Abstract: A focusing system which is applied to an image sensor integrated in a device system and includes a main control unit, an image processing unit, a digital processing unit, a storage unit and a protocol communication unit. The image processing unit, after obtaining an original image and a phase map corresponding to the original image, performs downsampling processing and data rearrangement processing on the original image to obtain a rearranged image. The digital processing unit infers the rearranged image through an artificial intelligence model to obtain a model processing result. The main control unit determines movement parameters of a focus motor according to the model processing result and the phase map, and determines control parameters based on the movement parameters, and the control parameters are sent to a driver unit of the device system through the protocol communication unit, to enable the focus motor to perform focusing.

Abstract: The present invention discloses an image enhancement system and an implementation method therefor. The system comprises a media signal processing apparatus, an image enhancement apparatus, a microscope body, and a binocular tube. The image enhancement apparatus comprises a housing, and a display device and a superposition lens group that are disposed in the housing, the display device is connected to the media signal processing apparatus, the superposition lens group is disposed on a main optical path of the microscope body, the binocular tube is disposed on the microscope body, the display device is configured to receive information data sent by the media signal processing apparatus and convert the received information data into an optical image, the optical image sent by the display device is superposed to the main optical path of the microscope body through the superposition lens group to form a superposed image, and the superposed image can be observed through the binocular tube.

Abstract: This application provides example display control methods, media, and terminal devices. One example display control method is applied to a vehicle. At least one projection device is installed in the vehicle. The example display control method includes receiving, by a terminal device, a display instruction. In response to the display instruction, the at least one projection device is controlled to perform projection in the vehicle, where an image projected by the at least one projection device is displayed in the vehicle.

Abstract: This disclosure is directed to methods and systems that establish a secure data channel between a host and a disaggregated hardware device (“DHD”) of a data center. The system comprises an initiator host that runs objects, such as virtual machines and containers. The host includes an initiator smart network interface card (“SNIC”). The initiator SNIC includes a virtual device, a trust platform module (“TPM”) and a security engine. The system also comprises a target host equipped with a DHD and a target SNIC. The target SNIC includes a TPM and a security engine. The TPM and the security engine of the initiator SNIC and the TPM and the security engine of the target SNIC establish a secure data channel between an object running on the host and the DHD.

Abstract: Embodiments of the present disclosure provide an information processing method and apparatus. The information processing method includes if a first interface includes at least one input area, responding to a first instruction to call up a target input information corresponding to a target input area at the at least one input area, where the target input information is one piece of the at least one information in a second interface. The information processing method further includes responding to a second instruction at the second interface and outputting the target input information in the target input area. Wherein, the first interface is different from the second interface, thereby improving the input efficiency of information.

Abstract: An example method of offloading a compute task to an accelerator by an application executing in a host cluster includes: sending, by an application executing in an initiator host, the compute task to a virtual accelerator in the initiator host, the virtual accelerator paired with a hardware accelerator in a target host of the host cluster; forwarding, by the virtual accelerator, the compute task to the hardware accelerator in the target host over a network; and receiving, at the application via the virtual accelerator, a result of the compute task from the hardware accelerator over the network.

Abstract: A computing environment can include a host system that maintains a guest system, and a hardware component configured to implement artificial intelligence (“AI”) methods of processing and analyzing date. The guest system can provide a virtual computing environment that receives a request to implement an AI application, and utilize a framework and a guest library to convert data from the AI application into an intermediate representation (“IR”). The host system can receive the IR with a virtual device (“VD”), and utilize an IR backend to translate the IR into hardware operations for the hardware component. Translated hardware operations can be provided to, and carried out by, the hardware component to provide an implementation of the AI application. Results of the hardware operations can be transmitted from the VD of the host system to a VD driver of the guest system, virtualizing the hardware component relative to the guest system.

Abstract: A GIS mechanical fault diagnosis method and the device are disclosed. The method includes: collecting vibration signals to be measured of various excitation sources of GIS in mechanical operation; performing wavelet packet-feature entropy vector extraction on the vibration signals to be measured, when it is determined that the vibration signals to be measured are abnormal according to standard vibration signals in the normal state; inputting the extracted wavelet packet-feature entropy vectors into the pre-trained BP neural network for GIS mechanical fault identification, and outputting the corresponding fault. The disclosure integrates the vibration signals under the action of various excitation sources, extracts the feature entropy vectors according to the entropy theory, and constructs and trains a BP neural network that can classify and recognize various GIS mechanical faults, so as to perform comprehensive and effective GIS mechanical faults diagnose.

Abstract: An example method of offloading a compute task to an accelerator by an application executing in a host cluster includes: sending, by an application executing in an initiator host, the compute task to a virtual accelerator in the initiator host, the virtual accelerator paired with a hardware accelerator in a target host of the host cluster; forwarding, by the virtual accelerator, the compute task to the hardware accelerator in the target host over a network; and receiving, at the application via the virtual accelerator, a result of the compute task from the hardware accelerator over the network.

Abstract: A computing environment can include a host system that maintains a guest system, and a hardware component configured to implement artificial intelligence (“AI”) methods of processing and analyzing date. The guest system can provide a virtual computing environment that receives a request to implement an AI application, and utilize a framework and a guest library to convert data from the AI application into an intermediate representation (“IR”). The host system can receive the IR with a virtual device (“VD”), and utilize an IR backend to translate the IR into hardware operations for the hardware component. Translated hardware operations can be provided to, and carried out by, the hardware component to provide an implementation of the AI application. Results of the hardware operations can be transmitted from the VD of the host system to a VD driver of the guest system, virtualizing the hardware component relative to the guest system.

Abstract: Provided are an imaging method and system for residual stress of a basin insulator and a method for preparing a test block. The imaging method includes cutting and preparing a standard industrial sample of a basin insulator and testing the acoustoelastic coefficient of the standard industrial sample; then obtaining the residual stress data of the basin insulator and obtaining the spatial point sound velocity distribution of the basin insulator; finally, obtaining a stress distribution cloud map of the basin insulator by calculation of the attribute value and the coordinate data of a to-be-measured location, and performing reliability verification based on the residual stress data.

Abstract: Provided are an imaging method and system for residual stress of a basin insulator and a method for preparing a test block. The imaging method includes cutting and preparing a standard industrial sample of a basin insulator and testing the acoustoelastic coefficient of the standard industrial sample; then obtaining the residual stress data of the basin insulator and obtaining the spatial point sound velocity distribution of the basin insulator; finally, obtaining a stress distribution cloud map of the basin insulator by calculation of the attribute value and the coordinate data of a to-be-measured location, and performing reliability verification based on the residual stress data.

Abstract: This disclosure is directed to methods and systems that establish a secure data channel between a host and a disaggregated hardware device (“DHD”) of a data center. The system comprises an initiator host that runs objects, such as virtual machines and containers. The host includes an initiator smart network interface card (“SNIC”). The initiator SNIC includes a virtual device, a trust platform module (“TPM”) and a security engine. The system also comprises a target host equipped with a DHD and a target SNIC. The target SNIC includes a TPM and a security engine. The TPM and the security engine of the initiator SNIC and the TPM and the security engine of the target SNIC establish a secure data channel between an object running on the host and the DHD.

Abstract: The present invention discloses an image enhancement system and an implementation method therefor. The system comprises a media signal processing apparatus, an image enhancement apparatus, a microscope body, and a binocular tube. The image enhancement apparatus comprises a housing, and a display device and a superposition lens group that are disposed in the housing, the display device is connected to the media signal processing apparatus, the superposition lens group is disposed on a main optical path of the microscope body, the binocular tube is disposed on the microscope body, the display device is configured to receive information data sent by the media signal processing apparatus and convert the received information data into an optical image, the optical image sent by the display device is superposed to the main optical path of the microscope body through the superposition lens group to form a superposed image, and the superposed image can be observed through the binocular tube.

Abstract: A vehicle positioning method/apparatus including obtaining odometer data from an odometer of a vehicle during driving, predicting, based on the odometer data and a first working state of a filter at a first moment, a second working state of the filter at a second moment, the second moment being after the first moment, predicting location information of the vehicle at the second moment based on the second working state, selecting a target road section that matches the location information from candidate road sections in an electronic map, determining matching point information corresponding to the location information in the target road section, and correcting the location information based on the matching point information, to obtain positioning information of the vehicle at the second moment, the positioning information and working states of the filter being defined in the same coordinate system.

Abstract: An example method of offloading a compute task to an accelerator by an application executing in a host cluster includes: sending, by an application executing in an initiator host, the compute task to a virtual accelerator in the initiator host, the virtual accelerator paired with a hardware accelerator in a target host of the host cluster; forwarding, by the virtual accelerator, the compute task to the hardware accelerator in the target host over a network; and receiving, at the application via the virtual accelerator, a result of the compute task from the hardware accelerator over the network.

Abstract: The present invention relates to an extension structure and an optical system. The extension structure comprises a first connecting base and a second connecting base. One end of the first connecting base forms a first connecting end, and one end of the second connecting base forms a second connecting end. The first connecting base and the second connecting base can be connected in a relatively rotatable manner, and the rotation axis lines of the first connecting base and the second connecting base are parallel. The optical system is arranged in the extension structure. A surgical microscope, comprising a lens body, the extension structure connected to the lens body, a rotating structure connected to the extension structure, and an eyepiece connected to the rotating structure. The extension structure and the rotating structure enables the eyepiece to move up and down relative to the lens body, the adjustment region is large.

Abstract: An example method of virtualizing a hardware accelerator in a host cluster of a virtualized computing system includes: commanding, at an initiator host in the host cluster, a programmable expansion bus device to reconfigure as a virtual accelerator based on specifications of a hardware accelerator in a target host of the host cluster; executing, in the programmable expansion bus device, software to emulate the virtual accelerator as connected to an expansion bus of the initiator host; receiving, at the programmable expansion bus device, compute tasks from an application executing in the initiator host; and sending, to the target host, the compute tasks for processing by the hardware accelerator.