Abstract: A real number sine/cosine wave basis function transform circuit includes a window segmentation element, a first transform element, a second transform element and a root-sum-square (RSS) element. The window segmentation element is provided to segment an in-phase output signal and a quadrature output signal to output an in-phase window signal and a quadrature window signal. The first and second transform elements are provided to transform the in-phase window signal and the quadrature window signal using a real number sine/cosine wave basis function to obtain a first transformed signal and a second transformed signal, respectively. The RSS element is provided to calculate an RSS value of the first and second transformed signals and output a real number sine/cosine wave basis function transformed signal.

Abstract: Provided is a multiplex PCR amplification method for identifying an unknown biological sample suspected to be from a human. The method comprises the following steps: 1) acquiring an unknown biological sample suspected to be from a human and which is to be detected; 2) directly adding said unknown sample or nucleic acid extracted from said unknown sample to a premixed PCR reagent; 3) running a PCR amplification program to conduct a multiplex PCR amplification reaction; and 4) detecting and analyzing PCR amplification products, wherein the premixed PCR reagent contains primers specific to human genetic markers and primers specific to nuclear chromosomal genes of non-human species. Also provided is a multiplex PCR amplification kit for species and human individual recognition and identification of an unknown biological sample.

Abstract: A non-contact body temperature measurement device includes a thermal imager, an anemometer and a processing unit. The thermal imager is provided to capture thermal images. The anemometer is provided to measure wind speed and output a wind speed signal. The processing unit is provided to process the thermal images according to the wind speed signal and remove the thermal image showing great variation in temperature between two consecutive frames. Consequently, an accurate body temperature can be measured through the processed thermal images.

Abstract: A diode and a power circuit are provided. The diode may include: a first electrode layer; a drift layer located above the first electrode layer, a doping concentration of the drift layer is less than that of the first electrode layer; and the drift layer includes an active region and a terminal region surrounding the active region; a second electrode layer disposed in the active region, where the second electrode layer and the drift layer are doped with impurities of different properties; and the second electrode layer includes a first region and a second region surrounding the first region, and the first region and the second region are separated by a first insulation trench, where the first region is connected to a power supply through a first conductor, and the second region is connected to the power supply through a second conductor, a first resistor, and the first conductor sequentially.

Abstract: Provided is a determination method of differential protection suitable for an electricity transmission line with multi-terminal T-connection.

Abstract: A FCFMSIL radar includes a SILO, a frequency conversion unit, an antenna unit, a demodulation unit and a processing unit. The frequency conversion unit converts an oscillation signal of the SILO into a FMCW signal. The antenna unit transmits the FMCW signal to an area as a transmitted signal and receives a reflected signal from the area as a received signal. The frequency conversion unit converts the received signal into an injection signal and injects it into the SILO. The demodulation unit demodulates the oscillation signal into an in-phase demodulated signal and a quadrature demodulated signal. The processing unit processes the in-phase and the quadrature demodulated signals to obtain a baseband signal and thus acquire a phase and a frequency of a tone in the frequency-domain baseband signal, and determines the tone corresponding to one or multiple objects based on the phase and frequency of the tone.

Abstract: A display module includes a display panel, a first optical adhesive layer disposed on a side of a display surface of the display panel, a touch panel disposed on a side of the first optical adhesive layer away from the display panel, and at least one isolation film between the display panel and the touch panel. The display panel includes a display region and a peripheral region that is provided with at least one alignment mark. The touch panel includes a plurality of peripheral signal lines. An orthographic projection of the peripheral signal lines on a plane where the display panel is located at least partially overlaps with an orthographic projection of the at least one alignment mark on the plane. An orthographic projection of each isolation film on the plane covers an alignment mark.

Abstract: Disclosed is a multi-dimensional analysis method for a tripping risk of a whole transmission line due to a lightning shielding failure. A quantity of thunderstorm days, a tower size, a terrain proportion, an altitude, and insulation configuration data are collected for a transmission line for which a tripping risk due to a lightning shielding failure needs to be analyzed, and a striking distance, an exposure distance, a lightning resisting level of the line after altitude factor correction, and a lightning shielding failure risk of a single-base tower are calculated in turn. Characteristics of a lightning shielding failure under different nominal heights, quantities of thunderstorm days, and terrains are studied. Representative combination conditions are selected to calculate a tripping risk of a typical tower due to the lightning shielding failure. A weight coefficient is extracted, to calculate a tripping risk of the whole line due to the lightning shielding failure.

Abstract: A system is configured to manage motor engagement in a vehicle by determining to engage a disengaged motor shaft with a drivetrain, and in response, activating a feedback controller based on a speed of the motor shaft and activating a feedforward controller. The system determines at least one metric for modifying an output of the feedforward controller. The at least one metric is based on the speed of the motor shaft and the desired speed, and may be applied as a gain to the output of the feedforward controller. The system generates a command based on the feedback controller, the feedforward controller, and the at least one metric, and causes the motor shaft and the drivetrain to be engaged based on the speed of the motor shaft and the desired speed. The system nulls output of the feedforward controller as the speed of the motor shaft approaches the desired speed.

Abstract: In a noncontact vital sign sensing device of the present invention, a gain detector is provided to detect a gain between an oscillation signal and a received signal. Gain detection can cancel out the amplitude noise of an oscillator such that frequency information of vital sign(s) of a subject can be extracted from the gain without null-point issue, and vital sign(s) of the subject located at any position within sensing range can be detected.

Abstract: The present disclosure provides methods, devices, systems, and storage mediums for live broadcast detection and data processing. In one exemplary embodiments, a user terminal device cooperates with a server and a camera device in a live broadcast system. The terminal device turns towards the camera device and outputs detection content within a detection time. It can be determined whether live broadcast content uploaded/captured by the camera device includes the detection content captured by the camera device within the detection time. If the detection content is found in the live broadcast content, it can be determined that unauthorized live broadcasting exists. Accordingly, corresponding measures can be taken to stop the unauthorized live broadcasting in a timely manner, which helps improve the security of user information.

Abstract: A magnetic tunnel junction (MTJ) is disclosed wherein a free layer (FL) interfaces with a first metal oxide (Mox) layer and second metal oxide (tunnel barrier) to produce perpendicular magnetic anisotropy (PMA) in the FL. In some embodiments, conductive metal channels made of a noble metal are formed in the Mox that is MgO to reduce parasitic resistance. In a second embodiment, a discontinuous MgO layer with a plurality of islands is formed as the Mox layer and a non-magnetic hard mask layer is deposited to fill spaces between adjacent islands and form shorting pathways through the Mox. In another embodiment, end portions between the sides of a center Mox portion and the MTJ sidewall are reduced to form shorting pathways by depositing a reducing metal layer on Mox sidewalls, or performing a reduction process with forming gas, H2, or a reducing species.

Abstract: A mapping method, an electronic device and a readable storage medium, which relate to the fields of map generation technologies, indoor localization technologies, are disclosed. The mapping method includes: acquiring current frame point cloud data of a target scenario to obtain a submap sequence and an active submap corresponding to the current frame point cloud data; acquiring initial posture data of the current frame point cloud data, and obtaining target posture data of the current frame point cloud data according to the initial posture data and the active submap; obtaining at least one posture constraint condition according to the target posture data of the current frame point cloud data and the submap sequence; and performing posture optimization on the submap sequence according to the at least one posture constraint condition, and obtaining a mapping result of the target scenario according to the submap sequence after the posture optimization.

Abstract: Systems and methods presented herein generally relate to greenhouse gas emission management and, more particularly, to greenhouse gas emission management systems and methods for performing greenhouse gas detection sensor placement planning, leakage source tracing, and quantification of leakage source detections for oil and gas production facilities.

Abstract: This disclosure provides a device environment identification method, a device environment identification apparatus, an electronic device and an autonomous vehicle, and relates to the field of artificial intelligence, in particular to the field of autonomous driving technology, sensor technology, etc. The method includes: obtaining data collected by a sensor of a device from an environment where the device is located; extracting feature information from the collected data; and generating an identification result of the environment in accordance with the feature information, the identification result being used for indicating a corresponding relationship between the environment and calibration of the sensor.

Abstract: In various examples, a 3D surface structure such as the 3D surface structure of a road (3D road surface) may be observed and estimated to generate a 3D point cloud or other representation of the 3D surface structure. Since the estimated representation may be sparse, a deep neural network (DNN) may be used to predict values for a dense representation of the 3D surface structure from the sparse representation. For example, a sparse 3D point cloud may be projected to form a sparse projection image (e.g., a sparse 2D height map), which may be fed into the DNN to predict a dense projection image (a dense 21) height map). The predicted dense representation of the 3D surface structure may be provided to an autonomous vehicle drive stack to enable safe and comfortable planning and control of the autonomous vehicle.

Abstract: In various examples, to support training a deep neural network (DNN) to predict a dense representation of a 3D surface structure of interest, a training dataset is generated using a parametric mathematical modeling. A variety of synthetic 3D road surfaces may be generated by modeling a 3D road surface using varied parameters to simulate changes in road direction and lateral surface slope. In an example embodiment, a synthetic 3D road surface may be created by modeling a longitudinal 3D curve and expanding the longitudinal 3D curve to a 3D surface, and the resulting synthetic 3D surface may be sampled to form a synthetic ground truth projection image (e.g., a 2D height map). To generate corresponding input training data, a known pattern that represents which pixels may remain unobserved during 3D structure estimation may be generated and applied to a ground truth projection image to simulate a corresponding sparse projection image.

Abstract: In various examples, to support training a deep neural network (DNN) to predict a dense representation of a 3D surface structure of interest, a training dataset is generated from real-world data. For example, one or more vehicles may collect image data and LiDAR data while navigating through a real-world environment. To generate input training data, 3D surface structure estimation may be performed on captured image data to generate a sparse representation of a 3D surface structure of interest (e.g., a 3D road surface). To generate corresponding ground truth training data, captured LiDAR data may be smoothed, subject to outlier removal, subject to triangulation to filling missing values, accumulated from multiple LiDAR sensors, aligned with corresponding frames of image data, and/or annotated to identify 3D points on the 3D surface of interest, and the identified 3D points may be projected to generate a dense representation of the 3D surface structure.

Abstract: In various examples, a 3D surface structure such as the 3D surface structure of a road (3D road surface) may be observed and estimated to generate a 3D point cloud or other representation of the 3D surface structure. Since the representation may be sparse, one or more densification techniques may be applied to densify the representation of the 3D surface structure. For example, the relationship between sparse and dense projection images (e.g., 2D height maps) may be modeled with a Markov random field, and Maximum a Posterior (MAP) inference may be performed using a corresponding joint probability distribution to estimate the most likely dense values given the sparse values. The resulting dense representation of the 3D surface structure may be provided to an autonomous vehicle drive stack to enable safe and comfortable planning and control of the autonomous vehicle.

Abstract: In various examples, to support training a deep neural network (DNN) to predict a dense representation of a 3D surface structure of interest, a training dataset is generated using a simulated environment. For example, a simulation may be run to simulate a virtual world or environment, render frames of virtual sensor data (e.g., images), and generate corresponding depth maps and segmentation masks (identifying a component of the simulated environment such as a road). To generate input training data, 3D structure estimation may be performed on a rendered frame to generate a representation of a 3D surface structure of the road. To generate corresponding ground truth training data, a corresponding depth map and segmentation mask may be used to generate a dense representation of the 3D surface structure.