94 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.

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 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 system, method and computer-readable medium provides steps of merging one or more sources of IP addresses to create a merged database comprising a plurality of IP zones, user typing each of the plurality of IP zones, enhancing each of the plurality of IP zones, receiving an input address and selecting one or more of the plurality of IP zones having a predetermined statistical relationship to the input address.

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 spectral reflectance peak decomposition based quantitative inversion method of the hyperspectral remote sensing mineral content. The method comprises the seven steps of: 1. reading data in; 2. intercepting a reflection peak band; 3. converting a reflectance spectrum and an absorption spectrum; 4. carrying out continuum removal on the spectrums; 5. linearly decomposing the spectrums to obtain the mineral spectrum decomposition content; 6. establishing a statistical relationship between the mineral spectrum decomposition content and the real content; and 7. converting the calculated mineral spectrum decomposition content in the step 5 into the real mineral content according to the established statistical relationship in the step 6. The invention can not only be applied to hyperspectral data which is not covered by a mineral absorption spectrum band, but also can be used for hyperspectral data which is covered by the mineral absorption spectrum band in the spectrum band range, carries out quantitative mineral content inversion by comprehensively applying a spectral reflectance peak and an absorption spectrum band and improves the inversion precision and the inversion accuracy. The invention has practical value and broad application potential in the field of hyperspectral remote sensing mineral identification.

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.

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.

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.

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.

Wine characteristic data is related to consumer liking data to provide a predictive model that may be used in wine portfolio management, including selection, shelf placement, pricing, and promotion. The wine characteristic data may relate to wine attributes as determined by a trained panel of experts or by chemical analysis, or to production or process data or to a combination of these data. The consumer liking data may be hedonic data obtained from consumer tasting. The predictive model may be a determined statistical relationship between the characteristic data and the hedonic data. In application, the predictive model may be used to identify what wines will appeal to various consumer segments. Alternatively, the predictive model may be used to identify for particular consumer segments or even individual consumers wines that may be liked.

The invention relates to a method for synchronously realizing seismic lithofacies identification and quantitative assessment of uncertainty of the seismic lithofacies identification. The method comprises the steps of determining the type of the lithofacies and performing logging lithofacies definition, establishing a rock physical response relation between logging physical parameters and elasticity, establishing a probability statistical relation between the lithofacies and logging attributes, establishing the probability statistical relation of well-seismic scale elasticity parameters and constructing the statistical relation of the lithofacies and the seismic scale elasticity parameters, inverting the information of the probability distribution of the elasticity parameters of a target layer, obtaining the lithofacies probability information of the target layer by combining the inverted probability information of the elasticity parameters of the target layer and the statistical relation of the lithofacies and the seismic scale elasticity parameters, obtaining the maximum posterior probability solution of the lithofacies distribution according to the probability information of the lithofacies and outputting final model parameters. The method is capable of quantitatively characterizing the uncertainty of each link of lithofacies identification and the propagation and accumulation characteristics of the uncertainty in the lithofacies identification process, and also capable of performing uncertainty analysis on the seismic lithofacies identification; as a result, the reservoir evaluation risk is reduced; in short, the method is wide in application range.

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.

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.

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.

Disclosed are methods and devices for compressing and decompressing video data streams, according to which the statistical relationship between image symbols and the context assigned thereto is used for compression. Particularly disclosed is a context-sensitive encoding unit in which the image symbols filed in an image storage are assigned to different encoding branches via a context switch, where they are encoded and compressed by a Golomb encoder and a run length encoder.

The invention discloses a detector signal processing method and device based on a pulse width spectrum. The method comprises the steps that a first pulse width spectrum is collected, and the first pulse width spectrum is used for representing the statistical relation between signals to be detected, on the pulse width of the assigned threshold value, outputted by a detector; according to the corresponding relation between detector input signal energy marked in advance or the output signal amplitude and the output signals on the pulse width of the assigned threshold value, energy information, corresponding to the first pulse width spectrum, of the signals to be detected is determined. The device comprises a pulse width spectrum measurement circuit and a data processing circuit. The detector signal processing method and device have the advantages of being simple in structure, low in design difficulty and cost, easy to maintain, capable of not being lower than a traditional amplitude energy spectrum in performance, and suitable for spacecraft on-track and other application occasions.

A packaging filling apparatus, which can obtain the most suitable sealing quality by an automatic control without checking the condition of sealing by the operator on a regular basis, is provided. A transversal sealing apparatus 48 of the packaging filling apparatus includes a high-frequency oscillator 1, controller 2, and an inductor, which generates a magnetic field in said packaging material by receiving the output from the high-frequency oscillator, and is provided with a sealing quality control means 4, which transmits a control signal to the controller, based on a statistical relation between a plurality of effect factors affecting the quality of said transversal sealing 23 and the quality of said transversal sealing.

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.

A packaging filling apparatus, which can obtain the most suitable sealing quality by an automatic control without checking the condition of the sealing by the operator on a regular basis, is provided. A transversal sealing apparatus 48 of the packaging filling apparatus includes a high-frequency oscillator 1, controller 2, and an inductor, which generates a magnet field in packaging material by receiving the output from the high-frequency oscillator, and is provided with a sealing quality control means 4, which transmits a control signal to the controller, based on a statistical relation between a plurality of effect factors affecting the quality of a transversal sealing 23 and the quality of transversal sealing.