Abstract: A powered surgical device (10) includes a safety trigger assembly (62) that is movable from a safe position to an intermediate position, and subsequently to a fire-ready position. The safety trigger assembly (62) prevents firing of the surgical device (10) unless the safety trigger assembly (62) is in the fire-ready position and includes at least one safety button (120, 134) that extends through an outer housing (18) of the surgical device (10) and is accessible to a clinician to move the safety trigger assembly (62) to the fire-ready position. The surgical device (10) includes the outer housing (18) that shields the at least one safety button (120, 134) when the safety trigger assembly (62) is in the safe position to prevent inadvertent movement of the safety trigger assembly (62) from the safe position to the fire-ready position.

Abstract: A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.

Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.

Abstract: A first housing and a second housing of a foldable device are rotatably connected through a rotating shaft mechanism. A first chamber is provided between a flexible display of the device and the first housing, a second chamber is provided between the flexible display of the device and the second housing, and a third chamber is provided between the flexible display of the device and the rotating shaft mechanism. A flexible thermal sheet is disposed in space formed by the first chamber, the second chamber, and the third chamber. The flexible thermal sheet is fastened to the first housing, passes through the third chamber along the flexible display, and extends to the second chamber. The flexible thermal sheet slidably cooperates with the rotating shaft mechanism, the second housing, and parts that correspond to the rotating shaft mechanism and the second housing and that are of the flexible display.

Abstract: This disclosure provides an antenna module and a communication device. The antenna module includes a ground plane, a first antenna, a second antenna, and a first decoupling structure. A cross-sectional height of the first decoupling structure, a distance between the first decoupling structure and the first antenna, and a distance between the first decoupling structure and the second antenna are set to reduce an amount of coupling between the first antenna and the second antenna. This facilitates a miniaturized design of the antenna module, and improves isolation on a premise thereby ensuring antenna efficiency.

Abstract: This application provides an antenna module and a communication device. The antenna module includes a radiating element, a ground element, and a feed element. The feed element is a transmission line structure formed on an insulation support. The feed element includes a feed transmission part and a ground part. The feed transmission part and the ground part are not equal in width, and are configured to implement current balance of the antenna module.

Abstract: Self-checkout vehicle systems and methods comprising a self-checkout vehicle having a camera(s), a weight sensor(s), and a processor configured to: (i) identify via computer vision a merchandise item selected by a shopper based on an identifier affixed to the selected item, and (ii) calculate a price of the merchandise item based on the identification and weight of the selected item. Computer vision systems and methods for identifying merchandise selected by a shopper comprising a processor configured to: (i) identify an identifier affixed to the selected merchandise and an item category of the selected merchandise, and (ii) compare the identifier and item category identified in each respective image to determine the most likely identification of the merchandise.

Abstract: An antenna for a wireless communication device, such as a Wi-Fi access point is provided. The antenna includes an electrically conductive radiation structure including a plurality of radially extending radiation slots, each of which has an open outer end at a perimeter of the electrically conductive radiation structure and defines a respective radiation portion of the electrically conductive radiation structure. The antenna includes a feeding network configured to feed an RF signal to the electrically conductive radiation structure, the feeding network includes a plurality of feeding arms configured to feed the RF signal into each radiation portion of the electrically conductive radiation structure for exciting each radiation portion to emit electromagnetic waves.

Abstract: The embodiments of the present disclosure provide a method and an apparatus for acquiring a RAW image, and an electronic device, the method including: obtaining an sRGB image; inputting the sRGB image into a preset image restoration model to obtain an initial RAW image corresponding to the sRGB image, wherein the preset image restoration model is a model obtained by training a preset neural network based on a first preset training set; adding a first preset noise to the initial RAW image to obtain a first noise RAW image; adding a second preset noise to the initial RAW image to obtain a second noise RAW image; inputting the first noise RAW image and the second noise RAW image into a preset noise addition model to obtain a target RAW image, wherein the preset noise addition model is a model obtained by training a preset neural network based on a second preset training set.

Abstract: A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.

Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.

Abstract: A fan includes a first blower and a second blower each having an impeller. The first blower includes a first motor and a first motor drive controller to control driving of the first motor and communicate with the second blower. The second blower includes a second motor and a second motor drive controller to control driving of the second motor and communicate with the first blower. The first motor drive controller controls the driving of the first motor based on a result of communication with the second blower.

Abstract: Examples of the present disclosure provide a method and an apparatus for denoising a low-light image, wherein the method includes: acquiring a low-light image in RAW domain; performing a preset image enhancement transformation on the low-light image in the RAW domain, and inputting the transformed image into a pre-trained denoising network model to obtain an output image; wherein, the denoising network model is trained based on sample images, and the sample images include a low-light image with simulated dead pixels and a noiseless image; performing an inverse transformation of the preset image enhancement transformation on the output image to obtain a denoised image. It can significantly reduce the influence of dead pixels of images on the process of denoising the low-light image and improve the quality of low-light image denoising.

Abstract: A fan includes a first blower and a second blower each having an impeller. The first blower includes a first motor and a first motor drive controller to control driving of the first motor and communicate with the second blower. The second blower includes a second motor and a second motor drive controller to control driving of the second motor and communicate with the first blower. The first motor drive controller controls the driving of the first motor based on a result of communication with the second blower.

Abstract: A shipping cover for a staple cartridge includes a body having an upper surface and a lower surface that is in close opposition to the staple cartridge when the shipping cover is secured to the staple cartridge. The shipping cover includes a latch that is received within a body of the staple cartridge to secure the shipping cover to the cartridge body. The latch is manually movable by a clinician to facilitate removal of the shipping cover from the staple cartridge.

Abstract: The embodiments of the present application provide a denoising method, apparatus, electronic device and medium, which relates to the technical field of image processing. The method comprises: inputting an image to be processed into an image denoising model, which is a model obtained by training a convolutional neural network model based on a preset training set, wherein the preset training set includes multiple groups of annotation data and sample data corresponding to each group of annotation data, and each group of annotation data includes multiple noiseless images obtained by performing motion simulation processing on one reference noiseless image, and the sample data corresponding to the group of annotation data includes images obtained by superimposing noise to the multiple noiseless images respectively; acquiring denoised image data output by the image denoising model; converting the image data into an image, to obtain a denoised image corresponding to the image to be processed.

Abstract: A product state quantification and remaining life prediction method, the method comprising: T1, acquiring design data and operating data of a product; T2, establishing a design model of the product on the basis of the design data, performing data fusion according to the design data and operating data to obtain a predicted performance curve of the product, and selecting an optimized operating state point in the predicted performance curve; and T3, establishing a cost model and an operating flexibility model of the product on the basis of the predicted performance curve, and calculating a remaining life prediction of the product according to a performance demand or operating cost of the product.

Abstract: Various embodiments of the teachings herein include a dynamic prediction control method for a precision air conditioner. An example method includes: generating a three-dimensional simulation model on the basis of a simulation template according to static information of a hardware configuration and layout of an application scene where the precision air conditioner is located, wherein the three-dimensional simulation model and a static model of the hardware configuration and layout of the application scene correspond to each other; running a simulation on the basis of a dynamic parameter of the precision air conditioner corresponding to the three-dimensional simulation model and establishing a correspondence relationship between the dynamic parameter and a simulation result using machine learning, so as to generate a proxy model; and predicting a temperature distribution and change of the application scene on the basis of the proxy model and real-time dynamic data of the precision air conditioner.

Abstract: An antenna device includes a plurality of dipole antennas and a port. Each of the dipole antennas is connected to the port. The plurality of dipole antennas is arranged around the port. Each of the plurality of dipole antennas includes two ends. The ends of the dipole antennas are arranged in a plurality of pairs. Each pair includes one end of one of the dipole antennas and one end of another one of the dipole antennas. The two ends in each pair are arranged in proximity to each other. One or more switches are configured to switch between (1) an omnidirectional state, in which the ends of the dipole antennas are not connected to each other; and (2) a directional state, in which the two ends in each of one or more of the pairs are connected to each other.

Abstract: A method and an apparatus for generating image data, which relate to the technical field of image processing. The method comprises: obtaining a first pixel value of each pixel in a first image based on original pixel values of the first image acquired by an image acquisition device when ambient light brightness is greater than a first preset brightness threshold; obtaining a second pixel value of each pixel by dividing the first pixel value of this pixel by a preset multiple; the second preset brightness threshold is less than the first preset brightness threshold; obtaining a third pixel value of each pixel by adding Poisson noise based on a total system gain of the image acquisition device on the basis of the second pixel value of this pixel; generating original pixel values of a target image which corresponds to the first image for which the ambient light brightness is less than the second preset brightness threshold based on respective third pixel values.