3104 results about "System model" patented technology

A system for intelligent monitoring and management of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a real-time energy pricing engine, virtual system modeling engine, an analytics engine, a machine learning engine and a schematic user interface creator engine. The real-time energy pricing engine generates real-time utility power pricing data. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The machine learning engine stores and processes patterns observed from the real-time data output and the predicted data output to forecast an aspect of the electrical system.

A surgical robotic system automatically calibrates tubular and flexible surgical tools such as endoscopes. By accounting for nonlinear behavior of an endoscope, the surgical robotic system can accurately model motions of the endoscope and navigate the endoscope while performing a surgical procedure on a patient. The surgical robotic system models the nonlinearities using sets of calibration parameters determined based on images captured by an image sensor of the endoscope. Calibration parameters can describe translational or rotational movements of the endoscope in one or more axis, e.g., pitch and yaw, as well as a slope, hysteresis, or dead zone value corresponding to the endoscope's motion. The endoscope can include tubular components referred to as a sheath and leader. An instrument device manipulator of the surgical robotic system actuates pull wires coupled to the sheath or the leader, which causes the endoscope to articulate.

Systems and methods for performing power analytics on a microgrid. In an embodiment, predicted data is generated for the microgrid utilizing a virtual system model of the microgrid, which comprises a virtual representation of a topology of the microgrid. Real-time data is received via a portal from at least one external data source. If the difference between the real-time data and the predicted data exceeds a threshold, a calibration and synchronization operation is initiated to update the virtual system model in real-time. Power analytics may be performed on the virtual system model to generate analytical data, which can be returned via the portal.

A system and method for providing data to a model of a building system includes a building control system with a communications network, a control subsystem for generating module deployment data and transmitting the module deployment data over the communications network, a memory for storing a three dimensional model of at least a portion of a building and a computer. A computer program executed by the computer includes computer instructions for associating module deployment data received from the communications network with the three dimensional model and modifying the three dimensional model based upon the module deployment data.

The invention provides an unsupervised domain-adaptive brain tumor semantic segmentation method based on deep adversarial learning. The method comprises the steps of deep coding-decoding full-convolution network segmentation system model setup, domain discriminator network model setup, segmentation system pre-training and parameter optimization, adversarial training and target domain feature extractor parameter optimization and target domain MRI brain tumor automatic semantic segmentation. According to the method, high-level semantic features and low-level detailed features are utilized to jointly predict pixel tags by the adoption of a deep coding-decoding full-convolution network modeling segmentation system, a domain discriminator network is adopted to guide a segmentation model to learn domain-invariable features and a strong generalization segmentation function through adversarial learning, a data distribution difference between a source domain and a target domain is minimized indirectly, and a learned segmentation system has the same segmentation precision in the target domain as in the source domain. Therefore, the cross-domain generalization performance of the MRI brain tumor full-automatic semantic segmentation method is improved, and unsupervised cross-domain adaptive MRI brain tumor precise segmentation is realized.

A system for analyzing an interactive voice response (IVR) system of a call processing center determines a complete sequence of events occurring within the IVR system. The IVR system being operable to automatically accept calls from callers and respond to input from the callers. The system models a call flow of the IVR system as a non-deterministic finite-state automaton. A recording of a plurality of calls to the call processing center is split, such that each of plural calls to the call center is in one audio file. For a plurality of calls, the system detects a complete sequence of DTMF and / or speech input to the IVR system, detects selected prompts issued by the IVR system, and inputs the detected sequence of DTMF and / or speech input as well as the detected prompts issued by the IVR system into the finite-state automaton to determine a call-event sequence for that call. The call-event sequence includes information regarding how that call left the IVR system.

A system for an intelligent web-based monitoring and management of an electrical system is disclosed. The system comprises a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the electrical system; a web application server communicatively connected to the data acquisition component, the web application server configured to transmit a user interface to a client terminal, the web application server comprising: a virtual system model database communicatively connected to the data acquisition component, the virtual system model database configured to store a virtual system model of the electrical system, a power analytic simulation engine comprising a virtual system modeling engine communicatively connected to the virtual system model database, the virtual system modeling engine configured to generate a predicted data output for the electrical system utilizing the virtual system model of the electrical system, and an analytics engine communicatively connected to the virtual system model database, the analytics engine configured to monitor the real-time data output and the predicted data output of the electrical system, and to initiate a calibration and synchronization operation to update the virtual system model when a difference between the real-time data output and the predicted data output exceeds a threshold, and a client terminal communicatively connected to the web application server, the client terminal configured to display the user interface.

A system for providing real-time modeling of an electrical system under management is disclosed. The system includes a data acquisition component, a virtual system modeling engine, and an analytics engine. The data acquisition component is communicatively connected to a sensor configured to provide real-time measurements of data output from an element of the system. The virtual system modeling engine is configured to generate a predicted data output for the element. The analytics engine is communicatively connected to the data acquisition system and the virtual system modeling engine and is configured to monitor and analyze a difference between the real-time data output and the predicted data output.

A technique for establishing usage control over digital assets such as computer files. The system model not only tracks authorized users' access to files, but monitors passage of such files to uncontrollable removable storage media or through network connections and the like which may indicate possible abuse of access rights. In accordance with a preferred embodiment, an autonomous independent agent process running at a point of use, such a background process in a client operating system kernel, interrupts requests for access to resources. The agent process senses low level system events, filters, and aggregates them. A policy engine analyzes sequences of aggregate events to determine when policy violations occur.

Systems and methods for real-time modeling of a microgrid. In an embodiment, real-time data is acquired from a microgrid. Predicted data for the microgrid is generated using a first virtual system model of the microgrid, which comprises a virtual representation of energy sources within the microgrid. The real-time data and the predicted data are monitored, and a calibration and synchronization operation is initiated to update the first virtual system model in real-time when a difference between the real-time data and the predicted data exceeds a threshold. Parameters of the first virtual system model can be modified to create a second virtual system model, and aspects can be forecasted for the microgrid operating under the modified parameters of the second virtual system model. In a further embodiment, market price information can be received, and optimization solutions can be generated based on the market price information.

A highly automated non-confining system to continuously, or at selected time intervals identify, measure, monitor and manage the consumption behavior, substance intake, body weight and growth of individual animals in their usual production environment including range, pasture, feedlot, dairy and farm without disruption to typical behaviors in order to determine, analyze, model and predict a variety of conditions relating to animal health, productivity, efficiency and quality. A transmitter generally attached to the animal identifies the individual animal by a unique individual code. A weighing device measures animal weight while an animal is consuming substances. An antenna receives the unique signal from the transmitter and a transmitting and receiving device sends acquired signals to a computer and receives instructions from a computer. A computer acquires signals and modification factors incorporated in the computer generate an event or interval measurement of an animal's weight and gain, growth rate and substance consumption, and the animal behavior affecting the measurement. A visual identification mechanism marks cattle that the computer system has determined require intervention. The system models and predicts animal health and growth, performance, carcass characteristics, feed utilization, manure and methane output.

A method for the estimation of the state variables of nonlinear systems with exogenous inputs is based on improved extended Kalman filtering (EKF) type techniques. The method uses a discrete-time model, based on a set of nonlinear differential equations describing the system, that is linearized about the current operating point. The time update for the state estimates is performed using integration methods. Integration, which is accomplished through the use of matrix exponential techniques, avoids the inaccuracies of approximate numerical integration techniques. The updated state estimates and corresponding covariance estimates use a common time-varying system model for ensuring stability of both estimates. Other improvements include the use of QR factorization for both time and measurement updating of square-root covariance and Kalman gain matrices and the use of simulated annealing for ensuring that globally optimal estimates are produced.

A system for providing real-time modeling of protective device in an electrical system under management is disclosed. The system includes a data acquisition component, a virtual system modeling engine, and an analytics engine. The data acquisition component is communicatively connected to a sensor configured to provide real-time measurements of data output from protective devices within the system under management. The virtual system modeling engine is configured to update a virtual mode of the system based on the status of the protective devices and to generate predicted data for the system using the updated virtual model. The analytics engine is communicatively connected to the data acquisition system and the virtual system modeling engine and is configured to monitor and analyze a difference between the real-time data output and the predicted data output. The analytics engine is also configured to determine the bracing capabilities for the protective devices.

A system and method for providing data to a model of a building system includes a building control system with a communications network, a control subsystem for generating module deployment data and transmitting the module deployment data over the communications network, a memory for storing a three dimensional model of at least a portion of a building and a computer. A computer program executed by the computer includes computer instructions for associating module deployment data received from the communications network with the three dimensional model and modifying the three dimensional model based upon the module deployment data.

A system for real-time three-dimensional (3D) visualization of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine, a machine learning engine and a 3D visualization engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The machine learning engine stores and processes patterns observed from the real-time data output and the predicted data output to forecast an aspect of the electrical system. The 3D visualization engine renders the virtual system model and the forecasted aspect into a 3D visual model.

A computer system models human memory by deriving associations between objects, events, and the context of the computer user or users. These associations can be dynamically generated, changing depending on the behavior of the user and context. Examples of areas in which this system can be used include time management (e.g., a calendar that presents time-based groupings of objects), people management (e.g., use analysis of user communications to rank importance of people to the user, groupings, and associations between people / groups and other objects such as documents, email), and general computer management (e.g., use analysis of user behavior to identify important objects and objects that are related to a current focus and context of the computer user).

An inertial (“INS”) / GPS receiver includes an INS sub-system which incorporates, into a modified Kalman filter, GPS observables and / or other observables that span previous and current times. The INS filter utilizes the observables to update position information relating to both the current and the previous times, and to propagate the current position, velocity and attitude related information. The GPS observable may be delta phase measurements, and the other observables may be, for example, wheel pick-offs (or counts of wheel revolutions) that are used to calculate along track differences, and so forth. The inclusion of the measurements in the filter together with the current and the previous position related information essentially eliminates the effect of system dynamics from the system model. A position difference can thus be formed that is directly observable by the phase difference or along track difference measured between the previous and current time epochs. Further, the delta phase measurements can be incorporated in the INS filter without having to maintain GPS carrier ambiguity states. The INS sub-system and the GPS sub-system share GPS and INS position and covariance information. The receiver time tags the INS and any other non-GPS measurement data with GPS time, and then uses the INS and GPS filters to produce INS and GPS position information that is synchronized in time. The GPS / INS receiver utilizes GPS position and associated covariance information and the GPS and / or other observables in the updating of the INS filter. The INS filter, in turn, provides updated system error information that is used to propagate inertial current position, velocity and attitude information. Further, the receiver utilizes the inertial position, velocity and covariance information in the GPS filters to speed up GPS satellite signal re-acquisition and associated ambiguity resolution operations

A method and apparatus for determining a fluid level and / or output flow during operation of a centrifugal pump, are provided, which may be used for production of gas and / or oil from a well, and include a vector feedback model to derive values of torque and speed from signals indicative of instantaneous current and voltage drawn by the pump motor, a pump model which derives values of the fluid flow rate and the head pressure for the pump from torque and speed inputs, a pumping system model that derives, from the estimated values of the pump operating parameters, an estimated value of fluid level and other pumping system parameters. Controllers responsive to the estimated values of the pumping system parameters control the pump to maintain fluid level at the pump input, near an optimum level, or within a safe operating range and / or output flow from the pump.

A system for real-time modeling of electrical system performance is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The power analytics server is comprised of a virtual system modeling engine, an analytics engine and a power system simulation engine. The virtual system modeling engine is configured to generate predicted data output utilizing a first virtual system model. The analytics engine is configured to synchronize the first virtual system model when a difference between the real-time data output and the predicted data output exceeds a threshold. The power system simulation engine is configured to store and process patterns and facilitate modification of parameters on the first virtual system model to create a second virtual system model; and forecast an aspect of the electrical system operating under parameters of the second virtual system model. The client terminal displays the forecasted aspects.

A method of conducting a sequence of linked simulation operations, utilizing a computer-based simulation model, commences with the performance of a first simulation operation to generate an output condition. A further simulation operation, which is defined to sequentially follow the first simulation operation, is then formed utilizing the simulation model. The second simulation operation at least partially and automatically inherits the output condition generated by the first simulation operation as an input condition. In this way, the second simulation operation commences with a configuration captured from a preceding simulation operation as an input condition. Multiple simulation operations may at least partially inherit a configuration from the first simulation operation.

An optimal path selection system extracts a connection subgraph in real time from an undirected, edge-weighted graph such as a social network that best captures the connections between two nodes of the graph. The system models the undirected, edge-weighted graph as an electrical circuit and solves for a relationship between two nodes in the undirected edge-weighted graph based on electrical analogues in the electric graph model. The system optionally accelerates the computations to produce approximate, high-quality connection subgraphs in real time on very large (disk resident) graphs. The connection subgraph is constrained to the integer budget that comprises a first node, a second node and a collection of paths from the first node to the second node that maximizes a “goodness” function g(H). The goodness function g(H) is tailored to capture salient aspects of a relationship between the first node and the second node.

A system generates optimal global set points for an environmental management system. The system comprises a system model for modeling components of a thermal plant, an objective function for modeling a parameter of the thermal plant, and an optimization engine for optimizing the parameter modeled by the objective function. The system model is coupled to an input data collector for receiving building data and weather data corresponding to a particular site. The system model includes models for thermal plant system components that may be implemented using classical models or artificial intelligence models. Classical models are those models that are implemented using linear programming, unconstrained non-linear programming, or constrained non-linear programming methodologies. The artificial intelligence models are those models that may be implemented using a fuzzy expert control system with crisp and fuzzy rules, genetic algorithms for optimization, or neural networks.

A system for setting WLAN node operating parameters includes at least one access point (AP) radio and a plurality of nodes in wireless communication with the AP radio according to media access control (MAC) parameters. Each of the plurality of nodes has a quality of service (QoS) threshold for wireless communication with the AP radio that is a function of the MAC parameters and includes a controller configured to provide individualized control of the MAC parameters. The controller is programmed to measure current settings for at least a portion of the MAC parameters for the node, input the current settings for those MAC parameters of the node into a WLAN system model to generate a system model output, and adapt a setting of at least one of the MAC parameters for the node to meet the QoS threshold for the node based on the system model output.

A simple yet effective and robust identification method is presented using process step responses for process identification that can provide a continuous transfer function with time-delay without iteration. A cascade relay provides accurate and reliable more points on the process frequency response. The internal model principle is employed to design single-loop controller of PID or high-order types with best achievable control performance for controller tuning, e.g. both single and multivariable cases are covered. The process identification and control design portions can be easily integrated into a control system auto-tuning package. Further, a general control scheme for disturbance rejection is given which can significantly improve disturbance rejection performance over conventional feedback systems with time delays. Practical issues such as noises, real-time implementation and tuning guidelines are also provided. The present invention provide general, systematic, effective, and applicable methods for process identification and control for a wide range of industries such as process and chemical plants, food processing, waste water treatment and environmental systems, oil refinery, servo and mechatronic systems, where a system model is needed for analysis, prediction, filtering, optimization and management, and / or where control or better control is required for their systems.

The invention discloses a human body attitude calculation method based on quaternion and Kalman filtering. The method comprises determining a vector coordinate system and a navigation coordinate system, determining an attitude matrix, respectively acquiring accelerated speed, angular velocity and magnetic induction intensity signals through an accelerometer, a gyroscope and a magnetometer, carrying out initial alignment on a human body attitude detection system, calculating initial attitude angles such as a pitching angle, a rolling angle and a heading angle, transforming the initial attitude angles into initial quaternion, carrying out system modeling according to a quaternion differential equation, inputting the initial quaternion as a measured value, carrying out data fusion on the attitude data through a Kalman filtering algorithm, outputting an estimated value which is updated quaternion, carrying out normalization processing on the updated quaternion to obtain final posture information, updating the attitude matrix and acquiring updated attitude angles. The human body attitude estimation method effectively improves the accuracy of human posture detection, has a fast response speed, has good stability and instantaneity and has a broad application prospect.

This computer implemented software invention supervises networked system resources with the goal of maximizing service availability, providing on-demand and uninterrupted access to service, and minimizing the down time due to failures. It is a cluster-wide solution that co-ordinates the states and activities of resources, assigns availability roles, implements recovery from failures, and implements overall system policy. To do this, it maintains a system model of the system's physical and logical configuration and models the resources using managed objects that provides an extensive representation of the states, roles, and relationships of the systems resources.