Abstract: Single-axis teeter-totter accelerometers having a plurality of anchors are disclosed. The plurality of anchors may be arranged about a rotation axis of the teeter-totter proof mass. Each of the plurality of anchors may be coupled to the proof mass by two torsional springs each extending along the rotation axis. The plurality of anchors allows an increased number of torsional springs to be coupled to the proof mass and thus greater torsional stiffness for the proof mass may be achieved. Due to the higher torsional stiffness, the disclosed single-axis teeter-totter accelerometers may be deployed in high-frequency environments where such increased torsional stiffness is required, for example, around 20 kHz and above.

Abstract: Mapping applications or smart contracts to a data confidence fabric. A smart contract is deployed and executed in a data confidence fabric based on trust requirements of the smart contract. The trust requirements are mapped to the nodes of the data confidence fabric. A ledger is created on the identified nodes and the application is deployed to and run on the identified nodes.

Abstract: A method, system, and computer program product for fraud management with a shared hash map. A shared hash map may include a plurality of identifiers mapped to a plurality of buckets by at least one hash function. One or more buckets of the plurality of buckets may include at least one blockchain. The at least one blockchain may include fraud data associated with one or more fraudulent transactions. A method may include storing the shared hash map, receiving an update to the shared hash map, and providing a copy of the shared hash map. A method may include storing a local copy of the shared hash map, receiving transaction data associated with a transaction, accessing fraud data in the local copy of the shared hash map, and determining an authorization or a denial of the transaction based on the fraud data.

Abstract: A route anomaly detection and remediation system analyzes a prefix for each route received to validate the route. A route monitoring component provides a centralized querying system for all routers from all devices to study routing history. A route collection component receives and stores all routes from multiple routers at a server. A set of microservice analysis components performs prefix analysis on each received route. Each microservice analysis component analyzes one or more portions of the prefix for each route to detect hijacked routes, leaked routes, withdrawn routes and/or other unhealthy routes before the routes are utilized for routing traffic on the network. The analysis performs new prefix validation and identifies healthy routes. Alerts identifying invalid routes are transmitted to an incident management system. Healthy routes are approved for usage by routers on the network to prevent network outages while improving network reliability, availability and stability.

Abstract: A system for a system for controlling a vehicle fuel-level display includes one or more processors and a memory communicably coupled to the one or more processors and storing a fuel-level display control module. The module includes computer-readable instructions that when executed by the one or more processors cause the one or more processors to, responsive to generation of a control signal, control operation of the vehicle so as to cause the fuel-level display to display a predetermined false low-fuel level.

Abstract: A mobile device based multi-analyte testing analyzer for use in medical diagnostic monitoring and screening, and a method of manufacturing the same are disclosed. A reflectance based, colorimetric test strip reader for use with a mobile device having a jack plug receiving socket, said test strip reader adapted for removably receiving a test strip having a test strip longitudinal axis, comprising a housing; a jack plug operably coupled to and extending from said housing and adapted for operable coupling with said jack plug receiving socket; a test strip adapter including structure defining a test strip receiving channel; a light source oriented within said housing for directing light toward said test strip receiving channel to illuminate a test strip arranged within said test strip adapter; and a light sensor oriented within said housing to sense light reflected from a test strip carried by said test strip receiving channel.

Abstract: Systems and methods for information retrieval are described. Embodiments generate a dense embedding for each of a plurality of media objects to be searched, generate a sparse embedding for each of the media objects using an encoder that takes the dense embedding as an input, wherein the sparse embedding satisfies a sparsity constraint that is applied to at least one layer of the encoder during training, and perform a search on the plurality of media objects based at least in part on the sparse embedding.

Abstract: A method may include determining that a digit pattern has been input on a user device to initiate a call; transmitting the digit pattern to a device that stores a list of digit patterns to which calls are not to be completed; receiving, from the device, data that indicates whether the digit pattern is on the list of digit patterns; prohibiting the call from being initiated with a network when the data indicates that the digit pattern is on the list of digit patterns; and initiating the call with the network when the data indicates that the digit pattern is not on the list of digit patterns.

Abstract: A system includes a computer for a vehicle including a processor and a memory. The memory stores instructions executable by the processor to determine a first location of the vehicle, to send the first location to a stationary infrastructure element, to receive, from the stationary infrastructure element, a second location of the vehicle determined from (a) infrastructure sensor data upon identifying the vehicle from a plurality of vehicles, and (b) the first location sent by the vehicle, and to determine a third location of the vehicle based on the infrastructure-determined second location and the first location.

Abstract: An example apparatus includes a first frame buffer configured to store video data; a second frame buffer configured to store video data; and one or more processors configured to: reconstruct samples of a first block of a current picture of video data; store, in parallel, a compressed version of the samples of the first block of video data in the first frame buffer and an uncompressed version of the samples of the first block of video data in the second frame buffer; and responsive to determining to reconstruct a second block of the current picture of video data using intra block copy: obtain, from the second frame buffer, samples of a predictor block located in the current picture of video data, the predictor block at least partially overlapping the first block of video data; and predict, based on the obtained samples of the predictor block, samples of the second block.

Abstract: An access point configured to manage client devices connected to the access point. The access point initiates an operational change. The access point generates an announcement to be included in a network frame based on the operational change. The announcement includes at least a list of neighboring access points with which the client devices can connect to and a first time period by which the client devices must connect to at least one neighboring access point included in the list of neighboring access points. The access point broadcasts the network frame to the client devices. Upon expiration of the first time period, the access point disassociates client devices that remain connected to the access point.

Abstract: Provided are systems, methods, and computer-readable medium for a simulation platform that can generate simulated activity data for testing a security monitoring and control system. In various examples, the simulation platform can parse the activity data from a cloud service to generate a template, where each entry in the template describes an action and the fields associated with the action. The simulation platform can further generate a configuration that describes a test scenario. The simulation platform can use the configuration and the template to generate the particular action, including randomizing some or all of the fields of the action. When input into the security monitoring and control system, the system can operate on the simulated activity data in the same way as when the system ingests live activity data.

Abstract: In various examples, a first network interface duplicates received network traffic and forwards a first set of network traffic data to a central processing unit (CPU) and a second set of identical network traffic to one or more parallel processing units (PPUs). In an embodiment, the one or more PPUs analyze the second set of network traffic to identify whether the second set of network traffic is malicious. First, the one or more PPUs filter and classify the second set of network traffic into flows, or logical groupings or subsets of the second set of network traffic. Second, the one or more PPUs sort the network packets within each flow and extract features of interest specific to each flow. Using the extracted features of interest, one or more deep learning techniques infer a status indicating whether each flow is malicious (mal) or good.

Abstract: A process of manufacturing a foot mat is disclosed. The process includes providing a mold containing a plurality of first and second cavities, pouring a first solution of predefined colors in the plurality of first cavities of the mold and injection molding of a second solution in the plurality of second cavities of the mold to form a foot mat.

Abstract: A method for recovering data. The method including collecting identity factors at a user device, wherein hashes of the identity factors are configured to be stored at a server. The method including generating at the user device a dynamic password based on the identity factors and a Salt configured to be generated by the server and configured to be delivered to the user device. The method including generating at the user device a data key and encrypting the data key using the dynamic password to generate an encrypted data key configured to be stored at the server. The method including encrypting at the user device data items using the data key to generate encrypted data items configured to be stored at the server. As such, the data items are recoverable by presenting the identity factors to the server.

Abstract: A method for controlling a robotic vehicle in a delivery environment includes causing the robotic vehicle to deploy from an autonomous vehicle (AV) at a first AV position in the delivery environment. The method further includes localizing, via a robotic vehicle controller, an initial position within a global reference map using a robot vehicle perception system, receiving, from the AV, a 3-dimensional (3D) augmented map and localizing an updated position in the delivery environment based on the 3D augmented map and the global reference map. The robot vehicle perception system senses obstacle characteristics, and generates a unified 3D augmented map with robot-sensed obstacle characteristics. The method further includes generating a dynamic path plan to a package delivery destination using the unified 3D augmented map, and actuating the robot vehicle to the package delivery destination according to the dynamic path plan.

Abstract: Embodiments are directed to methods and systems for automatically determining a resource layout. An example embodiment begins by obtaining data indicating a position and a task performed by each resource of a plurality of resources. Then, for each resource of the plurality, a respective zone on a plane of interest occupied by the resource is automatically determined using the obtained data indicating the position and the task performed by the resource. In turn, determined zones of two or more resources of the plurality of resources are automatically combined into a combined zone based upon criteria and a file, e.g., a CAD/CAM file, indicating a layout of the plurality of resources on the plane of interest is automatically created based upon the determined zones and the combined zone.

Abstract: The disclosure describes embodiments for vehicle-to-everything (V2X) data transfer for automated vehicles. In some embodiments, a method includes providing or attempting to provide, by a communication unit of an ego vehicle, digital data to a communication device based on a mode of the communication unit, where the digital data is relayed by the communication device to be received by a server. The method includes determining, by a processor of the ego vehicle, feedback that describes a bandwidth constraint of the communication unit. The method includes modifying, by the processor, the mode based on the feedback so that the mode is consistent with the bandwidth constraint and the digital data is successfully received by the server.

Abstract: Autoscaling comprises: accessing operational data associated with a pool of servers; determining an expected load associated with a service provided by the pool of servers based at least in part on the operational data; determining an estimated capacity associated with the service provided by the pool of servers; determining that an autoscale operation is to be performed based at least in part on the expected load and the estimated capacity, wherein the autoscale operation automatically scales out one or more additional servers or automatically scales in one or more servers in the pool of servers; and performing the autoscale operation.

Abstract: The present disclosure provides an application development platform and associated software development kits (“SDKs”) that provide comprehensive services for generation, deployment, and management of machine-learned models used by computer applications such as, for example, mobile applications executed by a mobile computing device. In particular, the application development platform and SDKs can provide or otherwise leverage a unified, cross-platform application programming interface (“API”) that enables access to all of the different machine learning services needed for full machine learning functionality within the application. In such fashion, developers can have access to a single SDK for all machine learning services.