant is a lubricous fluoropolymer or silicone polymer. Methods of applying a durable coating are also disclosed.

Abstract: Apparatus, methods, and computer-readable media for facilitating prioritizing PDCP retransmission and/or control information in dual connectivity scenarios are disclosed herein. An example method for wireless communication at a first network node includes receiving PDUs for transmitting to a second network node while operating in a dual connectivity mode associated with a first RLC leg and at least a second RLC leg, the PDUs associated with at least one of control information or retransmission data. The example method also includes transmitting first scheduling information via the first RLC leg and transmitting second scheduling information via the second RLC leg based on the PDUs being associated with at least one of the control information or the retransmission data. The example first network node may include a UE or a base station.

Abstract: A phone tree traversal system includes an input device configured to receive a user call request, a memory, and one or more processors. The one or more processors analyze the user call request to identify an entity to call and an objective of the call, and obtain a map of a phone tree utilized by an automated call receiving system of the entity. The phone tree includes at least one node with multiple path segments that branch from the node, and each node includes a respective prompt. The one or more processors determine a route along the map to an endpoint of the phone tree associated with the objective. During the call, the one or more processors navigate the phone tree to reach the endpoint by submitting information in response to the respective prompt at each node along the route that is determined.

Abstract: Systems and methods of communicating in a network use a physical device. The physical device includes hardware including a management data input/output interface and firmware configured to cause the hardware to provide a logical message interface using the management data input/output interface. The logical message interface is used to receive messages for configuring and/or managing the physical device.

Abstract: In some examples, a server may determine that a case, created to address an issue of a computing device, is closed and perform an analysis of steps in a process used to close the case. The analysis may determine a length of time of each step and determine that a time to close the case or complete a particular step was at least a predetermined amount faster than average. The server may use machine learning to create a survey question to determine a technique used to close the case or complete the particular step faster than average and to determine one or more incentives to provide a technician that closed the case. An answer from the technician to the survey question may include the technique used to close the case or complete the particular step faster than average. The technique may be shared with other technicians.

Abstract: Provided is a process including: obtaining, for a plurality of entities, entity logs, wherein: the entity logs comprise events involving the entities, a first subset of the events are actions by the entities, at least some of the actions by the entities are targeted actions, and the events are labeled according to an ontology of events having a plurality of event types; training, with one or more processors, based on the entity logs, a predictive machine learning model to predict whether an entity characterized by a set of inputs to the model will engage in a targeted action in a given duration of time in the future; and storing the trained predictive machine learning model in memory.

Abstract: The disclosed systems and methods are directed to a computer-implemented method for use in designing a service. In at least one embodiment, a method includes designing a service with one or more generic virtual network functions (VNFs), where the generic VNFs are defined independent of vendor sourcing information. One or more trained machine learning (ML) models are used to identify VNFs available from VNF vendors that may source one or more VNFs similar to the generic VNFs. The service is implemented using VNFs provided by one or more VNF vendors, where the VNFs provided by the one or more VNF vendors have network functionality generating similar to the one or generic VNFs.

Abstract: Methods, systems, apparatus, and program products that can generate scaled-down load test models for testing real-world loads are disclosed herein. One method includes providing a test environment of a system including multiple nodes. The test environment includes virtual nodes corresponding to the system nodes and each virtual node functions under a virtual load similar to each corresponding node functioning under a real-world load. The method further includes utilizing a machine learning algorithm to repeatedly apply at least one virtual load to the virtual node(s) in the test environment until a scaled-down load test model mimicking the system under a pre-defined real-world load is generated. Here, the virtual load(s) applied to the virtual node(s) is/are comparatively smaller relative to each of corresponding real-world loads for the node(s) defining the pre-defined real-world load. Systems, apparatus, and program products that include and/or perform the methods are also disclosed herein.

Abstract: Techniques described herein relate to a method for managing nodes. The method may include sending, by a first node of nodes, a node information request to a social manager, where the node information request specifies a portion of a service to be provided to the first node; obtaining node information associated with a portion of the nodes from the social manager, where the portion of the plurality of nodes previously expressed node capability information and node configuration information associated with the portion of the service; identifying a second node of the portion of the nodes based on the node information to perform the portion of the service; and performing the service using the second node, where the second node performs the portion of the service.