90 results about "Dependent model" patented technology

A system, method, and various software products provide for consistent identification of web users across multiple web sites, servers and domains, monitoring and capture of data describing the users' web activities, categorization of the web activity data, aggregation of the data into time dependent models describing interest of users and groups over time. Categorization is made with respect to a category tree which may be standardized or customized for each web site. User groups may be defined based on membership rules for category interest information and demographics. Individual user profiles are then created for users automatically based on satisfaction of the user group membership rules. As new data is collected on a user over time, the category interest information extracted from the user's web activity is updated to form a current model of the user's interests relative to the various categories. This information is also used to automatically update group membership and user profile information. Identification of users across multiple sites is provided by a global service that recognizes each user and provides a globally unique identifier to a requesting web server, which can use the identifier to accumulate activity data for the user. Client side user identification is provided to track user activity data on web servers that do not communicate with the global service and do not process activity for category information. User profiles may be shared among web sites that form alliances. User activity data may be aggregated along various dimensions including users / user groups, categorization, and time to provide robust models of interest at any desired time scale.

Speaker recognition is attempted on input speech signals concurrently with provision of input speech signals to a speech recognition system. If a speaker is recognized, a speaker dependent model which has been trained on an enrolled speaker is supplied to the speech recognition system. If not recognized, then a speaker-independent recognition model is used or, alternatively, the new speaker is enrolled. Other speaker specific information such as a special language model, grammar, vocabulary, a dictionary, a list of names, a language and speaker dependent preferences can also be provided to improve the speech recognition function or even configure or customize the speech recognition system or the response of any system such as a computer or network controlled in response thereto. A consistency check in the form of a decision tree is preferably provided to accelerate the speaker recognition process and increase the accuracy thereof. Further training of a model and / or enrollment of additional speakers may be initiated upon completion of speaker recognition and / or adaptively upon each speaker utterance.

Fast and detailed match techniques for speaker recognition are combined into a hybrid system in which speakers are associated in groups when potential confusion is detected between a speaker being enrolled and a previously enrolled speaker. Thus the detailed match techniques are invoked only at the potential onset of saturation of the fast match technique while the detailed match is facilitated by limitation of comparisons to the group and the development of speaker-dependent models which principally function to distinguish between members of a group rather than to more fully characterize each speaker. Thus storage and computational requirements are limited and fast and accurate speaker recognition can be extended over populations of speakers which would degrade or saturate fast match systems and degrade performance of detailed match systems.

The invention discloses a software FMEA (failure mode and effects analysis) method based on level dependency modeling. The method includes 1, understanding an object to be analyzed completely and deeply as required, and determining an analyzing target; 2, establishing a system-grade level dependency model by utilizing outline design as a reference; 3, selecting a module to be analyzed and determine a failure mode thereof, analyzing a failure influence propagation path and a failure reason tracing path to determine a failure reason and the failure influence and provide improvements according to system-grade level dependency model reachability node analysis; 4, selecting a detailed-grade FMEA analyzing object according to a system-grade FMEA result; 5 establishing a detailed-grade level dependency model on the basis of detailed design or a pseudo-code of the selected object to be analyzed; 6, selecting key variables to be analyzed according to the detailed-grade level dependency model; 7, determining a specific failure mode of the key variables to be analyzed, and analyzing producing reasons and failure influences of the variables and providing improvements according to detailed-grade level dependency model reachability node analysis.

A method of operation of a navigation system includes: providing a history list including a request having a tag; assigning a probability to the request based on the tag to create a speaker dependent model; providing a returned result generated from the speaker dependent model; and updating the request and the tag of the history list based on a user's confirmation of the returned result for displaying on a device.

An impact assessment system and method for determining emerging criticality in a complex system is provided. The impact assessment system includes a component dependency model and an emergent criticality analyzer. The component dependency model describes the relationships between components in the system and their underlying dependency and criticality relationships. The impact assessment system receives component failure data from the complex system and uses the component dependency model and emergent criticality analyzer to determine the impact of the component failure on the criticality of remaining components in the system. The impact assessment system is thus able to determine how component failures in the complex system can impact the criticality of remaining components in the complex system and thus can assist in determining how those components may or may not be safely used in further operational activities.

A method, system, and computer program product are disclosed for using pattern-dependent models at early stages of the design process. This addresses the key disadvantage of prior approaches which are restricted to using such models later in the design process for IC designs that are nearly complete. Pattern-dependent manufacturing effects are extracted from early stage designs and using the extracted pattern-dependent effects to efficiently and effectively design the integrated circuit. One or more contexts are built around one or more units of the design, with examples of units being a block or cell. The units are then used in the context to generate pattern-dependent data as a basis for one or more pattern-dependent models.

A new packaging method for a wide range of MEMS for application on both the wafer and device scale. Titanium is used as the packaging material and both silicon and titanium MEMS devices are integrated on to a titanium substrate. A Nd:YAG pulsed laser is used to micro-weld the titanium cap to the substrate. A three-dimensional time dependent model of heat flow during laser beam welding is presented. The heat transfer and parametric design capabilities of COMSOL were employed for this purpose. Model calculations are compared and calibrated with experimental results of pulsed laser welds. The functionality and hermiticity of the proposed packaging was evaluated by packaging a self actuated Veeco Instrument AFM cantilever tip. The experimental measurements show that the resonance frequency and quality factor of the device stay the same before and after packaging and the applied technique has no effect on the device.

According to one aspect of the invention, a method is provided in which a set of multiple mixture monophone models is created and trained to generate a set of multiple mixture context dependent models. A set of single mixture triphone models is created and trained to generate a set of context dependent models. Corresponding states of the triphone models are clustered to obtain a set of tied states based on a decision tree clustering process. Parameters of the context dependent models are estimated using a data dependent maximum a posteriori (MAP) adaptation method in which parameters of the tied states of the context dependent models are derived by adapting corresponding parameters of the context independent models using the training data associated with the respective tied states.

The invention relates to an asphalt pavement structure analysis equivalent method based on a pavement material stress and strain dependent model. According to a structural form and a material type ofan asphalt pavement to be analyzed, the thickness of each layer, a Poisson ratio and a pavement material modulus stress (strain) dependent model are determined, the modulus of each layer of an asphaltpavement structure is represented by the pavement material modulus stress (strain) dependent model, a calculation and analysis system is established by combining a calculation load and an interlayercombination condition, the most unfavorable point of the stress of each layer of the asphalt pavement structure is taken as an equivalent calculation point, the final modulus of each structural layeris obtained through iteration calculation, and the stress, strain and displacement of any point in the asphalt pavement structure are calculated according to an elastic layered system theory on the basis of the final modulus. This method considers the influence of material nonlinearity on pavement mechanical calculation, and enables the stress analysis of the asphalt pavement structure to be morereasonable and perfect.

A method, system, and computer program for class detection and time mediated averaging of class dependent models. A technique is described to take advantage of gender information in training data and how obtain female, male, and gender independent models from this information. By using a probability value to average male and female Gaussian Mixture Models (GMMs), dramatic deterioration in cross gender decoding performance is avoided.

An integrated communications device provides an automatic speech recognition (ASR) system to control communication functions of the communications device. The ASR system includes an ASR engine and an ASR control module with an out-of-vocabulary rejection capability. The ASR engine performs speaker independent and dependent speech recognition and also performs speaker dependent training. The ASR engine thus includes a speaker dependent recognizer, a speaker independent recognizer and a speaker dependent trainer. Speaker independent models and speaker dependent models stored on the communications device are used by the ASR engine. A speaker dependent mode of the ASR system provides flexibility to add new language independent vocabulary. A speaker independent mode of the ASR system provides the flexibility to select desired commands from a predetermined list of speaker independent vocabulary. The ASR control module, which can be integrated into an application, initiates the appropriate communication functions based on speech recognition results from the ASR engine. One way of implementing the ASR system is with a processor, controller and memory of the communications device. The communications device also can include a microphone and telephone to receive voice commands for the ASR system from a user.

The present invention provides an embedded system design device and a method thereof using a target independent model comprises: a target independent model expressed in UML diagram type as a resource; a target independent model definition language for expressing the target independent model in language type; a profile where specific data for substantially controlling a particular embedded system is stored; a middle language configured by inserting contents of the profile into the target independent model definition language; a conversion language configured in the same linguistic type as the middle language, and for adding new data which does not exist in the middle language, or for changing particular contents; a target dependent model definition language generated by applying the conversion language to the middle language; and a modeling tool for performing a series of processing procedures of writing a diagram by using a UML (Unified Modeling Language), providing an interface tag which suggests resource items for extracting / generating the target independent model, and generating the target independent model to convert the independent model into the target dependent model.

According to one aspect of the invention, a method is provided in which a set of multiple mixture monophone models is created and trained to generate a set of multiple mixture context dependent models. A set of single mixture triphone models is created and trained to generate a set of context dependent models. Corresponding states of the triphone models are clustered to obtain a set of tied states based on a decision tree clustering process. Parameters of the context dependent models are estimated using a data dependent maximum a posteriori (MAP) adaptation method in which parameters of the tied states of the context dependent models are derived by adapting corresponding parameters of the context independent models using the training data associated with the respective tied states.

A computing system comprising a central processing unit (CPU), and memory coupled to the CPU and having stored therein instructions that, when executed by the computing system, cause the computing system to execute operations to generate a radiation treatment plan. The operations include accessing a minimum prescribed dose to be delivered into and across the target, determining a number of beams and directions of the beams, and determining a beam energy for each of the beams, wherein the number of beams, the directions of the beams, and the beam energy for each of the beams are determined such that the entire target receives the minimum prescribed dose. A quantitative time-dependent model-based charged particle pencil beam scanning optimization is then implemented for FLASH therapy.

A method, system, and computer program for class detection and time mediated averaging of class dependent models. A technique is described to take advantage of gender information in training data and how obtain female, male, and gender independent models from this information. By using a probability value to average male and female Gaussian Mixture Models (GMMs), dramatic deterioration in cross gender decoding performance is avoided.

The invention relates to a quantization parameter cascading method independent of a GOP structure, and the method comprises the steps: firstly, building an inter-frame distortion dependence model independent of the GOP structure through the research of a reference specific gravity relation between frames in coding; secondly, selecting proper parameters, and obtaining a coefficient of the distortion dependence model by using a neural network; and finally, on the basis of the principle of minimum coding overall rate distortion cost, realizing a quantization parameter distribution scheme by utilizing neural network output, and distributing an optimal quantization parameter to each video frame. According to the invention, the coding performance can be ensured on the premise that the coding process does not depend on a GOP structure.

A recognition model set is generated. A technique is described to take advantage of the logarithm likelihood of real data for cross entropy to measure the mismatch between a training data and a training data derived model, and compare such type of mismatches between class dependent models and class independent model for evidence of model replacement. By using change of cross entropies in the decision of adding class independent Gaussian Mixture Models (GMMs), the good performance of class dependent models is largely retained, while decreasing the size and complexity of the model.

A method, system, and computer program product are disclosed for using pattern-dependent models at early stages of the design process. This addresses the key disadvantage of prior approaches which are restricted to using such models later in the design process for IC designs that are nearly complete. Pattern-dependent manufacturing effects are extracted from early stage designs and using the extracted pattern-dependent effects to efficiently and effectively design the integrated circuit. One or more contexts are built around one or more units of the design, with examples of units being a block or cell. The units are then used in the context to generate pattern-dependent data as a basis for one or more pattern-dependent models.

A technique for identifying a minimum number of model elements associated with a model for generating a subset model of the model that includes receiving a model, a set of model elements and a set of dependency types associated with the model; assigning a collector component to each of the received model elements; locating a model element dependent on the received model element by one of the received dependency types; receiving from each collector a dependent model element, and for each dependent model element, determining whether the dependent model element has been collected by another collector with the same dependency type and updating a subset model list with the collected dependent model element to build a list of collected dependent model elements for generating a subset model in response to a negative determination.

The present invention relates to in vitro prognostic method for assessing the risk of death or of liver-related event in a subject, comprising: a. obtaining at least one, preferably at least 2, of the following variables from the subject: i. biomarkers measured in a sample from the subject; ii. clinical data; iii. binary markers; iv. blood test results; b. optionally obtaining at least one blood test result by univariate combination, preferably with a binary logistic regression, of the at least one variable obtained in step (a), said blood test not being a Fibrotest, c. obtaining at least one physical data from medical imaging or clinical measurement, preferably from elastometry, more preferably from Vibration Controlled Transient Elastography (VCTE), and d. mathematically combining in a multivariate time-dependent model said at least one variable obtained in step (a) and / or said at least one blood test result obtained in step b); and said at least one physical data, obtained in step (c) thereby obtaining a prognostic score.

The invention provides a railway travel route planning method and device based on a time dependence model, the method is combined with the actual condition of a Chinese railway network to modify a standard time dependence model, and the improved model can solve the problems of earliest arrival, least transfer, shortest travel time and the like in the Chinese railway network; an air-railway combined transportation model and an air-railway-ground combined transportation model are established based on the model; secondly, an improved time dependence model and a Dijkstra algorithm are used for solving the shortest path search problem of the China railway, the algorithm is accelerated by selecting a data structure of the Dijkstra algorithm and adopting an A * algorithm idea at the same time, and the algorithm efficiency is improved; and finally, the shortest path search algorithm is modified into a K-optimal path algorithm based on a backtracking idea to realize real-time solution of the problems of earliest K-optimal path arrival, least K-optimal transfer path, K-optimal path with the shortest travel time and K-optimal path with the lowest ticket price in Chinese railway network travelplanning.

In some embodiments, the invention includes calculating estimated weights for identified errors in recognition of utterances. Sections of the utterances are marked as being misrecognized and the corresponding estimated weights are associated with these sections of the utterances. The weighted sections of the utterances are used to convert a speaker independent model to a speaker dependent model.

The invention relates to the technical field of automated power communication, in particular to a GOOSE / SMV (generic object oriented substation event / sampled measured value) message subscribing method. The method includes the steps: an operating mode of a network adapter of a subscribing terminal is set into a mixed mode to receive all communication messages that a release terminal sends out, GOOSE / SVE messages are screened from the communication messages and are analyzed item by item to obtain subscription feature information of each message, displayed on a user interface; a user selects the certain message item and forms the corresponding feature information into a persistent file; the subscribing terminal subscribes to the required GOOSE / SMV messages through the subscription feature information included in the persistent file. The method has the advantages that the method is independent of model files, subscription failure caused by model error or inconsistence between models and actual messages is thoroughly avoided, and subscription accuracy is improved; compared with a method for subscribing to messages directly through SCD / CID (substation configuration description / configured IED description) files, the method ensures that less memory is used during system startup and that system startup is faster.

Disclosed is a method of estimating an arousal state of a person, the method comprising: providing one or more measurements of a physiological or behavioural variable relevant to the arousal state of the person; and updating a nonlinear physiologically based time-dependent model of arousal using the one or more measurements of the physiological or behavioural variable, thereby estimating an augmented state vector of the model, wherein the estimated augmented state vector of the model includes the arousal state of the person and one or more parameters of the model.

The invention relates to the field of civil engineering, and discloses a method for acquiring dynamic resilience mechanical characteristic parameters of aggregates, which comprises the following steps: 1) deriving a stress increment constitutive equation of the aggregates, and determining a stress loading sequence according to the equation; 2) performing a dynamic triaxial test on the granules according to the stress loading sequence, recording the stress level, the stress increment, the corresponding horizontal deformation and the corresponding vertical deformation of the test, and calculating the horizontal strain increment and the vertical strain increment; 3) introducing a stress dependence model of dynamic resilience mechanical characteristic parameters; and 4) performing parameter regression analysis, and determining model parameters to obtain a nonlinear dynamic resilience mechanical characteristic parameter prediction model including dynamic resilience modulus, Poisson's ratioand orthotropic parameters. According to the method, the model for predicting the dynamic resilience mechanical characteristic parameters of the aggregate under different stress states can be established, the dynamic resilience mechanical characteristic parameters under various stress states can be conveniently and accurately obtained, and the requirements of engineering construction are met.

The invention provides an implementation method used for data distribution service (DDS) application software and based on model driven architecture (MDA). The method comprises the steps of converting a DDS application layer data model into a DDS distribution layer data model, converting a platform-independent model combining the distribution layer data model, a function model and a structure model into a platform-dependent model, and converting the platform-dependent model into an executable program code. The invention further provides an implementation system used for the DDS application software and based on the MDA. The system comprises a data model conversion module, a platform model conversion module and a code generation module. By adopting the model-driven method, influence of change of a technology platform on a software system is avoided to the maximum degree, and the problems that models are difficult to manage, packaging is omitted, the development process is complex and coupling between an application layer and a bus is difficult in the prior art are solved.