1965 results about "Process information" patented technology

The present invention is directed to systems and methods for monitoring activities in an aviation environment. The system includes at least two monitoring units, each including at least two types of sensors, wherein: the sensors are mounted at a plurality of locations in the aviation environment. The system further includes a processing system being configured to receive said information from the sensors, to process said information to monitor and make predictions, and to combine sensor information by applying data fusion. The system is further configured to compare sensor information with predetermined safety operation criteria, and to generate an alert signal. The method of the invention includes obtaining sensor information, receiving said information from the sensors at a processing system, processing said information, comparing the processed information with predetermined safety operation criteria, and generating an alert signal.

Systems, methods, and computer program products for using artificial intelligence (AI) models, machine learning, and large language models to identify root causes of issues in a computing environment where multiple applications and computing devices operate. One or more AI models may determine adverse trends from one or more issue metrics, where an issue metric corresponds to issues occurring in a computing system. The AI models may identify issues corresponding to the adverse trends. From the identified issues, the AI models may determine root causes from the issues and the impacted area information and process information from the issues. From the issues and the impacted area information and process information from the issues the AI models may determine recommendations for rectifying the issues. The relations between the root causes, the impacted area information, the process information, and the issues may be formatted and displayed as a traversable network graph.

The invention relates to the technical field of nondestructive testing, and particularly discloses an automatic detection system and method based on a titanium plate welding part, and the method comprises the steps: obtaining an original physical field signal of a to-be-detected part under the excitation of a single energy field, and extracting a space energy attenuation gradient and time phase lag distribution through wavelet packet decomposition and Hilbert transform; constructing a dynamic propagation model for describing a signal propagation path evolution rule, and performing space-time registration and vector difference calculation with a preset ideal reference model to generate a difference evolution graph; high-dimensional topological feature mapping, density clustering and multi-scale persistence analysis are carried out on the atlas, and a stable abnormal mode caused by defects is identified and confirmed; and backtracking a dynamic evolution path of an abnormal mode, extracting defect core parameters, and completing three-dimensional positioning, type classification and security level evaluation in combination with process information.

The invention relates to an automatic control method and system for milling cutter machining, and the method comprises the steps: obtaining geometric feature data and technological parameter information of a milling cutter, and carrying out the machining analysis of the geometric feature data based on the technological parameter information, and obtaining the corresponding original machining flow information; acquiring machining flow sensing data of the milling cutter, and performing state association on the machining flow sensing data and the original machining flow information to obtain a corresponding real-time machining state group; real-time cutting parameters of the milling cutter are obtained, machining prediction is conducted on the original machining process information according to the real-time cutting parameters, and a corresponding machining quality trend is obtained; performing intelligent control optimization on the real-time processing state group and the processing quality trend to obtain a corresponding initial control scheme; and performing global parameter optimization on the initial control scheme according to the compensation control parameters to obtain a corresponding global processing optimization scheme. According to the invention, the real-time processing state group and the processing quality trend can be intelligently controlled and optimized.

The invention discloses an information resource efficient collaborative optimization method for a distributed computer system, which belongs to the technical field of information resource optimization control and comprises the following steps: executing a transaction according to a target lock element information set, monitoring popularity information of each resource segment, generating self-adaptive lock granularity decision information of each resource segment, and executing dynamic adjustment of lock granularity. And obtaining load sensing optimization parameters to complete lock competition optimization, and completing real-time iterative updating of lock element information and strategies. According to the method, the problems of resource competition and deadlock in the distributed system can be effectively solved, and the system performance and the resource utilization efficiency are improved. Transaction pre-allocation resources are reasonably allocated, the deadlock risk is reduced, lock granularity is dynamically adjusted according to resource segmentation popularity, lock competition optimization is completed based on load awareness optimization parameters, an adjustment result and the optimization parameters are synchronized to a distributed lock management library for real-time iteration updating, and it is ensured that a system always operates with an optimal strategy; and the distributed computer system efficiently and stably processes information resources in a cooperative manner.

The invention provides a fan full life cycle archive management system and a management method thereof, and the system comprises an Internet of Things data collection module which is installed on a key part of a wind turbine generator set and collects vibration, temperature and stress data; the full-life-cycle digital archive management module is used for recording full-process information of the fan from design to operation and maintenance based on a cloud database and a block chain technology, and ensuring data integrity and traceability; the AI predictive maintenance analysis module analyzes data and predicts faults by using deep learning and machine learning algorithms; the intelligent scheduling and maintenance decision support module is used for generating an optimal maintenance plan in combination with external factors; and the responsibility tracing and process optimization module is used for recording maintenance details to optimize the process and spare part management. The management method comprises the steps of data acquisition, storage, analysis, maintenance plan making, task execution and recording, effect evaluation, process optimization and the like. Through cooperative work of all the modules and implementation of the system method, accurate and efficient full-life-cycle management of the draught fan is achieved.

The invention discloses a good product visual identification method and system, a medium and a program product, and relates to the field of image data processing, and the method comprises the steps: determining the detection type of a to-be-traced product; the method comprises the following steps: when a process detection request is requested, acquiring abnormal process information for triggering detection, calculating a process correlation degree between each completed process and the abnormal process, and generating a to-be-detected sequence; in a final inspection request, extracting defect feature data of a to-be-traced product, determining an associated process set from the process flow database, and sequencing to generate a to-be-detected sequence; sequentially acquiring to-be-detected process images of each process ranked in the front from the to-be-detected sequence, and inputting the to-be-detected process images into a parallel detection channel for detection; when the result of the parallel detection channel is passing, updating the to-be-detected sequence, and obtaining a first process image for detection; and when the result of the parallel detection channel is abnormal, determining an abnormal process and stopping the detection. By implementing the method, the problem positioning efficiency based on visual identification can be improved.

The present application relates to the field of behavior recognition technology, and discloses a behavior recognition method, device, equipment, storage medium and computer program product, including: obtaining multi-source heterogeneous data collected by a multimodal sensor network, and performing spatiotemporal synchronization and fusion processing on the multi-source heterogeneous data based on a spatiotemporal synchronization algorithm to obtain target comprehensive data; extracting low-dimensional feature vectors from the target comprehensive data, and combining the attention mechanism to perform time series modeling on the low-dimensional feature vectors to construct a behavior dynamic model; performing behavior recognition on the real-time collected operation process information according to the behavior dynamic model, and outputting the personnel behavior category. By integrating multi-source heterogeneous data in the complex environment of the power plant, and accurately extracting key features, and capturing the dynamic change laws of behavior and state, the model can accurately distinguish various types of personnel behaviors under normal operating procedures or complex and changeable working conditions, and realizes real-time and accurate recognition of violations and abnormal behaviors in power plant operations.

The invention provides an intelligent production scheduling system and method for a coal industry scene, and the method comprises the steps: fusing multi-source production information (including equipment state information, coal quality index information and safety detection information) through a server, constructing a fault prediction model, and carrying out the fault prediction of the real-time production information; and generating a task list based on the fault prediction result, the real-time production information and the historical production information, matching a workflow and an optimal executor for each task in the task list, then sending the task to the PC terminal for execution, monitoring the execution progress of each task in real time, and urging the overdue task. And generating a corresponding report for each executed task based on the fused information, the fault prediction result, the real-time production information, the historical production information and the execution process information of each task, and sending the report to a display device for display. By adopting the method, the efficiency and the accuracy of production scheduling in a coal industry scene can be improved, the real-time performance of production scheduling can be ensured, and the statistics and the checking of the whole process link can be facilitated.

The invention relates to an intelligent planning method for an assembly sequence of a high-loading-density aviation equipment product. The intelligent planning method solves the problems that the efficiency is low and errors are prone to occurring when the assembly sequence is manually formulated. Comprising the following steps: Step 1: establishing an extraction method and a standardized expression method of three types of object information of parts, an assembly process and assembly constraints in a process information model, and forming an assembly process information model integrating a product structure, an assembly process, an assembly tool and the like; 2, related assembly process knowledge and resources are carded, an interference matrix, a connection matrix and a support matrix are formed to serve as input and constraint conditions of assembly sequence planning, an assembly sequence solving space is formed, an assembly sequence planning mathematical model is finally formed, and an assembly sequence candidate set is generated; step 3, carrying out the construction of an assembly sequence evaluation index; designing an assembly sequence evaluation index calculation mode, constructing an assembly sequence evaluation index calculation method, establishing a multi-criterion assembly sequence optimization method, and supporting acquisition of an optimal assembly sequence.

Provided in the present disclosure are a memory mechanism-based information processing method, an electronic device and a storage medium. The method comprises: acquiring information to be processed corresponding to a target user; searching in memory banks corresponding to the target user for knowledge related to said information, so as to use the searched knowledge to obtain a processing result corresponding to said information, the memory banks comprising a long-term memory bank and a short-term memory bank; if the used knowledge is knowledge in the short-term memory bank, recording a use behavior for the knowledge, the short-term memory bank being used for temporarily storing knowledge related to the target user, and when a use behavior corresponding to any knowledge in the short-term memory bank meets a preset condition, storing the knowledge meeting the preset condition into the long-term memory bank. The present disclosure can achieve hierarchical storage of memory, and simulate the memory mechanism of the real world to process information to be processed of users, thus improving the effect of interacting with the users, and improving the user experience.

The invention discloses a transmission method and device, Internet of Things equipment and electronic equipment, and belongs to the technical field of communication, and the transmission method comprises the steps that target Internet of Things equipment receives a first downlink message sent by first equipment, and the first downlink message is used for indicating at least one piece of Internet of Things equipment to initiate a random access process; wherein the first downlink message comprises at least one of the following items: identification information of the at least one piece of Internet of Things equipment; a cause is paged; accessing process information; transmitting data information; the access resource configuration information of the target Internet of Things device; time control information; the retransmission resource configuration information of the target Internet of Things device; the security information is used for carrying out authentication on the target Internet of Things equipment and carrying out encryption or decryption on transmission data; and a first indication, wherein the first indication is used for indicating the backoff time of data retransmission of the target Internet of Things equipment.

The invention relates to the technical field of artificial intelligence and material engineering, and discloses a formula optimization method and device, equipment and a storage medium, and the method comprises the steps: carrying out the knowledge extraction of an obtained structured formula data set and unstructured technical literature data in response to a formula optimization target input by a user, and generating a table literature knowledge set; inputting the table literature knowledge set and the formula optimization target into a large language model to obtain a generated text corresponding to the formula optimization target; performing logic rule screening and risk assessment on the generated text through a knowledge fusion layer to obtain text output conforming to a confidence threshold, and generating a new formula scheme according to the text output; and performing multi-objective optimization on the new formula scheme based on a preset experimental cost constraint condition, and outputting an optimized recommended formula and a support evidence chain. By automatically fusing innovative components and process information in literatures, the output recommended formula has scientific basis and interpretability, and the practicability and innovativeness of an automatic formula are improved.

The invention discloses a digestive endoscope disinfection process full-cycle monitoring and compliance verification platform and method, and the platform comprises a data collection and preprocessing module which is used for collecting and preprocessing real-time state data and environment data, and generating a standardized data set; the path optimization and decision module is used for simulating a plurality of operation paths of a disinfection process by utilizing a Monte Carlo tree search algorithm and selecting an optimal disinfection path; the compliance reasoning and verification module is used for reasoning symbol rules in the disinfection process; the block chain evidence storage module is used for writing the data blocks into a block chain account book to form a disinfection data chain; the intelligent contract processing module is used for performing real-time judgment, automatically triggering an alarm and recording non-compliance operation; and the feedback and query module is used for querying, retrieving and auditing the whole-process information, alarm records and compliance events of the disinfection process. According to the invention, intelligent optimization of the disinfection process, real-time compliance verification and on-chain evidence storage are realized, and the safety supervision efficiency is comprehensively improved.

The present application provides a large language model-based query statement generation method, apparatus, and device, and a medium. The large language model comprises a plurality of encoders. The method comprises: acquiring a query text; performing vectorization processing on the query text to obtain a target vector representation corresponding to the query text; inputting the target vector representation into the plurality of encoders, to perform encoding processing on the target vector representation by means of weight matrices of the encoders, so as to obtain context vectors corresponding to the encoders, wherein different encoders have different weight matrices; and generating a target query statement on the basis of the context vectors corresponding to the encoders. A model is allowed to focus on different information features in different attention heads, independently capture different aspects of a query text, and process information at multiple abstraction levels, thereby better capturing complex and abstract semantic relationships, effectively distinguishing the importance of information when processing complex and fuzzy questions, improving the accuracy of query statement generation.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a data generation method and device based on a non-uniform sampling path, equipment and a medium. Quantizing contribution degree values of all time points based on process information, generating contribution degree distribution of the time points, screening a plurality of key time points, constructing a non-uniform sampling path, and gradually generating target data from initial data by using the path and a flow matching generation model. Through a time point contribution degree analysis mechanism, on the basis of the actual contribution of each time point to the data generation result, the key time points are screened out, and the non-uniform sampling path is constructed, so that the generation quality is ensured, the redundant sampling steps are effectively reduced, the reasoning efficiency of the flow matching generation model is improved, and the calculation resource consumption is reduced; and the method has better practical application value.

The invention relates to the technical field of data processing, can be applied to business system platforms of medical health, financial science and technology and the like, and discloses a payment business processing method based on a process engine, which comprises the following steps: standardizing an input / output interface, packaging business logic into business nodes, and storing the business nodes in a node library. And selecting nodes, configuration information and a connection relationship according to service requirements, and generating a process model. And starting the process engine, and converting the process model to obtain a process instance. And extracting node information and a connection relationship, scheduling node execution, obtaining real-time data, and generating a dynamic adjustment decision. And according to the decision and the real-time data, adjusting a process instance execution path and node parameters, scheduling node execution, completing payment service processing, and storing process instance information in a historical record library. By standardizing the interface, packaging the service nodes, generating the process model and dynamically adjusting the execution path and parameters, the payment service processing is efficiently completed, the flexibility and efficiency are improved, and the process information is convenient to store and trace.

The invention belongs to the technical field of aircraft pipeline assembly, and particularly relates to an on-line detection method and system for the off-board assembly process of a pipeline, and the method comprises the following steps: constructing a tightening control model, and initializing model parameters; adjusting the conduit and the joint to an initial state and applying tightening torque; reading tightening process information in real time and drawing a tightening curve broken line graph; the initial assembly normalization is judged in real time; fitting a linear segment slope kj in real time; the standardability of the assembly process is judged in real time; the tightening torque maximum value Tmax and the tightening angle maximum value Amax are detected in real time; calculating an assembly result in real time; and assembling reliability is detected in real time. According to the invention, an assembling tool with torque acquisition and angle acquisition is utilized to acquire tightening torque and rotation angle in the assembling process, and data information in the tightening process is read in real time. And data information of the tightening process is input into the tightening control model, and meanwhile, external assembly control parameters and boundary parameters of the guide pipe machine are set, so that real-time online detection of the whole assembly process of the guide pipe is realized.

The invention provides a testing method and device, testing equipment, network equipment, a medium and a program product, and is applied to the technical field of testing. The method comprises the following steps: obtaining test requirement information of a to-be-tested scheme, and obtaining test process information obtained by executing the to-be-tested scheme by test execution equipment; analyzing the test process information according to the test requirement information by adopting a multi-modal large model to obtain a test intermediate execution instruction; and sending the test intermediate execution instruction to the test execution equipment for further test execution of the to-be-tested scheme. By adopting the method, the test process analysis in the multi-modal test process is realized by utilizing the analysis and reasoning capability of the multi-modal large model on the multi-modal information, and the test intermediate execution instruction for guiding the test execution is generated according to the test requirement information and is used for executing the subsequent test steps, so that the multi-modal test efficiency is improved under the multi-modal test scene. Automation of the interaction process is tested.

The invention provides a related method of linear motor equipment, the method is applied to industrial conveying, and the method comprises the following steps: creating a plurality of position points, the plurality of position points are distributed along a stator line body, the plurality of position points are used for controlling the moving path of a mover module, and the mover module is used for controlling the moving path of the mover module based on the conveying process information of the mover module. And corresponding dynamic pointing information is configured for each position point, and the dynamic pointing information is used for dynamically indicating a pointing object of the position point according to a conveying condition existing in the transportation scene. According to the method, the dynamic pointing information can be configured for each position point through the conveying process information of the mover module, the function of dynamically adjusting the pointing of the position points is achieved, the position points are used for controlling the moving path of the mover module, and the dynamic adjustment of the pointing of the position points can enable the moving path of the mover module to have variability; the moving flexibility of the mover module is improved, so that the transportation efficiency is improved, and the device is more suitable for complex and changeable working scenes.

A method of processing information related to a distributed item includes generating attachment information and acquiring a reference request and requester information. The attachment information is associated with history information accumulated for the distributed item and is to be distributed along with the distributed item. The reference request is made for a reference to the history information using the attachment information attached to the distributed item. The requester information contains at least location data of a requester terminal that made the reference request.

The invention relates to a notebook software vulnerability scanning method based on a security policy. According to the method, firstly, a security policy library of a target notebook is obtained, and the security policy library comprises access control rules, data operation limiting conditions and vulnerability detection reference requirements for different software types; collecting software running data of the target notebook computer, wherein the software running data comprises current running process information, file system operation records, network connection states and software configuration parameters; performing matching analysis on the software operation data and the security policy library to generate a preliminary scanning result; evaluating the risk level of the software vulnerability according to the preliminary scanning result; and finally, based on the risk level and the repair guide terms in the security policy library, generating software vulnerability repair guide information. Therefore, notebook software vulnerabilities can be scanned comprehensively and accurately, and effective repair guidance is provided.

The invention discloses a production process data management system and method based on process interface custom setting, and belongs to the field of production process data management. The MI process parameter setting module is used for setting parameter information of the process; the MI process interface setting module is used for displaying a parameter name list and a control selection list corresponding to the process, performing interface setting operation on parameter names and generating a control in a canvas area; automatically adjusting the coordinates and the sizes of the plurality of controls according to the generated coordinates and the sizes of the plurality of controls and historical process interface setting information; and the production and manufacturing indication module is used for displaying a process parameter information list on a production and manufacturing indication interface according to the process list, and displaying process parameter interface information in the expansion area according to the parameter information of each process in the process list and the interface setting information. Different types of process information can be displayed on the same interface, and the interaction experience is improved.

An apparatus, including a computer including a database which stores a controllable healthcare record and information contained in a master records file, and a distributed ledger and Blockchain technology system. The apparatus facilitates a video call between a user device and a provider device. The computer, after processing information for updating the controllable healthcare record, processes information for identifying a plurality of electronic records for the individual and a second healthcare provider associated with each electronic record. The computer updates each of the plurality of electronic records, and generates a record update message. The computer transmits the record update message to each of a plurality of second provider devices associated with each second healthcare provider. Information regarding the update to the controllable healthcare record and the update to each of the second records is stored in the distributed ledger and Blockchain technology system.

The invention discloses a software process control and monitoring method and device and electronic equipment. The process information is collected, the management and control strategy is generated and applied to the target client, and a simple and convenient mode is provided for setting the black list and the white list of the process, so that the complexity of manual operation can be reduced, the threshold for configuring the white list is reduced, the management efficiency is improved, and the user experience is improved. And it is ensured that only the software process conforming to the management and control strategy runs on the target client, so that management and control and monitoring of software not conforming to the current application scene are realized. Besides, main running processes are collected to determine black and white lists, and the collected processes are filtered, so that the interference is reduced while the consumption of time and performance during data acquisition is reduced; during matching, according to comprehensive consideration of process names, paths, file attributes and the like, misjudgment is reduced, and the difficulty of disguising as a white list is increased.

The embodiment of the invention provides a retrieval task processing method, system, device and equipment, a medium and a program product, and the retrieval task processing method comprises the following steps: obtaining task data of a target retrieval task, and extracting retrieval key features of the task data; task flow information of the target retrieval task is generated on the basis of the retrieval key features, and the task flow information comprises multiple retrieval processing stages of the target retrieval task and the stage execution sequence of the multiple retrieval processing stages; based on the stage execution sequence, calling a task processing component of each retrieval processing stage to execute the target retrieval task, and determining a stage processing result of each retrieval processing stage; and generating a task processing result of the target retrieval task based on the stage processing result of each retrieval processing stage. Through retrieval key feature driven task flow generation and componentized execution, flexible arrangement and accurate adaptation of a retrieval task processing flow are realized, and the problem of poor adaptability caused by retrieval task flow solidification is solved.

The invention discloses an electric power cross-operation dynamic risk prediction and early warning method, system, equipment and medium based on multi-modal data fusion, and relates to the technical field of intelligent electric power systems, and the method comprises the steps: collecting multi-source data of a cross-operation site in real time, including personnel spatial position data, equipment state data, environmental parameters and operation flow information; performing multi-modal fusion processing on the multi-source data, and constructing space-time risk association features; constructing a dynamic risk factor matrix, performing fusion calculation on the static risk reference value and the dynamic correction value, and dynamically updating the weight of each factor along with time; predicting a risk change trend based on the combination of a time sequence prediction model and a graph structure modeling method; and generating a three-dimensional visual risk thermodynamic diagram based on a prediction result, and triggering a multi-level early warning mechanism when a risk value exceeds a threshold value. The image is reconstructed through multi-modal fusion processing, and key edge features can be recovered in complex environments such as low illumination, high dynamic range and fast motion.

A computer using the systems and methods described herein can use a task agent to automatically select and manage different applications and agents to use to generate results in response to requests for information. The computer can iteratively execute the task agent to generate the results. For instance, the task agent can identify a set of applications to use to generate a result in response to an information request. The task agent can identify the set of applications based on an intent of the information request. The task agent can iteratively execute different sequences of applications from the set of applications to query and retrieve data from different data sources until determining the data that is necessary to generate a response to the request has been retrieved. The computer can generate the response from the retrieved data and present the response on a user interface.

The embodiment of the invention provides a data analysis method, system and equipment based on multiple message analysis rule tables, and belongs to the technical field of industrial data control. The data analysis method based on the multiple message analysis rule tables comprises the following steps: collecting communication protocol messages in an industrial control network communication process; performing network layer protocol parameter analysis on the communication protocol message, and determining a target message type; determining a plurality of pieces of industrial control behavior information according to the communication protocol message of the target message type; the multiple pieces of industrial control behavior information are combined, and industrial control behavior process information is determined; and performing visual display according to the communication protocol message and the industrial control behavior process information. According to the embodiment of the invention, the industrial control behavior information can be quickly identified by analyzing the communication protocol message, the efficiency and accuracy of industrial control are improved, and visual display provided by the embodiment of the invention realizes the intuition of industrial control and improves the use feeling.

The invention provides a method for quickly creating an orchestrable intelligence agent by utilizing a fixed rule, which comprises the following steps of: tool configuration: customizing a business logic code by a creator, and then adding a tool name and description on a configuration interface; and flow arrangement: according to the functions of the agent to be realized, after a user selects chain nodes on a system interface and fills in configuration items of related nodes, each node determines an input or output type, nodes of the same type or sub-type stipulate the processing flow direction of the flow, and after the user inputs and outputs, the system stores flow information. And agent creation: a series of visual configurations are compiled into logic codes by automatically generating a framework through the flow arrangement storage in the background, and built-in nodes are dynamically called through node configuration items to realize agent creation. According to the method, the capability of visually arranging the large model application is realized, the method is friendly to users in non-professional fields, the large model application can be rapidly enabled, and the threshold of integrating a digital assistant in an application system is reduced.