148 results about "Event tracking" patented technology

A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.

Systems and methods for managing the distribution of electrical power are disclosed. The system can maintain a status of each account of a plurality of accounts. Each account can correspond to an electrical power generation device, an electrical power consumption device, and an electrical power transmission device. The system can generate a first record object in response to the generation of a unit of power. The system can identify a first path identifying a source device and a destination device to transmit the unit of power. The system can generate a control signal to route the unit of power from the source device to the destination device. The system can update an event tracker to indicate the routing of the unit of power. The system can generate a second record object corresponding to the destination device. The system can update a second account to include the second record object.

The present invention relates to the technical field of electrical operation, and in particular to an automatic tracking system for safety events in an electrical operation process based on AI recognition, comprising a multimodal data acquisition module, a data preprocessing and fusion module, a safety event recognition module, an event tracking and positioning module, a risk assessment and early warning module, an automatic intervention module and a data storage module. The multimodal data of an operation site is acquired in real time by the multimodal data acquisition module, a dynamic feature set is generated by the data preprocessing and fusion module, safety events identify safety events in the electrical operation process, the event tracking and positioning module realizes dynamic positioning and trajectory tracking of the target, the risk assessment and early warning module assesses the risk level of the event and generates a multi-level early warning signal, and the automatic intervention module generates strategies such as equipment power-off, evacuation warning and operation suspension prompt according to the early warning signal and the positioning result; the present invention improves the real-time nature of electrical operation safety monitoring and the intelligent level of intervention.

A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.

A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.

The invention relates to the technical field of content recognition, in particular to an Al-based video content analysis method and system, and the method comprises the following steps: carrying out the image segmentation learning based on a video sequence through employing a U-Net convolutional neural network, analyzing scenes and elements in a video frame, recognizing and isolating key visual elements in a video through network learning, and carrying out the recognition of the key visual elements in the video. Comprising objects and figures. According to the method, image segmentation learning is carried out by adopting the U-Net convolutional neural network, key visual elements in the video can be identified and isolated more accurately, a clearer basis is provided for follow-up scene change and key event tracking, video content analysis is carried out by applying the graph neural network, the identification capability of dynamic scenes and events is enhanced, and the identification efficiency is improved. Deeper structured understanding is provided for video content indexing, the video quality is analyzed through a structural similarity index evaluation method, and the reason of visual quality reduction can be accurately recognized and improved.

The invention discloses a dynamic portrait construction method and system fusing a large model and user behavior data, belongs to the technical field of artificial intelligence and big data analysis, and aims to solve the problems of insufficient real-time performance, difficulty in multi-source data integration and high privacy risk in the traditional technology. The method comprises the following steps: collecting basic attributes, behavior sequences and unstructured data by burying points, and processing through an Apache Flink session window and a dynamic watermark; multi-modal feature extraction (discrete feature embedding, bidirectional LSTM coding behavior sequence and BERT coding text) is carried out, and joint embedding is generated through cross-modal contrast learning; generating three types of labels, namely a static label (rule engine), a dynamic label (1.3 B parameter quantity Nano-vLLM) and a predictive label (XGBoost), and dynamically adjusting weights; and realizing global model updating through federated learning and differential privacy. The system comprises a data acquisition layer, a feature extraction layer and a label generation updating layer. The real-time performance and accuracy of the portrait are improved, the privacy of the user is protected, and the commercial value in e-commerce, finance and other scenes is remarkable.

The invention provides a cross-domain collaborative information tracking and positioning auxiliary method and system, and the method comprises the steps: firstly collecting an original data set generated by a target event in a plurality of associated domains, carrying out the cross-domain identifier matching processing to obtain a standardized event data set, and then carrying out the information association processing of the standardized event data set, according to the method, context semantic features and cross-domain time sequence behavior features of a target event are generated, then collaborative analysis is performed on the features based on a preset collaborative analysis model, a cross-domain collaborative tracking index set is generated, and a dynamic tracking path topology is constructed according to the cross-domain collaborative tracking index set. According to the method and the device, the target event is tracked and positioned, the positioning auxiliary strategy matched with the target event is generated, and finally the positioning auxiliary strategy is synchronized to the cross-domain tracking system to activate the cooperative positioning operation, so that the cooperative processing of multi-domain information is realized, and the target event tracking and positioning accuracy and efficiency are improved.

The present system pertains to event tracking, involving the acquisition of event information, generation of compound hashes, and formation of a search data structure. Event information includes time-and-geolocation data and topic data for each event. Compound hashes, comprising a spacetime hash and a topic hash for each event, are generated based on this information. A search data structure is formed using these compound hashes, enabling the grouping of spacetime hashes and structuring of topic hashes. Upon receiving a query, the system executes a search based on the query's compound hash or parameters, returning matching event content. The system can also generate semantic descriptions of relevant events using a narrative generation model and predict event relevance using a preferential learning model.

The present disclosure relates to systems, methods, and computer-readable media for collecting operational data across a plurality of radio access network (RAN) components. For example, the systems described herein can identify data signals that are tracked by one or more RAN components. Based on these data signals, the systems can define any number of network events that may be tracked by event tracking agents that are deployed on each of the RAN component(s). The RAN components may then provide a stream of event instances to the systems for collecting, analyzing, and otherwise utilizing the network event data that is locally tracked by the respective RAN components.

The invention relates to the technical field of shaving board production, in particular to a shaving board production abnormal event intelligent detection and diagnosis system which comprises a parameter time sequence acquisition module, an abnormal point recognition module, a collaborative feature judgment module, a synchronous trend analysis module and an abnormal attribution positioning module. According to the method, continuous trend analysis and node sequence integration are carried out on various process parameters in the production process, a dynamic linkage system of batch information and parameter fluctuation is established, synchronous identification of abnormal parameters and nodes is realized, and parameter collaborative mutation and trend synchronous offset between process links are taken as a core basis for abnormality diagnosis; according to the method, the comprehensive precision of batch affiliation, exception types and node positioning is improved, the exception event tracking capability under the multi-node and multi-parameter condition is enhanced, the integration and exception traceability of parameter data in the whole production process are optimized, the quality risk caused by parameter fluctuation and process exception is reduced, and the risk management and control capability in the whole production process is optimized.

A method includes receiving an event tracking query for a patient health care transaction from a requestor; receiving state transition updates for the event from ones of a plurality of different transaction processing entities that are independently controlled with respect to each other; mapping the state transition updates to a representational workflow model, which defines a plurality of tracking states; generating an event tracking result based on the mapping of the state transition updates to the representational workflow model and the plurality of different transaction processing entities; and communicating the event tracking result to the requestor.

An example system includes a processor to receive an event trace. The processor can transform the event trace into a semantic story using a generated story template. The processor can input the semantic story into a fine-tuned model. The processor can receive a next skill prediction from the fine-tuned model.

A method for operational workflow transparency and end-to-end events tracking, the method includes at an event producer system, generating events, corresponding key business attributes, provider industry standard identifiers, patient identifiers, and patient information, and publishing the events and the key business attributes to a tracking system. At a tracking system, receiving and validating the events from the event producer system, generating a universally unique lexicographically sortable identifier (ULID) for an append-only log data structure for the respective event, generating a search index to enable search capabilities for the append-only log data structure, and temporally appending the respective event into the append-only log data structure for the corresponding prior-authorization case.

The present disclosure relates to systems, methods, and computer-readable media for collecting operational data across a plurality of radio access network (RAN) components. For example, the systems described herein can identify data signals that are tracked by one or more RAN components. Based on these data signals, the systems can define any number of network events that may be tracked by event tracking agents that are deployed on each of the RAN component(s). The RAN components may then provide a stream of event instances to the systems for collecting, analyzing, and otherwise utilizing the network event data that is locally tracked by the respective RAN components.

The invention relates to the field of security event tracking, in particular to a security event real-time tracking and tracing method and system based on artificial intelligence, and the system comprises a port switching module, a flow tracking module, a disk pointer module, a memory stack module and an attack clustering module, the port switching module is used for structuring a server database and outputting a threat model; the flow tracking module is used for tracking access flow, the disk pointer module is used for packaging temporary data packets, the memory stack module is used for storing the temporary data packets and pointers in a stack form, and the attack clustering module is used for clustering abnormal pointer clusters and identifying homologous attack flow. Meanwhile, repeated generation of security logs is reduced, the working efficiency of the security event protection system is improved, the efficiency and accuracy of real-time tracking and tracing of security events are improved, and the network security protection and emergency response capability is enhanced.

The invention provides a PCIE (Peripheral Component Interface Express) power consumption testing device, relates to the field of power consumption testing, and can break a barrier between hardware power consumption data and a software system log and innovatively utilize an operating system kernel event tracking system as a unified data fusion platform. A power consumption sampling point collected by external hardware in real time serves as a self-defined event and is injected into a kernel event tracking session in real time, so that the power consumption sampling point and a kernel state change event captured by a system coexist under the same high-precision timestamp, and a unified tracking event stream which is perfectly aligned in time is generated. On the basis, the PCIE abnormal mode is further automatically identified from mass tracking data. Through the deep learning model, the local time sequence characteristics of the power consumption sequence are coded, then the mode evolution rule of the full time domain is further captured, finally, the abnormal state of the PCIE link is accurately and automatically judged, and then the diagnosis efficiency and accuracy of the power consumption problem are improved.

Systems and methods described herein facilitate the tracking of events relating to property. For example, in certain embodiments, a system includes a property event detection device (e.g., smart home device, sensor device, and so forth) configured to detect activity (e.g., motion, light, sound, and so forth) proximate the property. The system also includes a property event tracking system configured to receive data (e.g., images, videos, facial recognition, movement recognition, object tracking, sound signatures, wireless data streams, and so forth) relating to the activity from the property event detection device, to determine whether the activity relates to a property event (e.g., home service, and so forth) for the property, and to store data relating to the property event in a distributed ledger (e.g., blockchain network) upon determination that the activity relates to the property event for the property.

The invention discloses a computer information exception identification and early warning method and system, and particularly relates to the field of exception identification and early warning. Through monitoring cross-layer event timestamp data generated by a host machine and a container side, the time record consistency of the two sides is evaluated; meanwhile, process-level behavior metadata captured by the virtual machine management program layer and the container kernel namespace layer are analyzed, and the visibility consistency degree of the multi-layer resource occupancy state is evaluated. And determining a cross-layer visibility dislocation risk degree, and when the risk reaches a high risk level, evaluating a multilayer lock competition abnormity risk by analyzing a kernel event tracking sequence. And finally, the time record consistency of the host machine and the container side, the visibility consistency degree of the multi-layer resource occupancy state and the multilayer lock competition abnormity risk are comprehensively analyzed, and the cross-layer visibility dislocation alarm level is evaluated, so that accurate identification and early warning of computer information abnormity are realized, and the operation safety and stability of a computer system are effectively guaranteed.

An event tracking system is provided. The system includes one or more sensors. The sensors are configured to generate data regarding an event occurring on a physical event surface. The system is configured to generate a plurality of virtual event surface sections corresponding to a physical event surface, and to receive the event data from the sensors. The event data from the physical event surface includes a first position indicator and an activity indicator. The system is configured to correlate the event data to the virtual event surface sections using the first position indicator, and to determine a result value associated with the event data based on the activity indicator. The system is configured to update accumulated result values of users based on the result value and the correlated virtual event surface sections. The system is configured to perform an action based on the updated accumulated result values.

The present disclosure relates to systems, methods, and computer-readable media for collecting operational data across a plurality of radio access network (RAN) components for determining and presenting a health profile for the RAN components. Systems described herein involve implementing event tracking agents on the RAN components, compiling instances of detected events via event streams from the respective RAN components, and determining a health profile that reflects a current or predicted health state for components that make up a RAN. The systems described herein may further generate and present a health profile presentation including interactive icons and features that enable an individual to view health profile data for specific RAN sites, RAN components, and even user devices associated with the tracked events. Systems described herein may perform various mitigation actions to overcome poor health conditions as they are observed or predicted over time.

The invention discloses a comprehensive quality control method for VSP processing interpretation data and related equipment, and the method carries out the quality control of the four processes of VSP data preprocessing and first arrival pickup, signal processing, corridor superposition and imaging, and VSP comprehensive interpretation, and achieves the remote quality control of VSP data. Quality control work is switched from an offline mode to an online mode; quantitative quality control; the quality control report can be generated by one key, so that the flexibility and the working efficiency of the quality control system are improved, the quality control cost is reduced, and the quality control report can be generated from the targets of uniform quality control standard and remote online quality control. VSP key algorithms such as wave crest and first arrival error, deconvolution effect analysis, event tracking algorithm, dynamic correction Gamma value, speed error analysis, DB spectrum calculation formula, Tar value calculation method and the like are researched and developed, a unified quality control standard is provided for four procedures of Tarim oil field VSP processing interpretation projects, and scientificity and reliability of data quality control results are ensured.

To provide high availability scheduler event tracking for scheduler configuration such as IBM Z workload scheduler configuration.SOLUTION: By a controller, an operational status of a tracker system that is configured to track and record a current status of a job and to report completion of the job to the controller, is monitored. The recording includes storing two copies of the current status. In response to determining, based on the monitoring, that the tracker system is operational, reception of a job completion message from the tracker system is waited for, and a job completion action based on the reception of the job completion message is performed. In response to determining that the tracker system is not operational, the current status of the job is obtained from a shared memory location, and the job completion action based on the current status indicating that the job has completed is performed.SELECTED DRAWING: Figure 1

The invention provides an attack detection method and device, electronic equipment and a storage medium, and the attack detection method comprises the steps: detecting whether there is an intersection between a memory region corresponding to a modified memory attribute and a function address range of a target event tracking function if the modification of the memory attribute of the target event tracking function is detected; if the intersection exists, obtaining function call stack information triggering the modification; and carrying out attack detection based on the function call stack information. Through the technical scheme provided by the invention, the modification monitoring of the memory area of the target event tracking function is combined with the function call stack information for triggering the modification, so that the ETW bypassing attack based on the memory patch mode is accurately detected.

The application provides a kind of information security event's tracking and tracing analysis method and system, method includes: real-time monitoring information security event whether there is alarm information, when monitoring the alarm information, obtain the original data message of the information security event;The attribute information of the industrial control protocol of the information security event is obtained by identifying the original data message;According to the attribute information, the malicious operation of the information security event is searched and matched with the malicious operation in the plan library, and the information security event is tracked and traced according to the matching result.The application provides a set of event alarm-quick message analysis-tracing tracking information security event tracking and tracing processing procedure, which can shorten the response time and improve the efficiency of emergency tracing tracking.

The invention provides a three-full-child-bearing-person management method based on big data, a block chain and an internet of things, and the method comprises the following steps: enabling a three-full-child-bearing-person management platform system to be matched with a school system, and synchronizing the associated data in real time; the method comprises the following steps: constructing an Internet of Things system in a set area, docking with a three-full-child-bearing management platform, dividing collected personnel data, regional management data and event tracking data marked with timestamps and data sequences into formatted data and non-formatted data by applying a big data dictionary technology, and carrying out classified storage on the formatted data and the non-formatted data; a user logs in the school system through verification, authority distribution is carried out in the three-full-child-bearing management platform system, a corresponding point value is set according to the authority, and the point value is stored in a database; and after the user carries out authority distribution, the user carries out data interaction in the school system in a data contract mode.

A random access memory device includes memory cells associated with each row for storing metadata related to accesses to that row. Events that may cause row hammer may be tracked on a row-by-row basis by counter values in the metadata dedicated cells. The counter values are stored in a subset of rows of the metadata dedicated memory array. Multiple counter values (e.g., those associated with multiple victim and / or aggressor rows) may be read and / or written with a single activation of the metadata dedicated row. The metadata dedicated row stores the counter values for both the accessed data row and nearby data rows, the metadata counter value(s) associated with both the accessed data some nearby data rows may be updated using the single access to the metadata dedicated row.

An embodiment of the present application provides a method for tracking a process created by the Windows Task Scheduler, which relates to the field of information security technology. The method includes: injecting a dynamic link library containing a context marshaling module into the task scheduler service process, and hooking the event tracing API in Windows Event Tracing with a hook function in the context marshaling module through the dynamic link library; obtaining parameter information in the event tracing API called by the unified background process manager of the system through the hook function, and constructing a task context of a thread based on the parameter information; when the security proxy module receives a callback for process creation, perform the following operations: determine whether the task context of the thread exists, and when the thread has a task context, operate on the created process according to the task context. The implementation manner provided by the present application realizes accurate capture of the task creation process.

Systems and methods for event tracking are disclosed. In one aspect, a set of venues is generated. A set of events that have occurred at one or more venues in the set of venues may be generated. One aspect includes querying a user media database associated with a user, and extracting metadata from one or more media files in the user media database. A match between at least a portion of the metadata and one or more events from the set of events may be determined. In an aspect, responsive to the determining, an entry in a matched events database corresponding to the match is created. A list of events attended by the user may be prepared. The list of events may include the matched events.