Abstract: A method, device, equipment for user grouping, and a non-transitory computer-readable storage medium are provided, which are applicable to the field of medical technology. The method includes the following. Net benefits of multiple users in a target project are obtained. According to the net benefits of the multiple users in the target project and a solution of the target project, a net-benefit coefficient corresponding to the solution is determined. For each grouping variable of the target project, a fluctuation value corresponding to the grouping variable is determined according to the net-benefit coefficient. According to a grouping variable with the largest fluctuation value, the multiple users are divided into multiple user groups. For each user group obtained by division, users in the user group are divided according to a fluctuation value corresponding to each grouping variable of the target project, until a user group meeting a preset condition is obtained.

Abstract: A method and device for neural network-based optical coherence tomography (OCT) image lesion detection, and a medium are provided. The method includes the following. An OCT image is obtained. The OCT image is inputted into a lesion-detection network model. A position, a category score, and a positive score of each lesion box in the OCT image are outputted through the lesion-detection network model. A lesion detection result of the OCT image is obtained according to the position, the category score, and the positive score of each lesion box. The lesion-detection network model includes a category detection branch configured to obtain, for each of the anchor boxes, a position and a category score of the anchor box, and a lesion positive score regression branch configured to obtain, for each of the anchor boxes, a positive score of whether the anchor box belongs to a lesion, to reflect severity of lesion positive.

Abstract: The present application relates to a blockchain system based on Ethereum, including a master node configured to receive a transaction request transmitted by a client terminal, perform transaction processing by calling a smart contract deployed in a consortium blockchain according to the transaction request to obtain transaction data; and use the transaction data to generate a block, and broadcast the block is to the plurality of backup nodes; backup node configured to receive the block and verify the transaction data of the block; the master node is further configured to generate a first-stage certificate using complete block information, and transmit the first-stage certificate to the plurality of backup nodes; the backup node is further configured to respectively generate a second-stage certificate and a third-stage certificate according to a block hash value in the first-stage certificate, and the second-stage certificate and the third-stage certificate are respectively used to negotiate on the block to ob

Abstract: A method for drug classification, a terminal device, and a non-transitory computer-readable storage medium are provided. An attribute feature vector of each of n atoms in a drug molecule to be detected and an attribute feature vector of a virtual atom are obtained. An adjacency matrix is constructed according to a connection relationship between the virtual atom and each of the n atoms and between the n atoms. An atom attribute feature matrix is constructed according to the attribute feature vector of each atom. The adjacency matrix and the atom attribute feature matrix are inputted into a graph neural network to determine a transfer feature matrix of the n atoms and the virtual atom. A molecular feature vector corresponding to the drug molecule to be detected is determined according to the transfer feature matrix. The molecular feature vector is inputted into a classifier to output a drug category.

Abstract: Systems and methods for characterizing a region of interest (ROI) in a medical image are provided. An exemplary system may include a memory storing instructions and at least one processor communicatively coupled to the memory to execute the instructions which, when executed by the processor, may cause the processor to perform operations. The operations may include detecting one or more candidate ROIs from the medical image using a three-dimensional (3D) machine learning network. The operations may also include determining a key slice for each candidate ROI. The operations may further include selecting a primary ROI from the one or more candidate ROIs based on the respective key slices. In addition, the operations may include classifying the primary ROI into one of a plurality of categories using a texture-based classifier based on the key slice corresponding to the primary ROI.

Abstract: A user permission data query method which includes obtaining a first data table including staff identification numbers and departments corresponding to the staff identification numbers, and obtaining a second data table including a correspondence relationship among the staff identification numbers, roles, and administration authority information; obtaining, from the second data table, a plurality of data records having the same staff identification number and the same role, calculating an MD5 value corresponding to the staff identification number and the role; screening various MD5 values that are different from each other, and obtaining the management departments and the management staffs respectively corresponding to the various MD5 values obtaining a MD5 value corresponding to the permission query request and determining the management departments and the management staffs corresponding to the MD5 value as permission data of a user, when a permission query request is received.

Abstract: A method for model deployment, a terminal device, and a non-transitory computer-readable storage medium are provided. The method includes the following. A to-be-deployed model and an input/output description file of the to-be-deployed model are obtained. Output verification is performed on the to-be-deployed model based on the input/output description file. If the output verification of the to-be-deployed model passes, an inference service resource is determined from multiple running environments and the inference service resource is allocated to the to-be-deployed model. An inference parameter value of executing an inference service by the to-be-deployed model based on the inference service resource is determined. A resource configuration file and an inference service interface of the to-be-deployed model are generated according to the inference service resource, if the inference parameter value is greater than or equal to a preset inference parameter threshold.

Abstract: An exclusive agent pool allocation method including collecting business data of agents; grouping agents according to the business data of the agents and forming multiple exclusive agent pools; calculating business skill values of agents according to the business data of the agents and classifying priorities of the agents; classifying priorities of agent pools according to the business data of the exclusive agent pools; and allocating calling user to the corresponding agent in the exclusive agent pool according to predetermined allocation strategy. The method solves the matching of the user and the agent in the region and the business level, allocates the agent resource according to the priority of the business skill, realizes the high match between the business skill of the agent and the business handled by the user, improves the pertinence and effectiveness of the agent service and promotes the satisfaction of the users.

Abstract: A method for topic early warning includes: acquiring a self-defined keyword; calculating similarity between the self-defined keyword and each word in a corpus, and acquiring extended keywords related to the self-defined keyword from the corpus according to the similarity; selecting a target keyword from the extended keywords according to a type of the extended keywords and similarity between the extended keywords and the self-defined keyword, and adding the target keyword to a target keyword list; performing real-time monitoring according to the target keyword in the target keyword list; and performing topic early warning when it is monitored that the number of topics corresponding to the target keyword reaches a preset threshold.

Abstract: A method of scanning website vulnerability comprising: reading a vulnerability scan task in a scan task pool; finding a website corresponding to the vulnerability scan task, acquiring access data of the website, and obtaining a popularity coefficient of the website according to the access data; acquiring historical vulnerability scan data and a vulnerability risk level table, and obtaining a security risk coefficient of the vulnerability scan task according to the historical vulnerability scan data and the vulnerability risk level table; acquiring update time data of the vulnerability scan task, and calculating a time coefficient of the vulnerability scan task according to the update time data; inputting the popularity coefficient, the security risk coefficient, and the time coefficient into a preset priority evaluation model for processing, and obtaining an execution priority weight of the vulnerability scan task; and executing vulnerability scan tasks in the scan task pool in descending order according to t

Abstract: An environment monitoring method and an electronic device are provided, the method divides the satellite image into a plurality of first divided images with overlapping areas, a first multi-dimensional feature map is obtained by inputting the plurality of first divided images into an environment monitoring model, the environmental monitoring model fully combines the correlation between the environmental information of different dimensions, the environmental features of a plurality of different dimensions are correlated through an association network. By utilizing the environment monitoring method, a large area of the environment monitoring effectively is realized, and accuracy of environmental detection is improved.

Abstract: A method of page displaying includes: obtaining page data of a current page of an application; the page data includes a screenshot and view identifiers and view names of a plurality of views; adding the plurality of view identifiers to a plurality of arrays having different levels according to a preset rule; building a multi-fork tree corresponding to the current page of the application using the array; generating hierarchical paths corresponding to the plurality of views according to the multi-fork tree, adding corresponding burial point frames to the corresponding views according to the hierarchical path, and transmitting the screenshot provided with burial point frames to the preset terminal, so that the preset terminal displays the screenshot with burial point frames.

Abstract: A deep learning based license plate identification method, device, equipment, and storage medium. The deep learning based license plate identification method comprises: extracting features of an original captured image by using a single shot multi-box detector to obtain a target license plate image; correcting the target license plate image to obtain a corrected license plate image; identifying the corrected license plate image by using a bi-directional long short-term memory model to obtain target license plate information. When the deep learning based license plate identification method performs license plate identification, the identification efficiency is high and the accuracy is higher.

Abstract: A speaker acquires audio data and performing processing. Audio features of the audio data are extracted. The audio features are inputted into a preset neural network model for training to obtain vector features. A first similarity value between a first vector feature and a second vector feature of a first speaker and a second similarity value between the first vector feature and a third vector feature of a second speaker are calculated. A loss function value is calculated and when is less than or equal to a preset loss function threshold, a training process of the speaker separation model is ended and parameters are updated. A two-speaker separation method, a terminal, and a storage medium are disclosed. Feature extraction capabilities of the model are enhanced, and accuracy of separation between speakers is improved, especially in long meetings and conversations.

Abstract: A cultivated land recognition method in a satellite image includes: segmenting a satellite image of the Earth into a plurality of standard images; and recognizing cultivated land area in each of the standard images using a cultivated land recognition model to obtain a plurality of first images. Edges of ground level entities in each of the standard images are detected using an edge detection model to obtain a plurality of second images. Each of the first images and a corresponding one of the second images is merged to obtain a plurality of third images; and cultivated land images is obtained by segmenting each of the third images using a watershed segmentation algorithm. Not only can a result of recognizing cultivated land in satellite images of the Earth be improved, but an efficiency of recognizing the cultivated land also be improved. A computing device employing the method is also disclosed.

Abstract: A data transmission method, including: acquiring business data to be uploaded which arc sent from a plurality of organizations; respectively checking whether or not the business data to be uploaded arc complete; acquiring business identifiers carried in the business data to be uploaded from organizations whose data are reviewed to be complete; performing first grouping on the business data to be uploaded from the organizations whose data arc reviewed to be complete, in accordance with the business identifiers; determining data size of the business data to be uploaded and acquiring a data size of each group after the first grouping; performing second grouping on a grouping result of the first grouping; and uploading the business data to be uploaded from the organizations whose data are reviewed to be complete in accordance with a grouping result of the second grouping.

Abstract: A method includes: obtaining a plurality of clinical red blood cell images, dividing red blood cells of different shapes at different positions in each of the red blood cell images into a plurality of submasks, and synthesizing the submasks corresponding to each of the red blood cell images to generate one mask to obtain a plurality of masks corresponding to the red blood cell images; collecting shape data of a plurality of red blood cells from the masks to obtain a training data set, calculating a segmentation boundary of each red blood cell in the training data set, and establishing a red blood cell shape data set based on the segmentation boundary of each red blood cell; collecting distribution data of each red blood cell in the red blood cell shape data set; and synthesizing the red blood cell shape data set into a plurality of red blood cell images.

Abstract: Systems and methods for characterizing a region of interest (ROI) in a medical image are provided. An exemplary system may include a memory storing instructions and at least one processor communicatively coupled to the memory to execute the instructions which, when executed by the processor, may cause the processor to perform operations. The operations may include detecting one or more candidate ROIs from the medical image using a three-dimensional (3D) machine learning network. The operations may also include determining a key slice for each candidate ROI. The operations may further include selecting a primary ROI from the one or more candidate ROIs based on the respective key slices. In addition, the operations may include classifying the primary ROI into one of a plurality of categories using a texture-based classifier based on the key slice corresponding to the primary ROI.

Abstract: The disclosure relates to a method of optimizing a database system, including: snapshotting performance data of each Structured Query Language sentence of the database system every preset first time, and arranging and storing snapshots according to a time sequence, wherein the performance data include the number of times of executions and a buffer gets data volume; correspondingly carrying out variance calculation on the performance data of the current snapshot and the performance data of the former snapshot respectively to calculate a total buffer gets data volume and a single-execution buffer gets data average volume which correspond to each SQL sentence within the preset first time; obtaining a value sum of the total buffer gets data volume and the single-execution buffer gets data average volume of each SQL sentence, and selecting an SQL sentence to be optimized on the basis of the value sum.

Abstract: A data storage method includes: acquiring target data to be stored, and classifying refresh rates of the target data to be stored according to a front-end system; subjecting the target data to be stored with high refresh rates as classified and the target data to be stored with low refresh rates as classified to a Hash calculation to obtain a first type Hash value and a second type Hash value; determining storage data segments corresponding to the first type Hash value and the second type Hash value according to a preset storage data segment determination relationship, and storing the target data to be stored with high refresh rates and the target data to be stored with low refresh rates into the storage data segments corresponding to the first type Hash value and the second type Hash value, respectively.