83 results about "Event risk" patented technology

A control system is provided for platooning a plurality of vehicles, each of which equipped with vehicle braking control systems and V2V communication system components. The system determines nominal following distances for each of said following vehicles relative to an immediately preceding vehicle, based in part on brake performance capabilities. Vehicle sensors throughout the platoon are implemented to monitor target vehicles positioned relative to the platoon, and some or all of the nominal following distances are dynamically adjusted to account for braking event risks associated with the target vehicles. Adjustment to following distances for trailing vehicles may be proactively applied even before braking reaction is determined or applied for a lead vehicle, and control signals are simultaneously generated implementing vehicle movement adjustments based on the following distance adjustments. Adjustments may be based on threshold violations associated with target vehicles in front, laterally merging into, or tailgating behind the platoon.

Risk events occurring on a computer system are logged over time and a risk profile is dynamically generated and updated based on the logged risk events. In one embodiment, a security policy is dynamically set and updated based on the risk profile.

This invention provides methods and systems for trading and investing in groups of demand-based adjustable-return contingent claims, and for establishing markets and exchanges for such claims. (FIG. 2, item 262, 263, 264, 265) The advantages of the present invention, as applied to the derivative securities and similar financial markets, include increased liquidity, reduced credit risk, improved information aggregation, increased price transparency, reduced settlement or clearing costs, reduced hedging costs, reduced model risk, reduced event risk, increased liquidity incentives, improved self-consistency, reduced influence by market makers, and increased ability to generate and replicate arbitrary payout distributions. In addition to the trading of derivative securities, the present invention also facilitates the trading of other financial-related contingent claims; non-financial-related contingent claims such as energy, commodity, and weather derivatives; traditional insurance and reinsurance contracts; and contingent claims relating to events which have generally not been readily insurable or hedgeable such as corporate earnings announcements, future semiconductor demand, and changes in technology.

Hybrid securities defined as last-to-default credit default swaps over multiple name baskets and having protection against event risk. In the preferred embodiment, the hybrid security is defined as a second-to-default credit default swap over a two-name basket, wherein the underlying reference obligors in the basket are uncorrelated or substantially uncorrelated. A portfolio of second-to-default swaps over two-name baskets is provided, wherein the portfolio is defined in a manner that further reduces default risk through enhanced diversification achieved by recombining underlying reference obligors in different second-to-default baskets. A structured investment in a portfolio of underlying second-to-default swaps over two-name baskets is provided using a collateralized debt obligation (CDO) structure.

The present disclosure includes biomarkers, methods, devices, reagents, systems, and kits for the evaluation of risk of a caradiovascular (CV) Event within 5 years. In one aspect, the disclosure provides biomarkers that can be used alone or in various combinations to evaluate risk of a CV event within 5 years. In another aspect, methods are provided for evaluating risk of a CV event within 5 years in an individual, where the methods include detecting, in a biological sample from an individual, at least one biomarker value corresponding to at least one biomarker selected from the group of biomarkers provided in Table 1. In a further aspect, methods are provided for evaluating the risk of a CV, where the methods include detecting, in a biological sample from an individual, at least one biomarker value corresponding to at least one biomarker selected from the group of biomarkers provided in Table 2. In a further aspect, methods are provided for evaluating the risk of a CV event in an individual, generally within 5 years, where the methods include detecting, in a biological sample from an individual, at least one biomarker value corresponding to at least one biomarker selected from the group of biomarkers provided in Table 3.

According to one embodiment of the invention, a computerized method for addressing intrusion attacks directed at a computer includes receiving a data stream corresponding to a potential attack on the computer and calculating an event risk rating for the data stream. Calculating the event risk rating includes determining at least one component risk rating. In one embodiment, the component risk ratings are: a signature fidelity rating indicative of the likelihood the potential attack will affect the computer in the absence of knowledge regarding the computer, an attack relevance rating indicative of the relevance of the potential attack to the computer, and a target value rating indicative of the perceived value of the computer. The method also includes responding to the potential attack based on the calculated risk rating.

Systems and methods for reducing acute incident risks for dementia patients are provided. Benefits of the systems and methods include reducing healthcare costs, improving patient and caregiver outcomes and reducing caregiver burden. A server system analyzes data related to a dementia patient and the corresponding caregivers (e.g., family member, paid caregiver, physician) and calculates an acute incident risk. Based on the acute incident risk, the server system determines patient therapies to reduce the acute incident risk and also identifies caregiver education to improve the caregiver belief state, which reduces the acute incident risk. The system periodically re-calculates the acute incident risk and identifies patient therapies and caregiver education and motivation to further reduce or maintain the acute incident risk.

A system and method are disclosed for analyzing security risks in a computer network. The system constructs asset relationships among a plurality of objects in the computer network and receives an event associated with a selected object, where the event has an event risk level. The system also propagates the event to objects related to the selected object if the event risk level exceeds a propagation threshold.

The embodiment of the invention provides a risk event alarm method and device. The method comprises the steps of: obtaining event risk parameters of a risk event to be evaluated in a plurality of information channels, and obtaining a propagation risk value of the risk event according to the event risk parameters of the information channels; obtaining a business risk value corresponding to the riskevent according to the business parameter of a business type to which the risk event belongs and risk parameters corresponding to the risk type to which the risk event belongs; and obtaining a totalrisk value of the risk event according to the propagation risk value and the business risk value; and if the total risk value is located in a predetermined alarm range, triggering alarm for the risk event.

A risk estimating system of network intrusion event comprises engine module for carrying out effectiveness analyzing filter and risk estimating calculation to intrusion event according to set condition , controlling and managing unit of engine module , display and report module of risk estimation result on intrusion event .

The present invention relates to a method and system for risk prediction for a support actuation system. The present invention includes a support actuation system for an automobile having a support actuation module and/or a risk prediction system. The risk prediction system includes a sensor, a processor, and/or a memory. The sensor detects images corresponding to identity data, environment data, event data, and/or behavior data, which are stored in the memory. The memory also stores a database including identities of users, environment risk values, event risk values, and/or behavior risk values. Using the identity data, the environment data, the event data, and/or the behavior data, the processor determines the environment risk value, the event risk value, the behavior risk value, and/or the total risk value for a user. When the total risk value is above a predetermined risk threshold, the support actuation module performs support actuation.

The embodiment of the invention discloses a vehicle insurance service data analysis method and system. The method comprises the steps of obtaining a vehicle pricing suggestion scheme corresponding todriving data through utilization of a vehicle insurance pricing analysis module; obtaining accident site data associated with a vehicle accident, and extracting before-accident driving data associatedwith the vehicle accident from the driving data based on accident occurring time; and generating a claim settlement decision reference scheme according to the accident site data and the before-accident driving data through utilization of a vehicle insurance claims settlement auxiliary model. According to the method and the system provided by the invention, the smart car information interconnection industry-oriented vehicle insurance data analysis method based on a safety multiparty computing system is provided; the reference for vehicle insurance precise pricing can be provided; a vehicle before-event risk threshold is computed; an accident process and an after-event site are analyzed; the reference for precise claim settlement decision can be provided; and the data is stored and verifiedthrough adoption of a blockchain technology, so the data is prevented from being tampered or disturbed.

The present disclosure relates to an industrial control network security early warning method and system, wherein the industrial control network security early warning method includes: obtaining security-related data of control events of the industrial control network; performing CEP analysis on the security-related data; and adopting a method based on deep learning The classifier performs risk identification of control events on the data analyzed by CEP. The industrial control network security early warning method and system of the embodiments of the present disclosure can be deployed in an industrial control site with limited resources, and is suitable for a single-node or multiple-node deployment environment, and the deployment method is more flexible. Moreover, the deployment method at the industrial control site reduces network delay, improves the processing and response speed of real-time data, and improves the risk warning capability. In addition, the use of deep learning-based classifiers for risk identification has higher identification accuracy, and the combination of CEP analysis and deep learning solutions has greatly improved the efficiency of risk identification.

The invention relates to methods and kits for assessing the risk, for an individual, of developing an adverse event upon treatment with a therapeutic antibody which is capable of Fab-arm exchange, said method comprising the steps of: a) providing a sample from an individual who is a candidate for treatment with said therapeutic antibody, b) assaying said sample for the presence of circulating IgG4 antibodies that binds an antigen known or suspected to be associated with a causative agent of said adverse event, and c) assessing, on the basis of the outcome of the assay of step b), the risk that the individual will develop said adverse event upon treatment with the therapeutic antibody, wherein the risk of development of said adverse event increases with increased level of said circulating IgG4 antibodies.

The invention discloses a financial futures trading system, which improves the trading speed, gives consideration to compliance risk control, provides rich pre-event and post-event risk control indexes for futures companies, and quickly controls risks. According to the technical scheme, the system comprises a member management terminal which is a client used by a broker company and is used for managing system and client information, checking real-time transaction data, displaying real-time data in a disk and setting risk control parameters; a transaction client terminal which is an order placing terminal for investors, and is used for reporting orders, withdrawing orders and querying funds and positions, and receiving market information of transaction products; and a preposed transaction risk control gateway which is deployed in a transaction channel and risk control preposed channel of the broker company, wherein the preposed transaction risk control gateway adopts a memory database for real-time calculation and quick serach, thus achieving quick data transmission between the transcation client terminakl and a transcation dealing system of an exchange. The connection between the preposed transaction risk control gateway and a physical database enables the broker company to control transcation risk and manage data in a real-time manner with the client management terminal.

By applying a data information risk control processing method and system based on cloud computing intelligence, an event risk description relation which covers more comprehensive and more accurate information can be obtained; and then event detection and analysis on a risk prediction level are carried out on related information such as business behavior operation intentions and business equipment network addresses of business participants in the obtained online business interaction records, and meanwhile, information covered by the event risk description relationship is more comprehensive and more accurate. When event detection and analysis at a risk prediction level are carried out, deep mining and analysis of various risk factors can be carried out from a global level through an event risk description relationship, so accurate and reliable risk control processing for online business interaction records is ensured, and thus, the risk control efficiency is improved. According to the embodiment of the invention, complete and reliable raw material information (event risk description relation) can be provided for risk control processing, so the trust index of business risk control processing is improved.

The invention discloses a risk early-warning method and system for a social public event, and the method comprises the steps: obtaining related information of telecommunication behaviors of a user and the related information of the public event; judging whether the user is an event affiliated person of the public event or not according to the related information of telecommunication behaviors of the user and the related information of the public event; carrying out the detection of the event affiliated person according to a preset abnormality detection rule, and carrying out the risk abnormality early-warning prompt of the social public event when an abnormality is detected. The method can maintain the social stability.

A method for producing an insurance model includes the steps of calculating insurance payouts, calculating daily call payouts, calculating statistics of insurance payout obligations, selecting an insurance premium, and selecting a hedge amount. One aspect of the present invention is to determine a combination of insurance premium to charge and a hedge amount to place using daily calls, or other such financial instruments, such that some measure of return of the total portfolio of the insurance policy meets some maximum or minimum criteria.

The invention discloses a sudden water pollution event risk evaluation method for a water conveyance project. The method comprises the following steps: to begin with, with characteristics of the water conveyance project and characteristics of sudden water pollution events and influence thereof being taken into comprehensive consideration, and based on a DPSIR module, an index system is established, and risk evaluation indexes covering driving force, pressure, state, influence and response five aspects, index grading standard and an index calculation model are provided; a risk evaluation index weight determination method based on an analytic hierarchy process is provided; and finally, overall influence of the sudden water pollution event on the water conveyance project and risk grade are determined through a comprehensive evaluation method. The method and the risk grade evaluation result can effectively judge the influence degree of the sudden water pollution events on the water conveyance project; a more accurate risk evaluation system is established; and the method can provide decision information support for making scientific and effective early warning and preplanning of management personnel of the water conveyance project, and has wide practical prospect.

The invention belongs to the field of network security technologies, and particularly relates to a network security correlation analysis method based on complex event processing. Different events from different network even sources are correlated and analyzed. According to the network security correlation analysis method, threatening influences on a whole network by security events and considerations given to importance of directly attacked equipment or software are taken into account, multi-level analysis is performed on security events generated by serial operation on the same object through a multi-level rule, and all security event risk values can be accumulated to achieve the purpose of integrally analyzing the object. The multi-level correlation matching mode is adopted, on one hand, the network security correlation analysis method meets the requirement of the logic mode that an attacker generally needs multiple steps when initiating attacks, on the other hand, risk accumulation summation is performed on the multiple events, and complex relations between the events are comprehensively considered. In this way, potential threats in the network are easily detected so that early warning and processing can be performed to protect the network.

The invention relates to a risk registering method of a petrochemical device. The risk registering method of the petrochemical device mainly solves the problems that in the prior art, the occurrence probability of the events, caused by people, such as non-planned parking is high and the stability of device operation is low. According to the technical scheme, in the risk registering method of the petrochemical device, qualitative analysis and a quantitative risk matrix are combined for conducting risk assessment, potential risks existing in the production process of the petrochemical device are recognized and assessed, analysis evaluation is conducted on the various risks, classifying, grading and sorting are conducted on the risks, a risk registering database system of the petrochemical device is established by using the database software technology, matching and querying of root causes are realized according to the analysis result, an intelligent operation event risk recognizing function is designed, intelligent correlation of MES (Manufacturing Evaluation System) operation events and a risk registering database is realized, and risk levels, classes, causes and operation recommendation of the operation events are provided timely. The risk registering method of the petrochemical device well solves the problems and can be used in risk registering of the petrochemical device.

The invention discloses an event risk early warning method based on data mining, electronic equipment and a medium. The event risk early warning method comprises the following steps: acquiring recorddata of a historical terrorist attack event and a to-be-tested event; Preprocessing the record numbers of the historical terrorist attack events and the to-be-tested events; Classifying the data obtained after data preprocessing by adopting a clustering algorithm, and dividing the data into a plurality of types of data; Extracting a plurality of features from each type of data by adopting a principal component analysis algorithm; Performing feature integration on all features extracted from all classes of data to obtain a feature set; Extracting a plurality of index features from the feature set by adopting a principal component analysis algorithm; Calculating the weight of each index feature by adopting an improved entropy weight method; And for the characteristic value of each index characteristic of each event, carrying out weighted calculation by adopting a corresponding weight, sorting calculation results from large to small, outputting a sorting sequence number of the to-be-tested event in all sorts as a result, and if the sorting sequence number is smaller than a set threshold value, sending out an early warning signal.