Abstract: A system and method is disclosed for determining a particular vehicle state based on a UWB signal received at a plurality of receiving nodes. A plurality of channel-impulse responses (CIRs) may be computed from the UWB signal received from the plurality of receiving nodes. A plurality of peak-based features based on a selected position and amplitude may be extracted from the plurality of CIRs. A plurality of correlation-based features may be generated by correlating the plurality of CIRs to a corpus of reference CIRs relating to a plurality of vehicle states. A plurality of maximum likelihood vehicle matrices may be generated by correlating the plurality of CIRs to the corpus of reference CIRs relating to the plurality of vehicle states. The vehicle state may then be determined by processing the plurality of peak-based features and correlation-based features using the machine learning classification algorithm.

Abstract: Correcting for antennae spatial distortions in Radio Frequency (RF) localization may be provided. A plurality of actual locations associated with a plurality of Access Point (APs) may be received. Then a plurality of signal strengths associated with the plurality of APs may be received. Based on the plurality of signal strengths, a model may be created that models a plurality of inference errors respectively corresponding to the plurality of APs between a plurality of inferred locations respectively corresponding to the plurality of APs and the plurality of actual locations. The model may then be used in determining a location of a device.

Abstract: A system and method is disclosed for determining a particular vehicle state based on a UWB signal received at a plurality of receiving nodes. A plurality of channel-impulse responses (CIRs) may be computed from the UWB signal received from the plurality of receiving nodes. A plurality of peak-based features based on a selected position and amplitude may be extracted from the plurality of CIRs. A plurality of correlation-based features may be generated by correlating the plurality of CIRs to a corpus of reference CIRs relating to a plurality of vehicle states. A plurality of maximum likelihood vehicle matrices may be generated by correlating the plurality of CIRs to the corpus of reference CIRs relating to the plurality of vehicle states. The vehicle state may then be determined by processing the plurality of peak-based features and correlation-based features using the machine learning classification algorithm.

Abstract: Disclosed are systems, apparatuses, methods, and computer-readable media for providing security postures for a service provided by a heterogenous system. A method for verifying trust by a service node includes receiving a request for a security information of the service node from a client device, wherein the request includes information identifying a service to receive from the service node, identifying a related node to communicate with the service node based on the service, after identifying the related node, requesting a security information of the related node, generating a composite security information from the security information of the service node and the security information of the related node, and sending the composite security information to the client device. The composite security information provides security claims for a service implemented by a heterogenous devices that have different trusted execution environments.

Abstract: A system and method is disclosed for determining a particular vehicle state based on a UWB signal received at a plurality of receiving nodes. A plurality of channel-impulse responses (CIRs) may be computed from the UWB signal received from the plurality of receiving nodes. A plurality of peak-based features based on a selected position and amplitude may be extracted from the plurality of CIRs. A plurality of correlation-based features may be generated by correlating the plurality of CIRs to a corpus of reference CIRs relating to a plurality of vehicle states. A plurality of maximum likelihood vehicle matrices may be generated by correlating the plurality of CIRs to the corpus of reference CIRs relating to the plurality of vehicle states. The vehicle state may then be determined by processing the plurality of peak-based features and correlation-based features using the machine learning classification algorithm.

Abstract: A set of factors affecting a sold volume of the product is collected at a store in a geographical portion of a geographical area. A subset of a set of area stores is identified having a corresponding sold volume of the product. An intrinsic capacity of the product is computed by adjusting the sold volume of an area store by a first volume where the first volume is due to a sale of a second product at the area store. A modified intrinsic capacity is computed by modifying an effect of a factor from the subset on the intrinsic capacity such that the effect is worse than an effect of the factor at the store. A virtual store is constructed using modified intrinsic capacities of a sub-subset of area stores. A target volume of the product is set at the store as the virtual intrinsic capacity at the virtual store.