Abstract: A system for planning an operation includes a communication interface and processor(s). The processor(s) is/are configured to: receive an indication that the drone is part of a set of assets, wherein the set of assets are tasked with performing element(s) of task(s), and the set of assets comprises a plurality of drones; communicate information pertaining to the element(s), wherein: 1) the information pertaining to the element(s) is communicated with at least one other drone; 2) the information pertaining to the element(s) is based at least in part on information obtained by sensor(s) of the set of assets; and 3) the information pertaining to the element(s) is used in connection with determining a plan to perform the task(s); and communicate information pertaining to the plan to perform the task(s), wherein the information pertaining to the plan to perform the task(s) is communicated with at least one other drone.

Abstract: Methods and Systems are provided for performing early onset diagnostics for clogged injectors using fuel trims collected from the Engine Management System and evaluated in different operating modes of the engine. Example implementations use fuel trims that can estimate the contrast in combustion ratio ? across different operating modes defined on the engine speed and calculated engine load plane. Features are extracted, then classified using machine learning to output a diagnosis according to different levels of fuel injector clogging.

Abstract: A high voltage fluid heater includes a housing that includes at least one of walls and openings along different sides of the housing to define at least one enclosure. The housing also includes an inlet and an outlet for fluid to flow into and out of the housing. The heater also includes a printed circuit board along a first plane along one side of the housing, a heating element controlled by the printed circuit board, a power transistor assembly including a plurality of power transistors, at least one thermal pad along a side wall of the housing, and at least one spring element. Each power transistor includes a plurality of lead frames emanating from the transistor and adapted to be connected to the printed circuit board. The fluid heater also includes a spring element adapted to be mounted on the housing.

Abstract: A system generating an environment for an operation using a set of assets includes processor(s) configured to: obtain data associated with task(s) to be performed by a set of assets, wherein: 1) the set of assets comprises semi-autonomous drones and 2) the data associated with the task(s) comprises parameter(s) pertaining to a geographic location in which at least one asset is to perform the task(s); determine a discretized representation of the geographic location, wherein the discretized representation comprises discrete elements each corresponding to a volume associated with the geographic location; annotate the discretized representation to create an annotated representation with the parameter(s) pertaining to the geographic location with a subset of the discrete elements based on a determination that the parameter(s) pertain to the geographic location; determine a plan to perform the task(s), wherein the plan is based on the annotated representation; and cause the task(s) to be performed.

Abstract: Systems and techniques are described herein for an adaptive camera preview frame rate. For example, a computing device can compare a current image frame of a scene with a previous image frame of the scene. The computing device can determine whether the scene comprises an idle scene scenario based on comparing the current image frame with the previous image frame.

Abstract: Embodiments of the present disclosure provide a method of communication in a base station (BS). The BS comprising a distributed unit (DU) and at least one radio unit (RU), said DU performs High-PHY processing and said RU performs low-PHY processing. The method comprises transmitting, by the DU, a control information to the at least one RU using at least one of a c-plane message and a m-plane message, and data using au-plane message. The u-plane message is transmitted in one of a semi persistent and periodic technique. The transmitting of the at least one of a c-plane message and am-plane message indicates the u-plane data as one of a semi persistent and a periodic, said transmitting is valid for the u-plane messages carrying the u-plane data for a predetermined time period.

Abstract: Embodiments of the present disclosure provide a method of communication in a base station (BS). The BS comprising a distributed unit (DU) and at least one radio unit (RU), said DU performs High-PHY processing and said RU performs low-PHY processing. The method comprises transmitting, by the DU, a control information to the at least one RU using at least one of a c-plane message and a m-plane message, and data using au-plane message. The u-plane message is transmitted in one of a semi persistent and periodic technique. The transmitting of the at least one of a c-plane message and am-plane message indicates the u-plane data as one of a semi persistent and a periodic, said transmitting is valid for the u-plane messages carrying the u-plane data for a predetermined time period.

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

Abstract: A system generating an environment for an operation using a set of assets includes processor(s) configured to: obtain data associated with task(s) to be performed by a set of assets, wherein: 1) the set of assets comprises semi-autonomous drones and 2) the data associated with the task(s) comprises parameter(s) pertaining to a geographic location in which at least one asset is to perform the task(s); determine a discretized representation of the geographic location, wherein the discretized representation comprises discrete elements each corresponding to a volume associated with the geographic location; annotate the discretized representation to create an annotated representation with the parameter(s) pertaining to the geographic location with a subset of the discrete elements based on a determination that the parameter(s) pertain to the geographic location; determine a plan to perform the task(s), wherein the plan is based on the annotated representation; and cause the task(s) to be performed.

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

Abstract: Some embodiments control access by applications to resources in a computing environment. An embodiment notes a request from an application to access a resource, determines a compliance status of the application based on access control policy compliance criteria, ascertains an authorization status of the request based on an authorization credential of the request and an authorization requirement of the resource, and responds to the request based on the compliance status and also based on the authorization status, thereby providing fine-grained access control. Access may also be controlled based on a request's beneficiary. An access request response may allow access, deny access, or ask for additional authorization. A compliance classifier reduces risk by dynamically updating compliance status after compliance criteria changes or attribute changes. An identity service access control architecture uses a compliance attribute to improve efficiency.

Abstract: A method includes generating a model for a content taxonomy using one or more machine learning (ML) techniques. The model comprises a plurality of metadata tags for electronic content. In the method, a plurality of electronic content items are received from a plurality of content management systems, and are analyzed using the one or more ML techniques. The method also includes assigning one or more of the plurality of metadata tags to each of the plurality of electronic content items based on the analysis, and transmitting to the plurality of content management systems via one or more application programming interfaces, a plurality of recommendations comprising which of the plurality metadata tags to apply to the plurality of electronic content items.

Abstract: Methods, systems, and computer-readable media for automated packetless network reachability analysis are disclosed. An analysis is performed of network configuration data for a network comprising a host computer. Based at least in part on the analysis, one or more ports at the host computer that are reachable from another computer are determined. Based at least in part on the analysis, one or more routes to the one or more ports are determined. A report is generated that is descriptive of the one or more ports and the one or more routes.

Abstract: This disclosure describes techniques for configuring and managing scalable global private networks associated with a service provider. Different input mechanisms, such as an API, a UI, or a CLI may be utilized to configure, and manage a global private network that spans across the cloud in different geographic locations and connects to different stand-alone networks. The user may proactively use the input mechanisms to configure and query different network resources to reactively configure settings for reacting to one or more events. The input mechanisms may also be utilized to define the network resources to be modeled within the global private network as well as connections within the global network. A user may configure events/metrics to be monitored, tasks/workflows to be performed, and the like. In some configurations, a network management service (NMS) may perform health monitoring and reachability monitoring to identify possible issues in the global network.

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

Abstract: Embodiments of the present disclosure provide a method of communication in a base station (BS). The BS comprising a distributed unit (DU) and at least one radio unit (RU), said DU performs High-PHY processing and said RU performs low-PHY processing. The method comprises transmitting, by the DU, a control information to the at least one RU using at least one of a c-plane message and a m-plane message, and data using a u-plane message. The u-plane message is transmitted in one of a semi persistent and periodic technique. The transmitting of the at least one of a c-plane message and a m-plane message indicates the u-plane data as one of a semi persistent and a periodic, said transmitting is valid for the u-plane messages carrying the u-plane data for a predetermined time period.

Abstract: Methods, systems, and computer-readable media for automated packetless network reachability analysis are disclosed. An analysis is performed of network configuration data for a network comprising a host computer. Based at least in part on the analysis, one or more ports at the host computer that are reachable from another computer are determined. Based at least in part on the analysis, one or more routes to the one or more ports are determined. A report is generated that is descriptive of the one or more ports and the one or more routes.

Abstract: A system for planning an operation includes a communication interface and processor(s). The processor(s) is/are configured to: receive an indication that the drone is part of a set of assets, wherein the set of assets are tasked with performing element(s) of task(s), and the set of assets comprises a plurality of drones; communicate information pertaining to the element(s), wherein: 1) the information pertaining to the element(s) is communicated with at least one other drone; 2) the information pertaining to the element(s) is based at least in part on information obtained by sensor(s) of the set of assets; and 3) the information pertaining to the element(s) is used in connection with determining a plan to perform the task(s); and communicate information pertaining to the plan to perform the task(s), wherein the information pertaining to the plan to perform the task(s) is communicated with at least one other drone.

Abstract: A system and method for grouping assets is disclosed. The system includes one or more processors configured to: receive, via the communication interface, data associated with one or more tasks to be performed by a set of assets, determine, from among a plurality of assets, the set of assets to perform the one or more tasks, including determining one or more capabilities associated with one or more characteristics of the one or more tasks, and determining the plurality of drones based at least in part on the one or more capabilities associated with one or more characteristics of the one or more tasks, and one or more drone capabilities respectively associated with the drones, and communicate an instruction to at least one drone in the set of assets, the instruction indicating that the one or more tasks are to be completed by the at least one drone.

Abstract: A system generating an environment for an operation using a set of assets includes processor(s) configured to: obtain data associated with task(s) to be performed by a set of assets, wherein: 1) the set of assets comprises semi-autonomous drones and 2) the data associated with the task(s) comprises parameter(s) pertaining to a geographic location in which at least one asset is to perform the task(s); determine a discretized representation of the geographic location, wherein the discretized representation comprises discrete elements each corresponding to a volume associated with the geographic location; annotate the discretized representation to create an annotated representation with the parameter(s) pertaining to the geographic location with a subset of the discrete elements based on a determination that the parameter(s) pertain to the geographic location; determine a plan to perform the task(s), wherein the plan is based on the annotated representation; and cause the task(s) to be performed.