117results about How to "Efficient modeling" patented technology

The invention provides a real-time three-dimensional face modeling method based on depth information; the method does not adopt any previous standard face models but realizes the three-dimensional real-time modeling through registration and integration of a plurality of face depth images. The method comprises the following steps: systematically building depth information acquired from kinect; separating facial images from the depth images; back projecting, so as to form three-dimensional point cloud; smoothing, registering, integrating, drawing and displaying. With the adoption of the real-time three-dimensional face modeling method used for the computer graph and image processing and based on the depth information, a three-dimensional real-time face model required by a user can be rapidly generated only through that the user sits in the front of kinect, so that the cost and time spent on three-dimensional face modeling through laser scanning in the past are greatly reduced, and errors caused by using two-dimensional images for three-dimensional face modeling are avoided, so that three-dimensional real-time face modeling is realized at a lower cost.

Businesses typically have large amounts of data about customer transactions and other customer information which is not fully utilized. The present invention provides a means of using this information to make predictions about future customer behavior, for example by estimating the probability that a customer will leave a bank. Using these predictions the business is able to take action in order to improve its performance. Using customer data a Bayesian statistical model is generated and this model used to generate statistical estimators of customer behavior. The statistical model is formed using hidden Markov model techniques by clustering customer data and attributes (e.g. Age, sex, salary) into a finite number of states. The number of states is unobserved and considered random. Bayesian prior probability distributions are specified and combined with the data to produce Bayesian posterior probability distributions. Using these Bayesian posterior probability distributions the statistical estimators are obtained. For example, Monte Carlo sampling techniques are used or alternatively the posterior distributions are calculated numerically or analytically.

A method of system design, and more particularly a method of designing systems that achieve a set of performance goals using a hierarchically partitioned system representation wherein performance simulations are performed at multiple levels within the hierarchy and are combined to simulate a system level result in order to reduce the aggregate time required for performance simulation.

A system for developing an application program having functionality that corresponds to a finite state machine (FSM) model includes a visual interface that generates a graphical environment on a display for displaying an FSM model representing functionality of the program, a dynamic state machine processor that uses XML descriptions associated with the FSM model to generate the program executed at run-time, and an extensible graphic user interface that provides the end-user interface features to the end-user as generated during run-time by the processor based on the FSM model.

The invention discloses a universal simulation box used for three-dimensional discrete element modeling and simulation of a rock and soil mass. 1) a universal simulation box is established, specified-size boundary plates in six directions of a box body are generated, the boundary plates are composed of a series of sphere particles, smaller-size buffer boundary pressure plates are respectively generated inside the six boundary plates, and the three-dimensional simulation box is established; 2) a particle accumulation body is generated in the box body, and no-gravity particles are randomly generated in the box body; 3) a three-dimensional model of different structures is established, files including delamination and demarcation coordinate files are imported, the particles outside an outlineare removed, and the three-dimensional model of the structures is formed; 4) material properties of the rock and soil mass are assigned to the three-dimensional model, a material attribute file of therock and soil mass is imported, parameters of the rock and soil mass are converted into parameters of the particles according to conversion formulas, the parameters are assigned to the particles, anda three-dimensional discrete element model with specified elastic properties and failure properties is established; and 5) loading of force, displacement and vibration is carried out through the boundary pressure plates, displacement and vibration are applied through boundaries, loads such as stress action are applied through the pressure plates, iteration operating is carried out, and a result is output.

The invention discloses a Kaplan turbine adjusting system dynamic model suitable for electric power system analysis, which comprises a speed governor model, a guide vane control system model, a blade control system model, a water turbine model and a water diversion system model, wherein the guide vane control system model and the blade control system model forms a Kaplan turbine dual adjusting system, the blade control system model takes a combined relationship existing between guide vane opening degrees and blade opening degrees into account, and the combined relationship is obtained by adopting a quintic polynomial curve fitting method; and the water turbine model takes the correction function of blade angles on water turbine efficiency into account on the basis of analyzing non-linear models, the mechanical power output of the water turbine model is affected by the guide vane opening degrees and blade opening degrees together, and the nonlinearity between the guide vane opening degrees and the mechanical power is metered and is described by adopting cubic polynomial fitting. The Kaplan turbine adjusting system dynamic model is exquisite and clear in structure, has distinct and easily-obtained model parameter meanings, is fast and efficient in modeling process, and has high practicability.

An audio processing circuit includes a crosstalk cancellation circuit that is advantageously simplified for use in audio devices that have closely-spaced speakers. In particular, crosstalk filtering as implemented in the circuit assumes that the external head-related contralateral filters are time-delayed and attenuated versions of the external, head-related ipsilateral filters. With this assumption, the circuit's crosstalk filtering is configurable for varying audio characteristics, according to a small number of settable parameters. These parameters include configurable first and second attenuation parameters for cross-path signal attenuation, and configurable first and second delay parameters for cross-path delay. Optional sound normalization, if included, uses similar simplified parameterization. Further, in one or more embodiments, the audio processing circuit and method include or are associated with a defined table of parameters that are least-squares optimized solutions. The optimized parameter values provide wider listening sweet spots for a greater variety of listeners.

A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.

Disclosed is an analysis methodology and equivalent RLC circuits that accurately model the effects of packaging circuitry, bond wire circuitry and other sources of cross talk within an integrated-circuit signal transmission system.

The invention discloses a no-reference video quality evaluation method based on three-dimensional spatial-temporal feature decomposition, which comprises the following steps of: constructing a qualityprediction network consisting of a spatial-temporal distortion feature learning module and a quality regression module, generating a no-reference training data set and a no-reference test data set, training the spatial-temporal distortion feature learning module and the quality regression module, and outputting the quality evaluation score value of each distorted video in the test set. The invention is used for accurately and efficiently extracting the quality perception characteristics of the time-space domain content from the input distorted video, the corresponding prediction quality scoreis obtained at the output end of the network, and the method has the advantages that the result is more accurate and the application is wider when the quality of the non-reference video is evaluated.

The invention discloses an impact type water turbine regulating system for electric power system stability analysis. The system comprises a regulator model, a spray needle servo system model, a deflector servo system model and an impact type water turbine model, wherein a signal input end of the regulator model inputs electric generator frequency and electric generator electromagnetic power; signal input ends of the spray needle servo system model and the deflector servo system model are connected with signal output ends of the regulator model; a signal input end of the impact type water turbine model is connected with signal output ends of the spray needle servo system model and the deflector servo system model; the regulator model calculates output of the regulator model according to input set frequency signals; the spray needle servo system model calculates opening degree output of a spray needle according to input of the regulator model; the deflector servo system model calculates opening degree output of a deflector model according to the set frequency signals; and the impact type water turbine model calculates mechanical power output of the impact type water turbine model according to opening degree input of the spray needle and opening degree input of a deflector. The system is exquisite and distinct in structure, well-defined and available in model parameter, fast, efficient and accurate in modeling process and high in practicability.

A method of treating the surfaces of medical instruments which are contaminated with prions includes contacting the surface with a composition containing a source of peroxide ions, such as hydrogen peroxide, at a molar concentration of at least 1.5M peroxide (equivalent to approximately 5% hydrogen peroxide) and preferably, about 2M peroxide (approximately 7% hydrogen peroxide). The composition is optionally in the form of a gel. The composition is retained in contact with the surfaces for about 1-2 hours until all or substantially all prion contamination is removed.

To provide efficient and effective modeling of data set, the data set is initially separated into several subsets which can then be processed independently. The subsets themselves are chosen to have some internal commonality, thus providing effective independent tools where possible. This commonality may include correlation between variables or interaction amongst the variables in the subset. Once separated, each subset is independently modeled, creating a subset model having predictive qualities related to the data subset. Next, the subset models themselves are aggregated to generate a overall final model. This final model is predictive of outcomes based upon all data in the data set, thus providing a more robust stable model.