206 results about "Model representation" patented technology

The invention discloses a digital twinning evolution mechanism and method for an intelligent mine scene, the digital twinning is formed by mutual coupling and evolution integration of a physical model, a logic model, a simulation model and a data model, and the method comprises the following steps: (1) defining the physical model; (2) representing the logic model; (3) establishing a simulation model; (4) optimizing the simulation model; (5) verifying the simulation model; (6) constructing a data model; and (7) performing digital twinning integration. According to the invention, by constructinga digital twinning model, data mirroring and information interaction between a digital twinning body and a physical entity are realized, and object twinning, process twinning and performance twinningof the physical entity and a virtual space digital twinning body are realized; according to the invention, through a digital twinning evolution mechanism and method, remote visual monitoring of a physical space intelligent mine scene is realized in a virtual space intelligent mine scene, and intelligent perception, real-time monitoring, accurate positioning and health prediction are carried out on mine application scene equipment.

The invention discloses a mine digital twinning model and a construction method thereof. The digital twinning model is formed by mutual coupling and evolution integration of a physical model, a logicmodel, a simulation model and a data model, and the construction method comprises the following steps: (1) constructing a physical model; (2) representing a logic model; (3) establishing a simulationmodel; (4) optimizing a simulation model; (5) verifying the simulation model; (6) constructing a data model; (7) performing digital twin representation. The method is based on a machine vision and deep learning algorithm, and by constructing a digital twinning model, object twinning, process twinning and performance twinning of a physical space physical entity and a virtual space digital twinningbody, and data mirroring and information interaction between the digital twinning body and the physical entity are realized; through a digital twinning model and a construction method thereof, remotevisual monitoring of a physical space mine scene, intelligent perception, real-time monitoring, accurate positioning and health prediction of the mine scene are realized in a virtual space mine scene.

A system and method for generating high-function browser widgets with full addressability are provided. With the system and method, custom JSP tags are utilized that generate JavaScript objects to provide the high-function browser widgets. The JavaScript objects, in turn, output HTML for use by a client side Web browser. These JavaScript objects have instance-level functions or actions that are encapsulated in the widget as well as a complete client-side model representation of the data also encapsulated in the widget object. These objects and actions are fully addressable by the developer via a getWidgetByID method on a global utility object. As a result, higher-level features and full inter-widget communication are achievable using the custom JSP tags of the present invention.

A method, system and computer program product for managing a browsing history for a web browser. The web browser is configured to display web page content. A web page is addressable by a Uniform Resource Locator. New page content from a server is received at the web browser. A subset of a current web page is replaced with the new page content. The subset thus replaced does not include a complete web page. A data entry is stored in a chronologically ordered history list. The data entry comprises a hierarchical, object-oriented model representation of the new page content. The model representation may be a subset of a Document Object Model. At least one history navigation button is provided for traversing the history list. Page content stored at the history list is redisplayed. Backward and forward navigation within applications embodying Web 2.0 technologies, including AJAX, is thus facilitated.

Techniques for generating a visual representation for a model representation in a manner whereby the model representation is not coupled to the visual representation. An abstract representation is generated based upon the model representation. Mapping rules are configured and used for generating the abstract representation from the model representation. A visual representation is then generated based upon the abstract representation.

Methods and apparatuses for still image compression, video compression and automatic target recognition are disclosed. The method of still image compression uses isomorphic singular manifold projection whereby surfaces of objects having singular manifold representations are represented by best match canonical polynomials to arrive at a model representation. The model representation is compared with the original representation to arrive at a difference. If the difference exceeds a predetermined threshold, the difference data are saved and compressed using standard lossy compression. The coefficients from the best match polynomial together with the difference data, if any, are then compressed using lossless compression. The method of motion estimation for enhanced video compression sends I frames on an "as-needed" basis, based on comparing the error between segments of a current frame and a predicted frame. If the error exceeds a predetermined threshold, which can be based on program content, the next frame sent will be an I frame. The method of automatic target recognition (ATR) including tracking, zooming, and image enhancement, uses isomorphic singular manifold projection to separate texture and sculpture portions of an image. Soft ATR is then used on the sculptured portion and hard ATR is used on the texture portion.

A system, method, and computer program for modifying a solid model representation that is manipulated in a computer having software instructions for design, comprising: a computer system, wherein the computer system includes a memory, a processor, a user input device, and a display device; a computer generated geometric model stored in the memory in the memory of the computer system; and wherein the computer system receives user input and accesses at least one data file having a plurality of geometric model definitions that define a geometric model; converts the geometric model definitions into a geometric representation of the geometric model; calculates a plurality of geometric conditions between at least one geometry identified by a user and the geometric model to create a set of constraints; and calculates a modified geometric model with a modified geometry according the set of constraints to display to the user; and appropriate means and computer-readable instructions.

The present invention relates to a method for simulating aspects of a lithographic process. According to certain aspects, the present invention uses transmission cross coefficients to represent the scanner data and models. According to other aspects, the present invention enables sensitive data regarding various scanner subsystems to be hidden from third party view, while providing data and models useful for accurate lithographic simulation.

A computer-implemented method for modeling and / or improving operational performance of an energy system includes providing a graphical user interface configured to allow a user to manipulate equipment icons into an energy system model representation, using modular, piece-wise linear equipment models to simulate non-linear behavior of equipment represented by the manipulated equipment icons to solve an energy system model represented by the manipulation, and displaying a solution of the energy system model.

A method for utilizing oral movements is used in speech assessment, speech therapy, language development, and controlling external devices. A device is used which includes a sensor plate having sensors to detect contact of the tongue with the sensor plate. One aspect of the invention allows viewing representations of contact of the tongue and palate during speech and comparing the representations with model representations displayed in a split screen fashion. The model representations may be generated by another speaker utilizing a sensor plate or by computer generated representations which have been electronically stored. The representations may be analyzed to assess speech proficiency and the model may be mimicked for speech enhancement.

A constrained non-linear approximator for empirical process control is disclosed. The approximator constrains the behavior of the derivative of a subject empirical model without adversely affecting the ability of the model to represent generic non-linear relationships. There are three stages to developing the constrained non-linear approximator. The first stage is the specification of the general shape of the gain trajectory or base non-linear function which is specified graphically, algebraically or generically and is used as the basis for transfer functions used in the second stage. The second stage of the invention is the interconnection of the transfer functions to allow non-linear approximation. The final stage of the invention is the constrained optimization of the model coefficients such that the general shape of the input / output mappings (and their corresponding derivatives) are conserved.

There is provided a method for classifying, identifying or verifying an object by representing the object by a respective sequence of vectors, modeling the sequence of vectors with a respective generative model such that the object is represented by the generative model, computing the distances between the generative models to form one or many kernel matrices based on the distance metric, and using the kernel matrices to classify, identify or verify the object. There is provided a system for determining a classification of an object having a representation module for representing an object by a respective sequence of vectors, a modeling module for modeling the sequence of vectors with a respective generative model such that the object is represented by the generative model, a distance computing module for calculating the distances between the generative models to form one or many kernel matrices based on the distance metric, and a determination module for classifying, identifying or verifying the object based on the kernel matrices.

A system, method, and computer program for modifying a solid model representation that is manipulated in a computer having software instructions for design, comprises: a computer system, wherein the computer system includes a memory, a processor, a user input device, and a display device; a computer generated geometric model stored in the memory in the memory of the computer system; and wherein the computer system receives user input and accesses at least one data file having a plurality of geometric model definitions that define a geometric model; converts the geometric model definitions into a geometric representation of the geometric model; calculates a plurality of geometric conditions between at least one geometry identified by a user and the geometric model to create a set of constraints; and calculates a modified geometric model with a modified geometry according the set of constraints to display to the user; and appropriate means and computer-readable instructions.

The invention relates to an Internet of Things data uncertainty measurement, prediction and outlier-removing method based on the Gaussian process. The method is a dynamical system method of estimating and collecting the standard deviation of Internet of Things perception sensor measurement errors and combining the Gaussian process modeling theory with autoregression model representations; prediction values and uncertainty measurement of observation data effective time sequence data are given, whether the data are missing values or outlier data is judged according to the information, and data supplement is correspondingly carried out. The method is a non-parameterized probability prediction method. Due to the fact that training set learning has the feature of tracing system dynamic states, judgment, early-warning and data supplement can be carried out on data exception and data missing phenomena in time according to the prediction value uncertainty and the sensor calibration standard deviation, the prediction error is small, and the accuracy is high. The Internet of Things data uncertainty measurement, prediction and outlier-removing method is used for controlling the quality of Internet of Things automatic observation data, and can ensure accuracy of collected data.

The invention relates to a cross-domain knowledge transfer tag embedding method and apparatus. The method comprises the steps of obtaining text data of a source domain and a target domain, performing model representation, solving word vector parameters of keywords in the source domain and the target domain, and performing transfer of keyword tags from the source domain to the target domain; obtaining nearest neighbors of labeled keywords in the source domain and the target domain, performing weight assignment on keywords of the nearest neighbors by keyword tags of the labeled keywords to obtain extended keyword tags; performing user-level keyword tag labeling according to extracted user-level text data; dynamically optimizing parameters of user-level keyword tag parts according to click and / or access data information of a user based on the word vector parameters of the keywords and the user-level keyword tags; and obtaining new user-level text data from the target domain, performing user-level keyword tag labeling prediction and sorting, and outputting a result. According to the method and the apparatus, the accuracy and high efficiency of tag labeling can be taken into account and business demands of business personnel are met.

In some embodiments, user-selectable / connectable model representations may be provided via a user interface to facilitate artificial intelligence development. The model representations may comprises first and second machine learning model (ML) representations corresponding to first and second ML models, and non-ML model representations corresponding to non-ML models. Based on user input indicating selection of the first and second ML model representations and a non-ML model representation corresponding to a non-ML model, at least a portion of a software application may be generated such that the software application comprises (i) an instance of the first ML model, an instance of the second ML model, and an instance of the non-ML model and (ii) an input / output data path between the instance of the first ML model and at least one other instance, the at least one other instance comprising the instance of the second ML model or the instance of the non-ML model.

A system and method for multi-level security filtering of model representations. Elements of an architecture and systems engineering model have associated security characteristics identifying the required level of security that a user must have in order to be able to obtain access to information about that element of the model. Based on these security characteristics and the security level of a user attempting to access the model, the content of the model is modified such that elements that are not accessible by a user having that security level are obscured or not visible to the user. The other elements of the model which are accessible by the user based on his / her security level are modified in the modified model so as to not provide information that would disclose the nature, character, or in some cases even the presence, of the elements that are not accessible by the user based on his / her security level.

A method and system for fusion of multi-modal volumetric images is disclosed. A first image acquired using a first imaging modality is received. A second image acquired using a second imaging modality is received. A model and of a target anatomical structure and a transformation are jointly estimated from the first and second images. The model represents a model of the target anatomical structure in the first image and the transformation projects a model of the target anatomical structure in the second image to the model in the first image. The first and second images can be fused based on estimated transformation.

A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

The present invention relates to a system, method, and apparatus that combine a novel specialized software program and a novel viewing program. The novel software program creates one or more photorealistic images of a 3D model at various camera angles. The novel viewing program allows the user to view the photorealistic images interactively directly on a web browser without third party proprietary software plugins. Also, the viewing program provides a novel approach to changing the colors of objects, by changing them dynamically.

An automated optimization system for generating multiple alternative training and transition plans for airline pilots which include a recall of furloughed pilots, and limits to deviation of pilot start bid periods for training assignments from a specific bid period, wherein such plans are cost optimized to track payroll costs of pilots recalled from furlough, and the combined time for solving an MIP Model representation and generating such plans therefrom is less than one hour.

The present invention relates to a method for generating hypotheses automatically from graphical models built directly from data. The method of the present invention links three key scientific concepts to enable hypothesis generation from data driven hypothesis-models: including the use of information theory based measures to identify informative feature subsets within the data; the automatic generation of graphical models from the informative data subsets identified from step one; and the application of optimization methods to graphical models to enable hypothesis generation. The integration of these three concepts can enable scalable approaches to hypothesis generation from large, complex data environments. The use of graphical models as the model representation can allow prior knowledge to be effectively integrated into the modeling environment.

An express spreadsheet visualization system configured to simultaneously display, update, and synchronize BIM model representations across spreadsheet applications and visualization handling applications. The express spreadsheet visualization system provides a synchronizing mechanism between the two representations. Users get the benefit of complete information in one place. Updates made to pertinent parts in a BIM model in either representation (visual or spreadsheet) are automatically reflected in the associated representation.

Systems and methods for correlating meta-data model representations and asset-logic model representations in a system model.

The invention provides a convolutional neural network filter pruning technology based on similarity learning. The method comprises the steps of obtaining the similarity between different filters through similarity survey; performing clustering on the filters according to the similarity; enabling the filters in the same cluster to become more and more similar through convergent training; and finally pruning the filters after the convergent training. The technology solves the problem that the model representation capability is reduced and needs to be re-trained in a convolutional neural networkfilter pruning process, so that the representation capability and precision of a network can be better retained; and in addition, the precision loss of the convolutional neural network is hardly caused, the precision of a model does not need to be restored through re-training, and the better balance of model precision and efficiency is achieved.

In a first exemplary embodiment of the present invention, an automated, computerized method for manipulating an image comprises the steps of manipulating the image to provide an intensity adjusted image, deriving a bi-illuminant dichromatic reflection model representation of the image and utilizing the bi-illuminant dichromatic reflection model representation to manipulate the intensity adjusted image to generate a color correct intensity adjusted image. In a preferred embodiment of the present invention, the step of manipulating the image to provide an intensity adjusted image is carried out by executing a gamma correction method.

The invention discloses a point cloud enhancement method based on subsection resampling and surface triangularization. The method comprises the specific steps that an input point cloud (imag file=' 2013107425845100004dest-path-image001. TIF' wi='13' he='32' / ) is divided to obtain the set (img file='752571des t-path-image002. TIF' wi='37' he='24' / ) of the subsets of the point cloud (img file='835430dest-path-image001. TIF' wi='13' he='32' / ), each subset (img file='2012107425845100004dest-path-imag003. TIF' wi='20' he='32' / ) is resampled, data noise is filtered out, and new point sets (img file='dest-path-image005. TIF' wi='23' he='32' / ) which are more even in space distribution are obtained; the sets (img file='250417dest-path-image006. TIF' wi='40 he='32 / ) of all the resampled new point sets are combined, a new point cloud (img file='dest-path-mage007. TIF' wi='16' he='32' / ) is obtained, the surface triangularization is carried out on the new point cloud (img file='114468dest-path-mage007. TIF' wi='16' he='32' / ), and a triangular mesh model ((img file='397682dest-path-image008. TIF' wi='15' he='32' / ) is obtained. According to the method, an environmental structure is restored accurately, and meanwhile the original edges and corners of the environment are prevented from being smoothed by mistake; different sampling densities are selected according to different model surface shape change intensity degrees, and model representation is more efficient. The point sets are projected to a two-dimensional plane to be triangulated at the part of the model, and the calculation efficiency ratio is higher than that of triangularization directly carried out in a three-dimensional space.

A computer-implemented method, computer program product and a system for supporting star and snowflake data schemas for use with an Extract, Transform, Load (ETL) process, comprising selecting a data source comprising dimensional data, where the dimensional data comprises at least one source table comprising at least one source column, importing a data model for the dimensional data into a data integration system, analyzing the imported data model to select a star or snowflake target data schema comprising target dimensions and target facts, generating a meta-model representation by mapping at least one source table or source column to each target fact and target dimension, automatically converting the meta-model representation into one or more ETL jobs, and executing the ETL jobs to extract the dimensional data from the data source and loading the dimensional data into the selected target data schema in a target data system.