Abstract: Systems and methods for training object detection models using adversarial examples are provided. A method includes obtaining a training scene and identifying a target object within the training scene. The method includes obtaining an adversarial object and generating a modified training scene based on the adversarial object, the target object, and the training scene. The modified training scene includes the training scene modified to include the adversarial object placed on the target object. The modified training scene is input to a machine-learned model configured to detect the training object. A detection score is determined based on whether the training object is detected, and the machine-learned model and the parameters of the adversarial object are trained based on the detection output. The machine-learned model is trained to maximize the detection output. The parameters of the adversarial object are trained to minimize the detection output.

Abstract: Described herein are systems, methods, and non-transitory computer readable media for triggering a sensor operation of a second sensor (e.g., a camera) based on a predicted time of alignment with a first sensor (e.g., a LiDAR), where operation of the second sensor is simulated to determine the predicted time of alignment. In this manner, the sensor data captured by the two sensors is ensured to be substantially synchronized with respect to the physical environment being sensed. This sensor data synchronization based on predicted alignment of the sensors solves the technical problem of lack of sensor coordination and sensor data synchronization that would otherwise result from the latency associated with communication between sensors and a centralized controller and/or between sensors themselves.

Abstract: A system may include a hose assembly and a controller. The hose assembly may comprise a plurality of sensor devices configured to generate sensor data regarding the hose assembly. The sensor data may include at least one of first sensor data regarding a bend radius of a first portion of the hose assembly, or second sensor data regarding an amount of torque at a second portion of the hose assembly. The controller may be configured to receive the sensor data from the plurality of sensor devices; determine a remaining life of the hose assembly based on the sensor data; and perform an action based on the remaining life of the hose assembly.

Abstract: Embodiments of the present disclosure are directed to methods and systems for assessing integrity of chromatography columns, systems, and processes. The methods and systems can comprise one or more of extracting a block and signal combination for analysis, performing a transition analysis, performing one or more statistical process controls, and/or implementing in-process controls based on the statistical process controls.

Abstract: Example imaging systems are disclosed. One example includes a signal source and a signal receiver configured to receive a reflected electromagnetic signal from an imaged object. The imaging system further includes a processor configured to, for each of N wavelengths, determine a phase value of a reflected component of the reflected electromagnetic signal having that wavelength. The processor may compute an estimated distance to the imaged object at least in part by mapping the plurality of phase values to a 2N-dimensional vector, and computing a plurality of zeroes of a trigonometric polynomial. For each of the plurality of zeroes, computing the estimated distance may further include computing a respective geodesic distance between the 2N-dimensional vector and a point along the curve evaluated at that zero, and selecting and outputting a shortest geodesic distance multiplied by a least common multiple of the wavelengths.

Abstract: An improved system and method of determining presence of stop signs at intersection based on multiple types of data including ground truth data, telemetry data, and/or trip stills gathered from vehicle devices. The data may be analyzed and aggregated by one or more models and/or neural networks to develop a prediction regarding presence of stop signs at individual intersections.

Abstract: A deviation inclination calculation unit (22) calculates a deviation score by using evaluation data obtained from a subject apparatus as an input, in each of a plurality of outlier detection methods specifying data deviated from other data from among subject data, and calculating deviation scores indicating deviation degrees of the data specified, and calculates deviation inclination information from the deviation scores calculated. An abnormality detection unit (23) calculates, for each abnormality pattern, a similarity degree between deviation sensitivity information indicating sensitivity for each of a plurality of abnormality patterns with respect to each of the plurality of outlier detection methods, and the deviation inclination information calculated, and detects an abnormality of the subject apparatus.

Abstract: A detection apparatus detects a tilt of a LiDAR apparatus that is mounted to a vehicle. The detection apparatus includes a distance image acquiring unit, a surroundings information acquiring unit, and a detecting unit. The distance image acquiring unit acquires a distance image that is expressed by a detection point group that is detected by the LiDAR apparatus. The surroundings information acquiring unit acquires surroundings information on a periphery of a traveling route of the vehicle. The detecting unit that determines the tilt of the LiDAR apparatus based on the acquired distance image and the acquired surroundings information.

Abstract: A controller for controlling a system having uncertainties in its dynamics subject to constraints on an operation of the system is provided. The controller is configured to acquire historical data of the operation of the system, and determine, for the system in a current state, a current control action transitioning a state of the system from the current state to a next state. The current control action is determined according to a robust and constraint Markov decision process (RCMDP) that uses the historical data to optimize a performance cost of the operation of the system subject to an optimization of a safety cost enforcing the constraints on the operation, wherein a state transition for each of state and action pairs in the performance cost and the safety cost is represented by a plurality of state transitions capturing the uncertainties of the dynamics of the system.

Abstract: A statistical method is used to separate periodic from non-periodic vibration peaks in machine vibration spectra. Generally, a machine vibration spectrum is not normally distributed because the amplitudes of periodic peaks are significantly large and random relative to the generally Gaussian noise. In a normally distributed signal, the statistical parameter Kurtosis has a value of 3. The method sequentially removes each largest amplitude peak from the peaks in a frequency region of interest in the spectrum until the Kurtosis has a value of three or less. The removed peaks, which are all considered to be periodic, are placed into a candidate peak list. As the process of building the candidate peak list proceeds, if the kurtosis of the remaining peaks in the frequency region of interest falls to three or less, the process stops and the candidate peak list is defined.

Abstract: Systems and methods for non-intrusive program tracing of a device are disclosed. The methods involve generating a program trace signal from at least one of power consumption and electromagnetic emission of the device; digitizing and decomposing the program trace signal into at least two digital program trace component signals including a low frequency program trace component and one or more high frequency program trace component signals; classifying fragments of the at least two digital program trace component signals of the program trace signal as at least one of a known portion of program code and an observed behavior of the device. Each of the at least two digital program trace component signals have different frequency bands and the bandwidth of each program trace component signal is smaller than the bandwidth of the program trace signal. Each of the high frequency program trace component signals include an envelope.

Abstract: A sensor information fusion device and a method thereof are provided. The sensor information fusion device includes a processor that generates a first track box and a second track box based on an object detected by a plurality of sensors and determines whether the first track box and the second track box are overlapped with each other and a storage storing data obtained by the processor and an algorithm run by the processor. The processor generates a merge gate expanded from the first track box and determines the first track box and the second track box are overlapped with each other when the second track box is included in the merge gate.

Abstract: Motion can be induced at a vehicle, e.g., by actuating components of an active suspension system, and first sensor data and second sensor data representing an environment of the vehicle can be captured at a first position and a second position, respectively, resulting from the induced motion. A second sensor can determine motion information associated with the first position and the second position. Calibration information about the sensor, the first sensor data, and the motion information can be used to determine an expectation of sensor data at the second position. A calibration error can be the difference between the second sensor data and the expected sensor data.

Abstract: A calibration device and method of calculating a global multi-degree of freedom (MDF) pose of a camera affixed to a structure is disclosed. The method may comprise: determining, via a computer of a calibration device, a calibration device MDF pose with respect to a global coordinate system corresponding to the structure; receiving, from an image system including the camera, a camera MDF pose with respect to the calibration device, wherein a computer of the image system determines the camera MDF pose based on an image captured by the camera including at least a calibration board affixed to the calibration device; calculating the global MDF pose based on the calibration device MDF pose and the MDF pose; and transmitting the global MDF pose to the image system such that a computer of the image system can use the global MDF pose for calibration purposes.

Abstract: A method, and a system for implementing the method, are disclosed wherein coordinates of survey region are used to locate small pieces of a seismic wave model, usually defined by their nodes (or vertices) and contain information about physical properties, such as liquid or solid, density, velocity that seismic waves propagates in it; and connects them to the appropriate source and receiver sensor. In particular, the method and system disclosed, generates a multi-layer mapping of the survey region by decomposing the survey region into cubes containing small pieces of seismic wave models (the elements), as well as source and receiver location. Those cubes are then indexed depending upon their location and the elements, sources and receivers are assigned to a particular cube thereby creating a multi-layer relationship between the survey region map, the cube map, the elements map, as well as the source and receiver locations.

Abstract: Systems, methods and apparatus for data collection in an industrial environment are disclosed. A system according to one embodiment can include a plurality of input sensors operatively coupled to a production line, the plurality of sensors communicatively coupled to a data collector having a controller, the controller including: a data collection band circuit structured to determine at least one collection parameter for at least one of the plurality of sensors from which to process output data, a machine learning data analysis circuit structured to receive output data from the at least one of the plurality of sensors and learn output data patterns indicative of a state of the production line, and a response circuit structured to adjust an operating parameter of a component of the production line based on one of a mismatch or a match of the output data pattern and the state of the production line.

Abstract: An evaluation system for processing measured data which include physical measured data detected with the aid of one or multiple sensors, and/or realistic synthetic measured data of the sensor(s), into one or multiple evaluation results. The system includes at least two input stages independent from each other, which are designed to receive measured data and process these measured data into precursors. At least one processing stage, receives the precursors from all input stages as inputs and is designed to process one or multiple input precursor(s) into a shared intermediate product. At least one output stage, which is designed to process the intermediate product into one or multiple evaluation result(s) of the evaluation system. A method for training the evaluation system. A method for operating the evaluation system is also provided.

Abstract: Methods and systems described herein are directed to determining properties of a subterranean formation using an acoustic wave-equation with a novel formulation in terms of a velocity model and a reflectivity model of the subterranean formation. The acoustic wave equation may be used with full-waveform inversion to build high-resolution velocity and reflectivity models of a subterranean formation. The acoustic wave equation may be also used with least-squares reverse time migration in the image and space domains, to build a reflectivity model of the subterranean formation with enhanced resolution and amplitude fidelity. The velocity and reflectivity models of materials that form the subterranean formation reveal the structure and lithology of features of the subterranean formation and may reveal the presence of oil and natural gas reservoirs.

Abstract: A processor performance measurement apparatus according to an embodiment includes a processor, in which the processor detects that a memory access occurs, the memory access being required to execute processing units or execute execution units by a processor to be measured, performs first estimation for estimating switching of the processing units or the execution units and second estimation for estimating which of the one or more processing units the processing unit being executed is or to which of the one or more processing units the execution unit being executed corresponds based on an address of an access destination of the memory access, measures respective performances in the processing units or the execution units based on an estimation result of the first estimation, and aggregates respective measurement results of the performances for each of the processing units based on an estimation result of the second estimation.

Abstract: Provided is a technique for monitoring energy consumption in an electric vehicle (EV) charging network. The technique is based on using messages from one or more EV charging stations, each of which comprises a timestamp, a station ID, a charging session ID, and an energy meter reading. Whenever a new message is received, it is first stored in a database, whereupon it is checked whether the database comprises an older message with the same station ID and charging session ID as the new message. If the older message is present in the database, a time difference and an energy difference between the new and older messages are calculated. Then, a time granularity level is selected based on the time difference. An energy consumption distribution between the timestamps of the new and older messages is obtained based on the time granularity level and the energy difference.