Abstract: A method of operation of a compute system includes: generating a skin segmentation including a non-skin region and a skin prediction based on a patient image; generating a body part segmentation based on the patient image; generating a cropped image based on the skin segmentation and the body part segmentation with the cropped image includes the non-skin region based on the skin prediction; generating a psoriasis segmentation based on the cropped image and the skin prediction; generating intermediate scores for erythema, induration, desquamation for the cropped image; and generating a full body PASI score based a psoriasis segmentation and the intermediate scores on the for displaying on a device to assist in diagnosis.

Abstract: The present disclosure relates to a plant disease control composition comprising a culture broth of Streptomyces sp. JCK-6141 strain or an extract of the culture broth of the strain, a preparation method therefor and a plant disease control method. The culture broth of the strain or an extract thereof exhibits extremely excellent antimicrobial activity when applied to a causative pathogen of plant disease and thus may be effectively used for plant disease control.

Abstract: Systems and methods for downhole gravel packing operations. The systems include a pressure activated fluid diverter and a plurality of inflow control devices attached to the pressure activated fluid diverter to form a section of a string. The pressure activated fluid diverter has a flow performance curve defined by: DP=AQ3+BQ2+CQ, where DP is the differential pressure across the pressure activated fluid diverter in psi and Q is the flow rate through the pressure activated fluid diverter in bpm, with a fluid passing therethrough being at room temperature, having a fluid density of 9.2 ppg, and a fluid viscosity of 1 cps, the flow performance curve of the pressure activated fluid diverter is equal to or below a maximum flow performance curve defined by A=0, B=313.43, C=?1.715.

Abstract: Systems and methods for downhole gravel packing operations are described. The systems include a pressure activated fluid diverter and a plurality of inflow control devices attached to the pressure activated fluid diverter to form a section of a string. The pressure activated fluid diverter has a flow performance curve defined by: DP=AQ3+BQ2+CQ, where DP is the differential pressure across the pressure activated fluid diverter in psi and Q is the flow rate through the pressure activated fluid diverter in bpm, with a fluid passing therethrough being at room temperature, having a fluid density of 9.2 ppg, and a fluid viscosity of 1 cps, the flow performance curve of the pressure activated fluid diverter is equal to or below a maximum flow performance curve defined by A=0, B=313.43, C=?1.715.

Abstract: Provided are a scalable data fusion method and related products. The scalable data fusion method is applied in a central device and includes: receiving sensing data transmitted by each of M first edge devices, wherein M is an integer equal to or greater than 1; fusing the sensing data transmitted by each of the M first edge devices to obtain M pieces of fused data respectively corresponding to the M first edge devices; distributing the M pieces of fused data to the M first edge devices respectively; receiving object information transmitted by each of the M first edge devices, wherein the object information is obtained based on the fused data; and integrating the object information transmitted by each of the M first edge devices and construct surrounding information based on the integrated object information.

Abstract: The present disclosure provides a method for checking a to-be-checked signal and related products. The method is applied in a checking device and includes: a first obtaining module, configured to obtain a to-be-checked signal carrying first control information, wherein the first control information is generated based on original control information; a second obtaining module, configured to obtain original checking information; a determining module, configured to determine the first control information according to the to-be-checked signal; and a checking module, configured to check correctness of the first control information according to the original checking information. The present disclosure can be used to enable reliability and functional safety on devices originally designed without features intended to support those functions.

Abstract: The present disclosure provides a method for checking a to-be-checked signal and related products. The method is applied in a checking device and includes: a first obtaining module, configured to obtain a to-be-checked signal carrying first control information, wherein the first control information is generated based on original control information; a second obtaining module, configured to obtain original checking information; a determining module, configured to determine the first control information according to the to-be-checked signal; and a checking module, configured to check correctness of the first control information according to the original checking information. The present disclosure can be used to enable reliability and functional safety on devices originally designed without features intended to support those functions.

Abstract: Provided are an acceleration method, an apparatus and a system on chip. The acceleration method includes: the accelerator receives N-th parameter information of an N-th layer from a controller, wherein M layer of the deep neural network correspond to M application specific integrated circuit in the accelerator, wherein M and N are positive integer, M?2, 1?N?M, executes computation of the N-th layer according to the N-th parameter information, and transmits N-th computation result information of the N-th layer indicates that the computation of the N-th layer is completed, to the controller, wherein the computation result information comprises computation result of the N-th layer. Then a complete flexibility for ASIC implementations of hardware accelerator can be achieved, and any kind of DNN based algorithms can be supported, which improves the universality of the accelerator.

Abstract: Provided are a scalable data fusion method and related products. The scalable data fusion method is applied in a central device and includes: receiving sensing data transmitted by each of M first edge devices, wherein M is an integer equal to or greater than 1; fusing the sensing data transmitted by each of the M first edge devices to obtain M pieces of fused data respectively corresponding to the M first edge devices; distributing the M pieces of fused data to the M first edge devices respectively; receiving object information transmitted by each of the M first edge devices, wherein the object information is obtained based on the fused data; and integrating the object information transmitted by each of the M first edge devices and construct surrounding information based on the integrated object information.

Abstract: A method allocates radio resources to a plurality of communications in a broadband telecommunication system, each communication being associated with at least one piece of user equipment, at least one of the communications being associated with a single piece of user equipment, the radio resources being distributed according to time and frequency between blocks of resources. The plurality of communications forms at least one group of communications and at least the same block of resources is allocated to the group of communications in order to transmit the plurality of communications.

Abstract: A method allocates radio resources to a plurality of communications in a broadband telecommunication system, each communication being associated with at least one piece of user equipment, at least one of the communications being associated with a single piece of user equipment, the radio resources being distributed according to time and frequency between blocks of resources. The plurality of communications forms at least one group of communications and at least the same block of resources is allocated to the group of communications in order to transmit the plurality of communications.

Abstract: An error correction encoding method is provided for encoding source digital data having the form of a frame, wherein the data can be classified into a plurality of classes. The present encoding method includes the following steps: a first encoding step for encoding data to be encoded formed by the data of a first class, to obtain encoded data; and implementing the following step successively for at least one other class: mixing data of the other class and the data encoded or to be encoded from a preceding encoding step; and encoding data to be encoded formed by mixed data to obtain encoded data. Related decoding methods, as well as encoding and decoding devices are also disclosed.

Abstract: In one embodiment, the present invention includes a processor having a plurality of cores and a control logic to control provision of a voltage/frequency to a first core of the plurality of cores independently of provision of a voltage/frequency to at least a second core of the plurality of cores. In some embodiments, the voltages may be provided from one or more internal voltage regulators of the processor. Other embodiments are described and claimed.

Abstract: An error correction encoding method is provided for encoding source digital data, having the form of a frame, wherein the data can be classified into N classes, where N is an integer at least equal to 2. The encoding method includes: a first step of recursive systematic convolutional encoding of the data of the class 1; an implementation of the following steps, for each n ranging from 1 to M, where M is a positive integer equal to or lower than N?1: nth mixing (108n+1) of a set formed by data of the class n+1 (102n+1), the systematic data and the parity data from a preceding encoding step; and (n+1)th recursive systematic convolutional encoding (110n+1) of data formed by the result of nth mixing. A decoding method is provided for decoding encoded data with the encoding method, using an associated encoding device and a decoding device.

Abstract: An error correction encoding method is provided for encoding in parallel source digital data, having the form of a frame, wherein said data can be classified into N classes, where N is an integer at least equal to 2. The encoding method includes: a first recursive systematic convolutional encoding step of data to be encoded, formed by the data of the class 1; and an implementation of the following steps, for each n ranging from 1 to M, where M is a positive integer equal to or lower than N?1: nth mixing of a set formed by the data of the class n+1 and the systematic data of the preceding encoding; and (n+1)th recursive systematic convolutional encoding of data to be encoded, formed by the result of the nth mixing. Also disclosed is a related decoding method, as well as an associated encoding and decoding devices.

Abstract: An error correction encoding method is provided for encoding source digital data having the form of a frame, wherein the data can be classified into a plurality of classes. The present encoding method includes the following steps: a first encoding step for encoding data to be encoded formed by the data of a first class, to obtain encoded data; and implementing the following step successively for at least one other class: mixing data of the other class and the data encoded or to be encoded from a preceding encoding step; and encoding data to be encoded formed by mixed data to obtain encoded data. Related decoding methods, as well as encoding and decoding devices are also disclosed.

Abstract: An error correction encoding method is provided for encoding in parallel source digital data, having the form of a frame, wherein said data can be classified into N classes, where N is an integer at least equal to 2. The encoding method includes: a first recursive systematic convolutional encoding step of data to be encoded, formed by the data of the class 1; and an implementation of the following steps, for each n ranging from 1 to M, where M is a positive integer equal to or lower than N?1: nth mixing of a set formed by the data of the class n+1 and the systematic data of the preceding encoding; and (n+1)th recursive systematic convolutional encoding of data to be encoded, formed by the result of the nth mixing. Also disclosed is a related decoding method, as well as an associated encoding and decoding devices.

Abstract: The present invention relates to an error correction encoding method for encoding so-called source digital data, having the form of a frame, wherein said data can be classified into N classes, where N is an integer at least equal to 2. The encoding method according to the invention comprises: a first step of recursive systematic convolutional encoding of the data of the class 1; an implementation of the following steps, for each n ranging from 1 to M, where M is a positive integer equal to or lower than N?1: nth mixing (108n+1) of a set formed by data of the class n+1 (102n+1), the systematic data and the parity data from a preceding encoding step; (n+1)th recursive systematic convolutional encoding (110n+1) of data formed by the result of nth mixing. The invention also relates to a method for decoding encoded data with the encoding method according to the invention, as well as associated encoding device and decoding device.

Abstract: Disclosed herein is a phosphorus compound represented by Formula 1: wherein each R is the same or different and is independently hydrogen, C1-C6 alkyl or C6-C12 aryl.

Abstract: A method for obtaining data from a user includes receiving a row selection in an input grid, where each column is associated with one of a plurality of primary input variables, and where each row is configured to display primary data corresponding with the plurality of primary input variables, receiving a request to expand the row to display an input form, where the input form comprises a plurality of fields, where each of the plurality of fields is associated with one of a plurality of supplementary input variables, and where the plurality of fields are configured to display supplementary data corresponding with the plurality of supplementary input variables. The method further includes expanding the row to display the input form, obtaining and storing supplementary data for the input form, collapsing the row to hide the input form, and displaying a summary of supplementary data stored for the input form.