Patents Examined by Kevin W Figueroa
  • Patent number: 9165248
    Abstract: A parallel genetic algorithm computing process tracks forward progress of a first sub-population across generations thereof. The first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem. At a current generation of the first sub-population, it is determined that forward progress of the first sub-population fails a set of one or more forward progress criteria. In response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, a local catastrophe is invoked on the current generation of the first sub-population. The first sub-population is re-populated after the local catastrophe is invoked. The first sub-population is re-established after re-populating while constraining migration to the first sub-population.
    Type: Grant
    Filed: August 24, 2012
    Date of Patent: October 20, 2015
    Assignee: International Business Machines Corporation
    Inventor: Jason F. Cantin
  • Patent number: 9165247
    Abstract: A parallel genetic algorithm computing process tracks forward progress of a first sub-population across generations thereof. The first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem. At a current generation of the first sub-population, it is determined that forward progress of the first sub-population fails a set of one or more forward progress criteria. In response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, a local catastrophe is invoked on the current generation of the first sub-population. The first sub-population is re-populated after the local catastrophe is invoked. The first sub-population is re-established after re-populating while constraining migration to the first sub-population.
    Type: Grant
    Filed: January 4, 2012
    Date of Patent: October 20, 2015
    Assignee: International Business Machines Corporation
    Inventor: Jason F. Cantin
  • Patent number: 9160398
    Abstract: Disclosed are a method and an apparatus for transmitting a sparse signal, and a method and an apparatus for recovering the sparse signal. The method for recovering a sparse signal by using a sparse signal recovering device that recovers a target signal from a received signal includes receiving a measurement signal with a noise signal from a sparse signal transmitting device which scans a target signal based on a measurement matrix, performing a mutual update procedure in which a likelihood probability is calculated by using a posterior probability of the target signal based on a relation between the target signal and the measurement signal, and the posterior probability is updated by using the likelihood probability, and recovering the target signal by performing maximum a posterior estimation for a final posterior probability output through the mutual update procedure.
    Type: Grant
    Filed: March 14, 2012
    Date of Patent: October 13, 2015
    Assignee: GWANGJU INSTITUTE OF SCIENCE AND TECHNOLOGY
    Inventors: Heung-No Lee, Kiseon Kim, Jaewook Kang
  • Patent number: 9135573
    Abstract: The disclosed embodiments provide a reputation system. The reputation system includes a statistical model associated with a set of items and a set of dimensions of the items in the reputation system, wherein the statistical model is trained using a positive class and a negative class. The reputation system also includes a scoring apparatus that applies the statistical model to a set of features for each of the items to estimate a set of reputation scores for the items. Finally, the reputation system includes a ranking apparatus that enables use of the set of reputation scores in the reputation system.
    Type: Grant
    Filed: March 17, 2014
    Date of Patent: September 15, 2015
    Assignee: LinkedIn Corporation
    Inventors: Mario S. Rodriguez, Viet Thuc Ha, Jessica V. Zuniga, Mathieu Bastian, Michael Conover
  • Patent number: 9122996
    Abstract: A method of performing real-time correction of a water stage forecast includes obtaining at least one predicted water stage of at least one time and a predicted water stage of a next time after the at least one time; obtaining at least one observed water stage of the at least one time; generating a system error of the water stage forecast according to the at least one observed water stage, the at least one predicted water stage, the predicted water stage of the next time, a Time Series method, and an Average Deviation method; utilizing a Kalman filter method to generate a random error of the water stage forecast; generating a water stage forecast correction of the next time according to the system error and the random error; and correcting a predicted water stage of the next time according to the water stage forecast correction and the predicted water stage.
    Type: Grant
    Filed: August 2, 2012
    Date of Patent: September 1, 2015
    Assignee: National Applied Research Laboratories
    Inventors: Ho-Cheng Lien, Shiang-Jen Wu, Chih-Tsung Hsu
  • Patent number: 9122987
    Abstract: Future travel times of a target vehicle traveling on a route from a starting point to a destination are predicted by first acquiring, by a probe vehicle, real-time probe data to alternative links from the starting point to the destination. Then, the future travel time for each link is predicted using a set of regression functions.
    Type: Grant
    Filed: January 17, 2013
    Date of Patent: September 1, 2015
    Assignee: Mitsubishi Electric Research Laboratories, Inc.
    Inventors: Michael Jones, Daniel Nikovski, Yanfeng Geng
  • Patent number: 9110983
    Abstract: Systems and methods may provide traversing data using metadata. In one example, a method may include gathering a textual description of a first object, wherein the textual description includes a word, generating a vector represent the textual description, assigning a first weight value to the word, associating an object space with the word including assigning a second weight value to the word, and associating an object space with the first object.
    Type: Grant
    Filed: August 17, 2012
    Date of Patent: August 18, 2015
    Assignee: Intel Corporation
    Inventors: Norma Saiph Savage, Rita H. Wouhaybi
  • Patent number: 9111228
    Abstract: Systems and methods are provided for combining multiple segmentations into a single unique segmentation that contains attributes of the original segmentations. This new segmentation forms an ensemble or combination segmentation that has a unique set of attributes from the original segmentations without enumerating every possible set of combinations. In one example, two or more segments are combined into a single segmentation using a technique such as k-means clustering or Self-Organizing Map Neural Networks. After the first combination phase is performed, a Bayesian technique is then applied in a second phase to adjust or further alter the ensemble combination of segments.
    Type: Grant
    Filed: October 29, 2012
    Date of Patent: August 18, 2015
    Assignee: SAS Institute Inc.
    Inventor: Randall S. Collica
  • Patent number: 9092727
    Abstract: Provided herein are various systems and methods of using an exam type data structure to map exam types in various formats to master exam types that may be associated with customized rules or other features.
    Type: Grant
    Filed: August 10, 2012
    Date of Patent: July 28, 2015
    Assignee: D.R. Systems, Inc.
    Inventor: Murray A. Reicher
  • Patent number: 9009083
    Abstract: A mechanism for automatic quantification of multimedia production quality is presented. A method of embodiments includes assembling data samples from users, the data samples indicating a relative production quality of a set of content items based on a comparison of production quality between content items in the set, extracting content features from each of the content items in the set, and learning, based on the data samples from the plurality of users, a statistical model on the extracted content features, wherein the learned statistical model can predict a production quality of another content item that is not part of the set of content items.
    Type: Grant
    Filed: February 15, 2012
    Date of Patent: April 14, 2015
    Assignee: Google Inc.
    Inventors: Sanketh Shetty, Jonathon Shlens, Hrishikesh Aradhye
  • Patent number: 8990132
    Abstract: A low-order model (LOM) of biological neural networks and its mathematical equivalents including the clusterer interpreter probabilistic associative memory (CIPAM) are disclosed. They are artificial neural networks (ANNs) organized as networks of processing units (PUs), Each PU comprising artificial neuronal encoders, synapses, spiking/nonspiking neurons, and a scheme for maximal generalization. If the weights in the artificial synapses in a PU have been learned (and then fixed) or can be adjusted by the unsupervised accumulation rule and the unsupervised covariance rule (or supervised covariance rule), the PU is called unsupervised (or supervised) PU. The disclosed ANNs, with these Hebbian-type learning rules, can learn large numbers of large input vectors with temporally/spatially hierarchical causes with ease and recognize such causes with maximal generalization despite corruption, distortion and occlusion.
    Type: Grant
    Filed: May 11, 2012
    Date of Patent: March 24, 2015
    Inventor: James Ting-Ho Lo
  • Patent number: 8983880
    Abstract: To provide an information spread scale prediction device capable of accurately predicting the number of future contributions for a specific topic in SNS and the like. The information spread scale prediction device includes: a learning text data input unit which acquires learning text data from a specific website; a node influence learning unit which calculates the influence for the number of statements by each group to which a node specifying a single specific user belongs for the topic from the number of statements by each classified topic, and stores it as learning data; a prediction text data input unit which acquires prediction text data from the specific website after storing the learning data; and a future contribution number prediction unit which predicts and outputs the number of contributions at a specific future time of the topic based on the number of statements of each topic and the learning data.
    Type: Grant
    Filed: November 1, 2012
    Date of Patent: March 17, 2015
    Assignee: NEC Corporation
    Inventors: Kenji Aoki, Satoshi Morinaga
  • Patent number: 8924320
    Abstract: A characteristic forecasting system is disclosed. The characteristic forecasting system may have a memory and a processor. The memory may store instructions, that, when executed, enable the processor to generate at least one chromosome using a genetic algorithm, the chromosome including data values for variables of one or more equations used to generate forecast data for a target item. The processor may also be enabled to calculate a chromosome value for the chromosome based on a goal function associated with the genetic algorithm and determine at least one process parameter value for the chromosome at a time interval of the forecast data. The processor may also compare the process parameter value to a process constraint value representing a process limitation associated with the target item and modify the chromosome value for the chromosome responsive to a determination that the process parameter value does not satisfy the process constraint value.
    Type: Grant
    Filed: February 7, 2012
    Date of Patent: December 30, 2014
    Assignee: Caterpillar Inc.
    Inventor: Anthony James Grichnik
  • Patent number: 8868473
    Abstract: Systems, methods, and other embodiments associated with decision making with analytically combined split conditions are provided. In one embodiment, a method for classifying data is provided. An input data sample is received for classification as belonging to one of two possible classes. The input data sample includes a set of attribute values. The method includes evaluating the set of attribute values with a tree function that defines a decision boundary of a classification tree. The tree function classifies an input data sample as belonging to one of the two possible classes based, at least in part, on the attribute values of the input data sample. In another embodiment parameters of the tree function are derived by applying a gradient descent parameter update rule to the training data samples.
    Type: Grant
    Filed: October 24, 2011
    Date of Patent: October 21, 2014
    Assignee: Oracle International Corporation
    Inventors: Aleksey Urmanov, Anton Bougaev
  • Patent number: 8856058
    Abstract: A business rules engine includes dynamic objects to support dynamically addressable facts. The business rules engine is configured to reduce the need for developer resources to provision resources and adjust/adapt input data and output which would traditionally be required. As a result significant cost advantages are provided in the use of a business rules engine.
    Type: Grant
    Filed: January 4, 2012
    Date of Patent: October 7, 2014
    Assignee: NICE Systems Technologies Inc.
    Inventors: David Brooke Martin, Arkadiy Isaakovich Reznik
  • Patent number: 8812422
    Abstract: The invention provides a system and method for describing polymorphisms or genetic variants based on information about mutations and relationships among them. The invention uses object-oriented concepts to describe variants as variant objects and relations among those variants as variant relation object, each object being an instance of an abstract class of genomic feature and able to contain any number of other objects. Information about genetic disorders is stored in association with the object that represents the pathogenic variant. Genetic test results are used to access corresponding objects to provide a report based on variants or polymorphisms in a patient's genetic material.
    Type: Grant
    Filed: November 2, 2012
    Date of Patent: August 19, 2014
    Assignee: Good Start Genetics, Inc.
    Inventors: Marcia M. Nizzari, Benjamin H. Breton, David L. Tefft, Xavier S. Haurie