29 results about "Event level" patented technology

The invention belongs to the technical field of aviation flight training, particularly relates to a multi-module collaborative flight simulator control panel and method, and solves the problems that an existing system is low in interaction efficiency, subjective in evaluation, lagged in early warning and time-consuming in comment. The system depends on traditional IOS hardware, and is provided with an intelligent voice interaction module which recognizes teacher voice through ASR, generates an instruction through intention recognition and three-level slot completion, and cooperates with double-layer flight stage recognition logic to guarantee interaction accuracy; the flight quality monitoring module operates a rule engine and an enhanced LSTM neural network in parallel, and outputs a comprehensive flight quality score in combination with an adaptive fusion algorithm; the real-time reminding module dynamically adjusts the early warning priority according to the event level and the flight stage, and multi-mode early warning is provided; and the intelligent comment module fuses the multi-source data and generates a personalized structured report according to the priority of the template. According to the invention, intelligent interaction, quantitative evaluation and automatic commenting of training are realized, and the training efficiency and evaluation objectivity are improved.

The embodiment of the application discloses a kind of traffic network scheduling control method, system based on space-time big data, electronic equipment, belong to the technical field of electronic data processing, method steps include: the following steps are executed in edge side: receiving and analyzing terminal raw data, filtering and trajectory generation using the rules issued by cloud end;Call fusion engine to perform space-time alignment and matching on multi-source trajectory, generate fusion trajectory;Based on fusion trajectory, traffic flow, average speed are calculated synchronously, and input to event risk assessment model to output risk probability value;After comparing risk probability value with threshold, event level is generated and corresponding alarm is triggered.In cloud side, server converges multi-dimensional information uploaded by each node for macro analysis and model iteration optimization, and periodically issues updated strategy and configuration to edge node to dynamically adjust its processing logic, so as to realize intelligent traffic control from cloud end global optimization to edge real-time execution.

The disclosure generally describes methods, software, and systems for integration of attribution reports and auxiliary data sources. Data including aggregated summary reports and event level reports is received from a first system. Additional raw affirmative action data related to the aggregated summary reports and event level reports is received from a second system. A matrix is created with rows for interaction events and columns for raw affirmative action data. Denoised aggregated counts and denoised event counts are determined from the received reports. The matrix fields are optimized by resolving conflicts between raw counts, denoised aggregated counts, and denoised event counts.

The invention discloses an event-driven adaptive sampling and hierarchical transmission method based on a data change rate. The event-driven adaptive sampling and hierarchical transmission method specifically comprises the steps that S1, an equipment end collects industrial equipment operation data at a fixed frequency and generates a data frame; s2, the server side calculates the data change rate of adjacent data frames from the same equipment, and generates an abnormal score based on the change rate; s3, the server side divides the data frame into event levels at least including a heartbeat level, a conventional level, an abnormal level and an accident snapshot level according to the abnormal score Score; s4, the server performs adaptive adjustment on an issuing strategy to the client according to the event level; s5, the server triggers an accident snapshot level event, and reliably transmits and issues the accident snapshot level event to the client through a TCP; and S6, the server side enables the data of different event levels to enter different priority queues and dispatches and issues the data according to the priorities. According to the invention, through event grading, sampling self-adaption and grading transmission, priority arrival of key abnormal data and complete reservation of accident data are realized.

This application discloses a competition rights management system, method, apparatus, and related equipment. The system includes: a blockchain network consisting of provincial nodes deployed in various provincial-level administrative regions and core nodes deployed in the Chinese Athletics Association. The provincial nodes employ the Hyperledger Fabric framework, and the nodes interact using the Practical Byzantine Fault-Tolerant (PBFT) consensus algorithm; edge computing nodes deployed at the event site, communicating with the blockchain network, for real-time collection of athlete performance, event level, and regional difficulty coefficient data; a smart contract module deployed in the blockchain network, for determining a comprehensive score based on athlete performance, event level, and regional difficulty coefficient data, and dynamically adjusting competition rights based on the comprehensive score and preset conditions; and a competition rights allocation engine coupled to the smart contract module, for generating a competition rights allocation scheme based on the comprehensive score, host city requirements, and athlete influence data.

The application discloses a data storage method of an electronic speed regulator and the electronic speed regulator, relates to the technical field of electronic speed regulator control, and discloses the data storage method of the electronic speed regulator and the electronic speed regulator. The data storage method of the electronic speed regulator and the electronic speed regulator disclosed realize differentiated storage of data of different importance degrees by dynamically selecting a storage area and a sampling frequency based on an event level, solve the problems that storage resources are not reasonably allocated and key data is prone to loss in a traditional scheme, have the advantages that a storage strategy can be dynamically adjusted according to an event level, storage resource configuration can be optimized, and the saving integrity of key data and fault diagnosis accuracy are improved.

The application provides a network public opinion video content analysis method based on multi-modal fusion, and relates to the technical field of network information processing.The method comprises the following steps: by splitting the public opinion video into an audio stream and an image frame sequence, structurally analyzing picture text and speech content respectively, and completing semantic embedding and cross-modal alignment under a unified time axis, introducing a bidirectional cross-modal attention and a gating fusion mechanism to realize deep fusion of multi-modal information, and further combining multi-role consistency, semantic superposition effect and emotion and fact collaborative features for joint modeling at an event level scale, so as to realize overall understanding of network public opinion video content and accurate determination of public opinion risk level.The application can fuse multi-modal information as a whole and realize joint modeling to analyze network public opinion video content.

This invention relates to the field of intelligent alarms and discloses a store intelligent alarm and voice reminder method based on event classification, comprising the following steps: collecting and preprocessing multi-source data from stores through a full-domain sensing terminal to construct a core data feature library; constructing an event classification scoring model based on the feature library, completing dimension weight initialization and risk quantification classification; dynamically scoring real-time events and determining whether to trigger proactive reminders, generating standardized alarm information; classifying reminder objects according to event levels and collaboratively pushing text and voice reminders; simultaneously implementing a duplicate alarm suppression and timeout escalation mechanism to avoid alarm proliferation and response delays; and finally iteratively optimizing the classification model based on the handling data. This invention achieves accurate event classification, differentiated proactive reminder push, and intelligent linkage between voice and text, effectively solving the problems of frequent false alarms, chaotic reminders, untimely responses, and lack of closed-loop optimization in traditional store alarms, thereby improving alarm effectiveness and handling efficiency.

The application discloses a kind of processing method and processing system for community security emergency event, before the event of community security emergency event, event handling power is pre-configured access event processing system, event bursts after having timely receiving event discovery ability, and can timely and effectively classify event, and carry out effective event handling power resource matching, utilize the optimal event handling power after matching and carry out event emergency event processing, and form to each event handling feedback, the comprehensive matching of processing power and event level, cost factor in the community range of sudden security event, through the access of multidimensional security handling power, and multidimensional security event receiving response processing, realize the sustainable optimization processing method of community security event;It can be aimed at community production fire control, flood prevention and so on, through effective emergency handling of emergent event, improve community people's sense of security and happiness.

This invention discloses a multi-source sensing data fusion and event reasoning method based on edge computing and knowledge graphs, relating to the field of remote monitoring technology. The method includes the following steps: Step 1, synchronous acquisition of multi-source sensing data; Step 2, location semantic mapping and appliance operating status identification; Step 3, the edge gateway constructs a set of current observation facts based on the current functional area number, current area dwell time, appliance status register content, and the time interval to which the current timestamp belongs, determining the current event type and current event level; Step 4, the cloud server performs incremental updates to the home scene event knowledge graph based on event feedback records and distributes the updates to the edge gateway. This invention achieves three-dimensional fusion sensing of location information, electricity consumption behavior, and temporal context, possessing advantages such as strong privacy protection, good interpretability, and a response measure that matches the level of risk.

The present disclosure relates to a method, an apparatus, a computer program product and a system for event identification and notification. The method includes identifying an event based on at least one of a video and audio temporally aligned with the video; allocating event levels for the events based on a preset grading mode; and determining a notification mode for the event based on the event level.

The invention relates to the technical field of protection engineering, in particular to a facility system first-aid repair resource allocation method for a complex uncertain attack scene, which comprises the following steps of: S1, acquiring a facility system network structure and a facility number, and evaluating a facility initial function; s2, determining the level of an adverse event; s3, determining facility system first-aid repair resource preset planning constraint conditions, and constructing an improved facility system first-aid repair resource preset planning model; and S4, solving the first-aid repair resource preset planning model by adopting an adaptive random search algorithm (ARS-SVM) fused with a support vector machine to obtain an optimal solution of the first-aid repair resource configuration of the facility system. According to the method, the resource demand satisfaction degree expectation which maximally considers the conditional value-at-risk is taken as a target, the demand is regarded as a random variable, the probability distribution is obtained through historical data fitting, and the auxiliary variable is introduced to quantify the demand fluctuation, so that the urgent repair recovery accuracy can be improved, the cost effectiveness can be balanced, and the system adaptability can be enhanced.

The embodiment of the invention provides a self-adaptive fan variable pitch controller and a method thereof, which are used for carrying out dynamic self-adaptive adjustment on weights of targets such as power tracking and load suppression in a model predictive control cost function through a power grid event level and a unit load level which are monitored in real time. Through the method, the controller can autonomously switch and optimize the control priority according to the actual working condition, the power response is preferentially guaranteed when the power grid needs to be supported, the load is actively inhibited when the load is too large, and the emphasis is emphasized on generating capacity maximization under the conventional working condition; and finally, the optimal balance of the power generation efficiency, the structural safety and the power grid friendliness of the fan under the complex operation condition is realized, and the intelligent level and the comprehensive performance of the unit are remarkably improved.

This invention discloses a data processing method, apparatus, device, and storage medium. The method includes: acquiring at least two event data sequences generated by a target user in at least two business domains; extracting features from each event data sequence corresponding to each business domain to determine event feature information corresponding to each business domain, and performing information fusion to determine first fused feature information; performing cross-attention processing on pairwise event data belonging to different business domains to determine event-related feature information corresponding to each event data combination, and performing information fusion to determine second fused feature information; and determining target fused feature information based on the first and second fused feature information. Through the technical solution of this invention, coarse-grained fusion at the business domain level and fine-grained fusion at the event level can be combined, improving the data fusion effect between multiple business domains and thus improving the accuracy of user analysis.

The application discloses an intelligent video summary system based on cross-modal alignment, relates to the technical fields of cross-modal alignment and video processing, and aims to solve the technical problems that in the prior art, a fine cross-modal alignment mechanism is lacked during multi-modal summary generation, the time sequence offset among frames, phonemes and words cannot be solved, and global consistency cannot be realized at the event level and the semantic paragraph level, specifically, an improved hierarchical cross-modal alignment algorithm and a dynamic weight distribution mechanism are introduced to solve the problems of multi-modal feature time sequence misplacement, semantic inconsistency and rigid weight distribution in the video summary, fine alignment of frames, phonemes and words is realized through soft dynamic time warping and sparse optimal transmission, and event level and semantic paragraph level representations are generated in combination with time sequence change detection and hierarchical attention, so that the accuracy of cross-modal fusion is improved.

The invention provides a power grid dispatching real-time information generation method and system, relates to the technical field of power grid dispatching management, and aims to solve the problems of low automation degree and insufficient pertinence of dispatching information generation. The method comprises the following steps: acquiring event parameters of an electric power security event; judging an event type according to the event parameter, and when the event type is a preset accident type, automatically determining an accident event level based on a preset rule; automatically matching a target information template from a template library according to the event type and the determined accident event level; and automatically filling the accident event level and other event information into the target information template to generate scheduling real-time information. According to the method, the events are classified and graded, and the template is accurately matched, so that the accuracy and pertinence of information generation are improved, and the working efficiency is improved.

The application discloses a kind of multimodal data fusion analysis and processing method and system, it is related to edge computing technical field;The method includes obtaining the control state sequence of target equipment, current response sequence and image sequence, extracts each modal candidate response time, constructs edge disturbance description quantity and candidate event fragment;Call event template to build cross-modal propagation sequence constraint graph, inverse solve virtual time scale sequence and form sequence deviation quantity;According to virtual time scale sequence, reconstruct event level synchronization fragment, extract logic jump feature, current dynamic feature and visual motion feature, generate event attribution credibility and event fusion representation quantity;According to event attribution credibility, output fusion analysis result, and feedback type update is carried out to propagation time delay interval, the application can improve the accuracy, stability and self-adaptive updating capability of multimodal event analysis.

The application discloses a kind of virtual-real fusion three-dimensional engine time axis control method, equipment and medium, the method includes: based on virtual-real fusion scene constructs multidimensional data mapping time axis model, establishes time axis basic framework, forms initial time axis model;Based on initial time axis model, the spatiotemporal alignment processing of real-time heterogeneous data stream and historical data is executed bidirectionally synchronized, and multi-source data is filled to time axis, and complete time axis dataset is constructed;Based on complete time axis dataset, event prediction and analog deduction based on timing deep learning are executed, and future time domain is extended to time axis, and form visual simulation timeline;Based on visual simulation timeline, realize visual interaction and dynamic scene real-time rendering based on event semantics, complete time axis data human-computer interaction output, and feedback interaction instruction to time axis basic framework.The application realizes the full cycle, high accuracy, event level time dimension control to complex virtual-real fusion scene.

Systems and methods are provided for providing automatic communication from a vehicle in the event of a stop event, thermal event, or thermal propagation event. A vehicle may detect a vehicle event using one or more vehicle sensors. The vehicle may also identify an event type and an event level based on data from the one or more vehicle sensors. Then based on the identified event type and the identified event level, the vehicle may automatically transmit a message from the vehicle to an authority and output an alert to a user of the vehicle indicating a corrective action based on the event type and the event level.

The invention provides a college ice and snow sports production and education fusion course resource management system, belongs to the technical field of education and sports, and aims to realize classified management and rapid retrieval on course resource integration, improve the utilization efficiency of teaching resources, assist teaching and autonomous learning of teachers and students, assist enterprise cooperation and docking to promote deep cooperation between colleges and enterprises, and improve the efficiency of production and education. The teacher management subsystem improves the teacher quality and stability, enriches the teaching content methods, develops the practice innovation ability of students through course setting innovation, improves the competition level and influence through competition organization management, provides feedback for teaching training, and improves the teaching quality and stability. Scientific research and development are promoted by scientific research and innovation management, industry-university-research combination is realized, personalized teaching and talent training are supported by the student management module, stable operation and data safety of the system are ensured by the system management unit, and ice and snow sports development and talent training in China are comprehensively promoted.

The invention discloses an enterprise public opinion index monitoring model which comprises an index library management module, a monitoring enterprise management module, an enterprise monitoring timed task module and a monitoring center. The index library management module is used for acquiring network news text data from a public opinion data source and preprocessing and storing the network news text data; the monitoring enterprise management module is used for analyzing and processing the network important public opinion information preprocessed by the index library management module, and forming a public opinion event level conversion mechanism according to an analysis result of analysis and processing; the enterprise monitoring timed task module is used for monitoring enterprise public opinion data in a timed manner; and the monitoring center list displays enterprise monitoring results. Negative public opinions of enterprises are covered and monitored to the greatest extent and most timely through an informatization system, institution and project default risks are found timely, and the risk management and control efficiency of companies is improved.

The invention discloses a network security investigation method based on a behavior sequence, and relates to the technical field of network security, which comprises the following steps: performing normalization processing on massive heterogeneous original logs to construct a uniform event stream basis, introducing a double attention coding mechanism, performing local context focusing on a normalized event stream on an event level, and obtaining a uniform event stream; according to the method, the short-term intention of the threatening threatening system is analyzed to construct a tactical fragment sequence capable of representing the short-term intention, then long-time-sequence context focusing is carried out again on the tactical level, the discrete tactical fragment sequences are aggregated into global context representation capable of describing a complete attack chain, and finally accurate threatening scoring is carried out based on the global context. Therefore, by performing automatic and deep construction and cognition on the context scene of the attack behavior, accurate and efficient investigation on complex attacks can be realized, so that the automatic analysis level and response capability of network security threats are effectively improved.

The invention relates to the technical field of power system simulation, and discloses a cyber-physical fusion simulation-oriented event synchronization adaptive scheduling method, which comprises the steps of calculating heterogeneous state entropies of a power side and a communication side, and quantitatively representing a system operation state; performing dynamic semantic judgment on the network events based on the state entropy, identifying strong coupling and weak coupling events, and forcibly upgrading event levels when the system is in emergency; calculating an elastic time window width according to semantic attributes, and deciding a global synchronization moment; generating virtual input to drive an electric power simulator to run in advance when weak coupling is performed and the time window is in the elastic time window; the deviation between the real input and the virtual input is calculated at the synchronization time, and thus direct compensation or rollback recalculation is performed. By dynamically adjusting the synchronization strategy and the posterior error correction mechanism, the problems of low rigid synchronization efficiency and poor relaxation synchronization precision are effectively solved, and adaptive balance of joint simulation precision and efficiency is realized.

The invention discloses an event causal relationship identification method and system based on two channels and a multilayer graph convolutional network, and relates to natural language processing. Comprising the following steps: inputting and preprocessing a text to obtain a lexical sequence, event mention and an event set; performing dual-channel coding, and fusing BiLSTM (Bidirectional Long Short Term Memory) and Transform to extract local and global features; performing multi-layer graph convolutional network processing, constructing a lexical-level, mention-level and event-level three-layer graph structure, and aggregating information through a GCN with residual connection; predicting a causal relationship, fusing multi-source features to construct event embedding, and predicting the causal relationship through an MLP classifier; and training and optimizing the model. The system comprises text input, two-channel coding, a multilayer graph convolutional network, a prediction module and the like. The method solves the problems of insufficient co-reference relationship modeling, weak hierarchical semantic capture and the like, improves the recognition precision of the causal relationship of the document-level event, has high generalization ability and practical level, and can be widely applied to the scenes of public opinion analysis, disaster detection and the like.

This application provides a hybrid log collection and alarm method and system, relating to the fields of log processing and operation and maintenance monitoring. The method includes: generating preset logs in kernel mode and writing them to a lock-free circular buffer with multiple producers and a single consumer; a user-mode server acquiring logs in batches via NetLink and sending them to the server via asynchronous UDP, either individually or in batches, according to event level; the server using a Bloom filter to remove duplicate logs and suppress duplicate logs, while non-duplicate logs are asynchronously written to disk; and an intelligent analysis process collecting and analyzing logs at intervals negatively correlated with log rate, triggering alarms when rules are met. This application solves the problems of balancing real-time performance and throughput in existing kernel log collection, resource waste from duplicate log storms, and high kernel overhead by constructing a pipeline with a lock-free buffer and NetLink cross-layer transmission, dual-mode UDP sending, and Bloom filter pre-suppression, achieving low-latency, high-throughput processing and reducing resource consumption.

The invention relates to the field of resource scheduling, and discloses a land-sea-air-space rescue force integrated situation display and resource scheduling optimization system, which comprises a resource integration module, a communication path module, a to-be-processed set module, an initial task module, a feasible path module and a task scheduling module, the resource integration module fuses the state and environment data, generates a situation data stream, and separates an event information set and an available resource set from the situation data stream. The communication path module generates a communication path and a spatial distance thereof according to the positions of the event and the resource. And the to-be-processed set module determines a to-be-processed matching pair by comparing the distance with the resource coverage mileage. The initial task module judges event levels according to state parameters and event properties, and sorts matching pairs according to the event levels to form an initial task set. And the feasible path module corrects the path by taking the environmental obstacle as a constraint to obtain a feasible path and estimated arrival time consumption. And the task scheduling module finally takes the path and the time consumption as space-time constraints, binds an initial task set and outputs a final task scheduling set. According to the invention, the efficiency of land-sea-air-space rescue force integrated situation display and resource scheduling can be improved.

The application discloses a medical instrument data classification method based on LLM, and particularly relates to the technical field of medical instrument data; first, multi-source medical instrument text data is rearranged across sentences and aligned at an event level, semantic trajectories are constructed, and trajectory features are extracted; further, a device state constraint graph is constructed to constrain the trajectory features in terms of path consistency, and fused features are obtained; on this basis, a distribution alignment method based on optimal transmission theory is introduced to align the features between different semantic trajectories; subsequently, a multi-view prompt template containing counterfactual disturbance is constructed, semantic divergence areas are identified in combination with consistency measurement, joint discriminative reasoning is performed through disturbance inversion, and a final classification result is output; the application can effectively improve the recognition ability of low-frequency hidden anomalies and improve the accuracy and robustness of the classification result.

The invention discloses an emergency processing method, device and equipment, a medium and a product. The method comprises the steps of obtaining event information; inputting the event information into a preset query model, and performing information semantic extraction on the event information by the preset query model to obtain event semantics; querying event attributes corresponding to the event semantics from a preset enhanced retrieval generation system according to the event semantics, wherein the event attributes comprise event classification and event levels; performing alarm analysis based on the event semantics and the event classification to obtain alarm information; and querying a processing strategy corresponding to the alarm information from a preset enhanced retrieval generation system based on the alarm information and the event level, so as to process the event information according to the processing strategy. According to the embodiment of the invention, the intelligent degree of emergency recognition can be improved, manual intervention is reduced, integrated analysis of multi-dimensional data is realized, and the processing efficiency is improved.

The application discloses a kind of urban event grading early warning disposal resource scheduling methods of fusion edge computing, belong to city management, intelligent emergency scheduling field.Rely on internet of things terminal and city sensor, realize the real-time collection of multidimensional event data such as traffic, environment, security, etc., weighted adaptive fusion and anomaly detection are carried out by edge node, realize data front-end intelligent preprocessing.Adopt fusion feature hierarchical inference algorithm, combined with rule discrimination and deep learning model, complete event automatic classification.According to event level, edge-cloud cooperation realizes grading early warning and resource scheduling, ordinary event is responded in situ by edge node, and major event and above are uploaded to cloud simultaneously, drive global decision and resource optimization scheduling.Through whole-process performance feedback, dynamically optimize grading, early warning and scheduling strategy, improve the intelligentization and efficiency of city emergency response.