2516 results about "Computational model" patented technology

Systems and methods for energy monitoring and for providing the user with contextual information on the energy usage of a building area are disclosed. The methods may comprise performing an energy audit of a building and using the audit data and a building physics simulator to construct a computational model of the building's energy usage. An energy budget may be derived based on the computational model. The building's actual energy usage is reported with contextual information on energy usage from the computational model, the energy budget, historical data on energy usage, and other sources. The systems generally include energy monitoring hardware, a building physics simulator engine, and an interface. The interface may be implemented in hardware or software. The components of the system may be located in one building, or a central monitoring station with a building physics simulator engine may communicate with energy monitoring hardware in several buildings.

An analyzer for maintaining and analyzing source code is disclosed. The analyzer includes a software translator for converting conventional source code into an intermediate language, slicing capability based upon weakest precondition determination, dual direction flow analysis and incorporation of a computational model to facilitate iterative code.

A method and system for generating a patient specific anatomical heart model is disclosed. A sequence of volumetric image data, such as computed tomography (CT), echocardiography, or magnetic resonance (MR) image data of a patient's cardiac region is received. A multi-component patient specific 4D geometric model of the heart and aorta estimated from the sequence of volumetric cardiac imaging data. A patient specific 4D computational model based on one or more of personalized geometry, material properties, fluid boundary conditions, and flow velocity measurements in the 4D geometric model is generated. Patient specific material properties of the aortic wall are estimated using the 4D geometrical model and the 4D computational model. Fluid Structure Interaction (FSI) simulations are performed using the 4D computational model and estimated material properties of the aortic wall, and patient specific clinical parameters are extracted based on the FSI simulations. Disease progression modeling and risk stratification are performed based on the patient specific clinical parameters.

A method for determining cardiac status comprises for a given patient, constructing a patient-specific, three-dimensional, computational model of the patient's heart; and executing the constructed computational model, said executing generating a quantitative analysis of cardiac function. A method of performing cardiac surgeries comprises: a) assessing surgical options based on a patient-specific, three-dimensional, computational model of a patient's heart; and b) performing surgery based on one or more of the surgical options. A computer system comprises: a) a data source containing data of a patient's heart; b) a modeler coupled to receive data from the data source, the modeler generating a patient-specific, three-dimensional, computational model of the heart based on the heart data; and c) a processor routine for computationally providing information about a certain cardiac function using the three-dimensional heart model and for applying computational, quantitative analysis of the cardiac function, wherein the quantitative analysis of the cardiac function provides an assessment for surgical options, optimizing surgical techniques, or predicting outcomes.

The invention relates to a device and a method for identifying and evaluating an emergency hot topic. The device is provided with four component parts including a text acquisition unit, a text expression unit, a topic clustering unit and a topic evaluation unit. The device and the method are characterized in that only a title, introduction, relevant features and other information of a text of a news report are extracted and regarded as an effective sample set identified by the hot topic. Compared with the existing full text extraction, the experiment result shows that the result of the existing full text extraction is similar to the result of the partial text extraction, but the operation of the device and the method is greatly simplified. Compared with a classical model, an improved feature weight calculation model is good in execution efficiency and strong in adaptability of text representation capability. The model is used for evaluating the hot value of clustered topics, and the calculated hot topic accords with the expected effect and is adaptive to the features of the emergency news report. In a word, in the process of processing the text of the emergency news report, the device and the method have good performance in aspects of calculation complexity, result accuracy and timeliness.

The invention discloses an application management method. The method comprises the following steps: obtaining current application scene information, a pre-stored first application probability of each application program applied under each application scene, and a second application probability of each application program applied under each application scene during triggering cleaning of background application programs; inputting the current application scene information, all the first application probabilities and all the second application probabilities into a preset Bayesian network probability calculating model and calculating a third application probability of each background application program applied under the current application scene; and closing the background application programs with third application probabilities being smaller than a preset probability threshold value. The invention also discloses a mobile terminal and a computer-readable storage medium. Through the application management method, the accuracy of application management of the mobile terminal can be improved.

System and method for creating a graphical program that uses multiple models of computation (MoC). A first plurality of graphical program elements is assembled in a graphical program in response to first input, where the assembled first plurality of graphical program elements have a first MoC. A structure is displayed in the graphical program indicating use of a second MoC for graphical program elements comprised within the interior of the structure. A second plurality of graphical program elements is assembled within the structure in response to second input, where the assembled second plurality of graphical program elements have the second MoC. The graphical program is executable to perform a function, for example, by executing the assembled first plurality of graphical program elements in accordance with the first model of computation, and executing the assembled second plurality of graphical program elements in accordance with the second model of computation.

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.

An architecture for capture and generation, and a set of methods for characterization, prediction, and classification of traffic in packet networks are disclosed. The architecture consists of a device that stores packet timing information and processes the data so that characterization, prediction, and classification algorithms can perform operations in real-time. A methodology is disclosed for real-time traffic analysis, characterization, prediction, and classification in packet networks. The methodology is based on the simultaneous aggregation of packet arrival times at different times scales. The traffic is represented at the synchronous carrier level by the arrival or non-arrival of a packet. The invention does not require knowledge about the information source, nor needs to decode the information contents of the packets. Only the arrival timing information is required. The invention provides a characterization of the traffic on packet networks suitable for a real-time implementation. The methodology can be applied in real-time traffic classification by training a neural network from calculated second order statistics of the traffic of several known sources. Performance descriptors for the network can also be obtained by calculating the deviation of the traffic distribution from calculated models. Traffic prediction can also be done by training a neural network from a vector of the results of a given processing against a vector of results of the subsequent processing unit; noticing that the latter vector contains information at a larger time scale than the previous. The invention also provides a method of estimating an effective bandwidth measure in real time which can be used for connection admission control and dynamic routing in packet networks. The invention provides appropriate traffic descriptors that can be applied in more efficient traffic control on packet networks.

The present invention provides a method for designing and making a customized ophthalmic lens, such as a contact lens or an intraocular lens, capable of correcting high-order aberrations of an eye. The posterior surface of the customized contact lens is designed to accommodate the corneal topography of an eye. The design of the customized ophthalmic lens is evaluated and optimized in an optimizing routine using a computational model eye that reproduces the aberrations and corneal topography of an eye. The present invention also provides a system and method for characterizing the optical metrology of a customized ophthalmic lens that is designed to correct aberrations of an eye. Furthermore, the present invention provides a business model and method for placing an order for a pair of customized ophthalmic lenses.

A method and a computer system, for providing an assessment for disease status of a disease, such as a cardiovascular disease, employ construction of image-based 3D computational model of an organ representative of the disease status; computationally obtaining a certain mechanical distribution using the 3D-organ model; and computational, quantitative analysis of the mechanical distribution to provide an assessment for disease status of a disease. The image-based 3D computational model includes a fluid-structure interaction and multiple components within the organ.

The invention provides an academic resource recommendation service system and method. The method comprises the following steps: crawling academic resources on an internet by using an LDA (Latent Dirichlet Allocation)-based focused crawler, classifying the academic resources according to preset A types by using an LDA-based text classification model, and storing the academic resources in a local academic resource database, wherein the system further comprises an academic resource model, a resource quality value calculation module and a user interest module; implanting a tracking software module at a user terminal, combining interesting subjects and historical browsing behavior data of the user, respectively modeling the academic resource model and the user interest module by virtue of four dimensions such as the academic resource type, subject theme distribution, key word distribution and LDA latent theme distribution, calculating the similarity between the academic resource model and the user interest preference module, combining the resource quality value to calculate the recommendation degree, and finally perform academic resource Top-N recommendation for the user according to the recommendation degree. According to the method disclosed by the invention, personalized accurate recommendation of the academic resources is performed according to the identity, interest and browsing behaviors of users, and the working efficiency of scientific research personnel is improved.

A method for maintaining consistent unit relationships during graphical pharmacological computational model construction is disclosed. A graphical user interface is presented through which a user may place and connect objects representing pharmacokinetic and pharmacodynamic elements. The user may specify units definitions for variables and constants using unit expressions. As the objects are converted into an internal format representing the statements of the corresponding computational model, the unit expressions are included in this internal format as multidimensional data type information. This multidimensional data type information is regularly and automatically propagated for each statement in the internal format to identify inconsistent units. When such inconsistent units are identified, a warning message is generated to notify the user, substantially immediately after the inconsistent units are created.

A computational model which integrates a complex circulatory model and a finite element to determine the dynamics of a left ventricle continuously over consecutive cardiac cycles. The model includes determining a LV pressure (plv) using a circulatory model, using a finite element model plv as input and determining a LV volume (vlv), computing a LV elastance according to: elv=plv / vlv, driving the circulatory model with the elv; and returning to determining a LV pressure and starting the next iteration, wherein the steps continue at a sufficient time resolution for a desired number of entire cardiac cycles. The dynamic Young's modulus functions are assigned to individual finite elements, resulting in a time-varying left ventricular elastance that drives the circulatory model.

Mechanisms for operating a prover device and a verifier device so that the verifier device can verify the authenticity of the prover device. The prover device generates a data string by: (a) submitting a challenge to a physical unclonable function (PUF) to obtain a response string, (b) selecting a substring from the response string, (c) injecting the selected substring into the data string, and (d) injecting random bits into bit positions of the data string not assigned to the selected substring. The verifier: (e) generates an estimated response string by evaluating a computational model of the PUF based on the challenge; (f) performs a search process to identify the selected substring within the data string using the estimated response string; and (g) determines whether the prover device is authentic based on a measure of similarity between the identified substring and a corresponding substring of the estimated response string.

A system for measuring an ability of a subject. The system includes a set of tasks that require the subject to provide one or more spoken responses. A speech recognition system, which is coupled to receive the spoken responses, provides an estimate of the spoken responses. The estimate may be an estimate of the linguistic content and / or other characteristics of the response. The speech recognition system has an associated operating characteristic relating to its ability to recognize and estimate the content of responses and elements of responses. A scoring device converts the response estimate into one or more item scores. A computation device provides a subject score using a scoring computation model that depends upon the expected item-dependent operating characteristics of the speech recognition system.

This invention generally relates to natural gas and methylotrophic energy generation, bio-generated fuels and microbiology. In alternative embodiments, the invention provides nutrient amendments and microbial compositions that are both specifically optimized to stimulate methanogenesis, or “methylotrophic” conversion. Additionally, the invention provides methods to develop nutrient amendments and microbial compositions that are both specifically optimized to stimulate methanogenesis in a given reservoir. The invention also provides methods for the evaluation of potentially damaging biomass formation and scale precipitation resulting from the addition of nutrient amendments. In another embodiment, the invention provides methods for simulating biogas in sub-surface conditions using a computational model.

The invention relates to an evaluating system and method for community influence in a social network. The method comprises the steps that a social network chart with social network users as nodes and user relationships as sides is built; according to the social network chart, the community structure of the social network is obtained by carrying out community division through the label propagation algorithm; according to the social network chart and matrixes which communities belong to, the parameter of the community influence is calculated, and the initial influence of each community is generated; according to the transmission probability model of the influence, an influence transmission probability matrix is generated; according to the influence transmission probability matrix and the community influence iterative computation model, the community influence is iterated and upgraded until the iteration end condition is met, the influence value of each community is obtained, and the sequence of the community influence, namely, the influence estimation result of each community in the social network is obtained after normalization. The system and method can effectively analyze the distribution of the community influence in the social network and can be used for high-influence community mining, thereby being capable of being applied to the fields of network marketing and the like.

A method and system for non-invasive assessment of renal artery stenosis is disclosed. A patient-specific anatomical model of at least a portion of the renal arteries and aorta is generated from medical image data of a patient. Patient-specific boundary conditions of a computational model of blood flow in the portion of the renal arteries and aorta are estimated based on the patient-specific anatomical model. Blood flow and pressure are simulated in the portion of the renal arteries and aorta using the computational model based on the patient-specific boundary conditions. At least one hemodynamic quantity characterizing functional severity of a renal stenosis region is calculated based on the simulated blood flow and pressure in the portion of the renal arteries and aorta.

The invention belongs to the technical field of wireless communication networks, and discloses a federated learning information processing method and system, a storage medium, a program, and a terminal. A parameter serve confirms a training task and an initial parameter and initialize a global model. The parameter server randomly selects part of participants to issue model parameters, encrypts themodel parameters and forwards the model parameters through the proxy server; the participants receive part of parameters of the model and cover the local model, and the model is optimized by using local data; the participant calculates a model gradient according to an optimization result, selects a part of the model gradient for uploading, adds noise to the uploading gradient to realize differential privacy, encrypts the uploading gradient and forwards the uploading gradient through the proxy server; the parameter server receives the gradients of all participants, and integrates and updates the global model; and the issuing-training-updating process of the model is repeated until an expected loss function is achieved. According to the invention, data privacy protection is realized; the communication overhead of a parameter server is reduced, and anonymity of participants is realized.

The invention discloses a power grid multi-source data fusion method and system based on a multi-element heterogeneous model. The method comprises the following steps of multi-source data access, metadata storage, unified device modeling and data extraction, model matching degree calculation and multi-element data fusion. The system mainly comprises the five modules of multi-source data access, metadata storage, unified device modeling and data extraction, model matching degree calculation and multi-element data fusion. A unified model including multi-source system data is established by deeply analyzing the multi-source system data, automatic association is performed through model traversal comparison and model matching degree calculation according to the matching degree, automatic data integration and fusion of 90% or above is achieved, unfused data details and detailed causes are accurately analyzed, integration and fusion of various service data are achieved, and the overall fusion quality is effective managed and controlled.

The invention discloses a general machine learning algorithm model training method and system, and computing nodes. The general machine learning algorithm model training method comprises the following steps: before initialization, a machine learning algorithm model is divided into m model partitions, each model partition copy is configured to one corresponding computing node, and the computing nodes obtain input data according to the configured model partition copies to compute the model partition copies; the computing nodes upload model parameter information obtained by computation to corresponding parameter servers, the parameter servers compute model parameters according to the obtained model parameter information, and the computing nodes obtain the model parameters from the parameter servers to update local model parameters. The system comprises configuration equipment, the computing nodes and the parameter servers, wherein each computing node comprises an input and output unit, a computing unit and a synchronization unit. The general machine learning algorithm model training method and system disclosed by the invention are unrelated to a machine learning algorithm and are high in computing efficiency.

A method for diagnosing a system is provided. The method may include obtaining a plurality of input parameters from the system. The system may generate actual values of one or more output parameters based on the plurality of input parameters. The method may also include independently deriving values of the one or more output parameters, based on the plurality of input parameters, using a computational model, and detecting a divergence between the derived values and the actual values. Further, the method may include identifying respective desired statistic distributions of the plurality of input parameters, based on the actual values of the one or more output parameters, using the computational model.

The invention relates to a method for objectively and quantifiably evaluating noise fret degree in a vehicle based on an auditory model, in particular to an evaluation method of psychoacoustics and vehicle sound quality. The method comprises the following steps: designing a dummy head model; imitating a processing mechanism of the middle ear and the inner ear of a human body to the sound by usingan auditory peripheral calculation model; collecting vehicle noise signals under the working conditions of uniform, accelerated and idle speed; pre-treating the noise sample and processing the loudness in specification; obtaining a psychoacoustics parameter by using a sound quality calculation model; obtaining subjective evaluation result test data by using a grouped and paired comparison method;calculating and painting a correlated scatter plot chart between each parameter and the ranking value of the subjective evaluation result; and analyzing and calculating to obtain the objectively quantifiable model of the subjective fret degree under each working condition. The invention can realize the psychoacoustic parameter calculation of objectively evaluating the sound quality with differentvehicle types, gears and speeds, wherein the calculated value has good pertinence and consistency with the evaluated result of the subjective evaluation method. The invention has stable evaluated result and high reliability, and can improve the sound quality and competitiveness of vehicles combined with the design of new CAE cars.

A system and method are proposed for measuring confusability or similarity between given entry pairs, including text string pairs and acoustic model pairs, in systems such as speech recognition and synthesis systems. A string edit distance (Levenshiten distance) can be applied to measure distance between any pair of text strings. It also can be used to calculate a confusion measurement between acoustic model pairs of different words and a model-driven method can be used to calculate a HMM model confusion matrix. This model-based approach can be efficiently calculated with low memory and low computational resources. Thus it can improve the speech recognition performance and models trained from text corpus.

A method and system for non-invasive hemodynamic assessment of coronary artery stenosis based on medical image data is disclosed. Patient-specific anatomical measurements of the coronary arteries are extracted from medical image data of a patient. Patient-specific boundary conditions of a computational model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements of the coronary arteries. Blood flow and pressure in the coronary arteries are simulated using the computational model of coronary circulation and the patient-specific boundary conditions and coronary autoregulation is modeled during the simulation of blood flow and pressure in the coronary arteries. A wave-free period is identified in a simulated cardiac cycle, and an instantaneous wave-Free Ratio (iFR) value is calculated for a stenosis region based on simulated pressure values in the wave-free period.

A materials characterization method models dynamic, non-linear, temperature-dependent stress, strain, hysteresis, creep, and loss of elasticity at high strain, both in test samples and in Finite Element Analysis (FEA). Incorporating universal properties of statistical mechanics and adapting domain models from ferromagnetics to the higher-dimensional realm of stress tensors, the model is applicable to polymers, rubbers, liquids, and metals in elastic and plastic deformation. The model quantifies the dynamics of both plastic and brittle failure. Apparatus and methods are shown for testing material samples and matching the computational model to sample characteristics, leading to a set of characterizing parameters and predictive simulations using those parameters. Though apparatus and testing protocols of the invention yield optimum characterizations, pre-existing data from conventional testing yield useful results.