Abstract: Apparatuses and methods are disclosed for handling integrated circuits in automated testing. The handler apparatus includes an upper assembly that is selectively translatable above a testing surface and a lower bracket extending from and positioned below the upper assembly. The lower bracket forms a first opening, is selectively moveable upward and downward, and includes a rotatable finger extending downward to pick up and place an integrated circuit in a socket. The handier may further include an image sensor to detect potential error conditions, and a tool extending from the lower bracket to open and close a lid on the socket. The methods include sensing an image of an integrated circuit during certain phases of testing, analyzing the image to determine if the integrated circuit is positioned correctly, and correcting any detected error conditions before continuing with the automated testing.

Abstract: An example method of allocating channels to access points (AP) is presented. A network manager may determine weights of the APs based on a channel metric and a location metric for APs. Further, the network manager may identify a first set of APs based on the weights and allocate a dedicated first channel to each of the first set of APs for its sole use. Accordingly, each of the first set of APs may use a respective dedicated first channel thereby reducing the performance impact on other APs. Further, the network manager may identify a second set of APs based on the weights and allocate second channels for sharing among the second set of APs. Since the second set of APs does not share any channel with the first set of APs, the performance of the second set of APs may not be impacted due to the first set of APs.

Abstract: Methods, systems, and devices for data management are described. A data management system (DMS) may receive a request to access metadata stored in a distributed metadata repository. The request may have a first semantic format compatible with a first version of the distributed metadata repository. The DMS may translate the first semantic format of the request to a second semantic format compatible with a second version of the distributed metadata repository. The DMS may perform the semantic translation according to a label in the request. Accordingly, the DMS may determine whether a current version of the metadata corresponds to the first version of the distributed metadata repository or the second version of the distributed metadata repository, and may access the metadata in the distributed metadata repository based on the request and the current version of the metadata.

Abstract: Methods, systems, and media for presenting media content are provided.

Abstract: In some examples, a computing device may implement a method that includes receiving microservice profile information at a microservice profiler, performing lexical analysis of the microservice profile information (where the lexical analysis produces tokenized information), generating microservice modification information by performing machine learning analysis of one or more inputs (where the one or more inputs comprise the tokenized information), and outputting the microservice modification information from the microservice profiler. The microservice profile information describes one or more characteristics of a microservice. The lexical analysis is performed by a lexical analysis engine of the microservice profiler, and the machine learning analysis is performed by a machine learning system of the microservice profiler.

Abstract: This application relates to apparatus and methods for automatically determining item relevancy based on textual information. In some examples, a computing device receives a search query, and a plurality of items corresponding to the search query. The computing device may identify one or more features of the search query. The computing device may generate relevancy values for each of the items based on the features of the search query, and features of each of the plurality of items. For example, the computing device may generate, for each of the items, a plurality of relevance values, each relevance value generated based on a feature of the search query and corresponding features of the item. The computing device may transmit the generated relevancy values for the plurality of items. In some examples, the computing device may rank the plurality of items based on the generated relevancy values.

Abstract: Methods, systems, and computer program products for selection of a witness during virtualization system recovery after a disaster event. A recovery plan is configured to identify a witness that is then used to elect a leader to implement the recovery. Various system, and/or network, and/or component failures and/or various loss of function of components of the virtualization system can trigger initiation of the recovery plan. Based on the particular recovery plan that is invoked upon a determination of a network outage, or component failure or loss of function of a component of the virtualization system, a particular witness corresponding to a subset of entities of the particular recovery plan is selected. The witness is used to elect the leader, and the leader initiates actions of the recovery plan. The implementation of the recovery plan includes consideration of the health of components that would potentially be involved in the recovery actions.

Abstract: Methods, apparatus, and processor-readable storage media for automatically validating design parameters for enterprise applications are provided herein. An example computer-implemented method includes obtaining image data and code data of a given application associated with an enterprise; processing at least a portion of the image data against at least a portion of design parameters of the enterprise by processing the at least a portion of the image data and a set of design-compliant image data using similarity algorithms; processing at least a portion of the code data against at least a portion of the design parameters by performing an automated scan of the at least a portion of the code data against at least one code-related portion of the design parameters; and performing automated actions based on the processing of the image data and/or the processing of the code data.

Abstract: A method being implemented via execution of computing instructions configured to run at one or more processors and stored at one or more non-transitory computer-readable media. The method can include training two sets of item embeddings for items in an item catalog and a set of user embeddings for users, using a triple embeddings model, with triplets. The triplets each include a respective first user of the users, a respective first item from the item catalog, and a respective second item from the item catalog, in which the respective first user selected the respective first item and the respective second item in a respective same basket. The method also can include randomly sampling an anchor item from a category of items selected by a user. The method additionally can include generating a list of complementary items using a query vector associated with the user and the anchor item.

Abstract: A tissue repair patch having an outer side and an inner side is described. The tissue repair patch includes a structural component comprising collagen and/or chorion and a regenerative component comprising amniotic tissue. Methods of tissue repair using the tissue repair patch are also described.

Abstract: A method and a system for generating required feature output by providing a FaaS (Function-as-a-Service) based feature library using a DAG (Directed Acyclic Graph), are disclosed. A library is configured to store logic codes being generated for a plurality of features and the library is then deployed on a FaaS engine. At least one feature selection configuration from a user is received by the FaaS engine. The DAG implements at least one transformation based on the at least one feature selection configuration, and the FaaS engine thereby generates the required feature output for the user.

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: Aspects of the disclosure provide a method of identifying off-road entry lane waypoints. For instance, a polygon representative of a driveway or parking area may be identified from map information. A nearest lane may be identified based on the polygon. A plurality of lane waypoints may be identified. Each of the lane waypoints may correspond to a location within at least one lane. The polygon and the plurality of lane waypoints may be input into a model. A lane waypoint of the plurality of lane waypoints may be selected as an off-road entry lane waypoint. The off-road entry lane waypoint may be associated with the nearest lane. The association may be provided to an autonomous vehicle in order to allow the autonomous vehicle to use the association to control the autonomous vehicle in an autonomous driving mode.

Abstract: A system and method include migrating, by a migration controller, a first entity of a first subset of entities from a source site to a target site in a virtual computing system based on an asynchronous mode of replication. The system and method also include replicating, by the migration controller, data of a second entity of a second subset of entities from the source site to the target site based on a synchronous mode of replication in parallel with the migration of the first entity for dynamically adjusting a recovery time objective parameter.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that generates path prediction data for agents in the vicinity of an autonomous vehicle using machine learning models. One method includes identifying an agent in a vicinity of an autonomous vehicle navigating an environment and determining that the agent is within a vicinity of a crossing zone, which can be marked or unmarked. In response to determining that the agent is within a vicinity of a crossing zone: (i) features of the agent and of the crossing zone can be obtained; (ii) a first input that includes the features can be processed using a first machine learning model that is configured to generate a first crossing prediction that characterizes future crossing behavior of the agent, and (iii) a predicted path for the agent for crossing the roadway can be determined from at least the first crossing prediction.

Abstract: Embodiments of the present disclosure provide for improved mapping from sequential semi-structured data of a first custom data format to a second custom data format. The improved mechanism for mapping between custom data formats significantly reducing the amount of manual effort otherwise used for creating mapping rules. Example embodiments utilize a state extractor model that extracts an untrained modified finite state machine embodied by a skeleton set of extracted states from particular sequential semi-structured input data, and generate a trained modified finite state machine that maps the first custom data format to the second custom data format based at least in part on the untrained modified finite state machine, sequential semi-structured input data of the first custom data format, and database structured output data of the second custom data format. The trained modified finite state machine may be used for subsequent processing data of the first custom data format.

Abstract: Methods, systems, and computer program products for selection of a witness during virtualization system recovery after a disaster event. A recovery plan is configured to identify a witness that is then used to elect a leader to implement the recovery. Various system, and/or network, and/or component failures and/or various loss of function of components of the virtualization system can trigger initiation of the recovery plan. Based on the particular recovery plan that is invoked upon a determination of a network outage, or component failure or loss of function of a component of the virtualization system, a particular witness corresponding to a subset of entities of the particular recovery plan is selected. The witness is used to elect the leader, and the leader initiates actions of the recovery plan. The implementation of the recovery plan includes consideration of the health of components that would potentially be involved in the recovery actions.

Abstract: A method, system and computer-usable medium are disclosed for executing a comparative analysis of microservice profiles and recommending modifications to a microservice. In at least one embodiment, a plurality of microservice analysis daemons and a plurality of microservices are deployed to nodes of a network. Run-time execution characteristic of the plurality of microservices are monitored and gathered by the analysis daemons for microservices executed at the node at which the microservice analysis daemon is deployed. Microservice profiles are generated using the run-time execution characteristics data and data retrieved from a service registry. Recommendations regarding modification of one or more microservices are made based on the results of a microservice profile comparative analysis.

Abstract: A method and a system for refining column mappings using byte level attention based neural model are disclosed. Based on a plurality of synthetic data and a plurality of input column names, an encoded data is generated for each of the one or more by present in the input column names. The encoded data is used to train a deep learning (DL) model having a word level auto regressive decoder for identifying at least one meaning for each byte of each of the received plurality of input column names. Further, a plurality of pre-existing column descriptions may be used to determine whether or not the identified at-least one meaning matches with at least one description of the plurality of column descriptions. Subsequently, fine tuning or refining of the meanings may be conducted to adequately obtain corresponding mapping prediction output.

Abstract: Systems and methods provide deceleration fuel cutoff regeneration of a gas particulate filter. A powertrain system includes an exhaust system containing the gas particulate filter, which is configured to collect particulate matter from an exhaust gas stream of the powertrain system. A temperature sensor is configured to monitor a temperature of the gas particulate filter. A loading monitor, such as a sensor and/or a model, is configured to provide a loading input of particulate loading of the gas particulate filter. At least one controller is configured to: determine, by comparing the loading input to stored values, whether the gas particulate filter requires the regeneration; effect a warmup of the gas particulate filter when the determination shows the gas particulate filter requires the regeneration; and initiate the regeneration when a value received from the temperature sensor meets a minimum threshold level.