Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: Methods and systems related to intelligent space management are described. An example method of monitoring an environment includes receiving a first image of an environment captured by a camera, receiving a point cloud of the environment generated by a lidar device, registering at least a portion of the point cloud with at least a portion of the first image, receiving, from a user device, a user selection of a zone in the environment based on a user interaction with a second image presented on the user device, the second image including at least one of a portion of the first image or a portion of the point cloud, and monitoring point cloud data collected by the lidar device for the selected zone.

Abstract: An information processing apparatus includes: a factual attribute determining unit that determines a factual attribute that can be confirmed to be a fact with respect to a user based on user-provided data having been provided by the user oneself or history data of the user; an inferred attribute determining unit which determines an inferred attribute having been inferred with respect to the user based on user-related data including at least the factual attribute related to the user; and a credit score inferring unit that infers a credit score to be set to the user based on an attribute data group including the factual attribute and the inferred attribute related to the user.

Abstract: A storage device includes: a storage controller to receive one or more notifications corresponding to host data transferred from a host device to the storage device over a storage interface; and a response circuit connected to the storage controller, the response circuit to trigger a response to the host device, and including: a first counter to track the one or more notifications, the one or more notifications corresponding to an entirety of the host data such that each of the notifications corresponds to a portion of the host data; a second counter to track one or more acknowledgements received from the storage controller, the one or more acknowledgments corresponding to the one or more notifications such that each of the acknowledgments corresponds to a notification; and a response trigger to select one of the first counter and the second counter to trigger the response to the host device.

Abstract: Disclosed is an autonomous vacuum system that detects and responds to obstructions in a cleaning channel of the vacuum. Pressure sensors repeatedly measure pressure at different points in the cleaning channel, and the autonomous vacuum system analyzes the pressure measurements to determine whether an obstruction is likely present. Such a determination may be made based on, e.g., computed pressure differentials across the pressure sensors, and/or pressures of individual pressures sensors. The autonomous vacuum system can respond to the detection of an obstruction by, for example, performing a change in vacuum speed, such as ramping up to or near a maximum speed, and then decreasing again to a more normal speed.

Abstract: A cleaning system may have a brush roller that moves dust and debris towards a duct opening for collection. The cleaning system may be an autonomous vacuum robot or include an autonomous vacuum robot. The cleaning system may include guards that reduce the likelihood that fibrous debris wraps around rotating portions of the brush roller (e.g., around a drive pinion). Buffer zones in the brush roller may receive fibrous debris that would otherwise wrap around the brush roller and increase undesirable friction during operation. The brush roller is configured to be unlocked from a position contacting the inner surface of a cleaning head of the cleaning system. The fibrous debris stored in the buffer zones may be suctioned into a debris collection compartment of the cleaning system after the brush roller is unlocked. The cleaning system includes a wedge to seal a cavity for ingesting debris within the cleaning head from the environment.

Abstract: An autonomous vacuum includes mopping and sweeping functionalities. A magnetic locking system secures a cleaning head of the autonomous vacuum into a mopping position when in a mopping state, allowing the vacuum to move a mop roller back and forth to scrub stubborn stains on a floor surface without the cleaning head shifting into an alternate sweeping position. The autonomous vacuum also includes snorkel ducts to direct fluid waste and water from the mop roller to a waste bag without mixing the fluid waste with dry waste collected by a sweeping system. The snorkel ducts are configured to kink shut when the cleaning head is in a sweeping state, to avoid unnecessary suction through the snorkel system. Additionally, the mopping system includes cleaning logic routines that can sense and control mop roller saturation and drying, and that can perform automatic mop cleaning.

Abstract: A storage device includes: a storage controller to receive one or more notifications corresponding to host data transferred from a host device to the storage device over a storage interface; and a response circuit connected to the storage controller, the response circuit to trigger a response to the host device, and including: a first counter to track the one or more notifications, the one or more notifications corresponding to an entirety of the host data such that each of the notifications corresponds to a portion of the host data; a second counter to track one or more acknowledgements received from the storage controller, the one or more acknowledgments corresponding to the one or more notifications such that each of the acknowledgments corresponds to a notification; and a response trigger to select one of the first counter and the second counter to trigger the response to the host device.

Abstract: The present disclosure include an exemplary method comprising receiving a transaction history comprising transaction information associated with a plurality of transactions for an entity, wherein the transaction information involves transactions completed between employees of the entity and one or more merchants; detecting, using a machine learning algorithm, one or more leakage events associated with a transaction, the one or more leakage events comprising a first leakage event, wherein the first leakage event indicates a non-compliance of a spending rule of the entity by a participant in the transaction, wherein the one or more detected leakage events are analyzed as inputs to improve performance of the machine learning algorithm using unsupervised machine learning; and performing an analysis of a compliance level of the entity based on performing the detection of the one or more leakage events for the plurality of transactions.

Abstract: A process is disclosed to identify the minimal set of sequential and combinational signals needed to fully reconstruct the combinational layout after emulation is complete. A minimal subset of sequential and combinational elements is output from the emulator to maximize the emulator speed and limit the utilization of emulator resources, e.g., FPGA resources. An efficient reconstruction of combinational waveforms or SAIF data is performed using a parallel computing grid.

Abstract: Systems and methods are disclosed for generating interactive user interfaces for evaluating transactions of an organization. For example, a system can be configured to receive transactions for an organization and determine a first subset of the transactions during a trip at a first location that is different from a home location of a consumer. A respective transaction associated with a second location that occurred during the trip is identified. The respective transaction is assigned to the first subset of the of transactions for the trip. A second subset of the transactions of a spending type is determined. A parameter value associated with the spending type is identified. A parameter adjustment is determined. The system is configured to cause a display of a spending type user interface on a client device and receive a selection of a parameter component.

Abstract: An adjustable-focus PV (picture/video) camera in a mixed-reality head-mounted display (HMD) device operates with an auto-focus subsystem that is configured to be triggered based on location and motion of a user's hands to reduce the occurrence of auto-focus hunting during camera operations. The HMD device is equipped with a depth sensor that is configured to capture depth data from the surrounding physical environment to detect and track the user's hand location, movements, and gestures in three-dimensions. The hand tracking data from the depth sensor may be assessed to determine hand characteristics—such as which of the user's hands or part of a hand is detected, its size, motion, speed, etc.—within a particular region of interest (ROI) in the field of view of the PV camera. The auto-focus subsystem uses the assessed hand characteristics as an input to control auto-focus of the PV camera to reduce auto-focus hunting occurrences.

Abstract: The system may be configured to perform operations including receiving a transaction history comprising transaction information associated with a plurality of transactions for an entity; analyzing transaction information associated with a transaction of the plurality of transactions; and detecting a leakage event associated with the transaction. Detecting the leakage event may comprise determining a payment method for the transaction in response to the analyzing the transaction information; and comparing the payment method to a desired payment method, wherein the leakage event is detected in response to the payment method differing from the desired payment method.

Abstract: Techniques are described for optimizing streaming video encoding profiles.

Abstract: A process is disclosed to identify the minimal set of sequential and combinational signals needed to fully reconstruct the combinational layout after emulation is complete. A minimal subset of sequential and combinational elements is output from the emulator to maximize the emulator speed and limit the utilization of emulator resources, e.g., FPGA resources. An efficient reconstruction of combinational waveforms or SAIF data is performed using a parallel computing grid.

Abstract: A traceability system for a bulk commodity supply chain is provided. The system includes a tracking device, a location determination subsystem, and at least one computing device having at least one processor. The location determination subsystem is configured to determine positional information of the tracking device while placed in a bulk commodity traveling along the bulk commodity supply chain. The processor receives the positional information from the location subsystem, extracts positional values from the positional information, and processes the positional values to identify motion primitives. A modeling tool is applied to the identified motion primitives to produce a positional path of the tracking device, which is output, for example, via a user interface. The positional path represents travel of the bulk commodity along the supply chain.

Abstract: Techniques are described for optimizing and assigning video encoding ladders.

Abstract: The system may be configured to perform operations including receiving a transaction history for a consumer having transaction information associated with a plurality of transactions; detecting within the transaction information for each transaction a characteristic, resulting in a plurality of characteristics; calculating a respective value associated with each characteristic, wherein the respective value is at least one of a number or percentage of transactions having the characteristic; assigning a respective weight to each characteristic, producing an assigned respective weight for each characteristic; applying the assigned respective weight to the respective value associated with each characteristic to produce a respective weighted value for each characteristic; combining the respective weighted values of the plurality of characteristics; and/or producing a compliance score in response to the combining the respective weight values.

Abstract: Systems and methods for detecting extrinsic parameter miscalibration for light detection and ranging (“LiDAR”) devices are disclosed. According to one embodiment, a LiDAR detection method includes scanning, by a LiDAR system comprising one or more LiDAR devices, a field-of-view during one or more time periods, wherein the LiDAR system moves along a non-linear path during at least a subset of the one or more time periods. Return signal data obtained during at least the subset is aggregated and fiducial markers represented by the aggregated return signal data are identified. Each of the identified fiducial markers are compared to a respective reference fiducial marker of a plurality of reference fiducial markers. Based on the comparison, miscalibration of an extrinsic parameter associated with a position and/or an orientation of at least one of the LiDAR devices is detected. An action is initiated to remediate the detected miscalibration of the extrinsic parameter.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for facilitating efficient retrieval of diagnostic information from a computing endpoint that experiences a failure condition. For example, systems described herein may detect or otherwise identify a failure condition associating with the computing endpoint operating in an erroneous or unpredictable matter. Systems described herein may involve carving out a portion of memory on the computing endpoint that is accessible to a host system (e.g., a CPU). Systems described herein may further provide a discoverable resource that enables a host system to identify and collect the diagnostic data in response to identifying a failure condition in an efficient manner and without requiring that the computing endpoint be capable of responding to data requests.