Patent application number | Description | Published |
20100321012 | DRIVE COIL, MEASUREMENT PROBE COMPRISING THE DRIVE COIL AND METHODS UTILIZING THE MEASUREMENT PROBE - The invention provides a drive coil and measurement probe comprising the drive coil. The measurement probes can be used, for example, in in-situ, non-destructive testing methods, also provided herein. | 12-23-2010 |
20110196625 | MULTIPHASE FLOW METERING WITH PATCH ANTENNA - Various methods of metering a multi-phase composition in a pipe using patch antenna(s), that operate in a radio or microwave frequency range, are disclosed including locating and then exciting the patch antenna(s) over a range of frequencies; measuring transmitted and reflected signals over time; estimating a shift in a resonant frequency from a baseline resonant frequency; then calculating a permittivity of the composition, based on the shift; and calculating a phase composition of the multi-phase composition. The present invention has been described in terms of specific embodiment(s), and it is recognized that equivalents, alternatives, and modifications, aside from those expressly stated, are possible and within the scope of the appending claims. | 08-11-2011 |
20110215799 | MAGNETIC INSPECTION SYSTEMS FOR INSPECTION OF TARGET OBJECTS - Inspection systems provided herein may include a drive coil capable of being excited to generate a substantially uniform magnetic field about an object. The object includes a ferromagnetic adhesive adhered thereto. The inspection systems may also include an array of sensor coils adapted to detect the magnetic field from the drive coil after the magnetic field interacts with the ferromagnetic adhesive and to produce a voltage output corresponding to the detected magnetic field. | 09-08-2011 |
20130106409 | EDDY CURRENT ARRAY PROBE | 05-02-2013 |
20130111982 | Systems and Methods For Use In Monitoring Operation Of A Rotating Component - A system for use in monitoring operation of a rotor assembly is provided. The system includes a plurality of clearance sensors including at least a first clearance sensor configured to measure a distance between the first sensor and a surface of a lockwire tab, and a monitoring unit coupled to the plurality of clearance sensors, the monitoring unit configured to receive measurements from the plurality of clearance sensors, and determine whether a crack exists in the rotor assembly based on the received measurements. | 05-09-2013 |
20140139211 | MAGNETIC INSPECTION SYSTEMS FOR INSPECTION OF TARGET OBJECTS - Inspection systems provided herein include drive coils capable of being excited to generate a substantially uniform magnetic field about an object. The object includes a ferromagnetic adhesive adhered thereto. The inspection systems may also include an array of sensor coils adapted to detect the magnetic field from the drive coils after the magnetic field interacts with the ferromagnetic adhesive and to produce a voltage output corresponding to the detected magnetic field. | 05-22-2014 |
Patent application number | Description | Published |
20090150436 | METHOD AND SYSTEM FOR CATEGORIZING TOPIC DATA WITH CHANGING SUBTOPICS - The embodiments of the invention provide a method for the automatic identification of changing subtopics within topics. The method begins by receiving customer satisfaction data having unstructured data objects. Next, the data objects are automatically categorized into pre-defined topics, wherein the pre-defined topics do not change throughout the customer satisfaction analysis. The pre-defined topics can be automatically defined based on a history of customer satisfaction data. Following this, a clustering analysis is automatically performed to identify subtopics of the data objects within the pre-defined topics. The subtopics are more specific than the pre-defined topics, and the subtopics can change. Further, the clustering analysis can include extracting features from the data objects and grouping the features into the subtopics. Each of the subtopics includes features having a predetermined degree of similarity. | 06-11-2009 |
20100332424 | DETECTING FACTUAL INCONSISTENCIES BETWEEN A DOCUMENT AND A FACT-BASE - Techniques for identifying one or more inconsistencies between an unstructured document and a back-end fact-base are provided. The techniques include automatically parsing a query document and comparing the document with a back-end fact-base comprising facts relevant to the document, identifying one or more inconsistencies between information mentioned in the document and the facts stored in the back-end fact-base, and providing a response to the query document, wherein the response additionally includes the one or more identified inconsistencies. | 12-30-2010 |
20110251839 | METHOD AND SYSTEM FOR INTERACTIVELY FINDING SYNONYMS USING POSITIVE AND NEGATIVE FEEDBACK - Determining synonyms of words in a set of documents. Particularly, when provided with a word or phrase as input, in exemplary embodiments there is afforded the return of a predetermined number of “top” synonym words (or phrases) for an input word (or phrase) in a specific collection of text documents. Further, a user is able to provide ongoing and iterative positive or negative feedback on the returned synonym words, by manually accepting or rejecting such words as the process is underway. | 10-13-2011 |
20140180692 | INTENT MINING VIA ANALYSIS OF UTTERANCES - According to example configurations, a speech processing system can include a syntactic parser, a word extractor, word extraction rules, and an analyzer. The syntactic parser of the speech processing system parses the utterance to identify syntactic relationships amongst words in the utterance. The word extractor utilizes word extraction rules to identify groupings of related words in the utterance that most likely represent an intended meaning of the utterance. The analyzer in the speech processing system maps each set of the sets of words produced by the word extractor to a respective candidate intent value to produce a list of candidate intent values for the utterance. The analyzer is configured to select, from the list of candidate intent values (i.e., possible intended meanings) of the utterance, a particular candidate intent value as being representative of the intent (i.e., intended meaning) of the utterance. | 06-26-2014 |
Patent application number | Description | Published |
20110166850 | CROSS-GUIDED DATA CLUSTERING BASED ON ALIGNMENT BETWEEN DATA DOMAINS - A system and associated method for cross-guided data clustering by aligning target clusters in a target domain to source clusters in a source domain. The cross-guided clustering process takes the target domain and the source domain as inputs. A common word attribute shared by both the target domain and the source domain is a pivot vocabulary, and all other words in both domains are a non-pivot vocabulary. The non-pivot vocabulary is projected onto the pivot vocabulary to improve measurement of similarity between data items. Source centroids representing clusters in the source domain are created and projected to the pivot vocabulary. Target centroids representing clusters in the target domain are initially created by conventional clustering method and then repetitively aligned to converge with the source centroids by use of a cross-domain similarity graph that measures a respective similarity of each target centroid to each source centroid. | 07-07-2011 |
20110167064 | CROSS-DOMAIN CLUSTERABILITY EVALUATION FOR CROSS-GUIDED DATA CLUSTERING BASED ON ALIGNMENT BETWEEN DATA DOMAINS - A system and associated method for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively. | 07-07-2011 |
20120191712 | CROSS-DOMAIN CLUSTERABILITY EVALUATION FOR CROSS-GUIDED DATA CLUSTERING BASED ON ALIGNMENT BETWEEN DATA DOMAINS - A computer program product evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively. | 07-26-2012 |
20120191713 | CROSS-DOMAIN CLUSTERABILITY EVALUATION FOR CROSS-GUIDED DATA CLUSTERING BASED ON ALIGNMENT BETWEEN DATA DOMAINS - A process for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source- target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively. | 07-26-2012 |
20120197892 | CROSS-DOMAIN CLUSTERABILITY EVALUATION FOR CROSS-GUIDED DATA CLUSTERING BASED ON ALIGNMENT BETWEEN DATA DOMAINS - A computer system for evaluating cross-domain clusterability upon a target domain and a source domain. The cross-domain clusterability is calculated as a linear combination of a target clusterability and a source-target pair matchability, by use of a trade-off parameter that determines relative contribution of the target clusterability and the source-target pair matchability. The target clusterability quantifies how clusterable the target domain is. The source-target pair matchability is calculated as an average of a target-side matchability and a source-side matchability, which quantifies how well target centroids of the target domain are aligned with the source centroids and how well source centroids of the source domain are aligned with the target centroids, respectively. | 08-02-2012 |
20140122492 | CROSS-DOMAIN CLUSTERABILITY EVALUATION FOR CROSS-GUIDED DATA CLUSTERING BASED ON ALIGNMENT BETWEEN DATA DOMAINS - A method and system for evaluating cross-domain clusterability upon a target domain and a source domain. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by the target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of the source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability. The cross-domain clusterability is transferred to a device. | 05-01-2014 |
Patent application number | Description | Published |
20120072421 | SYSTEMS AND METHODS FOR INTERACTIVE CLUSTERING - Systems and associated methods provide a cluster-level semi-supervision model for inter-active clustering. Embodiments accept user provided semi-supervision for updating cluster descriptions and assignment of data items to clusters. Assignment feedback re-assigns data items among existing clusters, while cluster description feedback helps to position existing cluster centers more meaningfully. The feedback can continue until the user is satisfied with the clustering achieved or one or more predetermined stopping criteria have been reached. | 03-22-2012 |
20120124044 | SYSTEMS AND METHODS FOR PHRASE CLUSTERING - Systems and associated methods for enhanced concept understanding in large document collections through phrase clustering are described. Embodiments take as input an initial set of phrases and estimate centroids using a clustering process. Embodiments then generate new phrases around each of the current centroids using the current phrases. These new phrases are added to the current set, and the clustering process is iterated. Upon convergence, embodiments finalize clusters based on phrases of any given length. | 05-17-2012 |
20130080436 | PHRASE CLUSTERING - Systems and associated methods for enhanced concept understanding in large document collections through phrase clustering are described. Embodiments take as input an initial set of phrases and estimate centroids using a clustering process. Embodiments then generate new phrases around each of the current centroids using the current phrases. These new phrases are added to the current set, and the clustering process is iterated. Upon convergence, embodiments finalize clusters based on phrases of any given length. | 03-28-2013 |
20130224713 | ENHANCING KNOWLEDGE BASES USING RICH SOCIAL MEDIA - Methods and arrangements for developing knowledge bases from social media. A question is obtained from social media. Social media are consulted, and a legitimacy of the question is ascertained. All the answers to the question are harvested from the social media including the rich media that is associated with these answers, and the question is filtered out if determined not to be legitimate. | 08-29-2013 |
20130224714 | ENHANCING KNOWLEDGE BASES USING RICH SOCIAL MEDIA - Methods and arrangements for developing knowledge bases from social media. A question is obtained from social media. Social media are consulted, and a legitimacy of the question is ascertained. All the answers to the question are harvested from the social media including the rich media that is associated with these answers, and the question is filtered out if determined not to be legitimate. | 08-29-2013 |