Abstract: A seismic sensor includes a measurement unit configured to measure acceleration; an earthquake determination unit configured to determine whether or not an earthquake has occurred based on the acceleration measured in a predetermined determination period; an index calculator configured to calculate an index value indicating a scale of an earthquake in an earthquake processing period after the predetermined determination period, when the earthquake determination unit determines that an earthquake has occurred; a continuous earthquake determination unit configured to determine whether or not an earthquake has occurred, based on the acceleration measured in the earthquake processing period; and a shut-off determination unit configured to inhibit output of the shut-off signal regardless of the index value when the continuous earthquake determination unit determines that no earthquake has occurred.

Abstract: A magnetic sensor device includes first and second surfaces, and first and second inclined surfaces, which are inclined with respect to the first surface; first through third magnetic sensor units for detecting magnetism in first through third axial directions; and a signal processing unit that performs signal processing on the basis of first through third sensor signals output from the first through third magnetic sensor units. The first axial direction is a direction orthogonal to the first surface, and the second and third axial directions are directions orthogonal to each other on the first surface. The first and second magnetic sensor units are provided on the second inclined surface, respectively. A corrected signal generation unit included in the signal processing unit generates first and second corrected signals, which are the first and second sensor signals corrected in accordance with the inclination angles of the first and second inclined surfaces.

Abstract: Embodiments of the present disclosure provide a method and system for recognizing a mine microseismic event, and belong to the field of mine data processing.

Abstract: An overlay metrology system may receive overlay data for in-die overlay targets within various fields on a skew training sample from one or more overlay metrology tools, wherein the in-die overlay targets within the fields have a range programmed overlay offsets, wherein the fields are fabricated with a range of programmed skew offsets. The system may further generate asymmetric target signals for the in-die overlay targets using an asymmetric function providing a value of zero when physical overlay is zero and a sign indicative of a direction of physical overlay. The system may further generate corrected overlay offsets for the in-die overlay targets on the asymmetric target signals, generate self-calibrated overlay offsets for the in-die overlay targets based on the programmed overlay offsets and the corrected overlay offsets, generate a trained overlay recipe, and generate overlay measurements for in-die overlay targets on additional samples using the trained overlay recipe.

Abstract: Systems and methods for determining shear failure of a rock formation are disclosed. The method includes receiving, by a processor, a plurality of parameters related to physical properties of the rock formation, applying the plurality of parameters to a predetermined failure criterion, and determining shear failure of the rock formation based on the failure criterion. In some embodiments the failure criterion is a modified Hoek-Brown failure criterion that takes into consideration an intermediate principal stress, and the difference between normal stresses and an average confining stress.

Abstract: A method of underwater tsunami detection includes detecting a trigger event using disruption of at least one of a plurality of hard disk drives (HDDs), each different one of the plurality of HDDs in a different one of a plurality of autonomous underwater vehicles (AUVs). A time and location of each of the at least one HDD for the trigger event is logged. Based on at least one of the HDD disruptions, times, and locations of the at least one HDD of the plurality of HDDs, a size, strength, and direction of a tsunami caused by the trigger event is determined. Information regarding the tsunami is transmitted to a monitoring station.

Abstract: Systems, methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests to generate an output are provided. In some examples, user information may be received by a system and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. A user interface may be generated including instructions for executing the identified tests. Upon initiating a test, data may be collected from one or more sensors in the computing device. The data collected may be transmitted to the system and may be processed using one or more machine learning datasets to generate an output.

Abstract: The present disclosure provides a laser speed measuring method, control device and a laser velocimeter, and relates to the technical field of security inspection. The laser speed measuring method comprises the steps of: acquiring detection data within a predetermined detection angle range in a plurality of paralleled horizontal planes having different heights, from a plurality of laser rays detected towards a road extending direction in the horizontal plane; acquiring three-dimensional point cloud data according to the detection data; determining a position of a measured object in the road extending direction according to the three-dimensional point cloud data; and determining a speed of the measured object according to the position change of the measured object along the road extending direction at different timing.

Abstract: A press machine includes: a learning-model generating unit that uses one data from among data collected from sensors, as an objective variable, and uses data other than the one data as an explanatory variable to perform machine learning to generate a learning model for the one data, the generation being performed for all the data; a predicted-value calculating unit that inputs an actually measured value of data other than one data from among the data collected from the sensors, into the learning model for the one data to calculate a predicted value of the one data, the calculation being performed for all the data; a degree-of-abnormality calculating unit that calculates a degree of abnormality based on a difference between an actually measured value and a predicted value of the data; and a degree-of-abnormality outputting unit that outputs the calculated degree of abnormality.

Abstract: A wireless adapter (10) is removably connected to an electronic device (30) to provide wireless connectivity for the electronic device (30). One or more operating parameters of the wireless adapter (10) are measured whilst the wireless adapter (10) is in use. A measure of the temperature of the wireless adapter (10) is obtained based on the measured one or more operating parameters.

Abstract: To generate dispersion curves for acoustic waves in a radially layered system, a matrix M containing solutions to the wave equation subject to the boundary conditions of the system is constructed. The reciprocal condition number (RCN) of the matrix M is determined as a function of acoustic wave frequency and slowness. The local minima of the RCN in the frequency-slowness plane produces the dispersion curves corresponding to allowable acoustic modes in the system. A sensitivity analysis which identifies the dispersion curves dependent on a selected parameter. The dispersion curves independent of the perturbed parameters are eliminated by perturbing the modeling parameters and generating the RCN of the perturbed matrix M and then subtracting the RCN values of the unperturbed matrix M, leaving the dispersion curves that exhibit dependence on the selected parameter.

Abstract: Methods and systems for identifying near-surface heterogeneities in a subterranean formation using surface seismic arrays can include: recording raw seismic data using sensors at ground surface; applying a band bass filter to the raw seismic data using a central frequency; picking a phase arrival time for the filtered data; generating an initial starting phase velocity model for tomographic inversion from the raw seismic data; applying tomographic inversion to the filtered data to generate a dispersion map associated at the central frequency; repeating the applying a band bass filter, picking a phase arrival time, generating an initial starting velocity model, and applying tomographic inversion steps for each of a set of central frequencies; and generating a three-dimensional dispersion volume representing near-surface conditions in the subterranean formation by combining the dispersion maps.

Abstract: The present application relates to tunnel monitoring and measuring, more particularly, to a quick fixing device for measuring a tunnel peripheral convergence and an application method thereof. A right-angle steel sheet includes a first steel sheet and a second steel sheet which are vertically fixed with each other. The fastener vertically penetrates the first steel sheet, and an explosive powder loading portion on a rear end of the fastener is arranged at a side of the second steel sheet. The reinforcing steel sheet is respectively connected to the first steel sheet and the second steel sheet as a reinforcing bar. A through hole is provided on the reinforcing spacer, through which the reinforcing spacer is sleeved on the fastener. The reinforcing spacer is arranged between the explosive powder loading portion on the rear end of the fastener and the first steel sheet.

Abstract: A system and method of executing a convolution layer of a neural network may include: (a) selecting an output spatial position (OSP) of an output matrix data element of the convolution layer; (b) selecting, based on the selected OSP, a non-zero input element of an input matrix data element; (c) producing, based on the selected OSP, a vector of kernel elements from a kernel matrix data element; (d) performing a vectoral multiplication operation of the selected non-zero input element and the vector of kernel elements, and accumulating a product of the vectoral multiplication in a vector register of a processor; (e) repeating (c) and (d) with subsequent non-zero input elements and corresponding vectors of kernel elements to obtain an outcome of the convolution of the selected OSP; and (f) repeating (a) through (e) with subsequent selection of OSPs, to obtain an outcome of the convolution layer.

Abstract: Methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests and collecting and analyzing social data to generate an output are provided. In some examples, user information may be received and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. Upon initiating a test, data may be collected from the one or more sensors. The collected sensor data may be transmitted to the system and processed using one or more machine learning datasets. Additionally, social data may be collected and analyzed using one or more machine learning datasets to generate a social profile. The sensor data and social profile may be used together to generate an output.

Abstract: A method for operating a micromechanical inertial sensor, including: translating an acceleration into a deflection of two detection electrodes that are displaced in opposite directions; ascertaining a difference in the spacing of the two detection electrodes; converting the difference in the spacing into an acceleration value using a scaling factor; and applying a linearization process to the acceleration value.

Abstract: A plurality of multifunctional underwater 3D displacement meters are arranged in a lattice and connected sequentially; four rotation shafts may be rotatably mounted in a housing and extend in a vertical direction, one end of the rotation shaft and the housing are connected to a compressible spring, four perforations penetrate the housing in a circumferential direction at intervals, the metallic lines correspond to the perforations one to one, one end of the metallic line is wound around the rotation shaft, and the other end thereof penetrates out of the perforation and is connected to the metallic line of the adjacent 3D displacement meter; and the displacement meter corresponds to the metallic line for measuring a take-up and pay-off length of the metallic line, and a three-axis acceleration sensor and a fluxgate monitor inclination angle change and azimuth angle change of the 3D displacement meter.

Abstract: The present disclosure provides a diffracted wave imaging method, device and electronic apparatus. The method comprises: acquiring pre-stack seismic wave field data of a to-be-processed area; extracting target data of a target imaging point; fitting target time sample points in the target data based on the Gaussian model and solving the fitting function to determine a distribution range of the stationary point position signal of the reflected wave in the target data; determining migration imaging data of the target imaging point based on the target data and the distribution range; and determining a diffracted wave imaging result of the to-be-processed area based on the migration imaging data of all the imaging points in the to-be-processed area.

Abstract: Systems and methods for picking seismic stacking velocity based on structures in a subterranean formation include: receiving seismic data representing a subterranean formation; generating semblance spectrums from the seismic data representing the subterranean formation; smoothing the semblance spectrums; and picking stacking velocities based on the smoothed semblance spectrums.

Abstract: Data to be processed includes vector element values of an input vector and matrix element values of a model matrix associated with a neural network model. A vector-matrix multiplication module receives a set of matrix element values for performing a vector-matrix multiplication operation. Processing the data includes computing a plurality of intermediate vectors based on element-wise vector multiplication between different subsets of the vector element values and different respective pre-processing vectors. The vector-matrix multiplication module is loaded with a core matrix, and the input vector is multiplied by the model matrix based on separately multiplying each of the intermediate vectors by the loaded core matrix.