33 results about "Risk research" patented technology

The invention discloses a method and device for extracting microplastics in dewatered sludge. The method comprises the following steps: carrying out freeze-drying homogenization on the dewatered sludge, then adding a density solution and stirring to obtain turbid liquid, and standing until the turbid liquid is layered completely; transferring microplastics particles which float in a non-precipitating layer to a filter membrane under the effect of an air pump, and rapidly collecting the microplastics particles; continuously adding the density solution into a filter flask and keeping the solution parallel and level to a suction nozzle, and then washing a pipe for several times to transfer the microplastics particles adhered to the wall of the pipe to the filter membrane; adding the intercepted microplastics particles into a hydrogen peroxide solution, and carrying out shock reaction to remove organic matter impurities in the sludge; and drying to remove residual liquid, and cooling to obtain the final microplastics particles. The method has the advantages that the microplastics particles in the dewatered sludge are extracted on the basis of a density separation principle, and the method is rapid and simple to operate, low in sample demand quantity, high in microplastics particle recycling rate, good in reproducibility, high in practicality and widely applicable to ecological environment risk researches of the microplastics in the dewatered sludge.

The invention relates to a three gorges reservoir area water body eutrophication risk assessment early warning system and an analysis method thereof, and belongs to the technical field of water resource early warning. The system comprises a data acquisition subsystem, a preprocessing subsystem, a data analysis subsystem, an eutrophication evaluation subsystem, a risk early warning subsystem and anauxiliary subsystem. The data acquisition subsystem acquires various types of index parameters and stores the acquired data into a database. The preprocessing subsystem classifies, sorts and screensthe collected data, performs data normalization and dimension removal processing, and provides a basis for subsequent data analysis. Evaluation and early warning are objective and accurate, reservoirarea water eutrophication trend analysis and risk early warning processing can be timely and efficiently achieved, reservoir area water environment supervision efficiency can be improved, and technical support is provided for reservoir area water environment safety and eutrophication prevention and control. And the method can also be applied to eutrophication risk research of other reservoirs similar to rivers and lakes.

The invention discloses a method for preparing rodlike fluorescent labeled microplastics. The method comprises the steps of adding plastic fibers to a mixed solution of a dye stock solution and n-hexane for fluorescent labeling, winding the plastic fibers on a reel to align the plastic fibers and coating the plastic fibers with a frozen section medium; freezing, cutting into blocks, arranging the blocks into a cube, and fixing the cube on a histotome for continuous slicing; and finally washing slices by using ultrapure water, drying and weighing. Through the method, the common fluorescent microplastics of different shapes in the environment can be conveniently and quickly obtained, qualitative and quantitative analysis of distribution and enrichment rules of the microplastics of different shapes in an environment medium and a living body is facilitated, and the method can be widely applied to ecological environment risk research of various microplastics.

The invention relates to the technical field of risk management, and particularly relates to a disaster risk early warning management system based on cloud computing. The system comprises an infrastructure management unit, a data processing unit, a risk research unit and an early warning management unit. The data processing unit is used for processing the monitoring data; the risk research unit is used for calculating and evaluating the risk level of the disaster based on cloud computing; and the early warning management unit is used for displaying the analysis result and performing early warning. According to the design of the invention, various meteorological target state data can be acquired in real time, classified and counted, and disaster risks can be identified, evaluated and graded; the harm degree of natural disasters to the region can be evaluated more accurately; and disaster risk prediction conditions can be displayed in a multi-element manner, and predicted disaster risks can be fed back to the public in various manners so that emergency treatment and prevention arrangement can be performed in time, and casualties and economic loss conditions possibly caused by disasters can be reduced.

The invention discloses a meteorological disaster risk research and judgment method and system, and the method comprises the following steps: collecting meteorological disaster data corresponding to apreset monitoring region, and determining disaster-bearing body information corresponding to the meteorological disaster data; obtaining a pre-constructed disaster scene model corresponding to the meteorological disaster data; and analyzing the meteorological disaster data and the disaster-bearing body information based on the disaster scene model to obtain a meteorological disaster risk level corresponding to the meteorological disaster data. Visibly, by implementing the embodiment of the invention, the corresponding disaster scene model can be determined according to the acquired meteorological disaster data, and then the influence of the meteorological disasters is analyzed according to the disaster scene model to obtain the meteorological disaster risk level, so that the accuracy of early warning and forecasting of events influenced by the meteorological disasters is improved.

The invention discloses a recognition and early warning method for an abnormal behavior website, and the method comprises the steps of suspicious website clue recognition, website feature data analysis, operation subject information analysis, network public opinion data analysis, abnormal behavior website risk study and judgment and the like, and can fully guarantee a scanning range and recognition accuracy, and guarantee effective recognition of webpage text content; the method has the advantages that abnormal behavior website operation feature recognition is more accurate, the recognition rate is accurate, the network abnormal behavior suspicion of the target website is proved through multiple information levels, the network abnormal behavior risk research and judgment dimension is expanded, the abnormal behavior website recognition accuracy is effectively improved, and the false alarm rate is reduced.

The invention provides a coal mill blocking early warning method and system, and the method comprises the steps: recognizing the coal feeding condition of a coal mill according to the coal feeding amount data of the coal mill, and obtaining a recognition result; monitoring the running state of the coal mill according to the recognition result to obtain a monitoring result; according to the monitoring result, risk interval division is conducted on the coal feeding amount data, and time series data of continuous risk intervals are obtained; performing trend analysis and prediction on the time series data of the continuous risk interval to obtain analysis and prediction results; and according to the analysis and prediction result, outputting a coal mill wear blockage early warning grade. According to the technical scheme, hierarchical risk research and judgment and continuous risk window division are carried out, and window feature extraction and trend analysis and prediction based on time/frequency domain feature analysis are carried out, so that graded alarming on coal mill blockage is realized.

The invention provides a target person dynamic risk early warning method based on trajectory prediction and related equipment. The method comprises the following steps: acquiring data information of a target person; dividing the data information into basic information and historical time sequence feature information; constructing a target personnel knowledge graph according to the basic information, and determining a target personnel characteristic value list based on the target personnel knowledge graph; inputting the historical time sequence feature information into a pre-constructed time sequence prediction model, and outputting predicted time sequence feature information through the time sequence prediction model; combining the target person characteristic value list and the prediction time sequence characteristic information to obtain a future time period characteristic value list; and obtaining a risk score of the target person through a pre-constructed risk research and judgment model based on the future time period feature value list. According to the method, the timeliness, the accuracy and the interpretability of the prediction and early warning result are considered, and the hysteresis problem of a traditional early warning technical scheme is solved.

The invention provides a construction method of an operation risk ontology of a rail transit system. The method comprises the following steps: starting from four aspects of man-machine environment management according to rail transit system operation accident characteristics, constructing five types of sub-word libraries representing accident characteristics, and carrying out weight setting on the five types of sub-word libraries; calculating risk conceptual words of the accident data text based on the accident data text and the five types of sub-word libraries by using an improved TF-IDF, calculating weight values of the risk conceptual words according to weights corresponding to the five types of sub-word libraries, and extracting hierarchical and non-hierarchical relationships among the risk conceptual words by using an improved K-means algorithm; and constructing the rail transit system operation risk ontology according to the risk concepts of the rail transit operation risk ontology, the hierarchical and non-hierarchical relationships between the risk concept words and the weight values of the risk concept words. According to the method, the urban rail transit operation accident text risk can be effectively extracted, important data support is provided for rail transit system operation risk research, and a solid foundation is laid for risk prevention and control research.

The invention provides a method and a gateway for home network environment security risk assessment and detection. According to the method, in combination with historical records and results of home network environment security risk research and judgment, a home network environment security risk index is calculated by comprehensively considering the importance of intelligent terminal equipment in a service application scene, the risk level of vulnerabilities and the severity of security risk influences, so the data acquisition and detection frequency is dynamically set; therefore, the data acquisition and detection frequency is more effective and reasonable.

The invention discloses a service management and control method, device and system and a computer readable storage medium, and the method comprises the steps: inputting various types of risk information obtained in real time into a pre-trained risk research and judgment model, and obtaining a target risk type; generating a first management and control scheme according to the target risk type and the risk information when the target risk type is the risk type independently processed by the front-end equipment; controlling the target object according to the first control scheme; when the targetrisk type is a risk type cooperatively processed by the front-end equipment and the rear-end equipment, generating a second management and control scheme according to the target risk type and the riskinformation; and managing and controlling the target management and control object according to the second management and control scheme. The system comprises an information acquisition device used for acquiring various risk information of a target management and control area in real time; and the processor inputs the various risk information transmitted by the transmission module into a pre-trained risk research and judgment model to obtain a target risk type, and controls the target control object according to the target risk type.

The invention provides a benzene occupational exposure and carcinogenic risk assessment method, which comprises four aspects: a risk understanding module for understanding the theoretical relationship between benzene and carcinogenic risk and understanding the harmfulness of benzene; a risk research module that is used for looking up related data of the relationship between benzene and carcinogenic risk and related experiments, and looking up knowledge of a related benzene exposure mode and exposure quantity; a risk calculation module that is used for replacing the exposed benzene content with the benzene dosage change in the human body and simulating, then simulating and calculating the change relation between the benzene content in the human body and the carcinogenic risk, and finally calculating the carcinogenic risk; and a risk evaluation module that is used for evaluating and analyzing a result of the risk calculation module. Numerical simulation is performed on the benzene dosage in a human body by using a PBPK model and applying ERDEM software; then simulation calculation is carried out on a change relation between the content of benzene in a human body and the carcinogenic risk by using a dose-reaction relation, and finally Monte Carlo simulation is executed by using crystic ball software to simulate the carcinogenic probability.

The invention discloses a text clustering picture recognition method, device and system, which are characterized in that processing software texts are vectorized and clustered through an artificial intelligence algorithm, native camera software information and risk processing software are automatically distinguished, risk software for risk research and judgment is accurately found out, automatic early warning of suspected risk software is realized, the whole system is optimized, and the workload of risk research and judgment and the manual operation risk are greatly reduced.

The invention relates to the technical field of computer information processing, and in particular relates to a grade protection risk research and judgment method based on an artificial neural network ANNs. The method quantifies grade protection risk research and judgment indexes, and mainly utilizes TSNE and ANNs methods to identify dimension reduction features of risk indexes distributed in multiple dimensions, so as to automatically obtain a corresponding risk value and a risk interval where the risk value is located; and meanwhile, expert knowledge is used for marking the action range and the risk resolution capability of risk resolution means such as safety equipment and safety management measures, the action range and the risk resolution capability automatically match output risk values and risk intervals, and an optimal safety protection scheme is obtained. According to the method, the mode that risk levels are obtained by traditional level protection risk research and judgment through a scoring table is broken through, the processing speed of the level protection risk research and judgment is greatly increased, automatic output of a safety protection scheme is achieved to a certain extent, and the defects that the efficiency of a traditional scoring table and manual research and judgment of an expert is low, and expert knowledge is difficult to reuse are overcome.

The invention discloses a network security information sharing system and method based on expert joint evaluation, electronic equipment and a storage medium, and belongs to the technical field of network security. The problem that an existing network security information sharing mechanism is large in member analysis ability difference and low in risk research and judgment accuracy is solved, a dynamic weighted expert committee and an active learning thought are introduced into the information sharing and research and judgment process, a center node conducts risk category research and judgment on all security information through a trained risk classifier, a research and judgment result is fed back to node experts, the experts improve the analysis process of the experts according to the research and judgment result, and the center node uploads all safety information and risk categories output by the risk classifier to a superior data service processing center after performing data backup on the safety information and the risk categories, so the risk research and judgment accuracy in the network security information sharing mechanism is greatly improved, and the member analysis capability in the network security information sharing mechanism is enhanced.

The invention provides an electric welding smoke occupational disease hazard risk assessment method, which comprises the following four aspects: a risk understanding module for understanding related information of electric welding smoke and understanding the harm of the electric welding smoke to human health; the risk research module that is used for researching historical data of electrowelding smoke exposure concentration and related data of epidemic diseases easily infected by people; the risk calculation module that is used for carrying out field detection on the concentration of the electric welding smoke dust according to historical data of the exposure concentration of the electric welding smoke dust, obtaining a concentration change diagram, carrying out analog calculation on the relationship between the change of the electric welding smoke dust in the lung of a person and the risk, and finally calculating the distribution condition of the risk; and the risk evaluation module that is used for evaluating and analyzing a result of the risk calculation module. According to the invention, SPSS software is utilized to make a concentration distribution diagram of the electric welding smoke dust, a dose-reaction model is utilized to simulate the relationship between the change of the electric welding smoke dust in the human lung and the risk, and finally Crystal ball software is utilized to perform Monte Carlo simulation to calculate the distribution condition of the risk.

The invention provides a technical method for risk assessment of odor pollutants in a workplace. The technical method comprises the following four aspects: a risk understanding module for understanding components of odor pollution and confirming the position of the odor pollution source; the risk research module that is used for researching historical air concentration data and historical sampling data of the odor pollutants and investigating the disgust degree of people to the odor pollutants; the risk calculation module that is used for summarizing data results of the odor pollutants to the air pollution concentration to make a related concentration distribution table, and analyzing investigated data about the disgust degree of people to the odor pollutants; and the risk evaluation module that is used for evaluating and analyzing the data result of the aversion degree of the odor pollutants. According to the invention, SPSS software is used for making a distribution diagram of the odor pollutants in the area near the odor pollution source to the air pollution concentration, a dose-reaction model is used for analyzing investigated data of the disgust degree of people to the odor pollutants, and an analysis result is obtained.

The invention discloses a risk research and judgment method based on multi-modal learning and LSTM, and the method comprises the following steps: obtaining related data which requires space-time information features and other multi-source data information; carrying out preprocessing and multi-modal information fusion on the data; performing data processing according to the proposed data stream togenerate intermediate result data; performing risk research and judgment based on the improved LSTM; and obtaining a risk research and judgment result and calculating the accuracy according to the verification set data. According to the invention, through a multi-modal information fusion technology, multi-source data is subjected to technical fusion, and a vector with a specific length is generated. At present, an LSTM model is excellently transformed and innovated to a certain extent, an existing method for carrying out risk research and judgment on special personnel through a manual or simple data statistics method is optimized, and the risk research and judgment method for the special personnel in the public safety field under the data background is provided.

The invention discloses a face recognition management method for a hospital. The face recognition management method comprises the following steps: S1, collecting face and iris information of a patientat an entrance of the hospital; establishing a patient initial database; S2, collecting, verifying and tracking patient face information at a registration window, a stairway, a doorway or a consultation desk position, perfecting a patient database and sharing data with a medical diagnosis and treatment management system; and S3, acquiring face and iris information of the patient through a handheld terminal in a ward, and matching and verifying the treatment medicine and items to be applied. According to the invention, a patient database is constructed from hospital admission, is gradually perfected and shares data with the medical diagnosis and treatment management system; in the diagnosis and treatment process, the hand-held terminal is used for conveniently collecting face and iris information of a patient to match and verify treatment medicine and items to be applied, and medication and diagnosis and treatment safety is guaranteed; according to the invention, patient emotional behavior information monitoring is added, risk research and judgment calculation is carried out, early warning is carried out according to the risk research and judgment calculation, and an emergency plancorresponding to the risk is responded to in a hospital security system.