Abstract: A system includes an input to receive a digital waveform signal, a memory, and one or more processors configured to execute code to cause the one or more processors to: generate a horizontal ramp sweep signal based on the digital waveform signal; receive a selection input to identify a segment of the digital waveform signal; gate the horizontal ramp sweep signal and the digital waveform signal based on the selection input to produce cyclic loop image data for the segment of the digital waveform; store the cyclic loop image data in the memory; and provide the cyclic loop image data as one or more inputs into a machine learning system.

Abstract: A method, sensor, and non-transitory computer-readable storage medium are provided for estimating actual amplitudes of a waveform. A machine learning model may be trained for an embedded system of a first three-axes sensor having a limited range to estimate the actual amplitudes of a waveform that saturates the first three-axes sensor in a direction of one of the three axes. The embedded system acquires a second waveform during use of a tool including the first three-axes sensor. The second waveform that occurs after a second waveform producing event is isolated. The embedded system extracts a multi-dimensional feature from the isolated second waveform and estimates, using the machine learning model, the actual amplitudes of the second waveform based on the extracted multi-dimensional feature.

Abstract: Examples provide a method and system for quantitatively measuring air turbulence. A turbulence measuring application on each user device in a plurality of user devices associated with a plurality of users at a plurality of different locations within an aircraft generates vibration data and positional data associated with turbulence detected at each user's location. The data is analyzed to eliminate noise due to user movements and other non-turbulence related events. An aircraft server aggregates the vibration data and the positional data generated by the user devices scattered throughout the aircraft. The aggregated data is analyzed to eliminate noise due to non-turbulence related events to create quantitative air turbulence data. The quantitative air turbulence data generated by one or more aircraft is used with weather and other related data to generate more accurate and precise turbulence predictions for aircraft.

Abstract: Performance information associated with a previous repetition of an exercise movement is received. Performance of one or more upcoming repetitions is predicted, based at least in part on the performance information associated with the previous repetition of the exercise movement. A failure classification of whether the one or more upcoming repetitions is associated with an occurrence of physical failure is performed, based at least in part on the predicted performance of the one or more upcoming repetitions of the exercise movement. A number of repetitions in reserve is determined, based at least in part on the failure classification.

Abstract: A passive integrated transponder (PIT)-based fish school trajectory monitoring method and system for a marine ranch are provided. The method includes: using a PIT reader to obtain PIT tag information of each fish of a target fish school during a monitoring period; generating a three-dimensional (3D) fish school trajectory map of the target fish school; generating a motion sequence of each fish, inputting the motion sequence of each fish into a motion trajectory correction model, and outputting a corrected motion sequence of each fish; generating a first corrected 3D fish school trajectory map of the target fish school during the monitoring period, and generating a second corrected 3D fish school trajectory map; and generating motion information of the target fish school, and feeding back the second corrected 3D fish school trajectory map and the motion information of the target fish school to monitoring personnel.

Abstract: This disclosure describes, in part, techniques for using multiple passive infrared sensors to determine a distance to an object. For instance, an electronic device may include a first passive infrared sensor including a first FOV that extends a first distance from the electronic device and a second passive infrared sensor including a second FOV that extends a second distance from the electronic device further than the first distance. The electronic device may generate first sensor data using the first passive infrared sensor and second sensor data using the second passive infrared sensor. The electronic device may then determine a first amplitude associated with the first sensor data and a second amplitude associated with the second sensor data and determine a ratio between the amplitudes. After the ratio is determined, the electronic device may determine a distance associated with the ratio, generate image data based on the distance, and send the image data to computing device(s).

Abstract: A method for removing tube wave interference from optical fiber acoustic wave sensing seismic data, including: acquiring seismic wavefield data which contains a tube wave and is collected by an optical fiber acoustic wave sensing instrument; calculating a root-mean-square amplitude of the waveform data cut on the seismic trace as an amplitude normalization factor; performing normalization processing on the amplitude value; performing de-tail mean filtering processing on the normalized amplitude value along the travel time of the tube wave, to obtain a predicted amplitude value; performing tube wave interference removal processing on each seismic trace, and performing inverse normalization processing to obtain the seismic wavefield data without tube wave interference. The method effectively suppresses the tube wave interference in the optical fiber acoustic wave sensing seismic data.

Abstract: A method for reducing thermal induced error in real-time for a sensor in a region of interest. The method includes receiving at least one data point from a temperature sensor, the temperature sensor configured to determine temperature for the sensor of interest. The method includes receiving at least one data point from the sensor, the sensor having thermal sensitivity and offset shift for a given temperature range. The method includes determining at least three percentage change coefficients for thermal sensitivity. The method includes determining at least three percentage change coefficients for thermal zero offset. The method includes calculating real-time thermal error reduction.

Abstract: A method, apparatus, system, and computer program product for managing a platform. A computer system generates a training dataset comprising historical metric values from historical sensor information for a set of metrics for a part and historical maintenance events for the part. The computer system trains a machine learning model using the training dataset. The computer system determines different maintenance thresholds for maintenance parameters for a metric in the set of metrics for performing maintenance on the part using the machine learning model trained with the training dataset. The computer system selects maintenance thresholds for the maintenance parameters from the maintenance thresholds meeting an objective to form a maintenance plan. The maintenance plan is used to determine when a maintenance action is needed for the part.

Abstract: Methods and devices for determining a measurement time period, receiving a plurality of signals associated with a monitored analyte level during the determined measurement time period from an analyte sensor, modulating the received plurality of signals to generate a data stream over the measurement time period, and accumulating the generated data stream to determine an analyte signal corresponding to the monitored analyte level associated with the measurement time period are provided. Systems and kits are also described.

Abstract: A subspace-based approach to synchrophasor estimation is provided. Embodiments described herein provide two improvements to subspace-based phasor measurement unit (PMU) algorithms based on estimation of signal parameters via rotational invariance techniques (ESPRIT) frequency estimation. The first is a dynamic, real-time thresholding method to determine the size of the signal subspace. This allows for accurate ESPRIT-based frequency estimates of the nominal system frequency as well as the frequencies of any out-of-band interference or harmonic frequencies. Since other frequencies are included in the least squares (LS) estimate, the interference from frequencies other than nominal can be excluded. This results in a near flat estimation error over changes in a) nominal system frequency, b) harmonic distortion, and c) out-of-band interference. Second, the computational burden of ESPRIT is reduced and the proposed algorithm runs in real time on resource-constrained platforms.

Abstract: A method of enhancing a gross depositional environment (GDE) map of a subsurface formation. The method includes obtaining the GDE map of the subsurface formation, including a lithology map of a plurality of lithotypes and obtaining a paleo-bathymetric map of the subsurface formation. The method further includes assigning an inverse mobility for each of the lithotypes and determining, using a computer processor, an enhanced GDE map based, at least in part, on the GDE map, the paleo-bathymetric map, and the inverse mobility for each of the lithotypes.

Abstract: An information processing apparatus includes a processor configured to: obtain failure information to identify details of a failure which has occurred in a target device on which failure analysis is to be performed; and superimpose and display information related to a part or a wire on a captured image of a printed circuit board included in the target device, the part or the wire being a possible cause for the failure identified by the failure information from multiple parts and wires disposed on the printed circuit board.

Abstract: A method and/or system configured to select state estimator operation settings based on one or more system inputs; and determine a battery state of a battery, based on sensor measurements associated with the battery, using a state estimator operating under the state estimator operation settings.

Abstract: A computer-implemented method for occupancy state detection in an area for a pre-determined point in time. In aspects, the computer-implemented method includes operations carried out by computer hardware components. The operations include determining a probability distribution over a list of possible occupancy states of the area at a previous point in time, determining measurement data related to the area at the pre-determined point in time, and determining a probability distribution over the list of possible occupancy states of the area at the pre-determined point in time based on the measurement data and the probability distribution over the list of possible occupancy states of the area at the previous point in time.

Abstract: A method for determining the quality of a hose in an automated analyser system, comprising the steps of collecting data of a wash curve by measuring the light intensity through a hose with an optical sensor during washing of a hose; determining and recording the voltage changes related to changing light intensities; extracting an aspiration time and time for completing of a an aspiration process from said data; determining changes in the data of the most recent wash curves. The disclosure further relates to a device for preforming said method.

Abstract: The present invention pertains to the fields of geology and geophysics, is designed for use for onshore seismic acquisition. The method involves distributing and arranging the elements used in the acquisition of two-dimensional seismic data from dynamite sources, enabling imaging quality to be improved. The use of sources of dynamite with single charges and variable weight at each shot point results in the generation of seismic waves with variable energy that provide reflections with complementary frequency and amplitudes content for use in the geophysical imaging of geological features. The stacking of this incremental content generated by charges of variable weights results in a significant improvement in the resolution of the processed seismic data on both the continuity of stratigraphic reflectors and existing geological framework.

Abstract: According to one embodiment, the failure analysis system of the semiconductor device includes a memory, a failure information management table, and an analyzing unit. The memory stores normal/failure information collected in a block unit and a column unit in a chip, in a plurality of inspection processes of the semiconductor memory. The failure information management table stores the normal/failure information in the block unit and the column unit stored in the memory, with an addition of product information, fabricating information including a lot number, a wafer number, and a chip address, process information, and test information, which are common information ranging over the inspection processes. The analyzing unit analyzes the normal/failure information in the block unit and the column unit ranging over the plurality of inspection processes, on the basis of the information stored in the failure information management table.

Abstract: Embodiments disclosed herein relate to electronic devices, and more particularly to estimating a damage risk level for an electronic device. A method disclosed herein includes measuring motion parameters of the electronic device, on the electronic device being dropped on a surface. The method further includes classifying the surface into at least one type by processing the measured motion parameters using a classifier module. The method further includes estimating a damage risk score depicting the damage risk level for the electronic device based on the classified surface, the measured motion parameters of the electronic device, and a usage history of the electronic device.

Abstract: Provided are a device, method, and computer-readable recording medium for detecting an earthquake in a microelectromechanical system (MEMS)-based auxiliary seismic observation network.