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.

Abstract: Methods and systems are disclosed for allocating tasks between apparatus in an IoT system in a manner to generally minimize the total amount of time to execute the tasks. At least one embodiment includes a computer-implemented method for allocating task processing between an internet of things (IoT) device and an edge device. The computer-implemented method includes collecting data from one or more sensors to execute a task having data size Xt; predicting a space complexity data size Xc for the task based on data size Xt, and allocating data for processing between the IoT device and edge device as a function of Xc. In at least one embodiment, the space complexity data size Xc is determined by applying Xt to the input of a long short-term memory neural network.

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: 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 method includes receiving code for computer programming, analyzing the code and extracting a plurality of configuration properties from the code. In the method, one or more configuration files are generated from the extracted plurality of configuration properties, and microservice code is generated from the one or more configuration files. The microservice code is configured for deployment on one or more cloud computing platforms.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving a user identifier, receiving an item identifier, determining user item quantity information related to quantities of the item previously selected by the user, determining a respective household size for each user, and determining aggregate household item quantity information related to quantities of the item previously selected by an aggregate of users of the same household size. If a first threshold level of the quantity of transactions is met, a recommended quantity is based on the user item quantity information, and if not, the recommended quantity is based on the aggregate household item quantity information. The user interface of the electronic device is updated to notify the user of the recommended quantity. Other embodiments are disclosed herein.

Abstract: As an example, a computing device may broadcast, via a software application, a message to multiple computing devices requesting devices to participate in an activity occurring at a particular time at a particular location. A subset of the multiple computing devices may gather at the particular location prior to the particular time to participate in the activity. Prior to the particular time, the computing device may discover the subset and create a peer-to-peer network. Based on a set of attributes associated with each computing device in the subset, the computing device may assign individual computing devices in the subset a role and a position. Each of the computing devices in the subset may be positioned in the particular location according to the position and perform the role at the particular time to collectively perform the activity.

Abstract: A method for grouping data in a data center into one or more maintenance domains (MD) which then processed, copied and mirror hosted as one or copies of maintenance domain. Each application running in the data center is evenly distributed across the MDs. For an maintenance one or more copy of the MD is updated and changes propagated through the copies of hosted MD. Thus, successfully shutting down only one or more MD for maintenance without affecting the availability of entire data center.

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

Abstract: In some examples, a security application may monitor data received from one or more of sensors of a computing device, one or more input devices of the computing device, or one or more biometric sensors of a smartwatch that is connected to the computing device. If the user is not logged in and the user that is carrying the computing device has an uneven gait or is stumbling, the security app may, when the user initiates a login process, gather additional data, such as, from the sensors, the smartwatch, or both. If the user makes too many errors, based on data from the input devices, when attempting to login or after logging in, the security application may gather additional data. If the additional data indicates that the user may be under the influence of prescription or recreational drugs or alcohol, the user may be prevented from logging in.

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 one or more machine learning models. One of the methods includes identifying an agent in a vicinity of an autonomous vehicle navigating through an environment and determining that the agent is within a vicinity of a crossing zone across a roadway. The crossing zone can be a marked crossing zone or an unmarked crossing zone. For example, the crossing zone can be an unmarked crossing zone that has been identified based on previous observations of agents crossing the roadway.

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, 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.