5483 results about "Modelling methods" patented technology

Method for automatically generating an implementation of input and output container reusable parts for a process model managed and executed by at least one computer system. The method of generating uses the specification of a process model extended by specifications associating the process model to a reusable part environment outside the workflow process environment and generates an implementation of said input and output containers as reusable parts residing within said reusable parts environment. The method of generating comprises an analysis of the specifications of said process model. Based on this analysis the method generates the associated input container reusable parts and associated output container reusable parts as implementations of said input and output containers.

Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. The outputs include the size of the consumer's spending wallet over a particular time period, the total number of the consumer's revolving cards, the consumer's revolving balance, the consumer's average pay-down percentage for revolving cards, total number of the consumer's transacting cards, the consumer's transacting balance, a number of balance transfers transacted by the consumer, the total amount of the consumer's balance transfers, the consumer's maximum revolving balance, the consumer's maximum transacting balance, the consumer's credit limit, size of the consumer's revolving spending, and the size of the consumer's transacting spending.

A system and method for managing churn among the customers of a business is provided. The system and method provide for an analysis of the causes of customer churn and identifies customers who are most likely to churn in the future. Identifying likely churners allows appropriate steps to be taken to prevent customers who are likely to chum from actually churning. The system included a dedicated data mart, a population architecture, a data manipulation module, a data mining tool and an end user access module for accessing results and preparing preconfigured reports. The method includes adopting an appropriate definition of churn, analyzing historical customer to identify significant trends and variables, preparing data for data mining, training a prediction model, verifying the results, deploying the model, defining retention targets, and identifying the most responsive targets.

The invention relates to a micro-interface enhanced reactor bubble scale structure-activity regulation and control model building method. The diameter dmax of the largest bubble of a micro-interface enhanced reactor and the diameter dmin of the smallest bubble of the micro-interface enhanced reactor serve as independent variables, the average diameter d32 of the bubble Sauter serve as a dependentvariable, and a numerical relationship is built; based on the Kolmogorov-Hinze theory, the relationship between the diameter dmax of the largest bubble of the micro-interface enhanced reactor, the diameter dmin of the smallest bubble and the parameters of the reactor is built. According to the method, the reactor bubble scale is associated with the structural parameter, the operation parameter andthe physical property parameter of the reactor by using specific numerical relationship, the numerical relationship has the guiding significance for the design of the reactor and can be applied to avariety of reactors, the versatility is good, by means of a bubble scale regulation and control model built through the method, by adjusting the structural parameter and the operation parameter of thereactor, and the maximization of energy efficiency and material efficiency in the reaction process can be achieved, or under the condition that reaction targets, energy consumption and material consumption are given, a high-efficiency reactor structure is designed.

The present invention provides a statistical modeling approach to automatic linguistic indexing of photographic images. The invention uses categorized images to train a dictionary of hundreds of statistical models each representing a concept. Images of any given concept are regarded as instances of a stochastic process that characterizes the concept. To measure the extent of association between an image and a textual description associated with a predefined concept, the likelihood of the occurrence of the image based on the characterizing stochastic process is computed. A high likelihood indicates a strong association between the textual description and the image. The invention utilizes two-dimensional multi-resolution hidden Markov models that demonstrate accuracy and high potential in linguistic indexing of photographic images.

The present invention relates to a method for computer-controlled modelling of customised earpieces. These earpieces include housings for hearing aids, wireless or connected communication devices (headsets, mobile phones, personal agents), loud speakers, tinnitus masking devices, devices recording vibrations in the skull and transforming these into audio signals, voice recognition devices, earplugs, noise blockers with selective frequencies or sound levels, Man Machine Interface (MMI) products that enable clear communication even in the noisiest environments, or products related to wireless Internet applications. All these earpieces may be worn in the user's meatus and / or auditory canal. The invention also relates to a computerised system for manufacturing such customised earpieces. In particular, the invention is directed to a computerised system that models an earpiece based on a three-dimensional replica of the user's meatus and / or auditory canal.

Computational methods are used to create cardiovascular simulations having desired hemodynamic features. Cardiovascular modeling methods produce descriptions of blood flow and pressure in the heart and vascular networks. Numerical methods optimize and solve nonlinear equations to find parameter values that result in desired hemodynamic characteristics including related flow and pressure at various locations in the cardiovascular system, movements of soft tissues, and changes for different physiological states. The modeling methods employ simplified models to approximate the behavior of more complex models with the goal of to reducing computational expense. The user describes the desired features of the final cardiovascular simulation and provides minimal input, and the system automates the search for the final patient-specific cardiovascular model.

Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. The outputs can be used as attributes to consider in developing a credit bureau scorecard.

An apparatus and method for image-based 3D photorealistic head modeling are provided. The method for creating a 3D photorealistic head model includes: detecting frontal and profile features in input frontal and profile images; generating a 3D head model by fitting a 3D genetic model using the detected facial features; generating a realistic texture from the input frontal and profile images; and mapping the texture onto the 3D head model. In the apparatus and method, data obtained using a relatively cheap device, such as a digital camera, can be processed in an automated manner, and satisfactory results can be obtained even from imperfect input data. In other words, facial features can be extracted in an automated manner, and a robust “human-quality” face analysis algorithm is used.

Various methods for improving the use of model based prediction of future blood glucose control in a patient having diabetes are described. A system for processing diabetes related information, including glucose information, for accurately predicting future glucose levels as a function of glucose data, carbohydrate intake, insulin delivery history and exercise history and then providing recommendations related to the predicted future glucose levels, is also described.

The present invention discloses a structural and mechanical model and modeling methods for human bone based on bone's hierarchical structure and on its hierarchical mechanical behavior. The model allows for the assessment of bone deformations, computation of strains and stresses due to the specific forces acting on bone during function, and contemplates forces that do or do not cause viscous effects and forces that cause either elastic or plastic bone deformation.

Systems and methods for providing adaptive, work-centered healthcare services via an adaptive user interface are provided. An example adaptive user interface apparatus includes a plurality of widgets providing applications and / or data to a user based on a particular data context, the plurality of widgets responsive to input from the user. The apparatus also includes a query engine providing customized query results from a connectivity framework of data sources based on a user query and the particular data context. The apparatus further includes a user interface display area configurable by the user to position widget(s) and query engine access to enable the user to access, input, and search medical information across a healthcare enterprise. The user interface includes an adaptive, work-centered interface employing an ontology modeling approach to characterize the user's workspace based on workflow activities and computation mechanisms to support the user's workflow and access to enterprise applications and data.

Methods and systems for performing one or more functions for a specimen using output simulated for the specimen are provided. One system includes one or more computer subsystems configured for acquiring output generated for a specimen by one or more detectors included in a tool configured to perform a process on the specimen. The system also includes one or more components executed by the one or more computer subsystems. The one or more components include a learning based model configured for performing one or more first functions using the acquired output as input to thereby generate simulated output for the specimen. The one or more computer subsystems are also configured for performing one or more second functions for the specimen using the simulated output.

Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumer's spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. The likelihood of default determined by the SOW model, when applied to a loan portfolio, can reduce the amount of credit enhancement required for an asset-backed securities rating.

A method s for specifying and implementing automation of business processes where the specification is independently manipulable by both the business process owner and technical implementers, and resulting technical elements can be tested for compliance with every detail in the specification. The method creates a single shared model suitable for understanding and execution in both the business and technical domains by focusing on the specification problem in the area of business automation. The solution to the specification problem lies in Information, Function, Flow (IFF or IF<2>) factorization of business processes. Models of the business are constructed by way of the IF<2 >modeling methodology. This is a complete model which includes, by construction, external specifications of each task included in the business model. The modularization problem is solved by preserving the partitioning of the system created in the business model. The automation system implements concrete modules that uniquely and directly correspond to particular elements whose external specification is determined by the business model.

Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. A SOW score focusing on a consumer's spending capability can be used in the same manner as a credit bureau score.

Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. A SOW score focusing on a consumer's spending capability can be used in the same manner as a credit bureau score.

The present invention is directed to the administration of various deferred compensation programs that can effectively reduce an individual's income or estate tax by assisting a company in the identification of appropriate employees, and through the use of a novel modeling method and apparatus to implement a deferred compensation program through a novel Rabbi Trust maintenance plan that permits the employees to benefit from their deferred compensation (such as stock options or life insurance benefits), while having a minimal financial impact on the company.

Methods, mediums and systems are provided to enable a user to program the behaviors of a Unified Modeling Language (UML) model in a graphical programming or modeling environment, such as block diagram programming environment. The UML model is exported into a text-based format, which is subsequently imported into the graphical programming or modeling environment. The graphical programming or modeling environment represents the UML model using functional blocks so that the user can program the behaviors of the UML model. The graphical programming or modeling environment also enables the user to simulate or execute the UML model to determine the behaviors of the UML model

The present invention provides a text implication relation recognition method which fuses multi-granularity information, and proposes a modeling method which fuses multi-granularity information fusionand interaction between words and words, words and words, words and sentences. The invention firstly uses convolution neural network and Highway network layer in character vector layer to establish word vector model based on character level, and splices with word vector pre-trained by GloVe; Then the sentence modeling layer uses two-way long-short time memory network to model the word vector of fused word granularity, and then interacts and matches the text pairs through the sentence matching layer to fuse the attention mechanism, finally obtains the category through the integration classification layer; After the model is established, the model is trained and tested to obtain the text implication recognition and classification results of the test samples. This hierarchical structure method which combines the multi-granularity information of words, words and sentences combines the advantages of shallow feature location and deep feature learning in the model, so as to further improve the accuracy of text implication relationship recognition.

The invention discloses a power system load modelling method, including the steps that: A, load classification based on daily active load curve; B, load modelling based on statistic synthesis method; C, load model parameter sensitivity analysis and range analysis based on simulation analysis; D, load model parameter node identification based on genetic algorithm, namely node identification is carried out by taking fitted local disturbance data as target, setting low sensitivity parameter value as statistic synthesis method surveying parameter value and adopting the genetic algorithm, so as to obtain multiple groups of load model parameters; E, load model parameter wide area check based on WAMS, namely load model parameter check is carried out by taking the multiple groups of solutions identified by node as initial value and taking accurate fitting on system wide area dynamic characteristic as target, so as to obtain unique solution capable of reflecting wide area dynamic characteristic when system is subject to disturbance. The invention solves the problems of multiple solutions and identifiability of overall measuring identifying method by load point classification and load model parameter aggregation and has popularization and application values.

Method and system for computation of advanced heart measurements from medical images and data; and therapy planning using a patient-specific multi-physics fluid-solid heart model is disclosed. A patient-specific anatomical model of the left and right ventricles is generated from medical image patient data. A patient-specific computational heart model is generated based on the patient-specific anatomical model of the left and right ventricles and patient-specific clinical data. The computational model includes biomechanics, electrophysiology and hemodynamics. To generate the patient-specific computational heart model, initial patient-specific parameters of an electrophysiology model, initial patient-specific parameters of a biomechanics model, and initial patient-specific computational fluid dynamics (CFD) boundary conditions are marginally estimated. A coupled fluid-structure interaction (FSI) simulation is performed using the initial patient-specific parameters, and the initial patient-specific parameters are refined based on the coupled FSI simulation. The estimated model parameters then constitute new advanced measurements that can be used for decision making.