16412 results about "Mathematical model" patented technology

A system, program product and method continuously optimize an ultrafiltration rate during an extracorporeal renal replacement process by modeling physiological and actual rate data. The system maps the sensed, physiological data to a mathematical model to assess the data in terms of the ultrafiltration rate. The model provides parameters used to predict where the treatment is headed based on current conditions. The system processes the parameters in terms of preset criteria to generate the optimized ultrafiltration rate. Where the system is networked, communication of the data may be accomplished using remote and online communication techniques.

A building heating/cooling system energy optimization method for a building having a heating/cooling system includes the steps of providing a mathematical model of the heating/cooling system, obtaining real-time weather information, reading the input water temperature (IWT), the output water temperature (OWT) and the supply air temperature (SA) output to the building, periodically transferring the IWT, the OWT and the SA to an optimization system which is operative to analyze the real-time data in coordination with the mathematical model by assigning at least three selected values in a range surrounding and including the current values of each of the IWT, the OWT and the SA and calculating the efficiency profile of the components of the heating/cooling system for each of the selected values, then cooperatively optimizing and selecting those values calculated to provide the highest efficiency profile, then periodically resetting the system values to those selected by the optimization system.

The present invention provides a configurable pricing system that allows users to define or modify data used to analyze, evaluate, improve, and design pricing changes according to the user's need. A Graphical user interface or some other type of user interface allows the user to access and review various data to be used during pricing optimization. The user may then modify this data as needed to improve the pricing evaluation, such as defining sales or pricing trends, or relationships between the product of interest and other competing items. The user interface may further display changes in pricing and the effects of the pricing changes, as caused by the user's changes. The interface may also allow the user to modify the mathematical model to be used during price optimization, as well as define variables, constraints, and boundaries to be considered during the price optimization.

A system for simulating a medical procedure performed on a subject, featuring a simulated organ, a simulated medical instrument and a locator for determining the location of the instrument in the organ. The system further features a visual display for displaying images from the medical procedure. The visual display also includes a three-dimensional mathematical model for modeling the organ, which is divided into a plurality of linear segments. The location of the instrument in the organ is used to select the segment, which in turn is used to select the images for display on the visual display.

An incontinence management system for monitoring wetness in one or more absorbent articles, includes input for receiving one or more sensor signals indicative of a presence of wetness in an absorbent article, processor for processing the one or more sensor signals and for performing an analysis of the signals to characterise wetness events occurring in an absorbent article and user interface for communicating with a user of the system. A mathematical model is used to characterise wetness events, receiving as inputs variables derived from sensor signals and optionally, patient and demographic data. The mathematical model can be configured and/or re-configured utilising observation data obtained while monitoring a patient for wetness. A diaper for use with such as system is also disclosed.

A fully automated package identification and measuring system, in which an omni-directional laser scanning system are used to read bar codes on packages entering the tunnel, while a package dimensioning subsystem is used to capture information about the package prior to entry into the tunnel. Mathematical models are created on a real-time basis for the geometry of the package and the position of the laser scanning beam used to read the bar code symbol thereon. The mathematical models are analyzed to determine if collected and queued package identification data is spatially and/or temporally correlated with package measurement data using vector-based ray-tracing methods, homogeneous transformations, and object-oriented decision logic so as to enable simultaneous tracking of multiple packages being transported through the scanning tunnel.

The invention belongs to the technical field of barrier detection, particularly relates to a field environment barrier detection method fusing distance and image information and aims to provide a method for detecting the common barriers under the field driving condition of an unmanned vehicle so as to plan a driving route for the vehicle and enhance the independent field driving capability of theunmanned vehicle. The method comprises the following steps of: establishing a mathematical model; detecting a laser radar distance data barrier; and fusing the image processing of a video camera and a result. By the method, the common barriers such as grasslands, roads, trees, bushes and the like under the field driving condition of the unmanned vehicle can be detected and recognized and color modeling is performed on a driving region, so that an abnormal part of the driving region is further detected. The environment around the vehicle can be partitioned into a non-driving region, the driving region, an unknown region and the like, so that the planning of the driving route of the vehicle is facilitated and the independent field driving capability of the unmanned vehicle is enhanced.

A new way of mixing instrumental and digital means is described for the general field of wave front sensing. The present invention describes the use, the definition and the utility of digital operators, called digital wave front operators (DWFO) or digital lenses (DL), specifically designed for the digital processing of wave fronts defined in amplitude and phase. DWFO are of particular interest for correcting undesired wave front deformations induced by instrumental defects or experimental errors. DWFO may be defined using a mathematical model, e.g. a polynomial function, which involves coefficients. The present invention describes automated and semi-automated procedures for calibrating or adjusting the values of these coefficients. These procedures are based on the fitting of mathematical models on reference data extracted from specific regions of a wave front called reference areas, which are characterized by the fact that specimen contributions are a priori known in reference areas. For example, reference areas can be defined in regions where flat surfaces of a specimen produce a constant phase function. The present invention describes also how DWFO can be defined by extracting reference data along one-dimensional (1D) profiles. DWFO can also be defined in order to obtain a flattened representation of non-flat area of a specimen. Several DWFO or DL can be combined, possibly in addition with procedures for calculating numerically the propagation of wave fronts. A DWFO may also be defined experimentally, e.g. by calibration procedures using reference specimens. A method for generating a DWFO by filtering in the Fourier plane is also described. All wave front sensing techniques may benefit from the present invention. The case of a wave front sensor based on digital holography, e.g. a digital holographic microscope (DHM), is described in more details. The use of DWFO improves the performance, in particular speed and precision, and the ease of use of instruments for wave front sensing. The use of DWFO results in instrumental simplifications, costs reductions, and enlarged the field of applications. The present invention defines a new technique for imaging and metrology with a large field of applications in material and life sciences, for research and industrial applications.

A medical device for predicting a user's future glycemic state includes a memory module, a processor module and a user alert module. The memory module is configured to receive and store a plurality of glucose concentrations as a function of time that were generated by a user's use of a continuous glucose monitor. The processor module is configured to derive first and second glucose prediction equations that are fits to the plurality of glucose concentrations stored in the memory module with the fits being based on first and second mathematical models, respectively. The processor module is also configured to calculate first and second predicted glucose concentrations at a future time using the first and second glucose prediction equations, respectively, and to also calculate an average predicted glucose concentration and a merit index based on the first and second predicted glucose calculations. The processor module is further configured to input the plurality of glucose concentrations as a function of time, the average predicted glucose concentration and the merit index into a trained model (e.g., a Hidden Markov Model) that outputs a set of glucose concentration probabilities for the future time and to then predict the user's future glycemic state based on the set of glucose concentration probabilities. The user alert module is configured to alert the user in a manner dependent on the predicted user's future glycemic state.

A fully automated package identification and measuring system, in which an omni-directional holographic scanning tunnel is used to read bar codes on packages entering the tunnel, while a package dimensioning subsystem is used to capture information about the package prior to entry into the tunnel. Mathematical models are created on a real-time basis for the geometry of the package and the position of the laser scanning beam used to read the bar code symbol thereon. The mathematical models are analyzed to determine if collected and queued package identification data is spatially and/or temporally correlated with package measurement data using vector-based ray-tracing methods, homogeneous transformations, and object-oriented decision logic so as to enable simultaneous tracking of multiple packages being transported through the scanning tunnel.

A fully automated package identification and measuring system, in which an omni-directional holographic scanning tunnel is used to read bar codes on packages entering the tunnel, while a package dimensioning subsystem is used to capture information about the package prior to entry into the tunnel. Mathematical models are created on a real-time basis for the geometry of the package and the position of the laser scanning beam used to read the bar code symbol thereon. The mathematical models are analyzed to determine if collected and queued package identification data is spatially and/or temporally correlated with package measurement data using vector-based ray-tracing methods, homogeneous transformations, and object-oriented decision logic so as to enable simultaneous tracking of multiple packages being transported through the scanning tunnel.

The power flow model of the multiterminal voltage-source converter-based high voltage DC (M-VSC-HVDC) transmission system for large-scale power systems is studied. The mathematical model is derived using the d-q axis decomposition of HVDC's control parameter. The developed model can be applied to all existing shunt voltage-source converter (VSC) based controllers, including Static Synchronous Compensator (STATCOM), point-to-point HVDC system, back-to-back HVDC system and multiterminal HVDC system. A unified procedure is developed for incorporating the proposed model into the conventional Newton-Raphson power flow solver. The IEEE 300-bus test system embedded with multiple HVDC transmission systems under different configurations are investigated. Simulation results reveal that the proposed model is effective and accuracy in meeting various control objectives.

A control system comprises a controller for positioning an actuator in a working fluid flow and a model processor for directing the controller as a function of a model feedback. The model processor comprises an output module, a comparator and an estimator. The output module generates the model feedback as a function of a constraint, a model state and a model input describing fluid parameters measured along the working fluid flow. The comparator generates an error by comparing the model feedback to the model input. The estimator generates the constraint and the model state, such that the error is minimized.

Methods and apparatuses for providing virtual temperature sensor to control temperatures in a data processing system. In one aspect, a data processing system includes a virtual temperature sensor to provide system temperature for different system configurations, and a controller coupled to the sensor to control operations of the data processing system according to the virtual temperature. The virtual temperature sensor typically derives the temperature of a particular configuration of the data processing system using mathematical models or one or more operating parameters of the data processing system. In one example, the mathematical models include a characterization table which provides the measured temperature data from various system configurations. These measurements are performed with temperature sensors positioned in ideal locations for different configuration, and are preprocessed to provide the virtual temperature computation. The characterization table also includes thermal characteristics, such as thermal time constant and thermal resistance, of the critical components at multiple thermal control states.

The present invention pertains to a portable apparatus for quantitatively measuring the concentration of specific substances in test samples of a lateral flow or microplate assay in medical, biomedical and chemical applications, and for making subsequent analysis and diagnosis. The portable apparatus includes a sample tray for carrying and aligning the test sample in the apparatus; a enclosure that may also serves as the frame of the apparatus; a digital image acquisition system that is used to obtain the digital image of the test sample on the sample tray; and a data display, processing, and analysis unit that is a general purpose or dedicated computer, such as a handheld computer (HHC), a pocket personal computer (PPC), a personal digital assistant (PDA), a palm-top computer, a laptop computer, or a dedicated microprocessor and associated hardware, for measuring the concentration of specific substances in the test sample, and making subsequent analysis and diagnosis, based on the measurement, statistical data, prior knowledge and mathematical model. The stated enclosure and frame, the digital image acquisition system, and the data display, processing and analysis unit are integrated to form the portable apparatus for various applications. The integrated apparatus of this invention, with a possible name—Portable Intelligent Multi-Diagnoser (PIMD), thus forms a portable and multiple-purpose tool for measuring the concentration of specific substances in test samples, and making subsequent analysis and diagnosis in a variety of settings, such as a mobile site, point of care or near patient care, and small laboratories.

The invention relates to an automatic selection method for machine learning in cloud computer environment. By using a cloud computing platform, a user can automatically and intelligently build a machine learning mathematic model which meets actual problems without building the operation environment of machine learning, selecting a machine to learn algorithm and even adjusting complicated machine learning functions and accompanying parameters but only using a Web method to upload sample data. Through the method, the use of machine learning is free from the environmental constraints and displays the advantages of the cloud computing platform, so that the machine learning model building is transparent to the user, so as to best reduce the use threshold of machine learning. The automatic selection method for machine learning in cloud computing environment solves the disadvantages of the unpredictability of model building selection, the manual experience of parameter adjustment, the difficulties of common users and the like when machine learning is applied in actual life.

Route planning methods for use by a package delivery service provider are disclosed that satisfy a stochastic daily demand while taking advantage of drivers' route familiarity over time. A model for estimating the value of driver familiarity is disclosed along with both an empirical and a mathematical model for estimating the value of route consistency, along with a Core Area Route Design which involves the concepts of combinational optimization, meta-heuristic algorithms, tabu search heuristics, network formulation modeling, and multi-stage graph modeling. In one embodiment, a service territory is divided into unassigned cells associated with a grid segment involving prior driver delivery stops, and a driver from a pool of unassigned drivers is assigned to a route based on examining each driver's grid segment visiting frequency limit with respect to a minimum limit so as to optimize driver selection based on of each driver's familiarity with the route.

A method for predicting a user's future glycemic state includes measuring a user's glucose concentration at intervals over a time duration, thereby generating a plurality of glucose concentrations as a function of time. First and second glucose prediction equations that are fits to the plurality of glucose concentrations based on first and second non-identical mathematical models, respectively, are then derived. The method also includes calculating first and second predicted glucose concentrations at a future time using the first and second glucose prediction equations, respectively. Thereafter, an average predicted glucose concentration and a merit index are calculated based on the first and second predicted glucose calculations. The plurality of glucose concentrations as a function of time, the merit index and average predicted glucose concentration are input into a trained model (for example, a Hidden Markov Model) that outputs a set of glucose concentration probabilities. The user's future glycemic state is then predicted based on the set of glucose concentration probabilities.