Abstract: Delay locked loop (DLL) circuitry system and a memory device are disclosed. The DLL circuitry system includes a timer unit and a DLL circuit coupled thereto. The timer unit is enabled to generate a DLL enable signal based on the signal instructing the entry into a low power consumption mode and a predefined timer condition. The DLL enable signal enables the DLL circuit to realign an internal clock signal with an external clock signal. In this way, the DLL circuit is avoided from being unable to align the internal clock signal with the external clock signal because the memory device enters the low power mode which causes the variation of the power supply voltage of the DLL circuit. Moreover, a read or write error that may occur when data is to be read or written immediately after exiting the low power consumption mode is also avoided.

Abstract: A method for detecting a slow node includes: obtaining a generated record for a first storage node, the generated record including a storage node generation time, and a number of times and consuming time for transmitting data to second storage nodes other than the first storage node; obtaining a valid record from the generated record, the valid record being generated within a preset time period, and the preset time period being within a time period between the storage node generation time and a current time; determining an average consuming time for the first storage node transmitting the data to each of the second storage nodes, based on the number of times and the consuming time in the valid record; and detecting the slow node in the second storage nodes based on the average consuming time.

Abstract: An apparatus can include an interface coupled to processing circuitry and cryptographic circuitry coupled to the interface. The cryptographic circuitry can receive a request from the processing circuitry over the interface to perform a cryptographic operation using a remote hardware security module (HSM) key component. The cryptographic circuitry can further transmit a command to a remote component to retrieve the remote HSM key component. Subsequent to receiving the cryptographic key component, the cryptographic circuitry can construct a trusted execution environment (TEE) instance and store the remote HSM key component in the TEE instance. The cryptographic circuitry can use the remote HSM key component to perform the cryptographic operation and provide a result of the cryptographic operation to the processing circuitry over the interface.

Abstract: A processing circuitry, a method to be performed at the processing circuitry, a computer-readable storage medium, and a computing system. The processing circuitry is to determine a first mapping between a first set of data parameters and first computing units of a computing network; select, based on the first mapping and on first data having a first workload associated therewith, one or more of the first computing units to execute the first workload, and send for execution the first workload to the one or more of the first computing units; determine a second mapping based on a change in computing units from the first computing units to second computing units, the second mapping between a second set of data parameters and the second computing units; and select, based on the second mapping and on second data having a second workload associated therewith, one or more of the second computing units to execute the second workload.

Abstract: A face modeling method and apparatus, an electronic device and a computer-readable medium. Said method comprises: acquiring multiple depth images, the multiple depth images being obtained by photographing a target face at different irradiation angles; performing alignment processing on the multiple depth images to obtain a target point cloud image; using the target point cloud image to construct a three-dimensional model of the target face. The present disclosure alleviates the technical problems of poor robustness and low precision of the three-dimensional model constructed according to the three-dimensional model constructing method.

Abstract: A neural network training method, an image processing method, and apparatuses thereof are provided. The neural network training method includes obtaining a first domain image and a second domain image, where the first domain image and the second domain image are unpaired images in different domains; obtaining a scaled first domain image by scaling, at an iteration, the first domain image; obtaining a training patch by cropping the scaled first domain image, where each training patch has a same number of pixels with different contents; inputting the training patch into the neural network at the iteration, and outputting an output patch; calculating a contrastive loss based on a query sub-patch and negative sub-patches selected from the training patch and a corresponding positive sub-patch selected from the output patch; and updating model parameters of the neural network based on the contrastive loss and a generative adversarial network loss.

Abstract: In one embodiment, a request is sent to an image registry for at least one virtual environment image block of an image for a virtual environment. The at least one virtual environment image block is processed upon reception of the at least one virtual environment image block from the image registry. The processed at least one virtual environment image block is communicated to a worker node that is to execute the virtual environment.

Abstract: A natural language processing (NLP) apparatus includes a housing, a built-in voice input interface; a built-in data communication interface configured to establish data communication with multiple types of appliances; a built-in NLP module, and a built-in control device. A first voice input is received through the built-in voice input interface; if the target appliance is a first appliance of a first appliance type, the first voice input is processed using a first NLP model of the built-in NLP module to obtain a first machine command, and the first machine command is sent via the built-in data communication interface to the first appliance; and if the target appliance is a second appliance of a second appliance type, the first voice input is processed using a second NLP model of the built-in NLP module, and the second machine command is sent via the built-in data communication interface to the second appliance.

Abstract: The present disclosure provides a method, an electronic device, and a medium for image fusion. The method includes calculating a fusion coefficient image M based on a first frame image I1 or based on both the first frame image I1 and a second frame image I2; calculating a first gradient D1 of the first frame image I1 and a second gradient D2 of the second frame image I2; calculating a preliminary fusion result J based on the image M, the first gradient D1 and the second gradient D2; and obtaining an output image I3 based on the image M, the first gradient D1, the second gradient D2 and the preliminary fusion result J, wherein brightness of the first frame image I1 is greater than brightness of the second frame image I2, and wherein the image M is used to mark fusion weights of pixels in the first frame image I1.

Abstract: A face modeling method and apparatus, an electronic device and a computer-readable medium. Said method comprises: acquiring multiple depth images, the multiple depth images being obtained by photographing a target face at different irradiation angles; performing alignment processing on the multiple depth images to obtain a target point cloud image; using the target point cloud image to construct a three-dimensional model of the target face. The present disclosure alleviates the technical problems of poor robustness and low precision of the three-dimensional model constructed according to the three-dimensional model constructing method.

Abstract: A detection method for an image acquisition device, a detection device for an image acquisition device, an electronic device and a computer readable storage medium are disclosed. The image acquisition device includes a light source and a diffuser, the diffuser is configured to scatter light emitted by the light source and the light emitted by the light source is irradiated on at least partial area of a scene, the image acquisition device includes: acquiring an image of the scene; determining an effective area of the image; and determining whether or not the diffuser is in an abnormal working state according to information of the effective area.

Abstract: The present disclosure relates to systems and methods of multi-camera. The method may include determining a level of a camera in a multi-camera system based on the status of an object, and determining a mode of the camera based on the level. The mode may relate to one of a bit rate, an I frame interval, or a coding algorithm. The method may further include generating a monitor file relating to the object based on the level of the camera in the multi-camera system.

Abstract: The present invention belongs to the technical field of health monitoring for civil structures, and a dynamically non-Gaussian anomaly identification method is proposed for structural monitoring data. First, define past and current observation vectors for the monitoring data and pre-whiten them; second, establish a statistical correlation model for the whitened past and current observation vectors to obtain dynamically whitened data; then, divide the dynamically whitened data into two parts, i.e., the system-related and system-unrelated parts, which are further modelled by the independent component analysis; finally, define two statistics and determine their corresponding control limits, respectively, it can be decided that there is anomaly in the monitoring data when each of the statistics exceeds its corresponding control limit.

Abstract: A method for detecting a slow node includes: obtaining a generated record for a first storage node, the generated record including a storage node generation time, and a number of times and consuming time for transmitting data to second storage nodes other than the first storage node; obtaining a valid record from the generated record, the valid record being generated within a preset time period, and the preset time period being within a time period between the storage node generation time and a current time; determining an average consuming time for the first storage node transmitting the data to each of the second storage nodes, based on the number of times and the consuming time in the valid record; and detecting the slow node in the second storage nodes based on the average consuming time.

Abstract: A method and system of customizing a portable voice-based control user interface for multiple types of appliances are disclosed.

Abstract: The present invention belongs to the technical field of health monitoring for civil structures, and a performance alarming method for bridge expansion joints based on temperature displacement relationship model is proposed. First, the canonically correlated temperature is proposed to maximize the correlation between bridge temperature field and expansion joint displacement; second, a temperature displacement relationship model for bridge expansion joints is established based on canonically correlated temperatures; then, a mean-value control chart is constructed to the error of temperature displacement relationship model; finally, reasonable control limits are determined for the mean-value control chart. A more accurate temperature displacement relationship model can be established based on canonically correlated temperatures, which is of important value to improve the performance alarming ability for expansion joint.

Abstract: This disclosure provides an image processing method, an electronic device and a non-transitory computer-readable storage medium, and relates to the field of image processing technique. The image processing method and apparatus and the electronic device provided by this application perform denoising on the to-be-processed image to obtain a denoised image, and then perform detail enhancement on the target area image extracted from the denoised image to obtain a detail enhanced image, thereafter fuse the denoised image with the detail enhanced image to obtain an output image. Since detail enhancement has been performed on the target area image, the obtained output image is sharper and the display effect is better.

Abstract: The present invention belongs to the technical field of health monitoring for civil structures, and an anomaly identification method considering spatial-temporal correlation is proposed for structural monitoring data. First, define current and past observation vectors for the monitoring data and pre-whiten them; second, establish a statistical correlation model for the pre-whitened current and past observation vectors to simultaneously consider the spatial-temporal correlation in the monitoring data; then, divide the model into two parts, i.e., the system-related and system-unrelated parts, and define two corresponding statistics; finally, determine the corresponding control limits of the statistics, and it can be decided that there is anomaly in the monitoring data when each of the statistics exceeds its corresponding control limit.

Abstract: The embodiment of the present disclosure relates to an image processing method, which includes: acquiring a first image and a second image captured for a same object; and determining depth information of the object according to the first image and the second image. The embodiment of the present disclosure further provides an image processing device and a computer readable medium.