561 results about "Pattern analysis" patented technology

A sensor network collects time-series data from a process tool and supplies the data to an analysis system where pattern analysis techniques are used to identify structures and to monitor subsequent data based on analysis instructions or a composite model. Time-series data from multiple process runs are used to form a composite model of a data structure including variation. Comparison with the composite model gives an indication of tool health. A sensor network may have distributed memory for easy configuration.

A system for empirically diagnosing a condition of a monitored system. Estimates of monitored parameters from a model of the system provide residual values that can be analyzed for failure mode signature recognition. Residual values can also be tested for alert (non-zero) conditions, and patterns of alerts thus generated are analyzed for failure mode signature patterns. The system employs a similarity operator for signature recognition and also for parameter estimation. Failure modes are empirically determined, and precursor data is automatically analyzed to determine differentiable signatures for failure modes.

A distributed pattern recognition training method includes providing data communication between at least one central pattern analysis node and a plurality of peripheral data analysis sites. The method also includes communicating from the at least one central pattern analysis node to the plurality of peripheral data analysis a plurality of kernel-based pattern elements. The method further includes performing a plurality of iterations of pattern template training at each of the plurality of peripheral data analysis sites.

A system for empirically diagnosing a condition of a monitored system. Estimates of monitored parameters from a model of the system provide residual values that can be analyzed for failure mode signature recognition. Residual values can also be tested for alert (non-zero) conditions, and patterns of alerts thus generated are analyzed for failure mode signature patterns. The system employs a similarity operator for signature recognition and also for parameter estimation. Failure modes are empirically determined, and precursor data is automatically analyzed to determine differentiable signatures for failure modes.

Method for detecting malicious behavioral patterns which are related to malicious software such as a computer worm in computerized systems that include data exchange channels with other systems over a data network. Accordingly, hardware and / or software parameters are determined in the computerized system that is can characterize known behavioral patterns thereof. Known malicious code samples are learned by a machine learning process, such as decision trees and artificial neural networks, and the results of the machine learning process are analyzed in respect to the behavioral patterns of the computerized system. Then known and unknown malicious code samples are identified according to the results of the machine learning process.

The cost of performing sophisticated software-based financial trend and pattern analysis is significantly reduced by distributing the processing power required to carry out the analysis and computational task across a large number of networked individual or cluster of computing nodes. To achieve this, the computational task is divided into a number of sub tasks. Each sub task is then executed on one of a number of processing devices to generate a multitude of solutions. The solutions are subsequently combined to generate a result for the computational task. The individuals controlling the processing devices are compensated for use of their associated processing devices. The algorithms are optionally enabled to evolve over time. Thereafter, one or more of the evolved algorithms is selected in accordance with a predefined condition.

A method, system and program product for determining movement data of a customer or customers in a store to analyze customer decisions and optimize product presentation and customer service in response to the analysis. The movement of customers through a store may be correlated with various environmental and economic factors to indicate impediments to customers purchasing a product. Product presentation may then be attenuated according to the results of the analysis by removing the impediments or providing incentives to purchase a product, optimally those products sold at higher profit margins, thereby increasing overall store profitability.

A sensor network collects time-series data from a process tool and supplies the data to an analysis system where pattern analysis techniques are used to identify structures and to monitor subsequent data based on analysis instructions or a composite model. Time-series data from multiple process runs are used to form a composite model of a data structure including variation. Comparison with the composite model gives an indication of tool health. A sensor network may have distributed memory for easy configuration.

An anomaly detector for a Controller Area Network (CAN) bus performs state space classification on a per-message basis of messages on the CAN bus to label messages as normal or anomalous, and performs temporal pattern analysis as a function of time to label unexpected temporal patterns as anomalous. The anomaly detector issues an alert if an alert criterion is met that is based on the outputs of the state space classification and the temporal pattern analysis. The temporal pattern analysis may compare statistics of messages having analyzed arbitration IDs with statistics for messages having those analyzed arbitration IDs in a training dataset of CAN bus messages, and a temporal pattern is anomalous if there is a statistically significant deviation from the training dataset. The anomaly detector may be implemented on a vehicle Electronic Control Unit (ECU) communicating via a vehicle CAN bus. The anomaly detector does not rely on an database of messages and their periodicity from manufacturers (dbc files) and in that sense is truly a zero knowledge detector.

A system and method for locating regions in a target image that match a template image with respect to color and pattern information. The method may comprise performing a first-pass search using color information obtained in a color characterization analysis of the template image in order to find a plurality of color match candidate locations. For each color match candidate location, a region proximal to the location may then be searched in detail, based on pattern information obtained in a pattern analysis of the template image.

Changes in wireless service user behavior are encouraged and produced to shape utilization patterns among cells within a rate plan region by using shaping rules which define potential discounts from a standard charge rate under certain cell-specific utilization conditions, analyzing the shaping rules and utilization statistics of a cell upon service initiation, generating a discount from the standard rate for underutilized cells. The user is notified of these discount opportunities using text messages, icons, or other means. Over time, the users learn that at certain places and times, significant discounts are offered, and thus changes their behavior to take advantage of those discounts, thereby shaping traffic in a manner desired by the service provider.

Methods for analyzing retinal tomography maps to detect patterns of optic nerve diseases such as glaucoma, optic neuritis, anterior ischemic optic neuropathy are disclosed in this invention. The areas of mapping include the macula centered on the fovea, and the region centered on the optic nerve head. The retinal layers that are analyzed include the nerve fiber, ganglion cell, inner plexiform and inner nuclear layers and their combinations. The overall retinal thickness can also be analyzed. Pattern analysis are applied to the maps to create single parameter for diagnosis and progression analysis of glaucoma and optic neuropathy.

A feature extractor samples points on an input pattern drawn in real time. In addition to X and Y coordinates, each sample has an up / down or Z coordinate value representing whether or not the sample point is a perceptible part of the pattern. The groups of coordinate values are transformed into respective sets of coefficients of Chebyshev polynomials by least-squares fit. A recognition unit can use the coefficients as features to identify the character. Additional features, such as aspect ratio and center of gravity, are also derived to aid in recognizing the pattern or reconstructing its image.

A method and system for a search engine for user generated content have been disclosed. According to one embodiment, a computer implemented method comprises receiving a search request from a client, the search request directed to user generated content. Relevant user generated content is retrieved, wherein retrieving comprises searching processed user generated content, and wherein processing user generated content comprises receiving first input data including text, creating a substring of text from the first input data and categorizing the substring to produce a concept associated with the substring, wherein the substring is categorized according to one of dictionaries or pattern analysis. An indication of sentiment is assigned to the concept associated with the substring and an indication of influence is assigned to the concept associated with the substring. The relevant user generated content is displayed.

A system for performing real-time failure mode analysis of a monitored system is disclosed. The system includes a data acquisition component, an analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the monitored system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and a machine learning engine.

The contributions of different tissues to a DNA mixture are determined using methylation levels at particular genomic sites. Tissue-specific methylation levels of M tissue types can be used to deconvolve mixture methylation levels measured in the DNA mixture, to determine fraction contributions of each of the M tissue types. Various types of genomic sites can be chosen to have particular properties across tissue types and across individuals, so as to provide increased accuracy in determining contributions of the various tissue types. The fractional contributions can be used to detect abnormal contributions of a particular tissue, indicating a disease state for the tissue. A differential in fractional contributions for different sizes of DNA fragments can also be used to identify a diseased state of a particular tissue. A sequence imbalance for a particular chromosomal region can be detected in a particular tissue, e.g., identifying a location of a tumor.

This invention provides a negative electrode material for a rechargeable battery with a nonaqueous electrolyte, characterized in that the negative electrode material contains polycrystalline silicon particles as an active material, the particle diameter of crystallites of the polycrystalline silicon is not less than 20 nm and not more than 100 nm in terms of a crystallite size determined by the Scherrer method from the full width at half maximum of a diffraction line attributable to Si (111) around 2θ=28.4° in an x-ray diffraction pattern analysis, and the true specific gravity of the silicon particles is 2.300 to 2.320.

Provided are a pattern analyzing / detecting method and a system using the same that are capable of detecting and effectively preventing an unknown malicious code attack. To detect such an attack, the method monitors the system to combine all behaviors exhibited within the system due to corresponding malicious codes, reprocess and learn the behaviors, analyze existing malicious behavior feature values (prediction patterns), and compare them with a behavior pattern exhibited by an execution code.

The present invention concerns a device and a method for pattern analysis of large volumes of data in order to make it possible to distinguish tendencies to co-variations and developments in time from one large database, preferably one composed by a number of smaller databases. The data in the database is divided into on the one hand objects and on the other variables. The method is characterized by first grouping the volume of data, whereby the variables are grouped to dimensions and objects to categories based on a variable or a dimension, by thereafter storing the aggregated database thus formed, by sorting the database with respect to dimensions and categories in order to position similar dimensions and categories in proximity to one another and by graphically presenting the volume of data, the grouping parameters, the sorting parameters, and the presenting parameters being controlled by the user, and by repeating the method the desired number of times while changing one or several of the parameters mentioned.

A system for performing real-time failure mode analysis of a monitored system is disclosed. The system includes a data acquisition component, an analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the monitored system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and a machine learning engine.

The human neural response is coupled with computer pattern analysis for robust single-event detection of significant non-stationary brain responses triggered upon occurrence of a task-relevant stimulus. Classifier performance is enhanced fusing together the outputs of multiple different classifiers albeit multiple spatial classifiers to extract a temporal pattern as the brain response evolves, time and frequency-based spatio-temporal classifiers, and / or EEG and pupillary classifiers.

Systems and method for operating and monitoring refrigerators are described. Temperature cycles within the compartment are characterized using statistical, frequency and pattern analysis techniques to derive a steady-state characteristic of temperature within the compartment. A thermal sensor inside the conditioned area is monitored and temperature data sets can be analyzed to determine performance in comparison to a baseline, and energy consumption. Analysis of continuous temperature readings taken from individual or groups of freezers identifies patterns of variations in temperature cycles from which feedback on efficiency can be inferred. Electrical load can be determined by measuring or estimating current usage and identifying periods of time when compressors are active in the refrigerator.

A database stores map data including road network data and landmark data. A route search unit searches for a route from a departure point to a destination point from the road network data stored in said database. A road pattern analysis unit analyzes a road pattern of the route by referring to the road network data, and obtains road pattern data as the analysis result. A route guidance information generation unit generates route guidance information of the route using the road pattern data and the landmark data along the route. A presentation unit presents the route guidance information.

A customer shopping pattern analysis apparatus includes a correlating information storage section, and a sub-area information storage section. Upon receiving specifications of a particular sub-area as analysis conditions, flow line data of customers who passed through the particular sub-area are extracted based on information specifying the particular sub-area in the sub-area information storage section and based on the flow line data of each of the customers. In addition, transaction data correlated with the flow line data extracted is specified with reference to data in the correlating information storage section. Then, information about correlations between the flow line data extracted and the transaction data is created. From the thus created information, the apparatus analyzes the shopping patterns of the customers in the shop.

In a policy handling system performing automatic execution, management, and control of a system, a policy retrieving section (102) retrieves a policy associated with a triggering condition, and notifies a policy-execution-pattern analyzing section (105) of the retrieved policy. A policy-operation-log retrieving section (106) refers to a policy-operation-log storage section (107) to acquire the number of triggering times of the retrieved policy in a predetermined history acquisition period. The policy-execution-pattern analyzing section (105) compares the number of triggering times of the retrieved policy against a predetermined threshold and causes an abnormality notifying section (108) to issue abnormality information when the number of triggering times exceeds the threshold.

By collecting or creating information written in a specific descriptive system, making a real model defining the concept handled in the organization activity, analyzing the domain for defining the words by stratifying each concept on the model of each basic concept of at least person, organization, article, document, meeting and event for composing the organization activity, analyzing the sentence pattern for defining the context by stratifying on the model of the concept of action, and by fitting and integrating the word defined by domain analysis and sentence pattern analysis into the context, a logical model corresponding to the real model is created. Thereby an organization activity database, in which information about various events necessary for organization activity and information of achievements resulting organization activity are integrated, is constructed.

A method of performing mass spectral analysis involving at least one of the isotope satellites of at least one ion, comprising acquiring a measured mass spectral response including at least one of the isotope satellites; constructing a peak component matrix with mass spectral response functions; performing a regression analysis between the acquired mass spectral response and the peak component matrix; and reporting one of statistical measure and regression coefficients from the regression analysis for at least one of mass spectral peak purity assessment, ion charge determination, mass spectral deconvolution, and mass shift compensation. A method for the identification of an ion in a sample through acquired MS scans, comprising obtaining an isotope pattern of an ion; constructing a projection matrix based on the isotope pattern or MS scan; projecting the isotope pattern or MS scan onto the projection matrix to calculate at least one of projection residual and projected data; and performing a statistical test on at least one of the projection residual and projected data to determine if the ion exists in the sample or if there is interference. A method which takes advantage of mass defect or isotope pattern analysis, and software and hardware for implementing all aspects of the invention.

Disclosed is an apparatus and method for compensating for estimated motion vectors by deciding whether a pattern image exists in target blocks for motion estimation. A motion estimation part compares a current block of a current frame / field to a search area established in a previous frame / field, calculates plural motion estimation error values, and estimates a temporary motion vector of the current block based on the plural motion estimation error values. A pattern decision part analyzes the calculated motion estimation error values, and decides that the current block is a pattern image. A motion compensation part produces a compensation motion vector of the current block by use of the plural motion estimation error values if the current block is decided as the pattern image. A motion vector selection part selects a final motion vector based on a result of the pattern decision part.