Patents Assigned to SAS Institute Inc.
  • Patent number: 11354566
    Abstract: A treatment model that is a first neural network is trained to optimize a treatment loss function based on a treatment variable t using a plurality of observation vectors by regressing t on x(1),z. The trained treatment model is executed to compute an estimated treatment variable value {circumflex over (t)}i for each observation vector. An outcome model that is a second neural network is trained to optimize an outcome loss function by regressing y on x(2) and an estimated treatment variable t. The trained outcome model is executed to compute an estimated first unknown function value {circumflex over (?)}(xi(2)) and an estimated second unknown function value {circumflex over (?)}(xi(2)) for each observation vector. An influence function value is computed for a parameter of interest using {circumflex over (?)}(xi(2)) and {circumflex over (?)}(xi(2)). A value is computed for the predefined parameter of interest using the computed influence function value.
    Type: Grant
    Filed: October 21, 2021
    Date of Patent: June 7, 2022
    Assignee: SAS Institute Inc.
    Inventors: Xilong Chen, Douglas Allan Cairns, Jan Chvosta, David Bruce Elsheimer, Yang Zhao, Ming-Chun Chang, Gunce Eryuruk Walton, Michael Thomas Lamm
  • Patent number: 11354583
    Abstract: Logical rules can be automatically generated for use with event detection systems according to some aspects of the present disclosure. For example, a computing device can extract a group of logical rules from trained decision trees and apply a test data set to the group of logical rules to determine count values corresponding to the logical rules. The computing device can then determine performance metric values based on the count values, select a subset of logical rules from among the group of logical rules based on the performance metric values, and provide at least one logical rule in the subset for use with an event detection system. The event detection system can be configured to detect an event in relation to a target data set that was not used to train the decision trees.
    Type: Grant
    Filed: April 8, 2021
    Date of Patent: June 7, 2022
    Assignee: SAS INSTITUTE INC.
    Inventors: Hamoon Azizsoltani, Prathaban Mookiah, Weichen Wang, Thomas J. O'Connell
  • Patent number: 11347686
    Abstract: An apparatus includes a processor to: instantiate data buffers of a queue, reading threads, and provision threads; within each reading thread, use an identifier provided in a data buffer of the queue to retrieve the corresponding data set part and part metadata from storage device(s), and store both within the data buffer; operate the queue as a (FIFO) buffer; within each provision thread, retrieve a row group from among multiple row groups and corresponding metadata from within the data buffer, use information in the metadata to decompress at least one column, and provide the data values of the row group to the requesting device or an application routine; and in response to each instance of storage of a data set part within a data buffer of the queue, analyze the availability of storage space and/or of processing resources to determine whether to dynamically adjust the quantity of reading threads.
    Type: Grant
    Filed: September 30, 2020
    Date of Patent: May 31, 2022
    Assignee: SAS INSTITUTE INC.
    Inventors: Brian Payton Bowman, Gordon Lyle Keener
  • Patent number: 11346751
    Abstract: A computing system receives a request for computer-generated likelihood(s) for candidate evaluations of an industrial product set according to a measurement system analysis (MSA). The MSA comprises tests for evaluating, according to a measurement standard, the industrial product set. The request indicates a metric set representing metric(s) each quantifying an estimate of contribution to variation in evaluating the industrial product set according to the MSA. The system generates a design comprising a respective input set for each test of the MSA. The respective input set comprises setting(s) for conducting a test of the MSA. The design is designed to isolate candidate sources for contributing to the variation in evaluating the industrial product set according to the MSA. The system (e.g., prior to the MSA) outputs, based on the metric set and the design, the computer-generated likelihood(s) for the candidate evaluations of the industrial product set according to the MSA.
    Type: Grant
    Filed: July 29, 2021
    Date of Patent: May 31, 2022
    Assignee: SAS Institute Inc.
    Inventors: Caleb Bridges King, Joseph Albert Morgan, Ryan Adam Lekivetz, Bradley Allen Jones
  • Publication number: 20220167469
    Abstract: An apparatus includes a processor to: within a first container, and prior to its uninstantiation, execute a first instance of a routine to cause the processor to monitor for and detect a job performance request in a job queue; and within a second container, execute a second instance of the routine to cause the processor to search the job queue for a job performance request, and in response to a combination of the uninstantiation of the first container, the storage of the job performance request in the job queue and there being no indication of completion of the job flow in the job queue, perform a combination of store an indication of the job flow performance commencing in the job queue, derive an order of performance of the set of tasks of the job flow and store a first task execution request in a task queue.
    Type: Application
    Filed: December 28, 2021
    Publication date: May 26, 2022
    Applicant: SAS Institute Inc.
    Inventors: Henry Gabriel Victor Bequet, Ronald Earl Stogner, Eric Jian Yang, Qing Gong
  • Patent number: 11341414
    Abstract: An apparatus includes processor(s) to: receive a request for a data catalog; in response to the request specifying a structural feature, analyze metadata of multiple data sets for an indication of including it, and to retrieve an indicated degree of certainty of detecting it for data sets including it; in response to the request specifying a contextual aspect, analyze context data of the multiple data sets for an indication of being subject to it, and to retrieve an indicated degree of certainty concerning it for data sets subject to it; selectively include each data set in the data catalog based on the request specifying a structural feature and/or a contextual aspect, and whether each data set meets what is specified; for each data set in the data catalog, generate a score indicative of the likelihood of meeting what is specified; and transmit the data catalog to the requesting device.
    Type: Grant
    Filed: February 2, 2021
    Date of Patent: May 24, 2022
    Assignee: SAS INSTITUTE INC.
    Inventors: Nancy Anne Rausch, Roger Jay Barney, John P. Trawinski
  • Patent number: 11334809
    Abstract: A computing system receives as candidate predictors, for a model set, a list of terms for computer identification in dataset(s). The system receives initial user selections in the graphical user interface (GUI) of a term set, a response variable, and target value(s) for the response variable. The term set comprises candidate predictors from the list. The response variable is for a response to input to an initial model of the model set. The system generates the initial model that estimates a relationship between the target value(s) and the term set. The system displays in the GUI a performance representation of the initial model for user comparison of models and an indication of a contribution, to the initial model, of terms of a subset of the term set. The system receives a subsequent user selection, in the GUI, to change an aspect of the initial model.
    Type: Grant
    Filed: June 8, 2021
    Date of Patent: May 17, 2022
    Assignee: SAS Institute Inc.
    Inventors: Ernest C. Pasour, Clayton A. Barker, Paris Faison
  • Patent number: 11335350
    Abstract: An apparatus includes processor(s) to: perform pre-processing operations including derive an audio noise level of speech audio of a speech data set, derive a first relative weighting for first and second segmentation techniques for identifying likely sentence pauses in the speech audio based on the audio noise level, and select likely sentence pauses for a converged set of likely sentence pauses from likely sentence pauses identified by the first and/or second segmentation techniques based on the first relative weighting; and perform speech-to-text processing operations including divide the speech data set into data segments representing speech segments of the speech audio based on the converged set of likely sentence pauses, and derive a second relative weighting based on the audio noise level for selecting words indicated by an acoustic model or by a language model as being most likely spoken in the speech audio for inclusion in a transcript.
    Type: Grant
    Filed: October 12, 2021
    Date of Patent: May 17, 2022
    Assignee: SAS INSTITUTE INC.
    Inventors: Xiaolong Li, Xiaozhuo Cheng, Xu Yang
  • Patent number: 11328225
    Abstract: A computing device selects a trained spatial regression model. A spatial weights matrix defined for observation vectors is selected, where each element of the spatial weights matrix indicates an amount of influence between respective pairs of observation vectors. Each observation vector is spatially referenced. A spatial regression model is selected from spatial regression models, initialized, and trained using the observation vectors and the spatial weights matrix to fit a response variable using regressor variables. Each observation vector includes a response value for the response variable and a regressor value for each regressor variable of the regressor variables. A fit criterion value is computed for the spatial regression model and the spatial regression model selection, initialization, and training are repeated until each spatial regression model is selected. A best spatial regression model is selected and output as the spatial regression model having an extremum value of the fit criterion value.
    Type: Grant
    Filed: November 11, 2021
    Date of Patent: May 10, 2022
    Assignee: SAS Institute Inc.
    Inventors: Guohui Wu, Jan Chvosta, Wan Xu, Gunce Eryuruk Walton, Xilong Chen
  • Patent number: 11328106
    Abstract: A computing system receives a request to generate computer-generated data for an experiment. The computer-generated data comprises generated inputs defining setting(s) for a plurality of factors for a design of the experiment. The generated inputs are generated to be representative of a respective design space of different design spaces for the design of the experiment. The system receives first characteristic(s) for specifying generation of the computer-generated data associated with a first design space. The system receives second characteristic(s) for specifying generation of the computer-generated data associated with a second design space. The system, responsive to the request, generates a design suite that comprises the computer-generated data that represents, in a first set of design cases of the design suite, settings constrained by the first design space, and represents, in a second set of design cases of the design suite, settings constrained by the second design space.
    Type: Grant
    Filed: July 1, 2021
    Date of Patent: May 10, 2022
    Assignee: SAS Institute Inc.
    Inventors: Ryan Adam Lekivetz, Joseph Albert Morgan, Caleb Bridges King, Bradley Allen Jones
  • Patent number: 11322976
    Abstract: Operational events associated with a target physical device can be detected for mitigation by implementing some aspects described herein. For example, a system can apply a sliding window to received sensor measurements at successive time intervals to generate a set of data windows. The system can determine a set of eigenvectors associated with the set of data windows by performing principal component analysis on a set of data points in the set of data windows. The system can determine a set of angle changes between pairs of eigenvectors. The system can generate a measurement profile by executing an integral transform on the set of angle changes. One or more trained machine-learning models are configured to detect an operational event associated with the target physical device based on the measurement profile and generate an output indicating the operational event.
    Type: Grant
    Filed: October 14, 2021
    Date of Patent: May 3, 2022
    Assignee: SAS INSTITUTE INC.
    Inventors: Thomas Dale Anderson, Priyadarshini Sharma, Mark Joseph Konya, James M. Caton
  • Patent number: 11321581
    Abstract: Physical-device anomalies and degradation can be mitigated by implementing some aspects described herein. For example, a system can determine a first data window and a second data window by applying a window function to streaming data. The system can determine a first principal eigenvector of the first data window and a first principal eigenvector of the second data window. The system can determine an angle change between the first principal eigenvectors of the two data windows. The system can then detect an anomaly based on determining that the angle change exceeds a predefined angle-change threshold. Additionally or alternatively, the system may compare the first principal eigenvector for the second data window to a baseline value to determine an absolute angle associated with the second data window. The system can then detect a degradation based on determining that the absolute angle exceeds a predefined absolute-angle threshold.
    Type: Grant
    Filed: May 5, 2020
    Date of Patent: May 3, 2022
    Assignee: SAS INSTITUTE INC.
    Inventors: Kyungduck Cha, Carol Wagih Sadek, Zohreh Asgharzadeh Talebi
  • Patent number: 11321954
    Abstract: Some examples herein describe time-series recognition and analysis techniques with computer vision. In one example, a system can access an image depicting data lines representing time series datasets. The system can execute a clustering process to assign pixels in the image to pixel clusters. The system can generate image masks based on attributes of the pixel clusters, and identify a respective set of line segments defining the respective data line associated with each image mask. The system can determine pixel sets associated with the time series datasets based on the respective set of line segments associated with each image mask, and provide one or more pixel sets as input for a computing operation that processes the pixel sets and returns a processing result. The system may then display the processing result on a display device or perform another task based on the processing result.
    Type: Grant
    Filed: November 3, 2021
    Date of Patent: May 3, 2022
    Assignee: SAS INSTITUTE INC.
    Inventors: Taiyeong Lee, Michael James Leonard
  • Patent number: 11314844
    Abstract: A singular value decomposition (SVD) is computed of a first matrix to define a left matrix, a diagonal matrix, and a right matrix. The left matrix, the diagonal matrix, and the right matrix are updated using an arrowhead matrix structure defined from the diagonal matrix and by adding a next observation vector to a last row of the first matrix. The updated left matrix, the updated diagonal matrix, and the updated right matrix are updated using a diagonal-plus-rank-one (DPR1) matrix structure defined from the updated diagonal matrix and by removing an observation vector from a first row of the first matrix. Eigenpairs of the DPR1 matrix are computed based on whether a value computed from the updated left matrix is positive or negative. The left matrix updated in (C), the diagonal matrix updated in (C), and the right matrix updated in (C) are output.
    Type: Grant
    Filed: October 19, 2021
    Date of Patent: April 26, 2022
    Assignee: SAS Institute Inc.
    Inventors: Hansi Jiang, Arin Chaudhuri
  • Publication number: 20220121967
    Abstract: Logical rules can be automatically generated for use with event detection systems according to some aspects of the present disclosure. For example, a computing device can extract a group of logical rules from trained decision trees and apply a test data set to the group of logical rules to determine count values corresponding to the logical rules. The computing device can then determine performance metric values based on the count values, select a subset of logical rules from among the group of logical rules based on the performance metric values, and provide at least one logical rule in the subset for use with an event detection system. The event detection system can be configured to detect an event in relation to a target data set that was not used to train the decision trees.
    Type: Application
    Filed: April 8, 2021
    Publication date: April 21, 2022
    Applicant: SAS Institute Inc.
    Inventors: Hamoon Azizsoltani, Prathaban Mookiah, Weichen Wang, Thomas J. O'Connell
  • Publication number: 20220117046
    Abstract: An apparatus includes a processor to: within a performance container, execute a performance routine to derive an order of performance of tasks of a job flow based on dependencies, begin performing the tasks, and store, within a job queue, a job performance status indication including task performance statuses; identify a set of sub flows within the job flow based on branches in the job flow; correlate each of the task performance statuses to a corresponding sub flow performance status; reduce the job performance status indication size by, for each sub flow in which all tasks have been completed, replace the corresponding task performance statuses with the corresponding sub flow performance status of completed, and for each sub flow with no task performed, replace the corresponding task performance statuses with the corresponding sub flow performance status of not executed; and transmit the job performance status indication to the requesting device.
    Type: Application
    Filed: December 21, 2021
    Publication date: April 14, 2022
    Applicant: SAS Institute Inc.
    Inventors: Henry Gabriel Victor Bequet, Ronald Earl Stogner, Eric Jian Yang, Qing Gong
  • Publication number: 20220114488
    Abstract: The computing device transforms lab data and field data into a first format suitable for execution with a supervised machine learning model to determine an input variable importance for a first set of input variables in predicting a field outcome, generates one or more logical rules of decision metrics, selects the one or more input variables that yields a higher input variable importance, generates one or more pass-fail indicators, combines the one or more pass-fail indicators generates one or more prediction factor rules, transforms the field data and the one or more prediction factor rules into a second format suitable for execution with a model to determine a treatment effect for the one or more prediction factor rules, and selects the prediction factor rule that maximizes the treatment effect of predicting the field outcome of a performance of compounds or biological actives within a range of uncertainty.
    Type: Application
    Filed: September 23, 2021
    Publication date: April 14, 2022
    Applicant: SAS Institute Inc.
    Inventors: John Wesley Gottula, Bryan Matthew Mutell, Michael Lee Henderson, II
  • Patent number: 11301473
    Abstract: A computing device responds to a membership overlap query. A list of unique member identifiers included in a plurality of datasets is created. A list of datasets of the plurality of datasets is defined for each unique member identifier. Each dataset included in the list of datasets includes a unique member associated with a respective unique member identifier. A unique list of datasets is defined from each list of datasets. A number of occurrences of each unique list of datasets is determined. A number of datasets included in each unique list of datasets is determined. Intersection data is created that includes a dataset list of each unique list of datasets in association with the number of occurrences of each respective, unique list of datasets and with the number of datasets included in each respective, unique list of datasets. An overlap response is determined using the created intersection data.
    Type: Grant
    Filed: November 18, 2021
    Date of Patent: April 12, 2022
    Assignee: SAS Institute Inc.
    Inventor: Pradeep Kumar Swain
  • Patent number: 11281689
    Abstract: A computing system creates interaction features from variable values in a transformed dataset that includes a variable value computed for each variable of transformed variables computed from a prior execution of a transformation flow applied to an input dataset. An interaction transformation flow definition indicates a subset of the transformed variables, a synthesis definition, and interaction transformation operations to apply to the transformed variables. The synthesis definition describes how the subset of the transformed variables are combined to compute a value input to the interaction transformation operations. A plurality of variable combinations of the subset is defined. A computation is defined for each combination and interaction transformation operation. An operation data value is computed for each computation from the transformed dataset. An observation vector is read from the transformed dataset and a current interaction variable value is synthesized for each combination.
    Type: Grant
    Filed: October 19, 2021
    Date of Patent: March 22, 2022
    Assignee: SAS Institute Inc.
    Inventors: Biruk Gebremariam, Taiping He
  • Publication number: 20220083709
    Abstract: An apparatus includes processor(s) to: receive a request to test goodness-of-fit of a spatial process model; generate a KD tree from observed spatial point dataset including locations within a region at which instances of an event occurred; derive, from the observed spatial point dataset, multiple quadrats into which the region is divided; receive, from multiple processors, current levels of availability of processing resources including quantities of currently available execution threads; select, based on the quantity of currently available execution threads, a subset of the multiple processors to perform multiple iterations of a portion of the test in parallel; provide, to each processor of the subset, the KD tree, the spatial process model, and the multiple quadrats; receive, from each processor of the subset, per-quadrat data portions indicative of results of an iteration; derive a goodness-of-fit statistic from the per-quadrat data portions; and transmit an indication of goodness-of-fit to another device
    Type: Application
    Filed: November 26, 2021
    Publication date: March 17, 2022
    Applicant: SAS Institute Inc.
    Inventor: Pradeep Mohan