Abstract: Certain aspects of the present disclosure provide techniques for performing machine learning computations in a compute in memory (CIM) array comprising a plurality of bit cells, including: determining that a sparsity of input data to a machine learning model exceeds an input data sparsity threshold; disabling one or more bit cells in the CIM array based on the sparsity of the input data prior to processing the input data; processing the input data with bit cells not disabled in the CIM array to generate an output value; applying a compensation to the output value based on the sparsity to generate a compensated output value; and outputting the compensated output value.

Abstract: Certain aspects of the present disclosure provide techniques for performing machine learning computations in a compute in memory (CIM) array comprising a plurality of bit cells, including: determining that a sparsity of input data to a machine learning model exceeds an input data sparsity threshold; disabling one or more bit cells in the CIM array based on the sparsity of the input data prior to processing the input data; processing the input data with bit cells not disabled in the CIM array to generate an output value; applying a compensation to the output value based on the sparsity to generate a compensated output value; and outputting the compensated output value.

Abstract: A lower vehicle body rear structure includes a rear floor integrally formed in a die-casting mode, rear floor longitudinal beam rear sections fixedly connected to the rear floor, a shelf, and a spare tire cabin. Rear floor longitudinal beams arranged on the two sides of the rear floor, and a rear floor middle cross beam and a rear floor rear cross beam which are connected between the rear floor longitudinal beams are formed on the rear floor, and rear wheel covers connected to the rear floor longitudinal beams are respectively arranged on the two sides of the rear floor. The shelf is located above the rear floor, and the two ends of the shelf are connected to the rear wheel covers by means of connecting plates; and the rear floor, the shelf and the two connecting plates are connected to form an annular structure.

Abstract: An Ethernet data transmission circuit, an Ethernet data transmission system and an Ethernet data transmission method are provided. The Ethernet data transmission circuit includes: a polarity processing circuit for processing a polarity carried by Ethernet data into a preset polarity; and an encoder for receiving the Ethernet data and the preset polarity carried by the Ethernet data, and encoding the Ethernet data. On the one hand, the security of Ethernet in a transmission process can be improved; on the other hand, without increasing workload of the encoder, the polarity processing circuit of the Ethernet data transmission circuit can be used to process the Ethernet data to be with a preset polarity, to facilitate the encoder to code.

Abstract: Devices and systems for controlling pressure during sensing are disclosed. Such sensors and/or systems may be embodied in a wearable user device. The wearable user device may include a cuff configured to apply a pressure to a portion of a user at a plurality of discrete pressure levels over a plurality of time periods; a biometric sensor configured to obtain a plurality of sensor measurements associated with a blood vessel of the user at corresponding ones of the plurality of discrete pressure levels during corresponding ones of the plurality of time periods; and a wearable structure including the cuff and the biometric sensor.

Abstract: This specification provides an LSM tree-based data storage method and a related device, applied to an LSM tree-based data storage system. The method includes: determining whether the first storage layer meets a merge condition for merging with the second storage layer, and if yes, selecting a to-be-merged target file from the at least one first file stored at the first storage layer, where the target file includes data corresponding to a target type; and searching the plurality of second sub-files for a target sub-file that includes data corresponding to the target type, and merging the target file and the target sub-file.

Abstract: Synchronized sensors and systems are disclosed. Techniques involving a synchronized sensor system for determining a physiological parameter of a user may include: obtaining one or more first measurements at a first location of the user via a first sensor; obtaining one or more second measurements at a second location of the user via a second sensor; and determining the physiological parameter of the user based on the one or more first measurements, the one or more second measurements, and a distance between the first location and the second location, the distance between the first location and the second location determined based on acoustic communication between the first sensor and the second sensor. In some implementations, acoustic communication may include ultrasound signals between the first sensor and the second sensor, which may be time synchronized by exchanging timestamps.

Abstract: A volume measurement method includes: receiving multiple pulse signals when a device under test (DUT) starts passing through a sensing gate; recording multiple X-axis values corresponding to multiple positions of the DUT in response to each pulse signal, and reading the multiple sensing data to calculate a Y-axis value and a Z-axis value corresponding to each X-axis value, wherein the multiple sensing data is obtained by sensing the DUT through the sensing gate; recording a maximum X-axis value corresponding to a final position of the DUT in response to a final pulse signal when the DUT finishes passing through the sensing gate; setting the maximum of the multiple Y-axis values corresponding to the multiple X-axis values as a maximum Y-axis value, and setting the maximum of the multiple Z-axis values corresponding to the multiple X-axis values as a maximum Z-axis value; and calculating a volume of the DUT based on the maximum X-axis value, the maximum Y-axis value and the maximum Z-axis value.

Abstract: This application discloses a method for monitoring SH of an epitaxial layer of a CMOS device, fabricating a measurement reference device, AA and STI structures of the measurement reference device being the same as those of the CMOS device to be monitored, polysilicon lines being formed on the AA and STI structures of the measurement reference device, the polysilicon lines on the AA structures being connected in series to obtain a first polysilicon line string, the polysilicon lines on the STI structures being connected in series to obtain a second polysilicon line string; obtain current I1 flowing through the first polysilicon line string and current I2 flowing through the second polysilicon line string; and performing calculation according to I1 and I2 to obtain SH of an epitaxial layer of the measurement reference device as SH of an epitaxial layer of the CMOS device to be monitored.

Abstract: Certain aspects of the present disclosure provide a method, including: storing a depthwise convolution kernel in a first one or more columns of a CIM array; storing a fused convolution kernel in a second one or more columns of the CIM array; storing pre-activations in one or more input data buffers associated with a plurality of rows of the CIM array; processing the pre-activations with the depthwise convolution kernel in order to generate depthwise output; modifying one or more of the pre-activations based on the depthwise output to generate modified pre-activations; and processing the modified pre-activations with the fused convolution kernel to generate fused output.

Abstract: Certain aspects provide an apparatus for signal processing in a neural network. The apparatus generally includes computation circuitry configured to perform a convolution operation, the computation circuitry having multiple input rows, and an activation buffer having multiple buffer segments coupled to the multiple the multiple input rows of the computation circuitry, respectively. In some aspects, each of the multiple buffer segments comprises a first multiplexer having a plurality of multiplexer inputs, and each of the plurality of multiplexer inputs of one of the first multiplexers on one of the multiple buffer segments is coupled to a data output of the activation buffer on another one of the multiple buffer segments.

Abstract: A multi-antenna module system includes a substrate, a plurality of first antenna modules, a plurality of second antenna modules, and a plurality of third antenna modules. The substrate has an opening. The first antenna modules are respectively disposed on the substrate and located on two opposite first sides and two opposite second sides for transmitting and receiving a first frequency band signal. The second antenna modules are respectively disposed on the substrate and located on two opposite third sides for transmitting and receiving a second frequency band signal. The third antenna modules are respectively disposed on the substrate and located on two opposite third sides and two opposite fourth sides for transmitting and receiving a third frequency band signal. The second antenna modules and the third antenna modules are respectively located between the first antenna modules.

Abstract: An automated guided vehicle (AGV) includes an image capturing device, a storage device, a fetching device, a driving device and a processor. The processor is configured to execute: controlling the AGV to move from a starting position to a target position according to a navigation coordinate system, the target position corresponding to the object to be fetched; capturing a depth image from the object to be fetched through the image capturing device; performing image recognition on the depth image to obtain reference pixel information; converting the reference pixel information to the navigation coordinate system according to a coordinate mapping algorithm to obtain a calibrated position; and determining an object-fetching route according to the target position and the calibrated position, and controlling the AGV to move according to the object-fetching route to fetch the object to be fetched.

Abstract: A multi-antenna module system includes a substrate, a plurality of first antenna modules, a plurality of second antenna modules, and a plurality of third antenna modules. The substrate has an opening. The first antenna modules are respectively disposed on the substrate and located on two opposite first sides and two opposite second sides for transmitting and receiving a first frequency band signal. The second antenna modules are respectively disposed on the substrate and located on two opposite third sides for transmitting and receiving a second frequency band signal. The third antenna modules are respectively disposed on the substrate and located on two opposite third sides and two opposite fourth sides for transmitting and receiving a third frequency band signal. The second antenna modules and the third antenna modules are respectively located between the first antenna modules.

Abstract: Systems, methods and instrumentalities are described herein for automating a medical environment. The automation may be realized using one or more sensing devices and at least one processing device. The sensing devices may be configured to capture images of the medical environment and provide the images to the processing device. The processing device may determine characteristics of the medical environment based on the images and automate one or more aspects of the operations in the medical environment. These characteristics may include, e.g., people and/or objects present in the images and respective locations of the people and/or objects in the medical environment. The operations that may be automated may include, e.g., maneuvering and/or positioning a medical device based on the location of a patient, determining and/or adjusting the parameters of a medical device, managing a workflow, providing instructions and/or alerts to a patient or a physician, etc.

Abstract: A tri-band antenna module includes a substrate, a first radiator, a second radiator, and a short-circuit structure. The substrate has a signal feed-in terminal and a ground terminal. The signal feed-in terminal is connected to the first radiator, and the ground terminal is connected to the second radiator. The first radiator includes a first extension block and a second extension block, and the second radiator includes a third extension block and a fourth extension block. The first extension block and the second extension block are separated by a first interval, and the third extension block and the fourth extension block are separated by a second interval. The short-circuit structure is connected between the first extension block and the third extension block, and the short-circuit structure is respectively separated from the first extension block and the third extension block by a first slot and a second slot.

Abstract: Certain aspects of the present disclosure provide a method for performing voice activity detection, including: receiving audio data from an audio source of an electronic device; generating a plurality of model input features using a hardware-based feature generator based on the received audio data; providing the plurality of model input features to a hardware-based voice activity detection model; receiving an output value from the hardware-based voice activity detection model; and determining a presence of voice activity in the audio data based on the output value.

Abstract: Certain aspects of the present disclosure provide a method for processing input data by a set of configurable nonlinear activation function circuits, including generating an exponent output by processing input data using one or more first configurable nonlinear activation function circuits configured to perform an exponential function, summing the exponent output of the one or more first configurable nonlinear activation function circuits, and generating an approximated log softmax output by processing the summed exponent output using a second configurable nonlinear activation function circuit configured to perform a natural logarithm function.

Abstract: Systems, methods and instrumentalities are described herein for automating a medical environment. The automation may be realized using one or more sensing devices and at least one processing device. The sensing devices may be configured to capture images of the medical environment and provide the images to the processing device. The processing device may determine characteristics of the medical environment based on the images and automate one or more aspects of the operations in the medical environment. These characteristics may include, e.g., people and/or objects present in the images and respective locations of the people and/or objects in the medical environment. The operations that may be automated may include, e.g., maneuvering and/or positioning a medical device based on the location of a patient, determining and/or adjusting the parameters of a medical device, managing a workflow, providing instructions and/or alerts to a patient or a physician, etc.

Abstract: An AGV navigation device is provided, which includes a RGB-D camera, a plurality of sensors and a processor. When an AGV moves along a target route having a plurality of paths, the RGB-D camera captures the depth and color image data of each path. The sensors (including an IMU and a rotary encoder) record the acceleration, the moving speed, the direction, the rotation angle and the moving distance of the AGV moving along each path. The processor generates training data according to the depth image data, the color image data, the accelerations, the moving speeds, the directions, the moving distances and the rotation angles, and inputs the training data into a machine learning model for deep learning in order to generate a training result. Therefore, the AGV navigation device can realize automatic navigation for AGVs without any positioning technology, so can reduce the cost of automatic navigation technologies.