7 results about "Residual risk" patented technology

This invention discloses a method for coal mine terminal risk scoring based on Bayesian networks, comprising the following steps: Step 1: Collecting coal mine terminal risk data to form a terminal risk dataset; Step 2: Extracting risk variable nodes, barrier variable nodes, and terminal scoring nodes, constructing a Bayesian network, and forming a node conditional probability table; Step 3: Performing deontization, triangulation, and clique partitioning to form a connection tree and a partition set; Step 4: Calculating the probability estimate of clique nodes and the barrier state description term; Step 5: Constructing propagation messages using an improved Shafer-Shenoy algorithm to form a penetrating residual component; Step 6: Performing state enhancement marginalization to form a partition set propagation message; Step 7: Forming the terminal residual posterior risk distribution; Step 8: Forming the coal mine terminal risk scoring result. This invention improves the ability to characterize coal mine terminal residual risk and the reliability of risk scoring.

A software based application for assessing, processing, and remediating cyber-risk in real time may comprise, without limitation, a profiling component, an analytic component, an evaluation component, and a monitoring component which may, in conjunction therewith, operate to allow an organization to adaptively adjust an organization's network security to continuously improve and mature same. Such components may operate to: (1) determine an organization's operational baseline; (2) identify risks and hazards inherent therein; (3) generate, and verify the efficacy of, remedial controls to such risks and hazards; (4) document and audit such determinations; and (5) continually monitor the organization's network security. In such a manner, the network security architecture of an organization may be remediated according to threat scenario-based control efficacy and residual risk determinations according to the agnostic, risk-focused, and system-based approach disclosed herein.

The present application relates to an AI-assisted real-time tissue recognition and cutting path planning system for microsurgery, which includes multi-modal acquisition, registration fusion, tissue segmentation, risk assessment and path planning output modules. Microscopic videos, fluorescence images, OCT depth maps, etc. are collected, and heart rate, blood pressure, instrument pose and force feedback are synchronously acquired; after camera calibration, registration and time alignment, a fusion input is formed. The tissue recognition CNN uses spatio-temporal aggregation and cross-modal attention fusion, and sets a differentiable safety distance field layer between fusion and decoding, generates a safety distance field based on instrument embedding and OCT depth gradient, as attention bias and skip-connection gating, outputs class map, boundary map, confidence and uncertainty. Based on the confidence and uncertainty, structure, mis-cut and residual risk maps are generated; under the constraints of kinematics and cuttability, trajectories containing path points, depth and speed are output, and superimposed acoustic and light warnings or robot instructions are output.

This invention discloses a coal mine disaster risk prevention and control platform based on multimodal perception and AI video recognition, relating to the field of video recognition technology. It includes a multi-source data acquisition module, a micro-scene construction module, a feature extraction module, a pseudo-anomaly removal module, and a linkage control module. The platform acquires video stream V, gas concentration G, wind speed W, temperature and humidity T, acoustic and vibration signals A, and roadway topology parameters L. It constructs a micro-scene unit U, extracts visual disturbance features Fv, gas response features Fg, thermal inertia features Ft, and acoustic and vibration mutation features Fa, generates a cross-modal causal consistency matrix C, and a non-disaster disturbance baseline B, obtains residual risk features R, and outputs the risk source location, propagation direction, and risk level result Y. This enables graded power outages, localized ventilation adjustments, directional spraying, personnel evacuation, and model self-updating, improving the accuracy of identifying precursors to minor coal mine disasters and enhancing linkage prevention and control capabilities.

This invention discloses a SOTIF data acquisition method and related equipment. In this invention, the cloud has a large data acquisition scope, thereby reducing reliance on closed sites or professional data collection fleets, and lowering the acquisition cost of multi-source heterogeneous data. Furthermore, First Automobile Works filters its collected multi-source heterogeneous data using first Shannon entropy and residual risk values. The filtered multi-source heterogeneous data corresponds to traffic environments with high levels of disorder. Therefore, by calling First Automobile Works to collect and upload multi-source heterogeneous data, a large amount of multi-source heterogeneous data that meets the application conditions of SOTIF can be easily obtained, providing data support for SOTIF. Moreover, the SOTIF data acquisition method is executed on the vehicle side, and by uploading the filtered multi-source heterogeneous data instead of the original full-volume data, the data processing burden on the cloud is significantly reduced, improving the implementation efficiency of SOTIF. This invention has wide applications in the automotive technology field.

Embodiments of the present application provide a kind of fusion security demand generation method, electronic equipment and storage medium.The method is in the development process of heavy vehicle automatic lateral control function, define the lateral control function related item including implementation function and expected function, obtain the hazard event of lateral control function related item by hazard and operability analysis, obtain the safety target of hazard event, vehicle safety integrity level and residual risk acceptance by hazard and risk analysis method, according to vehicle safety integrity level and residual risk acceptance, obtain target risk level in risk level table, establish function safety architecture according to target risk level and safety target, obtain safety constraint condition based on function safety architecture, and safety constraint body condition is converted into target safety demand, to analyze the hazard caused by lateral control failure and expected function deficiency, improve the development efficiency of automatic lateral control function, reduce development cycle, improve reliability and safety.

An institutional risk assessment method and apparatus are disclosed. The institution uses known inherent risk rules to assess customer data, obtaining first-risk customer data that matches the rules, and calculates known inherent risk index values. Next, based on risky customers and / or risk events not directly related to the institution contained in acquired external intelligence, a second-risk customer data set is selected from the customer data that did not match the rules, and an unknown inherent risk index is constructed, calculating its probability score. An inherent risk value is determined based on the known inherent risk index value and the unknown inherent risk probability score. Residual risk indicators are extracted from the acquired risk cases, and corresponding index values ​​are calculated; the remaining risk value is determined based on these index values. A risk assessment result for the institution is determined based on the inherent risk value and the remaining risk value. The risk cases include risk events directly related to the institution that have occurred or been discovered. The customer data contains private data, which requires privacy protection.