24 results about "Local call" patented technology

A system for an automated real-time fraud detection based on predictive analytics of call data including a processor of a call analysis server (CAS) node configured to host a machine learning (ML) module and connected to at least one user-entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: capture user call data including a plurality of key elements from the at least one user-entity node; parse the user call data to extract a plurality of classifying features based on the plurality of key elements; query a local calls database to retrieve local historical calls-related data based on the plurality of classifying features; generate at least one feature vector based on the plurality of classifying features and the local historical calls-related data; provide the at least one feature vector to the ML module coupled to an Artificial Neural Network (ANN); receive a plurality of user call ranking parameters from a call predictive model generated by the ML module using outputs of the ANN based on the feature vector; and generate a fraud verdict for the user call based on the plurality of call ranking parameters.

The invention provides a cutting head control system and method for ultra-precise high-power laser cutting equipment, and relates to the technical field of metal cutting, and the system comprises a workpiece screening module which screens and integrates multiple workpiece combinations produced in the same batch from a production task pool; the quota setting module is used for presetting production quota characteristics and a quota deviation range; the local calling module is used for calling design information of the workpiece and a cutting laser power interval; the nesting arrangement module is used for optimizing special-shaped nesting arrangement according to the workpiece design information to obtain target special-shaped nesting arrangement; the path optimizing module is used for optimizing a cutting path and positioning a target cutting path and a control sequence; and the cutting control module cooperatively controls the cutting head to execute cutting production. According to the method, the technical problems of low material utilization rate and poor cutting efficiency in the metal cutting process due to lack of integrated modeling of multi-workpiece mixed arrangement and cutting parameter collaborative optimization in the prior art are solved, and the metal cutting flexible production capacity and the material utilization rate are improved.

The invention discloses an enterprise data intelligent processing method and system based on cloud edge collaboration, and relates to the technical field of cloud computing, and the method comprises the steps: collecting a plurality of data collection sources of a target enterprise; analyzing local data call transmission scenes of the plurality of data collection sources to establish a plurality of local call relationship networks; analyzing a local calling demand according to the local calling relation network, planning an edge end data processing path, and generating the edge end data processing path; and finally, analyzing a cloud joint calling demand, and based on the edge end data processing path, executing data processing path planning from the edge end to the cloud to obtain an edge-cloud data processing path plan. According to the method and the device, the technical problems that data processing paths are disordered and resources are wasted due to the fact that the enterprise data cannot adapt to multi-source data differentiation processing requirements in local and cloud cooperative processing are solved, and the technical effects of adapting to the enterprise multi-source data differentiation processing requirements and realizing efficient enterprise data processing and data value conversion are achieved.

The application discloses a function-level defect positioning method based on a call graph and multi-level contrast learning, comprising constructing a local call graph containing class nodes and internal function nodes and a global call graph covering all functions; using Light-GCN to perform graph embedding learning on the two kinds of call graphs to generate local and global embedding vectors of the functions; meanwhile, a pre-trained code model is used to extract semantic embedding vectors of function codes, and a pre-trained language model is used to obtain semantic embedding vectors of defect reports; in order to optimize the model performance, a multi-level contrast loss function containing local contrast loss, global contrast loss and semantic contrast loss is designed, the matching relationship between the defect reports and the function embedding is effectively optimized by minimizing the loss function, so that the overall positioning capability is enhanced, and the defect positioning accuracy of the model is significantly improved.

The invention discloses a multi-agent collaborative calling method and system based on knowledge graph association, and relates to the technical field of data processing, and the method comprises the steps: carrying out semantic analysis on a task original demand text to extract a task feature vector; then a multi-agent semantic knowledge graph is called for matching, a target agent set is recognized, and a local calling sub-graph is constructed; then, the initial association weights of the sub-graphs are dynamically corrected based on the task feature vectors, and a real-time association matrix is obtained; then quantizing cooperation priority and dependence intensity, executing redundancy elimination based on semantic projection gradient, and generating a calling sequence in combination with a bottom layer physical load state; and finally, acquiring real-time physical load and resource occupation conditions during execution, executing conflict scheduling based on the dynamic access quota model, and issuing an adjustment instruction. The method has the advantages of accurate collaboration, dynamic self-adaption and good calling effect.

The invention discloses an interface calling path identification method and device, electronic equipment and a storage medium. The method comprises the steps that interface flow data of a target monitoring system is acquired, and the target monitoring system comprises multiple target services; determining request feature data corresponding to each request response data packet; dividing the interface traffic data according to the request feature data to obtain a plurality of traffic data blocks, each traffic data block corresponding to one business operation of one target business; for each traffic data block, determining a local calling path corresponding to the traffic data block according to the request feature data; and determining a service calling path corresponding to each target service of the target monitoring system according to the local calling path and the request feature data. Based on the technical scheme, automatic identification of the interface calling path can be realized, and the interface path identification efficiency is improved; and the interface calling path is constructed in a flow data division mode, so that the accuracy of the construction of the interface calling path is improved.

The invention discloses a micro-service merging deployment method and system based on self-adaptive routing of a Feign client, and the method comprises the steps: S100, extracting detailed metadata of each interface method at the last stage of Spring Boot application starting, and registering the detailed metadata in a mapping registry; s200, when a Feign client interface is called, the Feign client interface is captured and intercepted by a dynamic proxy mechanism of the Feign; s300, analyzing target information of the current Feign request, extracting a URL path to be called and an HTTP method, and selecting a calling method; s400, after it is determined that the local call is executed, a Spring Security security authentication object is constructed; s500, matching and converting the parameter list and the parameter list of the target controller method, and directly calling the target controller method in the current process; and S600, after the local method is executed, obtaining a return result, translating the return result into a return type declared by the Feign client interface, and returning the return type to the business code which initially initiates the call along the original path. And the process can be efficiently called without depending on an external service registration center.

The invention discloses a micro-service calling method, device and equipment based on aggregation type deployment. The method comprises the following steps: responding to a local calling request of a local micro-service in a local virtual machine for a second micro-service, reading whether a second package name where a second micro-service is located is configured in an annotation of starting an aggregation service calling client of the local micro-service through an aggregation service calling register used by an application program entry class of the local micro-service; wherein at least two micro-services are deployed in the virtual machine in an aggregation manner; each micro-service is provided with a client of the micro-service; and returning corresponding information according to whether the second package name is configured in the annotation of calling the client by starting the aggregation service. According to the embodiment of the invention, the requirements of micro-service deployment under different conditions can be met by setting the corresponding micro-service calling logic, and aggregation type deployment and independent deployment of the micro-service are considered.

This application relates to the field of simulation and testing technology, and in particular to a remote CAN simulation system and method. The system includes: a first terminal and a second terminal connected via Ethernet; the second terminal accesses the system to be simulated via a CAN bus or CANFD bus. The first terminal receives remote command parameters input from an external source, packages the remote command parameters based on a preset protocol to obtain a message body to be sent, and sends the message body to the second terminal. The second terminal receives the message body to be sent, parses it into a local call instruction, and calls the SocketCAN function according to the local call instruction to complete data interaction with the bus of the system to be simulated. This system provides a highly versatile remote CAN simulation architecture, which helps reduce system usage costs and facilitates deployment.

The invention relates to a table connection method and device and computer equipment, and belongs to the technical field of data processing.The method comprises the steps that in response to a table connection processing request for a first data table and a second data table, a first occupied memory of the first data table and a second occupied memory of the second data table are determined; and determining the target local shared memory pool according to the minimum occupied memory between the first occupied memory and the second occupied memory. And sending the data table corresponding to the minimum occupied memory to the target local memory shared pool, so that each computing node calls the data table corresponding to the minimum occupied memory from the target local memory shared pool, and executes a table connection operation for the first data table and the second data table. On the basis of the table connection establishment method and device, the network bandwidth occupied by data table transmission during table connection establishment is effectively saved, and due to the fact that each computing node can acquire the data table corresponding to the minimum occupied memory in a local calling mode, the table connection establishment efficiency is effectively improved.

The invention discloses an incoming call processing method and device, and belongs to the technical field of communication. The method comprises the following steps: when a non-white-list incoming call is received, answering the non-white-list incoming call by a local call model to obtain first call data; analyzing the first call data through the local call model, and determining a first incoming call type; the local call model is obtained by training according to a plurality of training data, and the training data comprises historical call data and an incoming call type label which are associated with each other; and when the first incoming call type is consistent with the shielded incoming call type, hanging up the non-white list incoming call.

The present invention discloses a microservice calling method, apparatus, and device based on aggregated deployment. The method comprises: responding to a local call request from a local microservice to a second microservice in a local virtual machine, reading, through the aggregated service call registrar used by the application entry class of the local microservice, whether the second package name of the second microservice is configured in the annotation of enabling aggregated service call client of the local microservice; wherein, at least two microservices are aggregated deployed in the virtual machine; each of the microservices has its own client; and returning corresponding information based on whether the second package name is configured in the annotation of enabling aggregated service call client. The embodiment of the present invention can adapt to the needs of microservice deployment in different situations by setting corresponding microservice call logic, taking into account both aggregated deployment and individual deployment of microservices.

The invention discloses a voice communication method and device, equipment, a storage medium and a product, and relates to the technical field of voice communication, and the voice communication method comprises the steps: determining a target virtual machine for executing a corresponding voice communication based on a local communication center service when a voice communication request initiated by a channel side is received, and executing a corresponding voice communication based on a voice proxy service. And acquiring a voice call event generated by the voice call service in the voice call process, and sending a corresponding call control instruction to the voice call service based on the voice proxy service and the voice call event so as to control the voice call. The conversation and conversation control are carried out by the service deployed on the virtual machine, and the channel party only needs to initiate the conversation to the voice conversation platform to realize the voice conversation and conversation control, so that the conversation in the mode does not need to consume relatively high cost to construct and maintain the voice conversation platform, and the conversation efficiency is improved. Therefore, the cost of voice communication is reduced.

The application provides a cutting head control system and method of an ultra-precision high-power laser cutting device, and relates to the technical field of metal cutting. The system comprises: a workpiece screening module that screens a plurality of workpiece combinations integrated in the same batch of production from a production task pool; a quota setting module that presets production quota characteristics and quota deviation ranges; a local calling module that calls design information of the workpieces and a cutting laser power interval; a nested arrangement module that optimizes irregular nested arrangement based on the design information of the workpieces to obtain a target irregular nested arrangement; a path optimization module that performs cutting path optimization to locate a target cutting path and a control sequence; and a cutting control module that cooperatively controls the cutting head to perform cutting production. The application solves the technical problem of low material utilization and poor cutting efficiency in the metal cutting process caused by the lack of integrated modeling of multi-workpiece mixed arrangement and cutting parameter collaborative optimization in the prior art, and improves the flexible production capacity and material utilization of metal cutting.

The invention relates to a call center intelligent telephone traffic distribution scheduling method and device, equipment and a medium. The method comprises the following steps: acquiring session metadata collected by a local call center system, performing standardized desensitization processing on the session metadata, and standardizing the session metadata into an inbound event in combination with meta-information of each call center system; performing session intention extraction, service complexity scoring and customer value estimation on the inbound event to obtain an enhanced interaction file; generating a candidate micro-queue list according to the enhanced interaction file and each system state snapshot, and performing expected cost estimation on each candidate micro-queue in the candidate micro-queue list to obtain an expected cost score corresponding to each candidate micro-queue; and based on the service constraint, solving according to the candidate microqueue list and the expected cost score thereof to obtain a scheduling decision, and initiating a resource reservation request to a target call center system pointed by the scheduling decision to obtain a resource reservation token and a transfer token. By adopting the method, the scheduling waiting time and the switching failure rate can be reduced.

This invention belongs to the field of software refactoring and serverless computing technology, specifically relating to a fine-grained service decomposition and dynamic deployment method for object-oriented applications in edge environments. By constructing a method call graph through static analysis, and for the first time applying a hybrid heuristic algorithm combining particle swarm optimization and genetic operators to this graph partitioning problem, it can intelligently find a decomposition scheme that minimizes cross-function communication overhead while satisfying the limited resource constraints of edge nodes. This fundamentally solves the contradiction between computing resources and communication latency that traditional decomposition methods struggle to balance. Furthermore, by introducing Function-as-a-Service (FaaS) proxies and wrappers, it achieves automated refactoring of the original object-oriented code, enabling seamless migration of tightly coupled local calls to a distributed FaaS environment. This significantly reduces the technical threshold and operational complexity of application migration, achieving fine-grained resource utilization and elastic scaling.

The invention discloses a calling method and device for machine tool communication drivers and electronic equipment, and relates to the technical field of communication, and the method comprises the steps: packaging each machine tool communication driver based on a development language of each machine tool communication driver in L machine tool communication drivers, obtaining a dynamic link library file / remote calling service corresponding to each machine tool communication drive; creating a local calling module corresponding to the dynamic link library file and a remote calling client corresponding to the remote calling service; creating an adapter corresponding to the local calling module and an adapter corresponding to the remote calling client to obtain M adapters; and controlling the target system, and calling the L machine tool communication drives based on the adapter interfaces corresponding to the M adapters. The technical problems of low communication efficiency and high communication cost when an upper-layer system calls a machine tool communication drive based on the prior art are solved.

The invention discloses a cross-programming language function call implementation method and device and a medium. The method comprises the steps that a function call request is sent to a webpage side; obtaining an execution result of the webpage end; and converting the object identifier in the execution result into a local object according to a preset function library, converting the target format data into a local data type to obtain a conversion result, and feeding back the conversion result to a local calling party. According to the cross-programming language function call implementation method and device and the medium, by unifying call parameters and interface definitions, positioning and executing functions by means of a preset object or a class matching mechanism, and converting result data by means of a preset function library, a cross-language function call link is opened in the whole process, and the cross-programming language function call efficiency is improved. The workload of adaptive development and compatibility testing is reduced, and the problem that the development and testing cost is high due to the fact that function-level cross-language calling between a local program developed by different programming languages and a network end program is difficult to achieve can be solved.

The invention provides a privacy set intersection method and device, a storage medium and a program product, relates to the technical field of computers, and is used for reducing the leakage risk of data in the transmission and processing process and improving the accuracy of an intersection result. The method comprises the following steps: receiving a filter sent by verification equipment; confusing the local call data of the matching device to obtain a confused data set, and sending the confused data set to the verification device to enable the verification device to encrypt the confused data set; receiving an encrypted confusion data set sent by the verification equipment; and matching with the encrypted confusion data set based on a filter to obtain a privacy data intersection.

The invention discloses an information leakage static detection method and system for a Springboot application, and belongs to the field of network technologies and security, and the method comprises the steps: analyzing a Jar file generated by the Springboot application, and converting a byte code into a Jimple intermediate code representation form; configuring a sensitive information source and an information leakage point; traversing and scanning all classes with Spring annotations, and searching entry classes in which sensitive information sources possibly exist; all interface methods in the entry class are scanned, if sensitive information exists in acquisition parameters of an interface method i, the interface method i serves as the entry method, a local call graph of the entry method is established, and data flow analysis is conducted on the sensitive information of the entry method; wherein in the data flow analysis process, whether the sensitive information flows into the information leakage point or not is identified, if the sensitive information flows into the information leakage point, the sensitive information is leaked, and the current flowing-in information leakage point is the information leakage position. The method is suitable for leakage static detection of the Springboot application, and is high in expandability, low in memory resource consumption and short in analysis time.

The application discloses an enterprise data intelligent processing method and system based on cloud edge cooperation, relates to the technical field of cloud computing, and comprises the following steps: collecting a plurality of data collection sources of a target enterprise; analyzing local data calling transmission scenes of the plurality of data collection sources to establish a plurality of local calling relationship networks; then analyzing local calling demands and planning edge end data processing paths according to the local calling relationship networks, and generating the edge end data processing paths; finally analyzing cloud end joint calling demands, taking the edge end data processing paths as the basis, executing edge end to cloud end data processing path planning, and obtaining edge-cloud end data processing path planning. The application solves the technical problem that enterprise data cannot adapt to differentiated processing demands of multi-source data in local and cloud end cooperative processing, leading to disordered data processing paths and resource waste, and achieves the technical effects of adapting to differentiated processing demands of multi-source data of enterprises, realizing efficient processing of enterprise data and data value conversion.

The invention discloses a local conference recursive cascade creation method of an SIP protocol, and the method comprises the steps: employing an inter-device recursive mode, achieving a distributed sub-conference system, and achieving the connection between a newly-added end device and a last end device through collecting SDP information reserved by the newly-added end device; a host is adopted to record equipment information of newly-added end equipment and reserved SDP information, recursive conference creation and management are achieved, and host invitation, control of mute and transfer by the host, self-exit of an intermediate member, removal of an administrator and host exit events are supported; compatibility of nearest direct connection equipment is adopted, and codec of different call connections is mixed. The method solves the problem that a single device cannot establish too many local calls.

The embodiment of the invention discloses a call processing method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of RTT calls. The method is applied to communication equipment, and the communication equipment supports real-time text RTT communication. The method comprises the following steps: starting an asynchronous call mode when detecting that opposite-end call equipment corresponding to the call equipment does not support the RTT call; in the asynchronous call mode, acquiring a first text input by a user on an RTT interface, converting the first text into a first voice, and sending the first voice to the opposite-end call device; and obtaining a second voice sent by the opposite-end call device, converting the second voice into a second text, and displaying the second text on the RTT interface. Thus, according to the scheme, when the opposite-end call device does not support the RTT function, it can still be ensured that a user of the call device of the home terminal obtains effective real-time text interaction experience.

The invention relates to a ransomware detection method based on a graph size model, which comprises the following steps: an API calling behavior feature extraction stage used for constructing an API calling graph, extracting a frequent sequence and generating API function description; the global call mode learning stage is used for learning global structure information of an API call graph through a graph neural network, capturing overall behavior characteristics of a ransomware sample, and obtaining a global call mode of the sample; the local call mode learning stage is used for learning a frequent call sequence through a large language model, understanding the most critical local frequent behavior of the ransomware sample and obtaining a local call mode of the sample; and the multi-scale information fusion stage is used for splicing the vector representations of the global calling mode and the local calling mode of the ransomware sample, inputting the spliced vector representations to a multi-layer perceptron for classification, and outputting a ransomware detection result. Compared with the prior art, the method has the advantages that the ransomware can be accurately identified, and the generalization detection capability on the novel ransomware is improved.