93 results about "Statistical relation" patented technology

The present invention presents embodiments of methods, systems, and computer-readable media for the retrieval, mining, filtering and visualization of information stored on a plural of computers connected to the Internet and on a local computer. Embodiments of this invention generate a conceptual search query using a description provided by a user, perform user selectable conceptual filtering of search results, concept following and link following to expand search results, search for files that may or may not contain certain information, rank concepts contained in search results or one or more files, compute relevancy rank of a file in search results, use conceptual path maps to display logic or statistical relationships among search results, monitor changes in information in a search or a file, and protect files or searches based on information contents.

Methods and apparatus are provided for analyzing a complex system that includes a number of subsystems. Each subsystem comprises at least one sensor designed to generate sensor data. Sensor data from at least one of the sensors is processed to generate binary evidence of a sensed event, and complex evidence of a sensed event. The complex evidence has more sophisticated mathematical properties than the binary evidence. The complex evidence comprises one or more of: a condition indicator (CI), a health indicator (HI), and a prognostic indicator (PI). A system fault model (SFM) is provided that defines statistical relationships between binary evidence, complex evidence, and an underlying failure mode (FM) that is occurring in the complex system. The binary evidence and the complex evidence are processed to identify failure modes taking place within one or more of the subsystems. Based on the binary evidence and the complex evidence and the SFM, diagnostic conclusions can be generated regarding adverse events that are taking place within the complex system, and prognostic conclusions can be generated regarding adverse events that are predicted to take place within the complex system.

An apparatus, and related method, for determining one or more association variables is described. The apparatus includes at least one processor, at least one memory, and at least one program module. The program module is stored in the memory and is configurable to be executed by the processor. The program module includes instructions for determining a statistical relationship between one or more temporal onsets corresponding to one or more events and a pattern of occurrence of a compound variable. The compound variable corresponds at least to a pattern of occurrence of a first variable and a pattern of occurrence of a second variable. The determining includes contributions from presence and absence information in the pattern of occurrence of the compound variable.

An example information system contains records of landmarks. The system obtains records of taxi trips between the landmarks and from the taxi trip information derives statistical relationships between the landmarks. A user can provide context information, such as an address or a type of activity. The user can then search the system for landmarks of interest to the user. The system retrieves and presents the user with a set of landmarks which match the user's query based in part on the statistical relationships.

A scaleable macro block rate control method particularly well-suited for MPEG video. There is provided a method to easily derive a quantization parameter (QP) value using information such as bit usage, previous QP values and SAD values from the past encoded and future frames. The method utilizes quantization estimation techniques based on statistical relationships between different intensity measures, such as distortion intensity, absolute difference intensity and mean of absolute difference intensity. The method is well-suited to applications utilizing MPEG video such as MPEG-1, MPEG-2, MPEG-4, JVT/H.264 standards and so forth.

The invention relates to a method for controlling damage of slope pre-splitting blasting digging based on a blast vibration test. The method comprises the following steps: establishing a statistical relation between the blasting particle peak vibration velocity at a plurality of blasting center distances and the damage depth under different altitude difference conditions by utilizing the blasting digging for a few front steps on the basis of the acoustic detection for a slope blasting digging damage area and the corresponding blasting vibration monitoring, and then utilizing the particle peak vibration velocity induced during the slope bench blasting process to forecast the depth of the digging damage area, and offering a control proposal for single-bump explosive quantity. After the relation between the particle peak vibration velocity and the slope blasting digging damage area is established according to a blasting vibration test result of the front steps and the acoustic detection for the damage area, subsequent steps are only subjected to blasting vibration monitoring, and geological data is combined for comprehensively analyzing and adjusting, so that the depth of the slope digging damage area can be determined and the operation is convenient, quick, high-efficient and economical. The rock slope blasting digging damage can be controlled by controlling the maximum single-bump explosive quantity. The method has high engineering popularization and application values.

An image processing system and method having a statistical appearance model for interpreting a digital image. The appearance model has at least one model parameter. The system and method comprises a two dimensional first model object including an associated first statistical relationship, the first model object configured for deforming to approximate a shape and texture of a two dimensional first target object in the digital image. Also included is a search module for selecting and applying the first model object to the image for generating a two dimensional first output object approximating the shape and texture of the first target object, the search module calculating a first error between the first output object and the first target object. Also included is an output module for providing data representing the first output object to an output. The processing system uses interpolation for improving image segmentation, as well as multiple models optimised for various target object configurations. Also included is a model labelling that is associated with model parameters, such that the labelling is attributed to solution images to aid in patient diagnosis.

Various technologies pertaining to dynamically identifying travel segments to be taken by a traveler traveling in a region are described herein, where observations about travel segments in the region are sparse and subject to alteration. A computer-implemented graph can be loaded into a memory, where the computer-implemented graph is representative of the region. The computer-implemented graph includes nodes that represent locations in the region and edges that represent travel segments of the region, where the edges have costs assigned thereto, and further where there is a defined statistical relationship between the costs. When an observation about a travel path is received, using the computer-implemented graph, inferences can be made about costs of traversing other travel paths in the region.

Aspects of the subject disclosure may include, for example, a computer that performs a statistical natural language processing analysis on a plurality of text documents to determine a plurality of topics, creates a proper subset of topics from the plurality of topics, based on user input, maps one or more topics in the proper subset of topics to each document in the plurality of text documents, thereby creating a plurality of topic-document pairs, identifies n-dimensions of bias for each topic-document pair from the text, creates clusters of topics from the proper subset of topics, and generates presentable content depicting each cluster of the clusters of topics according to a corresponding image configuration. The topics and n-dimensions of bias data can be further analyzed with co-collected structured data for statistical relationships. The topics and n-dimensions of bias data can be used for a publisher-subscriber network that uses content-driven routing when delivering raw data and summarized data via the network. Other embodiments are disclosed.

The provided method for high-resolution multispectral image comprises: to the original low-resolution image from satellite and the space-matched high-resolution full-color image, composing the simulated low-resolution full-color image by opposite wave band statistic relation; then, determining details to add by ratio on the original image and generate target image. This invention can eliminate spectral distortion efficiently.

The invention provides a wind power station short-term power prediction method. The wind power station short-term power prediction method comprises the steps that 1 a BP neural network is used for establishing the historical data statistics relationship between forecasting factors of a mesoscale numerical value weather forecast and the actually-measured wind speed, at the position of the hub height, of a single fan to generate a wind speed statistics downscaling model of the single fan; 2 according to the forecasting factors of the mesoscale numerical value weather forecast of a wind power station in the following 48 hours and the statistics downscaling model of the single fan in the step 1, the predicted wind speed, at the position of the hub height, of the single fan is generated; 3 according to historical data of the actually-measured wind speed of the single fan and the actually-measured power of the single can, a speed-power characteristic curve of the single fan is fit and the short-term predicted power of the fan is obtained through the combination of the predicted wind speed, at the position of the hub height, of the single fan. Therefore, by means of the wind power station short-term power prediction method, the uncertainty caused by the fact that the mesoscale resolution ratio is insufficient is reduced, and the short-term powder prediction precision of the wind power station is obviously improved.

The present invention is directed to a new joint estimation framework employing MAP estimation based on pixel-based latent variables for tissue types. The method combines the geometrical information described by latent MRF, statistical relation between tissue types and P-C coefficients, and Poisson noise models of PCD data, and makes possible the continuous Baysian estimation from detected photon counts. The proposed method has better accuracy and RMSE than the method using FBP and thresholding. The joint estimation framework has the potential to further improve the accuracy by introducing more information about tissues in human body, e.g., the location, size, and number of tissues, or limited variation of neighboring tissues, which will be easily formulated by pixel-based latent variables.

The invention relates to a pattern recognition method capable of achieving cluster, classification and metric learning simultaneously. According to the method, the Bayesian theory is used to construct probability relation matrix P between a cluster and a category, and final cluster and category results are enabled to only rely on a cluster center through the matrix; accordingly, cluster learning and classification learning can be achieved simultaneously under a frame. As the statistical relation between the cluster and the category can be reflected through the matrix P, meaningful information can be mined from the P, and design of classifier is transparent. From the cluster point, cluster learning monitoring results are provided, and potential structures of data can be obtained reliably; from the classification point, an effective classification learning mechanism is constructed, and good classification results can be obtained; and from the metric learning point, effective characteristic weight is provided, and significant degree of characteristics can be reflected.