682results about How to "Effective assessment" patented technology

Methods and systems for long term monitoring of one or more physiological parameters such as respiration, heart rate, body temperature, electrical heart activity, blood oxygenation, blood flow velocity, blood pressure, intracranial pressure, the presence of emboli in the blood stream and electrical brain activity are provided. Data is acquired non-invasively using ambulatory data acquisition techniques.

A health care operating system (10) includes multiple health care center objects (44). Smart devices (42) are coupled to the health care center objects (44) and include body internal control circuits (64, 70, 134). A database (20) stores information related to the health care center objects (44). A server (18) is coupled to the database (20). Multiple controllers (46, 156, 158, 314, 320, 353, 360) are coupled to the server (18) and write and/or read the information to and from the smart devices (42) utilizing electromagnetic induction. A health care center network (10) also includes the health care center objects (44) and the smart devices (42). The smart devices (42) inductively transmit identification signals. The database (20) stores the information. The controllers (46, 156, 158, 314, 320, 353, 360) within multiple facilities (172, 174, 342, 344, 346, 348, 350) communicate with the server (18) in response to the identification signals.

The present invention provides methods, systems, and computer program products that are useful for establishing contractual terms and agreements between health care providers and health care payors. For example, one embodiment of the present invention provides a method for predicting a person's payment of a medical debt. Another embodiment of the present invention provides a method for predicting a propensity of a group of one or more health care participants to pay an actual or potential medical debt.

The invention relates to a physiological signal quality evaluation method and system based on constrained estimation. The method comprises the following steps: receiving to-be-evaluated signal sections of a quasi-periodic physiological signal, performing pretreatment, waveform analysis identification and signal period segmentation to the signal sections, carrying out feature point detection to each cycle of signal section, and extracting preset physiological feature parameters of the physiological signal; for each signal section, combining the extracted physiological feature parameters to form feature vectors, performing constraint-based modeling according to transcendental knowledge of the physiological signal, and further establishing an analyzable evaluation system with constraint timing; and using a constraint evaluation model to trace sequential change of physiological parameters, combing a preset rule base and sequential change information, rating the signal quality of the quasi-periodic physiological signal, evaluating the validity of signal data of the signal sections of the quasi-periodic physiological signal, updating a time sequence evaluation system, and rating according to iteration of the periodic signal sections until the signal quality rating of all the signal sections of the quasi-periodic physiological signal is finished.

A system and method, a machine, and an article of manufacture of an occupational performance system and method for achieving occupational performance of competency based education and work force standards. The occupational performance system and method for achieving occupational performance includes: first, setting competency based goals with a goal setting diagram, to sequentially browse goal element lists, to sequentially select goal elements, to set competency based goals; second, recording in a performance record the competency based goals, goal status updates, progress notes, assessments, and artifacts in the performance record; and third, interacting in a community of practice including community members engaging in community activities, and sharing the performance record, and performing storage, retrieval, and operation of various combinations of occupational performance data fields selected from the competency based goals, performance record, and community of practice to improve occupational performance of the community of practice within the occupational performance system.

The invention relates to a network security situation assessment method, in particular, a Bayesian network-based multi-step attack security situation assessment method. The method includes the following steps that: multi-step attack generating patterns are mined through association analysis, so that an attack graph can be constructed; a Bayesian network is established according to the multi-step attack graph, attack wills, probability of success of attacks and the accuracy of event monitoring are defined as the probability attributes of the Bayesian network; based on the event monitoring, a multi-step attack risk is calculated according to the posterior reasoning and cumulative probability of the Bayesian network; and the security situations of a host and the whole network are quantitatively assessed according to a hierarchical quantitative assessment method. With the method of the invention adopted, the problem of lack of correlation analysis in a network security situation assessment process can be solved. According to the method of the invention, monitoring events are taken into risk assessment, and a network security situation assessment model is accurately established, and therefore, the effectiveness and real-time performance of the method of the invention can be enhanced.

The invention relates to a system for evaluating the performance of a satellite navigation system. The system has a real-time evaluation mode and a playback evaluation mode and comprises a system positioning accuracy evaluation module, a system velocity measurement accuracy evaluation module, a system availability evaluation module, a system completeness evaluation module, a configuration holding capacity evaluation module and a multipath delay evaluation module, wherein the system positioning accuracy evaluation module evaluates system positioning accuracy by calculating a user equivalent range error and using a statistical method; the system velocity measurement accuracy evaluation module obtains a system velocity measurement accuracy conclusion by calculating a user pseudo-range error and using the statistical method; the system availability evaluation module respectively calculates the availability of the common mode and a wide area differential mode to obtain a system availability conclusion; the system completeness evaluation module obtains a system completeness conclusion by calculating the completeness of three parts, namely a satellite, a ground operational control system and a receiver; the configuration holding capacity evaluation module obtains a configuration holding capacity conclusion by counting constellation occupied time percentage; and the multipath delay evaluation module obtains a multipath delay conclusion by calculating the delay, amplitude and phase difference of a multipath signal relative to a direct signal. The system is easy to implement in engineering and can effectively evaluate the performance of the satellite navigation system.

A cryosurgical device and system is provided comprising a pressurized container, a metered valve that regulates the retrieval of a coolant solution stored in the pressurized container and regulates the volume of coolant solution dispensed with each actuation of the device, an actuator that engages the metered valve when engaged, and directs the coolant solution to an extension tube, which directs the coolant solution away from the pressurized container, and an applicator head configuring an open-ended enclosure attached to a distal end of the extension tube.

The invention provides a grid-side regional distributed photovoltaic operation and maintenance management system and a grid-side regional distributed photovoltaic operation and maintenance management method. The management system and the management method orient to the requirements of provincial and municipal electric power companies for regional distributed photovoltaic grid-connected monitoring and operation management, achieve the regional distributed photovoltaic data acquisition, region monitoring, grid-connected management, billing supervision and safe operation inspection, solve the technical difficulties of data fusion, operational monitoring, data analysis and the like after provincial and municipal large-scale distributed photovoltaic access, improve a distributed photovoltaic integrated management system, enhance distributed photovoltaic integrated management level, operation and maintenance analysis level and operation service level, increase distributed power supply access efficiency, and ensure safe and economical operation of the power grid.

The invention discloses a detection method and device of surface defect of a mechanical part based on machine vision. The detection method comprises the steps of: carrying out positioning, filtration, enhancement, binaryzation, morphological treatment, boundary tracing, characterization extraction and the like on the collected surface images of the mechanical part; and judging whether a defect exists through the size of a defect area or not. The detection device comprises a position transmission module, a position control module, a clamp, an image collecting module and an upper computer for processing the image and sending a position control instruction, wherein under the control of the upper computer and the position control module, the position transmission module can move in an X direction, a Y direction and a Z direction, and can rotate around a Z axis; the image collecting module comprises a camera and a light source; and the camera and the position control module are respectively connected with the upper computer. By using the detection method and device, nondestructive detection is carried out based on the machine vision, irregular parts can be detected, no demagnetization problem exists; and the detection method and device have the advantages of high detection precision and high efficiency.

The invention discloses a photovoltaic power prediction method based on a convolutional neural network and meta-learning. The method belongs to the technical field of renewable energy development andutilization, and comprises the steps of establishing a deep convolutional neural network model, taking historical photovoltaic power data, historical meteorological data and numerical meteorological forecast data as model input, and taking photovoltaic power of a day to be predicted as output to form a model training sample; analyzing the weather type of the day to be predicted based on the radiation data in the numerical weather forecast, and selecting a similar day training sample; based on a meta-learning strategy and similar day training samples, training a neural network model by using eight loss function indexes, and outputting eight prediction results to realize point prediction and probability prediction of photovoltaic power. The invention also discloses a prediction system of themethod. The method can adapt to photovoltaic power prediction conditions of different seasons and different weathers, has extremely high prediction precision, and can effectively improve the operation stability of the photovoltaic grid-connected system.

Automated generation of reports based on insured persons' motor vehicle records. Insurance carriers can automatically obtain, at appropriate times, customized reports for use in monitoring and assessing insured persons. Incident data regarding the insured persons' motor vehicle records is received and translated, according to the insurance carriers' pre-set designations, into a customized report. For example, the insurance carriers can designate the reports' format, content, generation times, and output times. Such designations can depend upon other insurance-carrier-specific designations. For example, the designations can depend upon whether certain incident data is deemed “selective” or “non-selective.” For example, selective information can be more urgent to the insurance carrier than non-selective information. Allowing insurance carriers to designate when, how, and in what format, they wish to receive each of various types of information permits for more effective, more efficient, continuous monitoring and assessment of insured persons.

The invention relates to the field of information safety, and provides a dynamic virus detection method for equipment based on the Android system. The method comprises the following steps: the on-going target process required to be subjected to virus detection is acquired; a primitive API (Application Program Interface) function which is assigned in a dynamic library loaded through the target process is redirected into the API function in the interception program; the suspicious act of the target process is detected. According to the invention, interception and troubleshooting are performed in the Android underlying library, so that more underlying suspicious acts of the application program can be evaluated more effectively, and the detection method is a convenient and efficient virus detection method.

The invention provides an MODIS satellite high-precision monitoring method for chlorophyll-a in a eutrophic lake water body. The method comprises the following steps: screening a chlorophyll-a evaluation index (BNDBI) which is sensitive to the concentration change of chlorophyll-a and not affected by highly suspended matters, thin cloud and solar flares; acquiring the quantitative relationship between BNDBI and the concentration of chlorophyll-a on the basis of biological optical model simulation; acquiring a chlorophyll-a inversion algorithm based on ground measured spectrum (Rrs) and BNDBI by referring to water body spectral information and corresponding water body chlorophyll-a concentration of 2013-2014 lake field monitoring; acquiring the quantitative relationship between the ground monitoring and remote sensing reflectance ratio (Rrs) and Rrc after simulated Rayleigh scattering correction by simulating different aerosol types and thicknesses and different solar elevation angles, satellite observation angles and azimuth angles; and extending the chlorophyll-a inversion algorithm based on ground measured spectrum data to satellite image data after Rayleigh scattering correction. Based on the method, inter-annual and inter-monthly change rules and spatial distribution of chlorophyll-a in a eutrophic lake can be acquired accurately.

The invention discloses a microwave over-the-horizon radar echo chart calculating method, which comprises the following steps: 1) determination of relevant parameters, target parameters and environment parameters of a microwave over-the-horizon radar; 2) prediction of characteristic parameters of an evaporation waveguide and measurement of characteristic parameters of a surface waveguide; 3) calculation of an atmosphere waveguide or atmosphere refraction propagation sea surface glancing angle; 4) calculation of an atmosphere waveguide or atmosphere refraction propagation factor; 5) calculation of a sea clutter and target echo power diagram; and 6) simulation of a dynamic radar echo chart. The disclosed microwave over-the-horizon radar echo chart calculating method takes influence, formed under ocean hydrological conditions, of atmospheric duct propagation on sea surface echoes and target echoes into full consideration under the actual microwave over-the-horizon radar working environment, provides an actual radar beam sea surface grazing angle calculating method under the atmospheric refraction or atmospheric duct condition on the basis of radar system parameters and marine hydrometeorological parameters, and with relevant sea clutter models being combined, can effectively predicate and estimate the sea surface echo power.

The invention designs a cognitive assessment system comprising an information module, a test module and an analysis module. The information module is used for getting medical information matching the test module according to the data of an object and building a complete cognitive assessment database. The test module gets cognitive test data of the object through test, and includes the following five sub modules: an attention and executive function test module, a memory test module, a mathematics and computing power test module, a language test module, and an action and behavior control and plan test module. The analysis module determines the cognitive assessment result of the object according to the medical information acquired by the information module and the cognitive test data acquired by the test module. According to the invention, all sorts of cognitive functions are refined, mutual interference between cognitive domains is minimized by understanding the relationship and mutual influence between different capabilities, and the cognitive situation of an object is evaluated objectively to help clinicians to make an individualized rehabilitation plan for the assessment object.

The invention provides an optimal protection policy analysis system and method based on an improved ant colony algorithm. The system comprises a network risk assessment subsystem, an attack path prediction subsystem and a security policy management subsystem. The method comprises the following steps: 1) importing a Bayesian probabilistic model to describe the complex relationship between multiple steps of atomic attacks, and constructing an attack diagram by using the Bayesian belief network to evaluate a network security risk; 2) simulating a decision making process of an attacker in combination with the quantitative indexes of the protection cost and the gain, and predicting a possible attack path; and 3) using the improved ant colony algorithm capable of calculating the quasi-optimal solution within a polynomial time to solve the security policy selection problem on the attack path. By adoption of the optimal protection policy analysis system and method, a risk solution can be provided for a network security administrator in time, the attack path prediction and protection strategy selection problems in network security protection are solved, and the security of the whole network under the condition of limited protection resources is effectively protected.

The invention relates to a method for evaluating the functional safety of a safety instrument system, belonging to the technical field of functional safety of safety instrument systems. The invention aims at reliably simulating and monitoring the safety instrument system, evaluating the functional safety and studying the variation condition of common cause failure of the safety instrument system. The method comprises the following steps of: controlling the functional safety of a controlled system by a safety instrument system; analyzing the initial risk of the safety instrument system and determining the grade of safety integrity; verifying whether the safety instrument system reaches the determined grade of safety integrity; changing the constituting structures or devices of the safety instrument system; and repeating the above steps. In the technical scheme, the constituting structures or devices of the safety instrument system can be changed according to the studied specific condition to adapt for different application environments and requirements, and the variation condition of the common cause failure characteristic of the safety instrument system can be analyzed under different circumferences so as to provide important basis for studying the topic of common cause failure.

Provided is an electric power communication operation trend and business risk analyzing method based on deep learning. According to the deep learning theory, a multilayer deep confidence network architecture is constructed; electric power communication network history operation and monitoring data and related business system data governed by a district are used as training data of a learning model; all kinds of possible combinations of operation trend prediction and business risk evaluation are used as different output modes; finally a deep model which is capable of comprehensively judging electric power communication operation modes of the district is trained; history operation data and real-time business system data of the electric power communication network are used as test data of the model; and by using the trained deep network model parameters, operation trend prediction and business risk evaluation results of the electric power communication network can be obtained. The analyzing method is advantageous in that operation states of the electric power communication network can be more precisely evaluated; evidences are provided for business risks of the electric power communication network; and utilization efficiency of the electric power communication network is increased and safety of the electric power communication network is improved.

The invention discloses a TSN scheduling method oriented to a real-time application demand, and belongs to the technical field of the industry wireless network resource allocation. On the basis of thesoftware-defined network SDN, a time-sensitive software-defined network TSSDN is proposed, all time triggering flows and network topology are globally observed, the scheduling problem is imported into the TSSDN, and an integer linear planning (ILP) formula is proposed, the time slots are allocated to the time triggered flow, and the time slots are routed to avoid network queue; and meanwhile, theenergy utilization rate of the distributed time slots in the network can be maximized, and the routing and the transmission time table are computed. The TSN scheduling method disclosed by the invention solves the constraint optimization method for computing the transmission table is solved.