Abstract: Disclosed are systems and methods for scintillation-based neural network for RADAR target classification. In some aspects, a method includes generating a point cloud from radio frequency (RF) scene responses received from a radio detection and ranging (RADAR) sensor for a scanned scene; populating a rolling buffer with frame data from the point cloud, the frame data including radar cross section (RCS) values, RCS scintillation measurements, and velocity values for objects in the scanned scene; inputting the RCS scintillation measurements and velocity values for an object of the objects to a convolutional neural network (CNN); and receiving a classification of the object from the CNN, wherein the CNN is to utilize a probability density function (PDF) estimate of the RCS scintillation measurements and the velocity values to determine fits with one or more reference PDFs based on a Neyman-Pearson evaluation, and wherein the fits are assessed to classify the object.

Abstract: Curvelet-based low level fusion of camera and RADAR sensor information is disclosed and includes processing RADAR data corresponding to a scene to generate a RADAR point cloud and processing camera image data corresponding to the scene using a curvelet transform to identify a target of interest in the scene and generate for the target of interest a target type, (x,y) coordinate values, and a curvelet magnitude per decomposition level. If discrepancies exist between (x,y) coordinate values of the RADAR point cloud and the target type, (x,y) coordinate values, and curvelet magnitude per composition level of the target of interest, a portion of the RADAR data processing is repeated to regenerate the RADAR point cloud; otherwise, the RADAR point cloud to a perception stack of a vehicle.

Abstract: In one example, an optoelectronic module may include a stack assembly including an electrical integrated circuit and an optical integrated circuit electrically and mechanically coupled to one another, an interposer electrically and mechanically coupled to the stack assembly, and an optical connector to optically couple the optical integrated circuit with an array of optical fibers.

Abstract: A system and method employs a chatbot into which a user can input an inquiry/question regarding a risk related topic is disclosed. The user can obtain an answer to the inquiry. The system and method can receive, via a chatbot interface, an inquiry. An intent of the inquiry can be determined using a natural language processing (NLP) model. The inquiry can be matched, using a classifier, to a related data set based on the determined intent. An output can be generated based on the related data set in response to the inquiry. The output can be transmitted for display on the chatbot interface.

Abstract: UPS systems, methods, and computer-readable mediums utilizing electromechanical bypass relays to switch from an on-line mode of operation to a green/bypass mode of operation include control logic to adaptively adjust the timing of when an inverter of a UPS turns off to prevent backfeeding a utility. After the UPS is instructed to transition from the on-line mode to the green mode, a monitoring period begins. During the monitoring period, a parameter related to the output current of the inverter is monitored and compared to a predetermined threshold. If the parameter exceeds the predetermined threshold before a fixed period time has elapsed, the inverter is turned off early. If the inverter current does not exceed the predetermined value within the fixed period of time, the inverter is turned off.

Abstract: A map-based graphical user interface for a social media application displays to special social media activity information based on submission of geo-tagged social media items to the platform. For users and or submitted items that need predefined location fuzzing criteria, such activity is represented in the graphical user interface at an intentionally inaccurate position.

Abstract: Systems and methods are provided for evaluation of networks and changes thereto using automated analysis of network models. The automated analysis can be used to determine how to implement and mutate networks efficiently and effectively, to determine whether and why network resources are unable to communicate with each other, and the like. Automated analysis can allow users (e.g., network administrators) to define networks and pose changes to networks using high-level policies (e.g., written in a declarative language), have those polices automatically translated to lower-level implementation operations for analysis, and in some cases have results of the analysis presented back to the users in an easy-to-understand form.

Abstract: An electronic device includes a housing defining an internal volume, a front opening, and a rear opening. The electronic device can include a display component disposed at the front opening and a rear cover disposed at the rear opening. A logic board can be disposed in the internal volume. The device can also include a thin film thermopile including a cold junction bonded to the logic board and a hot junction bonded to the rear cover.

Abstract: A processing service of a provider network may protect media content from being tampered with when it is transmitted from the provider network/transcoder to untrusted networks (e.g., third-party networks/CDNs) and to a media player. The processing service (e.g., the transcoder) generates a public and a private key. The service uses the private key to digitally sign content portions (e.g., video frames) before distribution to untrusted CDNs. The provider network creates a manifest that includes the public key. To play the media content, the media player obtains a manifest that includes the public key (via a secure/trusted connection with the provider network). The media player may then obtain the media content from an untrusted edge server/CDN and validate it using the public key that was separately obtained from the manifest (to verify the content was not tampered with).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing the execution of the operations of a neural network. One of the methods includes obtaining data representing a graph characterizing a plurality of operations of a neural network, wherein each node of the graph characterizes an operation of the neural network and each edge of the graph characterizes data dependency between the operations; processing the data representing the graph using a graph embedding neural network to generate an embedding of the graph; and processing the embedding of the graph using a policy neural network to generate a task output, wherein the task output comprises, for each of the plurality of operations of the neural network, a respective decision for a particular optimization task.

Abstract: A processing service of a provider network may protect media content from being tampered with when it is transmitted from the provider network/transcoder to untrusted networks (e.g., third-party networks/CDNs) and to a media player. The processing service (e.g., the transcoder) generates a public and a private key. The service uses the private key to digitally sign content portions (e.g., video frames) before distribution to untrusted CDNs. The provider network creates a manifest that includes the public key. To play the media content, the media player obtains a manifest that includes the public key (via a secure/trusted connection with the provider network). The media player may then obtain the media content from an untrusted edge server/CDN and validate it using the public key that was separately obtained from the manifest (to verify the content was not tampered with).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for compiler optimizations using a compiler optimization network. One of the methods includes receiving an input program, wherein the input program defines a graph of operation modules, wherein each node in the graph is a respective operation module, and each edge between nodes in the graph represents one operation module receiving the output generated by another operation module. The input program is processed by a compiler optimization network comprising a graph-embedding network that is configured to encode operation features and operation dependencies of the operation modules of the input program into a graph embedding representation and a policy network that is configured to generate an optimization action for each of one or more nodes encoded in the graph embedding representation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing the execution of the operations of a neural network. One of the methods includes obtaining data representing a graph characterizing a plurality of operations of a neural network, wherein each node of the graph characterizes an operation of the neural network and each edge of the graph characterizes data dependency between the operations; processing the data representing the graph using a graph embedding neural network to generate an embedding of the graph; and processing the embedding of the graph using a policy neural network to generate a task output, wherein the task output comprises, for each of the plurality of operations of the neural network, a respective decision for a particular optimization task.

Abstract: A vehicle airbag system includes an airbag module, a seat detector, and an electronic controller. The airbag module has an airbag that is configured to be movably mounted to a vehicle roof structure. The seat detector detects a position of a vehicle seat. The electronic controller is in communication with the airbag module and the seat detector. The controller controls the airbag module to inflate the airbag in a predetermined direction based on detected position of the vehicle seat by the seat detector.

Abstract: A processing service of a provider network may protect media content from being tampered with when it is transmitted from the provider network/transcoder to untrusted networks (e.g., third-party networks/CDNs) and to a media player. The processing service (e.g., the transcoder) generates a public and a private key. The service uses the private key to digitally sign content portions (e.g., video frames) before distribution to untrusted CDNs. The provider network creates a manifest that includes the public key. To play the media content, the media player obtains a manifest that includes the public key (via a secure/trusted connection with the provider network). The media player may then obtain the media content from an untrusted edge server/CDN and validate it using the public key that was separately obtained from the manifest (to verify the content was not tampered with).

Abstract: Systems and methods for conducting a payment transaction at a vending machine using a mobile device are disclosed herein. A vending machine includes a Bluetooth Low Energy (BLE) module that is used to connect to a user's mobile device. The mobile device's web browser accesses a web page that establishes a BLE connection between the vending machine and mobile device and also facilitates a payment transaction with an online payment service provider without transmitting any payment information to the vending machine.

Abstract: This disclosure provides a multi-layered printed circuit board (PC) that has signal array region. The signal array region has a width and circumscribes a power core region and has signal vias connected to respective signal ball pads, and ground vias connected to respective ground ball pads within the signal array region that have an associated ball pad pitch. The PCB also has an inner current power layer. The signal and ground vias are arranged on the component layer in a pattern and extend into the inner current layer. The pattern forms current power paths across the width of the signal array region, such that the current power paths have a width that is at least about 50% as wide as the ball pad pitch.

Abstract: Embodiments herein provide systems and methods tracking the weight of an individual situated on a furnishing such as a chair or bed. One method generally includes receiving weight data at a weight sensor that is situated to recognize a change in weight on the furnishing, determining that a mobile device of the individual is proximately located to the weight sensor, and confirming by the mobile device that the change in weight is related to the individual.

Abstract: Embodiments herein provide systems and methods tracking the weight of an individual situated on a furnishing such as a chair or bed. One method generally includes receiving weight data at a weight sensor that is situated to recognize a change in weight on the furnishing, confirming that a fitness device is proximately located to the weight sensor, and transmitting the received weight data to a hosted service.

Abstract: A battery material includes: a conductive substrate; and a silicon material layer disposed on at least one side of the conductive substrate and including silicon fibers, at least some of which aggregate to form silicon fibrous spheres. A preparation method for the battery material includes: (a) providing a conductive substrate; (b) providing a silicon-based material, followed by depositing on a surface of the silicon-based material a film comprising amorphous silicon or crystalline silicon to form a silicon source material; (c) placing the silicon source material of step (b) on at least a side of the conductive substrate of step (a), wherein the distance between the conductive substrate and the silicon source material is less than 100 mm; and (d) heating the conductive substrate and silicon source material thus arranged in step (c) to allow the silicon source material to release amorphous silicon or crystalline silicon.