Abstract: This disclosure provides a method, apparatus, and computer-readable medium for wireless communication at a modem, comprising receiving, via an interface with a host, an internet protocol (IP) packet including a first transport protocol header and a first IP header. The IP packet has a size greater than a maximum transport unit (MTU) size allowable for each packet transmitted over a communication link. The modem segments the IP packet into a plurality of segments based on a segment size indicated by a segmentation policy. Each segment includes a respective derived segment transport protocol header and a respective derived segment IP header derived from the IP packet. Each of these derived headers includes at least one field based on the segmentation policy, and each of the segment transport protocol headers includes a checksum for the respective segment. Additionally, the modem transmits the plurality of segments over the communication link.

Abstract: A computing system including a processor configured to receive packet preamble binary data and packet header binary data associated with a satellite. The processor may generate a simulated signal that encodes the packet preamble binary data and the packet header binary data. The processor may receive a satellite downlink signal. Within each of a plurality of sample intervals of the satellite downlink signal, the processor may compute a respective correlation between the satellite downlink signal and at least a portion of the simulated signal. The processor may select an identified sample interval of the plurality of sample intervals based at least in part on the plurality of correlations. The processor may decode binary satellite signal data based at least in part on the identified sample of the satellite downlink signal. The processor may output the binary satellite signal data.

Abstract: An apparatus and method for inline scanned image enrichment is provided. The apparatus includes a computing device configured to receive a plurality of subject data, generate a candidate set to model the scan focal points from, digitally capture the slide using the identified focal points through machine-learning processes, processing the captured image to optimize its viewability, and storing the captured image in an accessible repository.

Abstract: A system, a computing platform, and a method of integrating data from a plurality of data sources are disclosed herein. The method includes receiving datapoints from the plurality of data sources via one or more connectors in real-time. The datapoints are received in accordance with a data model represented at least in part by the one or more connectors. The method includes generating relationships between the datapoints based on at least a semantic mapping of the datapoints using a semantic model, and integrating the datapoints from the plurality of data sources in real-time based on at least one of the relationships and the data model.

Abstract: Systems and methods include receiving an input including a plurality of data points; processing the input at times where data points are received; preprocessing the input at times where some data points are lagging, the preprocessing includes a computation based on one or more predicted input values for lagging data points and storing one or more predicted output values in a cache based on the one or more predicted input values; and responsive to receiving the lagging data points, obtaining an associated output value from the cache.

Abstract: A computing system including a processor configured to receive packet preamble binary data and packet header binary data associated with a satellite. The processor may generate a simulated signal that encodes the packet preamble binary data and the packet header binary data. The processor may receive a satellite downlink signal. Within each of a plurality of sample intervals of the satellite downlink signal, the processor may compute a respective correlation between the satellite downlink signal and at least a portion of the simulated signal. The processor may select an identified sample interval of the plurality of sample intervals based at least in part on the plurality of correlations. The processor may decode binary satellite signal data based at least in part on the identified sample of the satellite downlink signal. The processor may output the binary satellite signal data.

Abstract: Techniques for performing rendering operations are disclosed herein. The techniques include providing indices and vertices to a culling shader; culling primitives and outputting primitives and indices that are not culled; and generating information for a fine binning pass based on the indices and primitives that are not culled.

Abstract: The present invention achieves a technique that makes it possible to estimate a ground contact load of a vehicle with sufficiently high accuracy. A ground contact load estimation device (100) acquires a wheel angular speed, a steady load, and an inertia load of a vehicle, uses the steady load and the inertia load to cause a first gain calculation section (122) to calculate a first gain, multiplies a variation in wheel angular speed by a second gain so as to cause a tire effective radius variation calculation section (121) to calculate a tire effective radius variation, and multiplies the tire effective radius variation by the first gain so as to estimate a road surface load.

Abstract: Disclosed herein are methods and systems for automatically validating evidence of traffic violations. One instance of a method comprises receiving an evidence package comprising video frames showing a vehicle involved in a potential traffic violation. The video frames can be input into one or more deep learning models to obtain a plurality of classification results. The method can further comprise generating a score based in part on the classification results and evaluating the score against one or more thresholds to determine whether the evidence package is automatically approved, is automatically rejected, or requires further review.

Abstract: Methods and systems for updating a first assignment of resources include: identifying, by a computing device, based on data describing a first assignment of resources, one or more time periods of the first assignment of resources for which there is an under-assignment of resources; and automatically generating, by the computing device, using data describing one or more auxiliary resources, data describing a second assignment of resources which assigns one or more of the auxiliary resources to the identified one or more time periods.

Abstract: A data management system (DMS) may perform techniques for snapshotting a host environment data store using a resource volume. The DMS may transmit, to the host environment a first request for a full backup of a data store of the host environment, where the first request results in mounting of a resource volume in an empty state. The DMS may generate a snapshot of the resource volume after completion of the backup at the host. The DMS may transmit one or more second requests for incremental backups, where the second requests result in mounting of the volume in a state corresponding to a previous backup of the host. The DMS may generate a second snapshot of the resource volume. For a subsequent full backup, the DMS may cause mounting of the volume in the empty state to the host rather than mounting the resource volume corresponding to a prior snapshot.

Abstract: Disclosed herein are systems and apparatus for detecting a traffic violation. In one embodiment, a system for detecting a traffic violation comprises a context camera assembly and a license plate recognition (LPR) camera assembly. The context camera assembly can comprise a context camera housing containing a context camera, a context camera mount configured to mount the context camera housing to an interior of a carrier vehicle, and a context camera skirt coupled to and protruding outwardly from the context camera housing. The license LPR camera assembly can comprise an LPR camera housing containing one or more LPR cameras, an LPR camera mount configured to mount the LPR camera housing to the interior of the carrier vehicle, and one or more LPR camera skirts coupled to and protruding outwardly from the LPR camera housing.

Abstract: Technologies are generally described for delivery vehicles and containers for en route food product preparation. Modular food product preparation systems that may receive food items and supplies and prepare food product(s) en route such that the food product(s) is prepared by the time the system reaches a delivery destination may include trucks, railway cars, watercraft, and similar vehicles. Food preparation process steps and timing may be determined based on travel information (e.g., delivery destination, routes, etc.), as well as, food item and food product information. An on-board controller may determine the process steps and timing(s) and control operations of robotic devices arranged modularly in a container or vehicle to execute steps of the food preparation process. Alternatively or additionally, the on-board controller may receive instructions from a remote controller. Travel parameters of the vehicle may also be adjusted based on the food preparation process and/or travel information.

Abstract: A method for upgrading computing devices in a distributed computing environment is provided. The method includes receiving first and second rollout requests for a cluster relating to operational actions for computing devices associated with the cluster. A rollout status for the cluster is determined and the rollout requests are simultaneously performed on the cluster where the operational actions are simultaneously performed on the computing devices associated with the cluster. In addition, a rollout status is updated based on simultaneously performing the rollout requests for the cluster.

Abstract: Some embodiments provide a method of managing policy for a logical network spanning multiple datacenters, including at least first and second datacenters. The method is performed by a network management service operating in a public cloud to manage the datacenters. The method receives (i) a first policy configuration specifying logical network policy at the first datacenter from a first local network manager at the first datacenter and (ii) a second policy configuration specifying logical network policy at the second datacenter from a second local network manager at the second datacenter. The method consolidates the first and second policy configurations into a global policy configuration that also includes policy configuration defined at the network management service. The method uses the global policy configuration to manage the policy configurations for the logical network.

Abstract: In general, the disclosure describes techniques for dynamic application service level agreement (SLA) metric generation, distribution, and intent-based Software-Defined Wide Area Network (SD-WAN) link selection. For instance, a network device may determine a metric associated with an application or application-group. The network device may send the metric to a controller, and in response may receive from the controller a recommended SLA metric associated with the application or application-group. The network device may also compute an intent-based SLA metric based on the recommended SLA metric, one or more characteristics of one or more links connected to the network device, and a user configured intent model that defines a tolerance level to apply the recommended SLA metric. The network device may select, based on the intent-based SLA metric, a path to send traffic from the application or application-group.

Abstract: An apparatus includes circuitry configured to: receive a request from a radio access network algorithm to determine whether there is a distribution shift related to a temporal characteristic of a cell of a communication network; request data from a radio access network node or a controller platform related to the temporal characteristic; receive the requested data related to the cell from the radio access network node or the controller platform; determine whether there is a distribution shift related to the temporal characteristic; in response to determining that there is a distribution shift, select a learning type for an update to a model; and update the model such that, when the model is provided to an inference server, causes the radio access network algorithm to use the updated model to perform at least one action to optimize the performance of the radio access network node or other radio access network node.

Abstract: Some embodiments provide a method for deploying network management services for a plurality of tenants. The method is performed at a multi-tenant service executing in a container cluster implemented in a public cloud. For a first tenant, the method deploys a first set of network management services in the container cluster for managing a first group of datacenters of the first tenant. For a second tenant, the method deploys a second set of network management services in the container cluster for managing a second group of datacenters of the second tenant.

Abstract: Examples include maintaining a virtual pool of containers; receiving a request from a client for one of a plurality of services to performed; when the request includes client code, determining whether the request belongs to regular or priority queue based on two models; adding the request to an appropriate shard in the queue; getting the request from the selected one of the plurality of queues and assigning a container for the request from the virtual pool of containers, the client code to be executed in the container; and after the client code is executed in the container, deleting the container from the virtual pool.

Abstract: Aspects of the present disclosure provide techniques for classifying a trip. Embodiments include receiving, from a plurality of users, a plurality of historical trip records. Each of the plurality of historical trip records may comprise one or more historical trip attributes and historical classification information. Embodiments include training a predictive model, using the plurality of historical trip records, to classify trips based on trip records. Training the predictive model may comprise determining a plurality of hot spots based on the historical trip records, each of the plurality of hot spots comprising a region encompassing one or more locations, and associating, in the predictive model, the plurality of hot spots with historical classification information. Embodiments include receiving, from a user, a new trip record comprising a plurality of trip attributes related to a trip and using the predictive model to predict a classification for the trip based on the trip record.