123 results about "Probabilistic method" patented technology

A natural language understanding system is described which provides for the generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, in the preferred embodiment of the invention implemented by means of a Bayesian network, is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its "deep" or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics. In the preferred embodiment of the invention, spell checking and transformational processing as well as semantic analysis make use of semantic probabilistic determinations.

In general, the present invention is directed to systems and methods for finding the position and shape of an object using video. The invention includes a system with a video camera coupled to a computer in which the computer is configured to automatically provide object segmentation and identification, object motion tracking (for moving objects), object position classification, and behavior identification. In a preferred embodiment, the present invention may use background subtraction for object identification and tracking, probabilistic approach with expectation-maximization for tracking the motion detection and object classification, and decision tree classification for behavior identification. Thus, the present invention is capable of automatically monitoring a video image to identify, track and classify the actions of various objects and the object's movements within the image. The image may be provided in real time or from storage. The invention is particularly useful for monitoring and classifying animal behavior for testing drugs and genetic mutations, but may be used in any of a number of other surveillance applications.

Completely automated end-to-end method and system for markerless motion capture performs segmentation of articulating objects in Laplacian Eigenspace and is applicable to handling of the poses of some complexity. 3D voxel representation of acquired images are mapped to a higher dimensional space (k), where k depends on the number of articulated chains of the subject body, so as to extract the 1-D representations of the articulating chains. A bottom-up approach is suggested in order to build a parametric (spline-based) representation of a general articulated body in the high dimensional space followed by a top-down probabilistic approach that registers the segments to an average human body model. The parameters of the model are further optimized using the segmented and registered voxels.

Disclosed are probabilistic approaches to patient evaluation, warning and treatment of a neurological disorder. Disclosed techniques estimate probability distribution functions or cumulative distribution functions, determined by relying on representative historical profiles, comprising information in short and / or long timescales obtained at times that may be intermittent or temporally discontinuous from each other or from other events of interest. The patient may thereby be treated based on the determined probability information.

A computer program product is provided as a network quality control system to perform an automatic validation of all the World Wide Web pages. The quality control system aims at improving the quality of the World Wide Web by promoting widely accepted uniform standards such as HTML, and further by generating web documents that are valid and compliant with the standards according to which they are published. The quality control system actively seeks malformed web pages and corrects them in conformity with their publication standards. The quality control system also automatically determines the most probable addresses of the persons in charge of maintaining the non-conformant web documents using a probabilistic approach, notifies these persons of the non-conformity of their documents, and forwards the corrected web documents to their attention.

A recommendations system uses probabilistic methods to select, from a candidate set of items, a set of items to recommend to a target user. Some embodiments of the methods effectively introduce noise into the recommendations process, causing the recommendations presented to the target user to vary in a controlled manner from one visit to the next. The methods may increase the likelihood that at least some of the items recommended over a sequence of visits will be useful to the target user. Some embodiments of the methods are stateless such that the system need not keep track of which items have been recommended to which users.

The disclosed terrain model is a generative, probabilistic approach to modeling terrain that exploits the 3D spatial structure inherent in outdoor domains and an array of noisy but abundant sensor data to simultaneously estimate ground height, vegetation height and classify obstacles and other areas of interest, even in dense non-penetrable vegetation. Joint inference of ground height, class height and class identity over the whole model results in more accurate estimation of each quantity. Vertical spatial constraints are imposed on voxels within a column via a hidden semi-Markov model. Horizontal spatial constraints are enforced on neighboring columns of voxels via two interacting Markov random fields and a latent variable. Because of the rules governing abstracts, this abstract should not be used to construe the claims.

The invention applies a probabilistic approach to combining evidence regarding the correct classification of items. Training data and machine learning techniques are used to construct probabilistic dependency models that effectively utilize evidence. The evidence includes the outputs of one or more classifiers and optionally one or more reliability indicators. The reliability indicators are, in a broad sense, attributes of the items being classified. These attributes can include characteristics of an item, source of an item, and meta-level outputs of classifiers applied to the item. The resulting models include meta-classifiers, which combine evidence from two or more classifiers, and tuned classifiers, which use reliability indicators to inform the interpretation of classical classifier outputs. The invention also provides systems and methods for identifying new reliability indicators.

A recommendations system uses probabilistic methods to select, from a candidate set of items, a set of items to recommend to a target user. The methods can effectively introduce noise into the recommendations process, causing the recommendations presented to the target user to vary in a controlled manner from one visit to the next. The methods may increase the likelihood that at least some of the items recommended over a sequence of visits will be useful to the target user. Some embodiments of the methods are stateless such that the system need not keep track of which items have been recommended to which users.

Systems and methods create high quality audio-centric, image-centric, and integrated audio-visual summaries by seamlessly integrating image, audio, and text features extracted from input video. Integrated summarization may be employed when strict synchronization of audio and image content is not required. Video programming which requires synchronization of the audio content and the image content may be summarized using either an audio-centric or an image-centric approach. Both a machine learning-based approach and an alternative, heuristics-based approach are disclosed. Numerous probabilistic methods may be employed with the machine learning-based learning approach, such as naïve Bayes, decision tree, neural networks, and maximum entropy. To create an integrated audio-visual summary using the alternative, heuristics-based approach, a maximum-bipartite-matching approach is disclosed by way of example.

The present invention relates to systems and methods capable of characterizing populations of organisms within a sample. The characterization may utilize probabilistic matching of short strings of sequencing information to identify genomes from a reference genomic database to which the short strings belong. The characterization may include identification of the microbial community of the sample to the species and / or sub-species and / or strain level with their relative concentrations or abundance. In addition, the system and methods may enable rapid identification of organisms including both pathogens and commensals in clinical samples, and the identification may be achieved by a comparison of many (e.g., hundreds to millions) metagenomic fragments, which have been captured from a sample and sequenced, to many (e.g., millions or billions) of archived sequence information of genomes (i.e., reference genomic databases).

The present invention is embodied in a system and process for automatically learning a reliable color-based tracking system. The tracking system is learned by using information produced by an initial object model in combination with an initial tracking function to probabilistically determine the configuration of one or more target objects in a temporal sequence of images, and a data acquisition function for gathering observations relating to color in each image. The observations gathered by the data acquisition function include information that is relevant to parameters desired for a final color-based object model. A learning function then uses probabilistic methods to determine conditional probabilistic relationships between the observations and probabilistic target configuration information to learn a color-based object model automatically tailored to specific target objects. The learned object model is then used in combination with the final tracking function to probabilistically locate and track specific target objects in one or more sequential images.

Method and apparatus for programmatically generating interesting audio file playlists. A playlist generation mechanism may use an N-gram model of audio file ordering patterns found in a collection of human-generated playlists to automatically generate new playlists. Given play histories indicating one or more played audio files as input, statistical methods may be used to look for sequences of audio files that occur a statistically significant number of times in the N-gram model for inclusion in new, interesting playlists that incorporate the human element found in the collection of playlists. In some embodiments, one more backoff probability methods may be used to provide additional candidate audio files for playlists if there is insufficient coverage for an audio file in the N-gram model. In one embodiment, a class-based statistical model incorporating higher-level statistics for the audio files may be used to weight selection of audio file transitions from the N-gram model.

A probabilistic method of determining a second vehicle in the VANET to which a packet is to be forwarded from a first vehicle is provided. The method includes determining the second vehicle to forward the packet from the first vehicle based on pre-calculated expected latency data corresponding to the second vehicle, and forwarding the packet from the first vehicle to the determined second vehicle. The expected latency data is indicative of the latency expected for communication of the packet from the first vehicle to the destination if the packet is forwarded from the first vehicle to the second vehicle, and is calculated in advance of the step of the determining the second vehicle to forward the packet. The second vehicle to forward the packet may also be determined based on pre-calculated communication probability data corresponding to the second vehicle in addition to the pre-calculated expected latency.

The invention discloses a target tracking method with multi-spectrum image sensor fusion. The method adopts a four-level data fusion computing framework with certain versatility. The four-level data fusion computing framework is respectively a multi-characteristic fusion level, a multi-mode fusion level, a multi-model fusion level and a multi-sensor fusion level from top to bottom. The multi-characteristic fusion realizes the integration of a plurality of characteristic clues through the probabilistic method to guarantee enough characteristic information representing targets in different environments; the multi-mode fusion adopts handoff algorithm in a staging mode, integrates two adjacent tracking modes through a certain weighting coefficient, to ensure smooth transition between the modes and guarantee continuous tracking of the targets; the multi-model fusion adopts an interacting multi-model algorithm to solve the problem of stable switching among different moving models of the targets; the multi-sensor fusion adopts distributed type fusion tracking algorithm to select the advantages of all the sensors, and makes up the deficiencies between the sensors, to ensure the tracking to be more robust and more precise.

Methods and apparatuses for transient analyses of a circuit using a hierarchical approach. In one embodiment, the cells are grouped locally on the power supply network according to average power dissipation. A time varying current of each cell group is estimated using a probabilistic approach to represent the cell group so that the probability of a more severe waveform for the current of the cell group is under a certain level. For example, the cells in a group are partitioned as switching cells and non-switching cells using cell toggle rates for the determination of the time varying current. The circuit model of the power supply network includes the current sources according to the estimated time varying currents for the cell groups, the power supply wire resistance, the power supply to ground wire capacitance, well capacitance and the de-coupling capacitance from non-switching cells.

A method for preforming memory prefetching is disclosed. A stream length histogram (SLH) is initially generated based on a stream of Read and Write requests intended for a system memory. A determination is then made whether or not to issue a prefetch command after a Read request based on information within the generated SLH. In a determination that a prefetch command should be issued, prefetch command to be sent to the system memory is issued along with other commands.

Disclosed is a method for processing readily available radio network, timing and power information about cellular networks and typical measurements made by the mobile device and network. A probabilistic method is disclosed that uses both time (i.e., range) and power differences with known downlink transmitter antenna characteristics to locate mobiles with accuracy better than cell-ID with ranging, with high capacity, and without the need for field calibration.

The invention regards a system reliability or failure predicting apparatus and method that incorporates known information about system component failure into a system model and uses the model with or without other acquired system data to predict the probability of system failure. An embodiment of the method includes using probabilistic methods to create a system failure model from the failure models of individual system components, predicting the failure of the system based on the component models and system data, ranking the sensitivity of the system to the system variables, and communicating a failure prediction.

Goal-based availability and change management are handled over groups of heterogeneous storage controllers. Probabilistic and deterministic methods are employed to determine the allocation and placement of storage volumes to storage controllers, as well as the degree of data redundancy necessary to achieve data availability goals. The probabilistic methods can take into account past observations of controller availability, and operator beliefs, as well as the state of storage controller configuration, in coming up with a probabilistic estimate of future availability.

Determining the amount of resources that needs to be provisioned for a wired backhaul link of a wireless network using a probabilistic approach that makes the determination based at least in part on the type of coding scheme selection algorithm used to encode data transmitted by the transceiver to the wireless device over the air interface of the wireless network. Because the type of coding algorithm used depends on the amount of traffic at the air interface, variations in the coding algorithms used over a given period of time can be used to accurately determine the amount of bandwidth or resources that will be required on the backhaul link. Consequently, the amount of resources that should be provisioned for the backhaul link can be accurately determined.

A system and process for automatically learning a reliable color-based tracking system is presented. The tracking system is learned by using information produced by an initial object model in combination with an initial tracking function to probabilistically determine the configuration of one or more target objects in a temporal sequence of images, and a data acquisition function for gathering observations relating to color in each image. The observations gathered by the data acquisition function include information that is relevant to parameters desired for a final color-based object model. A learning function then uses probabilistic methods to determine conditional probabilistic relationships between the observations and probabilistic target configuration information to learn a color-based object model automatically tailored to specific target objects. The learned object model is then used in combination with the final tracking function to probabilistically locate and track specific target objects in one or more sequential images.

The disclosed embodiments include a method, apparatus, and computer program product for determining a suitable casing design for a well. For example, one disclosed embodiment includes a system that includes at least one processor and at least one memory coupled to the at least one processor and storing instructions that when executed by the at least one processor performs operations for receiving historical data associated with previously drilled wells; in response to a determination that the historical data associated with previously drilled well is relevant to the well, generating a first set of casing designs using a probabilistic approach and generating a second set of casing designs using a combination approach that combines the probabilistic approach with a deterministic approach; and selecting a suitable casing design from a resulting set of casing designs.

Data from crosswell seismic surveys is processed to provide crosswell time-lapse data to map fluid changes in a reservoir where time-lapse or 4D seismic data is unavailable or unreliable, such as in onshore reservoirs. The resultant processing results provide quantitative information for history matching purposes using a probabilistic approach to take in account uncertainties in the geological model and reduce uncertainties in reservoir production forecasts.

The invention provides an information security risk assessment method oriented to a typical metallurgy process control system and belongs to the technical field of industrial control system information security. The system robustness under different attack modes and policies is analyzed by establishing an attack model under the typical scenes of the metallurgy process, and therefore, the security risk assessment on the typical metallurgy process control system in different attack modes and a failure mode can be realized. Based on the risk theory, the method is used for performing the security risk assessment by use of a random probability algorithm by defining the metallurgy process control system as a physical information fusion system; from the two aspects of the occurrence probability and the influence of attack sources or failure sources, a security assessment method based on risk indexes is developed. Quantitative estimation is performed based on risk indexes; a security incident set is created based on the established physical information fusion model and attack model, and then the security incident set is combined with the calculated robustness assessment indexes for the quantitative estimation, and therefore, the weak security links in the control system can be located conveniently.

The invention relates to a risk-based tunnel supporting structure design method, comprising three links: determining the initial design scheme of a tunnel supporting structure, evaluating the risk of each supporting scheme, and making decision and analyzing the supporting schemes. In the method, a probability method and a risk analysis model are applied to carry out quantitative description to physical mechanics indexes of a surrounding rock and the uncertainty in geological exploration; the initial design scheme for supporting is given according to the level of the surrounding rock; space effect of tunnel excavation is considered and a convergence-confinement method is improved through the hardening process for pneumatically placed concrete supporting, the calculation procedures of the improved convergence-confinement method are used for analyzing the determined supporting design scheme, and the failure probability of the supporting and the surrounding rock is given under different construction parameters; and then the risk evaluation is carried out to the supporting design scheme, accident risk acceptance criteria is determined, and proper supporting design scheme is determined by a decision maker. In the method, the risk ideal is led in engineering practice for processing various uncertain problems in the tunnel structure design, so as to be beneficial to carrying out quantitative analysis and evaluation to the effect of the uncertain factors in the tunnel supporting structure design and ensure the safety and the investment control of the tunnel forcefully and comprehensively.

The invention discloses a hybrid AC / DC microgrid optimization operation method and device considering source-grid-load interaction, and the method comprises the steps: enabling a hybrid AC / DC microgrid to be divided into an AC power supply region and a DC power supply region; obtaining a parameter of demand-side load equipment, classifying loads, and obtaining a 24-hour load demand prediction value of a microgrid; obtaining parameters of a converter in the hybrid AC / DC microgrid, and determining a calculation formula of power conversion loss of the converter; estimating the distribution curves of maximum output and load power of a photovoltaic cell and a wind driven generator through employing a probability method; and optimizing the operation of the hybrid AC / DC microgrid through a random chance constraint Stackelberg game model. The device comprises a dividing module, a first obtaining module, a second obtaining module, an estimation module, and an optimization module. The method and device improve the economic benefit environment benefit of microgrid operation, achieve the purpose of energy saving and loss reduction, and facilitate the construction of a reliable, environment-friendly and low-carbon power supply environment for economy.

A probabilistic method for classifying observed CSEM response for a resistive anomaly to classify the response into multiple geologic categories indicative of hydrocarbon production potential. Each category is assigned a prior probability (301). For each category, conditional joint probability distributions for observed CSEM data in the anomaly region are constructed (303) from rock property probability distributions (302) and a quantitative relationship between rock / fluid properties and the CSEM data (304). Then, the joint probability distributions and prior probabilities for each category (305) are combined with observed data (307) and used in Bayes' Rule (306) to update the prior category probabilities (308). Seismic data may be used to supplement CSEM data in the method.