44 results about "Canonical model" patented technology

A computer system simulation method starts with algorithmically implementing a specification model independently of hardware architecture. High level functional blocks representing hardware components are connected together using a bus architecture-independent generic channel. The bus architecture-independent generic channel is annotated with timing and protocol details to define an interface between the bus architecture-independent generic channel and functional blocks representing hardware components. The interface is refined to obtain a CCATB for communication space. The read( ) and write( ) interface calls are decomposed into several method calls which correspond to bus pins to obtain observable cycle accuracy for system debugging and validation and to obtain a cycle accurate model. The method calls are replaced by signals, and the functional blocks representing hardware components are further refined to obtain pin / cycle-accurate models which can be manually or automatically mapped to RTL, or be used to co-simulate with existing RTL components.

A semantic database transaction monitor is provided that monitors database transactions by taking advantage of database replication technology. The invention receives one or more event streams of transaction data from one or more database replication software agents, originally from transaction logs, and then classifies each transaction, utilizing an inference engine populated with one or more source ontologies and a canonical ontology so that transaction metadata are normalized. The invention then can be utilized to create a data store across multiple databases for reporting and analysis. The invention can also be used to feed normalized database transactions to real-time graphics software for real-time reporting or alerting. Because the process obtains data from event streams, it does not significantly drain the resources of the databases and can provide virtually real-time monitoring. Moreover, it does not require recoding for updates to the databases, but only changes to the ontologies read at runtime.

The present invention relates to a method for operation of resonance dislocation image making equipment.Firstly, a dissection canonical model (M) with changeable geometric figure is selected for an examination object depending on diagnosis problems.And then, a plurality of compendia images are measured for areas including the examination object, and different compendia sweep parameters (UP) used for controlling measurement of the compendia images are determined according to the chosen dissection canonical model (M).An object construction (Z) is determined in the sectional view image data (UD) of the measured compendia images, and the canonical model (M) is personalized to match the object construction (Z).According to the chosen canonical model (M) and the diagnosis problems, subsequent dislocation images sweep parameters (SP) for the resonance equipment are selected and controlled, the chosen sweep parameters (SP) are personalized corresponding to the personalized canonical model (M), and a plurality of dislocation images are measured on the basis of the personalized sweep parameter (ISP). The invention also relates to a corresponding image processing system.

Apparatuses, computer program products, and methods for identifying redundancy and consolidation opportunities in databases and application systems are disclosed. In one embodiment, the apparatus may include at least one meta data scanner. The apparatus may also include an enterprise meta data source. The apparatus may further include a meta data repository. The meta data repository receives system-specific meta data from the at least one meta data scanner. The meta data repository may also receive enterprise canonical data model meta data from the enterprise meta data source. The meta data repository may be configured to generate at least one individual system CRUD matrix that may then used to produce an enterprise canonical model CRUD matrix. The enterprise canonical model CRUD matrix may be analyzed by a data mining clustering algorithm. The clustering algorithm may group together modules and database elements that may be redundant and may indicate opportunities for consolidation.

A method of generating a scenario includes generating a specification model by describing a specification in a predetermined descriptive language, extracting a plurality of operations from the specification model, generating a plurality of operation descriptions, each of which corresponds to one of the operations and includes an operation name and a constraint condition, generating at least one cause-effect graph that combines the operations based on the operation descriptions, and extracting as a scenario a series of operations from the cause-effect graph.

An embodiment in accordance with the present invention provides a method for non-invasively determining the functional severity of coronary artery stenosis. The method includes gathering patient-specific data related to concentration of a contrast agent within a coronary artery of a patient using a coronary computed tomography angiography scan (CCTA). The patient-specific data is used to calculate a patient-specific transarterial attenuation gradient for the coronary artery of the patient. The patient specific transarterial attenuation gradient is compared to previously collected data to determine an estimate of a pressure gradient and / or fractional flow reserve (FFR) for the patient. As more data is collected, the data can be added to the database in order to increase the accuracy of future assessments. The database can also be enhanced by adding data generated by canonical models and mathematical analysis.

According to some embodiments, a system includes a communication device operative to communicate with a user to obtain the one or more requirements associated with a specification model for a semantic module; a semantic module to receive the one or more requirements, store the one or more requirements and transform the one or more requirements into a semantic model; a specification module to receive the semantic model, store the semantic model, translate the semantic model and generate a specification model; a memory for storing program instructions; at least one specification model platform processor, coupled to the memory, and in communication with the specification module and the semantic module and operative to execute program instructions to: transform the one or more requirements into a semantic model by executing the semantic module; translate the semantic model into a graphical model by executing the specification module; and modify the graphical model by executing the specification module to generate the specification model; and generate a specification model that is human-readable and computer-readable for use in software design. Numerous other aspects are provided.

The invention discloses an image blind deblurring method based on edge self-adaption. To solve the problems that as for an existing total variation deblurring algorithm, edges and details of images are easily blurred, a de-mean gradient total variation canonical model is built, weighting coefficients are calculated in an iterated mode by means of local variance self-adaption of gradients of the images, and the ability of the deblurring algorithm to restore the edges and the details of the images. The image blind deblurring method comprises the following steps that (1) a blurred image is input, solutions to a gradient-region clear image and a blurring kernel are obtained alternately, and the initial blurring kernel of the blurred image is obtained; (2) the initial blurring kernel is used for conducting primary non-blind deblurring on the blurred image, and an initial clear image is obtained; (3) clustering is conducted on the initial clear image, the mean value and the weighting coefficient in the de-mean canonical model are updated, and a solution to the blurring kernel is obtained again; (4) the new blurring kernel is used for conducting secondary non-blind deblurring so as to obtain a clear image. Experimental results show that the image blind deblurring method based on edge self-adaption has better deburring effect than the prior art and can be used for image restoration.

Process engineering software applications have respective proprietary in nature and disconnected model representations of a manufacturing or processing facility. The invention method and apparatus extract from the various applications topology of equipment and streams for a facility. From the extracted data, a convertor or adapter of the invention system derives a common canonical model. To support the common canonical model (e.g., a Flowsheet object in embodiments), the converter / adapter maps or associates one or more physical assets to a logical asset, and arranges a working hierarchy of assets that can be navigated, queried and filtered.