7574 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.

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.

Resolution of an input image is converted more easily by using a method of AAM. For this purpose, a resolution conversion unit converts resolution of the image having been subjected to correction, and a face detection unit detects a face region in the resolution-converted image. A reconstruction unit fits to the face region detected by the face detection unit a mathematical model generated through the method of AAM using a plurality of sample images representing human faces having the same resolution as the image, and reconstructs an image representing the face region after the fitting. In this manner, an image whose resolution has been converted is obtained.

An unnecessary component such as acne is removed completely from a predetermined structure such as a face in a photograph image without manual operation and skills. An acne removal unit fits to a face region as the structure in the image a mathematical model generated according to a statistical method such as AAM using sample images representing the structure without the component to be removed, and an image reconstruction unit reconstructs an image of the face region based on parameters corresponding to the face region obtained by the fitting of the model. An image is then generated by replacing the face region with the reconstructed image. Since the mathematical model has been generated from the sample images of human faces without acne, the model does not include acne. Therefore, the reconstructed face image generated by fitting the model to the face region does not include acne.

The invention provides a gaming machine having manufacturer-limited parameter values or parameter value combinations selectable by an operator during gaming machine set-up. The parameter values preferably include different maximum pay lines associated with different denominations and are limited to those which have been determined by the manufacturer to provide optimum game play. The different maximum pay lines may be associated with different math models having substantially the same payback percentage values. Subsequent operator selection of the parameter values during gaming machine therefore setup allows the gaming machine having a single game theme or a gaming machine having multiple game themes to be configured with different maximum pay lines for each single game theme. As a result, the player can play a single theme wagering game with a first maximum pay line value and with a second maximum pay line value where the second maximum pay line value differs from the first maximum pay line value.

The present invention provides a decision management system to define, validate and extract data for predictive models. A system of sensors is deployed in a sample collection environment, where such sensors are used to collect data from a biological or chemical sample, with additional sensors for ambient data whose output as a form of metadata can characterize performance conditions including background ambient conditions. A format or sequence of processes is the basis for a math model to establish a logical weight to data for predictive modeling and event reporting. The present invention provides a computer or other sensor interface system with a primary sensor or sensors, network connection, and supplementary sensors to measure the conditions in which the primary data is captured. A software process allows for user inputs of data in order to establish the methods and rules for normal function.

Embodiments herein provide a non-invasive tracking system that accurately predicts the location of tumors, such as lung tumors, in real time, while allowing patients to breathe naturally. This is accomplished by using Electrical Impedance Tomography (EIT), in conjunction with spirometry, strain gauge and infrared sensors, and by using sophisticated patient-specific mathematical models that incorporate the dynamics of tumor motion. With the direction and speed of lung tumor movement successfully tracked, radiation may be effectively delivered to the lung tumor and not to the surrounding healthy tissue, thus increased radiation dosage may be directed to improving local tumor control without compromising functional parenchyma.

According to one aspect, transaction information is received and applied to multiple fraud risk mathematical models that each produce a respective raw score, which are transformed with respective sigmoidal transform functions to produce optimized likelihood of fraud risk estimates to provide to a merchant. In one embodiment, the respective fraud risk estimates are combined using fusion proportions that are associated with the respective risk estimates, producing a single point risk estimate, which is transformed with a sigmoidal function to produce an optimized single point risk estimate for the transaction. The sigmoidal functions are derived to approximate a relationship between risk estimates produced by fraud risk detection models and a percentage of transactions associated with respective risk estimates, where the relationship is represented in terms of real-world distributions of fraudulent transaction and non-fraudulent transaction. One embodiment is directed to computing respective risk test penalties for multiple risk tests in one or more of the multiple fraud risk mathematical models used to estimate the likelihood of fraud, given a certain pattern of events represented by the transaction information, wherein the respective risk test penalties are computed as the inverse of the sum of one and a false positive ratio for the respective risk test.

Sharpness is adjusted for more appropriately representing a predetermined structure in an image. A parameter acquisition unit obtains a weighting parameter for a principal component representing a degree of sharpness in a face region detected by a face detection unit as an example of the predetermined structure in the image, by fitting to the face region a mathematical model generated by a statistical method such as AAM based on a plurality of sample images representing human faces in different degrees of sharpness. Based on a value of the parameter, sharpness is adjusted in at least a part of the image. For example, a parameter changing unit changes the value of the parameter to a preset optimal face sharpness value, and an image reconstruction unit reconstructs the image based on the parameter having been changed and outputs the image having been subjected to the sharpness adjustment processing.

The invention belongs to the technical field of energy conservation, and relates to a variable frequency energy-saving control method for a refrigeration system. The control method comprises the steps of: determining the mass flow of a refrigerant according to the change or change trend of cooling load, then determining consumed power of a compressor which satisfies the flow, predicting the minimum condensation pressure which ensures that the thermal load of a condenser satisfies the cooling load and the power change of the compressor through an established energy-saving control mathematical model, and gradually adjusting the power frequency of the compressor to ensure that the rotating speed of the compressor reaches a predicted value; and adjusting the opening degree of an expansion valve to ensure that the condensation pressure reaches to be lowest, realizing the minimum pressure difference operation between the condenser and an evaporator, and ensuring that the operation energy consumption of the refrigeration system is lowest. The method solves the optimizing control problem of the compressor, the expansion valve and a fan in the system, utilizes the energy-saving control mathematical model to perform joint regulation on controllable factors (such as the rotating speed of the compressor, the opening degree of the expansion valve, and the air volume of an outdoor unit) of the operation of the system, ensures that the refrigeration system operates at a best operating point, and realizes the further energy conservation of the refrigeration system based on the variable frequency regulation.

The invention relates to a power distribution network double layer planning method considering the time sequence and the reliability. The method comprises: according to the meteorological files and the load power statistical data, obtaining the typical daily power time sequence curves of the wind electricity, the photovoltaic output and the load in different seasons; based on the opportunistic constraint planning method, creating a power distribution network framework and a distributed power capacity double layer planning mathematical model, including the objective function and the constraint condition; using the particle swarm optimization algorithm to solve the model and using the minimum spanning tree algorithm to ensure the radiation and connectivity structure of the distribution network during the iterative process; and obtaining the target network framework and the Pareto optimal solution set of the distributed power capacity so as to generate the best planning scheme. The invention solves the problems that unnecessary investment into the a power distribution network incurred by the fact that a traditional power distribution network planning method containing a distributed power supply cannot reflect the typical output characteristic of a distribution type new energy; and 2) that by incorporating the power distribution network power supply reliability into a model target function, the reliability target can be realized at the planning stage.

The present invention comprises a controller for the cascade H-bridge three-phase multilevel converter used as a shunt active filter. Based on the proposed mathematical model, the controller is designed to compensate harmonic distortion and reactive power due to a nonlinear distorting load. Simultaneously, the controller guarantees regulation and balance of all capacitor voltages. The idea behind the controller is to allow distortion of the current reference during the transients to guarantee regulation and balance of the capacitors voltages. The controller provides the duty ratios for each H-bridge of the cascade multilevel converter.

A whole-body mathematical model (10) for simulating intracranial pressure dynamics. In one embodiment, model (10) includes 17 interacting compartments, of which nine lie entirely outside of intracranial vault (14). Compartments (F) and (T) are defined to distinguish ventricular from extraventricular CSF. The vasculature of the intracranial system within cranial vault (14) is also subdivided into five compartments (A, C, P, V, and S, respectively) representing the intracranial arteries, capillaries, choroid plexus, veins, and venous sinus. The body's extracranial systemic vasculature is divided into six compartments (I, J, O, Z, D, and X, respectively) representing the arteries, capillaries, and veins of the central body and the lower body. Compartments (G) and (B) include tissue and the associated interstitial fluid in the intracranial and lower regions. Compartment (Y) is a composite involving the tissues, organs, and pulmonary circulation of the central body and compartment (M) represents the external environment.

In order to accurately remove an unnecessary periodic noise component from an image, a reconstruction unit generates a reconstructed image without a periodic noise component by fitting to a face region detected in an image by a face detection unit a mathematical model generated according a method of AAM using a plurality of sample images representing human faces without a periodic noise component. The periodic noise component is extracted by a difference between the face region and the reconstructed image, and a frequency of the noise component is determined. The noise component of the determined frequency is then removed from the image.

A computerized method is established to detect suspicious and fraudulent activities in a group of subjects by defining and dynamically integrating multidimensional risks, which are based on the characteristics of the subjects, into a mathematical model to produce a set of the most up-to-date representative risk values for each subject based on its activities and background. These multidimensional risk definitions and representative risk values are used to select a subset of multidimensional risk-weighted detection algorithms so that suspicious or fraudulent activities in the group of subjects can be effectively detected with higher resolution and accuracy. A priority sequence, which is based on the set of detection algorithms that detect the subject and the representative risk values of the detected subject, is produced to determine the priority of each detected case during the investigation process. To assist the user to make a more objective decision, any set of multidimensional risks can be used to identify a group of subjects that contain this set of multidimensional risks so that group statistics can be obtained for comparison and other analytical purposes. Furthermore, to fine-tune the system for future detections and analyses, the detection results are used as the feedback to adjust the definitions of the multidimensional risks and their values, the mathematical model, and the multidimensional risk-weighted detection algorithms.