86 results about "Risk status" patented technology

An arrangement for performing active malicious web page discovery is provided. The arrangement includes a web monitor module, which is configured to monitor a plurality of potential suspicious unified resource locators (URLs). The arrangement also includes a crawler module, which is configured to download the plurality of potential suspicious URLs. The arrangement further includes a malicious page identifier (MPI), which is configured to verify a set of risk statuses for the plurality of potential suspicious URLs.

A system for tracking compliance with policies related to management of risk for a given enterprise provides risk status feedback on a number of managerial levels. The system notifies users of potential problems with non-compliance of enterprise policies set on a high level of enterprise management, and prompts the users to take steps to achieve compliance. The enterprise policies are designed to protect the enterprise from various forms of risk associated with enterprise activities. Accordingly, minimizing risk across enterprise operations, subdivisions, projects and applications produces an overall benefit of reduced liability or exposure to liability for the entire enterprise. A compliance status is provided by business groups at all levels of the enterprise, and consolidated for each management level to which the risk status is promoted. Higher level managers can view summaries of risk management status for the business divisions, and select particular statuses to view the condition of compliance among various business groups for which the manager has responsibility.

The invention discloses a prediction method of driving risk based on a hidden Markov model. The method comprises the steps of (1) classifying driving risk states through a cluster analysis method based on vehicle operating characteristics, (2) estimating the influences of a driver behavior and surrounding traffic environment characteristics on a transition probability between driving risk states through multiple logistical models for different driving risk states, (3) with a risk state as a hidden state, with an actual observed vehicle movement variable as a state output value, with multiple logistic model parameters as parameter initial values of a state transition probability matrix, establishing a hidden Markov chain model that reflects the evolution rule of driving states, and (4) obtaining the vehicle operating characteristics in real time and predicting a future risk state based on the hidden Markov chain model. According to the method, the hidden Markov model which can reflect the above characteristic real-time change and has a variable state transition probability is established, the accuracy and prediction accuracy of a driving risk model are improved, and the real-time requirements of anti-collision warning can be satisfied.

A system for facilitating the provision of health care to patients, including computerised means (135) for logging patient data relating to health of the patients, and an administration system (105) in communication with the computerised means and configured to determine a risk status of each patient based on the patient data The administration system is also configured to, for each patient: transmit a first direction to a first health care provider to attend the patient, depending on the risk status of the patient; determine whether the first health care provider has confirmed attendance at the patient within a first time period; and transmit a second direction to a second health care provider to attend the patient within a second time period if attendance by the first health care provider was not confirmed.

The invention provides an obstacle trajectory prediction based auxiliary driving method and system. The method includes obtaining environment data around a vehicle collected by a vehicle sensor; determining the drivable area of a dynamic obstacle around the vehicle based on the environment data; predicting the driving trajectory of the dynamic obstacle by utilizing the historical status information and the drivable area of the dynamic obstacle; and judging the conflicting risk status of the driving trajectory of the dynamic obstacle and the driving trajectory of the vehicle. Thus, early warning can be performed by calculating the risk coefficients of the trajectory of the dynamic obstacle and the trajectory of the vehicle.

The invention discloses a karst tunnel water outburst and mud outburst overall process gradual dynamic risk assessment method. The method includes the steps that 1, in the tunnel investigation stage, the tunnel address and the hydrogeological information of the surrounding rock near the tunnel are obtained, that is, the hidden danger environment for water outburst of the tunnel is obtained, and the risk states of the geological conditions of all segments of the tunnel are known; 2, the risk rating value is worked out according to an expert evaluation vector and a factor weight vector, and consistency check is conducted; 3, danger factors are introduced to influence factors of risk evaluation, the hidden danger environment and the danger factors are considered comprehensively, water outburst risk evaluation is conducted, and the segment distribution feature with the tunnel water outburst risk is divided; 4. The values of all indexes are corrected in real time in combination with actual field construction so as to achieve dynamic evaluation of the water outburst and mud outburst risks. The purposes of optimizing construction organization design and avoiding medium and large water outburst geological disasters are achieved through dynamic construction risk evaluation and control, and important data are provided for later-period tunnel operation risks, and the method has very wide application prospects.

The invention provides an area integrated environment risk evaluation and portioning method, for reflecting the environment risk status of an area. The method comprises the following steps: obtaining area environment risk correlation information, and according to an area integrated environment risk system theory, through combination with the obtained area environment risk correlation information, constructing an area integrated environment risk evaluation index system, wherein the index system comprises a risk source harm index, a risk field intensity index, a risk acceptor vulnerability index and a risk control mechanism validity index; determining an index weight and quantification model of the index system; according to the determined index weight and quantification model of the index system, obtaining an area integrated environment risk index; and according to the area integrated environment risk index, performing risk partitioning on the area so as to obtain an area integrated environment risk partitioning graph. The method provided by the invention is applied to the field of environment science and environment risks.

The invention discloses a transmission line risk evaluation system. The system includes a collection module, an evaluation module, a storage module and a display module. The collection module collects transmission line operating data, tower specification parameters and meteorological real-time monitoring data. The evaluation module analyzes the collected data, carries out risk level evaluation on towers on transmission lines, and carries out risk state evaluation on sections on the transmission lines. The storage module stores the collected data and evaluation results. The display module displays the collected data and the evaluation results on a GIS platform. According to the system, processing and analysis results of the system are enabled to be highly accurate and applicable through connecting the transmission line data and the meteorological monitoring data in a butt-joint manner, data sharing is realized, and the platform is provided for transmission line display and an information concentration.

The present invention provides a construction road section risk evaluating method based on a cloud model. The main realization process comprises the steps of (1) data collection, and establishing an original database, (2) selecting an input variable, (3) carrying out input variable initial concept division, (4) carrying out concept jumping and extracting a cloud characteristic value, (5) constructing a rule database and determining a weight value, (6) finding an activation intensity maximum, and determining the level of concept, (7) carrying out rule database access, and obtaining a risk status level, and (8) calculating the concrete score of a driving risk status, and completing quantitative evaluation. According to the method, the cloud model theory is applied to the driving risk status evaluation of a construction road section, the fuzziness and randomness are considered comprehensively, and the method has better adaptability.

The invention discloses a station terminal fault risk early-warning method, a device thereof, a terminal and a storage medium. The method comprises the steps of acquiring current operation data of thestation terminal, wherein the current operation data comprise a current health parameter value; extracting a contrast health parameter value which comprises the preset threshold range of the currenthealth parameter value in a pre-established fault characteristic knowledge database and fault information that corresponds with the contrast health parameter value, calculating the extracted contrasthealth parameter value and the corresponding fault information in a preset algorithm, thereby obtaining the current fault risk state of the station terminal; wherein the fault risk state comprises a fault type and a fault type occurring probability; and when the fault type occurring probability reaches a preset fault early-warning threshold, giving out a fault early-warning signal. The station terminal fault risk early-warning method, the device thereof, the terminal and the storage terminal can realize early warning on a latent high-possibility fault risk and further improve timeliness in fault processing.

The invention provides a risk test method for power gird dispatching operation. The risk test method for the power gird dispatching operation comprises the steps: receiving a current operation command conducted to target equipment and confirming risk state information; obtaining the number of nodes which are beyond a voltage boundary, overload number of branches, actual voltage amplitude value of each node which is beyond the voltage boundary and actual transmitting power of each overload branch under the states of failed operation, successful operation and successful operation development; obtaining load reduction quantity after failure and load reduction quantity under successful operation; obtaining real-time probabilities when operation succeeds and fails; obtaining real-time probability of failure after operation fails and real-time failure probability of the target equipment when operation succeeds; obtaining a risk indicator of the current operation; and sending an alarm out when the risk indicator is larger than or equal to a preset value. The invention further provides a risk test device for the power gird dispatching operation. The risk test device for the power gird dispatching operation is capable of pre-testing security status of a power gird caused by the power gird dispatching operation and guaranteeing the safe operation of an electrical power system.

The invention mainly belongs to the transaction decision technology field and particularly relates to a transaction decision system based on a risk control quantitative model and a method. The system carries out multifactorial quantitative securities selecting and market timing and carries out real-time quantitative evaluation on investment risks, buy, sell, profit stop and loss stop instructions are provided through a client in real time, and the position risk state prompting information is further provided in real time; the system comprises an input module, a processing module, a transaction decision module and the client, wherein the client comprises an instruction output module. Through the system, an excellent transaction object and low-cost transaction opportunity are provided for the client through a multifactorial quantitative market timing model, simulation trial and error transaction is carried out through a risk control model, an error instruction is provided with a loss stop value, forced close out is realized, a profit stop value is provided for a correct instruction, and quantitative transaction or subjective transaction is provided.

Methods and systems for seamless adjustment of treatment are disclosed. A determination is made as to whether to intervene with a patient's treatment. Implanted device memory data is acquired over a pre-specified time period. Risk status is determined from the device memory data. Another external device memory data is acquired over a pre-specified time period. A determination is made as to whether to adjust treatment of the patient in response to the risk status, the data acquired from the implanted device memory and the external device memory data.

The invention relates to a method for recognizing a risk state of a power distribution network. The method is implemented by a serial computing method and a parallel computing method. In the serial computing method, risk state continuous recognition and tracking are performed after the risk state is recognized; in the parallel computing method, risk state continuous recognition and tracking and recognition of risk states of a power grid in various states and in each stage are performed at the same time; the serial computing method and the parallel computing method are different design ideas in the full power distribution network risk state recognition process, and the recognition results of the serial computing method and the parallel computing method are the same. By the method, judgment and evaluation of a risk index computing result are realized by adopting a design of a rule base, a knowledge base, a professional base and a risk base and online generation thereof, so that the risk state of the current power distribution network can be determined; due to the design of the rule base, the knowledge base, the professional base, a single and independent risk index for judgment is avoided and the judgment, the recognition and the evaluation of the risk state of the power distribution network are realized by adopting a comprehensive risk index.

The embodiment of the invention discloses a signal lamp fault detection method, device, equipment and medium, and relates to the field of traffic signal lamps. The method comprises the steps of obtaining operation parameters of a signal lamp to be detected; according to the operation parameters and pre-learned signal lamp operation rules, determining whether the operation state of the signal lampto be detected is in the fault state or the fault risk state. According to the signal lamp fault detection method, device, equipment and medium, the operation state of the signal lamp is automaticallyjudged.

The invention provides a food safety risk prediction method based on the hidden Markov model. The method comprises the steps: analyzing every step of a food supply chain, and finding out a critical control point of each step; analyzing the critical control point of each step and using the critical control point as a quantitative index of the HMM (hidden Markov model), and establishing a HMM; initializing parameters of the HMM, and training the parameters of the HMM according to a visible state sequence of the HMM and the real state of a system; and performing the risk assessment and value-at-risk calculation on the risk grade of the food supply chain. According to the invention, the HMM is adopted to assess the food quality and safety, the dynamics of every step is considered, the risk state can be responded in real time, a quantitative and qualitative-combined assessment method is adopted, the degree of the supply chain risk can be more precisely described than before, and the method is helpful for decision maker to timely adopt corresponding measures. The risk assessment model can assess the dairy product and has strong expansibility so as to apply to other fields of food safety.

The present invention relates to methods and devices for testing the physical condition of an individual. The methods and devices rely on the use of a marker of physical condition, and have applications including determining an individuals state of physical recovery from prior physical or athletic activity, determining an individuals physiological readiness for optimal physical performance, determining changes in the risk of (or for assessing progression of) cardiovascular disease in an individual, and for determining exercise and/or athletic training instructions for an individual based on their recovery state, physiological readiness to perform, and/or their cardiovascular disease risk status. The methods and devices require a comparison between the rate of increase in heart rate of an individual during a sub-maximal physical activity, and a predetermined reference measurement. A rate of increase in heart rate which is faster or slower than the predetermined reference measurement will allow determination of the individuals recovery state, physiological readiness to perform, and/or their cardiovascular disease risk status.

Embodiments relate to devices and methods for monitoring, identifying, and determining risk of congestive heart failure (CHF) hospitalization. Methods include determining physiological values of a patient by electrocardiogram (ECG), bioimpedance, and 3-axis accelerometer, filtering the physiological values, comparing physiological values to baseline parameters and determining CHF risk. Devices include a 3-axis accelerometers, bioimpedance sensors, and an electrocardiogram, each capable of measuring patient physiological values, and one or more processors to receive the measured physiological values.

The invention discloses an intrusion process layering online risk assessment system and a method, which are used for assessing the risk condition produced on three layers of the service, the host and the network of an occurrent intrusion process in real time. In the invention, on the layer of the service, an evidence theory is used for fusing multi vectors in an alarm thread to compute a risk index, wherein the vectors can response risk change conditions, the objective condition of intrusion risks is reflected by the risk index, and simultaneously, with target risk distribution reflected by subjective safety awareness, the risk condition of a target is comprehensively assessed; on the layer of the host, a risk assessment method based on a cask principle is provided; and on the layer of the network, a safety dependence network concept is provided, and an improved risk spreading algorithm is utilized so as to complete the risk assessment of the layer of the network. According to the invention, the alarm processes of alarm verification, aggregation and correlation as well as alarm confidence learning are closely combined with the risk assessment, so that the subjectivity, the fuzziness, the uncertainty and other problems in the risk assessment are better processed.

The invention discloses a wind turbine generator unit state monitoring system performance assessment method which includes building a Markovian model for reflecting state of a wind turbine generator unit, providing calculation steps and corresponding mathematical formulas of probability of different state of the system at a certain time; building a mathematical module reflecting state, including normal state and failure state, of a single sensor; building a system function reflecting the state of the whole monitoring system, and classifying the states of the system according to quantities of the sensors in normal states or in failure states into normal state, risk state and failure state. To keep the availability of the system is not lower than a certain preset value, the minimum quantity of standby sensors, the maximum quantity of standby sensors allowing to be short in the system are calculated and determined according to the steady-state value of the availability of the system. By the wind turbine generator unit state monitoring system performance assessment method, the basis can be provided for making daily maintenance plane for a wind turbine generator unit, and performance of the system can be kept to the utmost extent with lowest maintenance cost.

The invention discloses a Beidou satellite-based mountainous area bend vehicle anti-collision alarm method and system. The method includes the following steps that: after vehicles enter a mountainous area, and the position and speed information of the vehicles is obtained through Beidou positioning; latitudes and longitudes are converted into a Gaussian plane coordinate system through coordinate transformation, a distance between the two vehicles is calculated; and when the two vehicles are too close, collision risk state estimation is performed, and alarm signals are emitted according to alarm rules. According to the Beidou satellite-based mountainous area bend vehicle anti-collision alarm method and system of the invention, information such as the position and speed information of the vehicles is measured in real time through the Beidou satellite, the operating states of the vehicles in a bend are calculated, and the collision risk state of the vehicles in the bend is estimated, and the effective alarm of the vehicles in the bend of the mountainous area can be realized.

The invention discloses a method based on multi-model stacking fusion prediction, which aims at solving the problem of using weak variable to objectively and fairly evaluate the operation status of anenterprise in the absence of strong variable, and predicting the operation risk status of the enterprise in a period of time in the future. At first, that invention carry out data analysis on the enterprise operation behavior data, and carries out data preprocess and feature extraction on the enterprise operation behavior data; Using the extracted features to train several single models and verify the effectiveness of the model, select the optimal single model for stack fusion; The probability value of enterprise operation risk is predicted by the method of multi-single-model stacking fusion.This method has a good ability to predict the business exit risk of enterprises.