Patents by Inventor Brian Wallace

Brian Wallace has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250139185
    Abstract: A system for micro-credential opportunity discovery and earning via an installed browser extension. The system includes a server equipped with a processor and a memory that executes a micro-credential browser extension within a web browser environment. This extension is designed to dynamically scan web pages accessed via the browser, utilizing a comparison between the web page's URL and a database to detect embedded micro-credential opportunities unique to each URL. Upon detecting a micro-credential earning opportunity, the system automatically generates a user notification within the browser, presenting an opportunity to engage with specific content or actions that satisfy criteria for earning the micro-credential. The system further monitors user actions to confirm criteria completion and issues a digital badge as a verifiable record of the micro-credential.
    Type: Application
    Filed: April 1, 2024
    Publication date: May 1, 2025
    Inventor: Douglas Brian Wallace
  • Publication number: 20250042575
    Abstract: An electric pushback vehicle includes a frame having a forward portion and a rear portion. The vehicle further includes front drive axle and a rear drive axle configured to communicate power to ground engaging members. A traction battery is housed within the electric pushback vehicle and provides electric power to an electric motor to drive an output shaft. A transmission is connected to receive mechanical power from the electric motor through a torque converter.
    Type: Application
    Filed: October 10, 2024
    Publication date: February 6, 2025
    Inventors: Trevor Douglas ROEBUCK, Brian Wallace YODER, Patrick Dwaine WARDEN, Chase Cherek SCHOFIELD, Robert Charles BRADLEY, Anthony Christopher MORRIS, Joshua David BARNES, William Cole KOSTER, Ian Kendall BALK, James Chandler LIGGETT
  • Patent number: 12129049
    Abstract: An electric pushback vehicle includes a frame having a forward portion and a rear portion. The vehicle further includes front drive axle and a rear drive axle configured to communicate power to ground engaging members. A traction battery is housed within the electric pushback vehicle and provides electric power to an electric motor to drive an output shaft. A transmission is connected to receive mechanical power from the electric motor through a torque converter.
    Type: Grant
    Filed: October 13, 2020
    Date of Patent: October 29, 2024
    Assignee: Textron Inc.
    Inventors: Trevor Douglas Roebuck, Brian Wallace Yoder, Patrick Dwaine Warden, Chase Cherek Schofield, Robert Charles Bradley, Anthony Christopher Morris, Joshua David Barnes, William Cole Koster, Ian Kendall Balk, James Chandler Liggett
  • Patent number: 12070641
    Abstract: The present invention relates to a kit used to configure, assemble, and reassemble play set apparatuses. More specifically, the present invention relates to a kit with several components which may be used in conjunction with one or more other components to form play set apparatuses. Still more specifically, the present invention relates to a kit with components that may be configured to form play set apparatuses including but not limited to a balance beam, a seesaw, a chair, a slide, and a rocking device.
    Type: Grant
    Filed: August 4, 2022
    Date of Patent: August 27, 2024
    Assignee: BE WOOD, LLC
    Inventor: Brian Wallace
  • Publication number: 20240190246
    Abstract: A system detects the occurrence of a vehicle event designated as a trigger. The system obtains interaction data, representing user interface interactions with a user interface of a vehicle, recorded by the vehicle for a predefined time period leading to the event. Further, the system, for any obtained interaction data, compares the data to historical data indicating interactions with a user interface prior to previous events comparable to the detected event to determine whether there is at least one correlation between user interface interaction and the occurrence of events comparable to the detected event and, responsive to a determined correlation, instructs modification of an aspect of the user interface of the vehicle, the aspect associated with interactions represented by the interaction data.
    Type: Application
    Filed: December 9, 2022
    Publication date: June 13, 2024
    Inventors: Brian Wallace STOP, Adil Nizam SIDDIQUI, Mahmoud Yousef GHANNAM
  • Publication number: 20240101274
    Abstract: An electric pushback vehicle includes a frame having a forward portion and a rear portion. The vehicle further includes front drive axle and a rear drive axle configured to communicate power to ground engaging members. A traction battery is housed within the electric pushback vehicle and provides electric power to an electric motor to drive an output shaft. A transmission is connected to receive mechanical power from the electric motor through a torque converter.
    Type: Application
    Filed: October 13, 2020
    Publication date: March 28, 2024
    Inventors: Trevor Douglas ROEBUCK, Brian Wallace YODER, Patrick Dwaine WARDEN, Chase Cherek SCHOFIELD, Robert Charles BRADLEY, Anthony Christopher MORRIS, Joshua David BARNES, William Cole KOSTER, Ian Kendall BALK, James Chandler LIGGETT
  • Patent number: 11797826
    Abstract: A system is provided for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.
    Type: Grant
    Filed: December 18, 2020
    Date of Patent: October 24, 2023
    Assignee: Cylance Inc.
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Eric Petersen, Ming Jin, Ryan Permeh
  • Publication number: 20230040497
    Abstract: The present invention relates to a kit used to configure, assemble, and reassemble play set apparatuses. More specifically, the present invention relates to a kit with several components which may be used in conjunction with one or more other components to form play set apparatuses. Still more specifically, the present invention relates to a kit with components that may be configured to form play set apparatuses including but not limited to a balance beam, a seesaw, a chair, a slide, and a rocking device.
    Type: Application
    Filed: August 4, 2022
    Publication date: February 9, 2023
    Applicant: Be Wood, LLC
    Inventor: Brian Wallace
  • Patent number: 11336587
    Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for generation and management of controlled-use resources which allow the sender of an electronic resource transfer to limit the ways in which the recipient may use the received resources. This invention allows the sender to maintain control over the products or services purchased with transferred resources, as well as personalize a transfer for a recipient by selecting a favorite merchant or spending category of the recipient. The invention may also benefit a plurality of merchants and other third party entities which may obtain new customers as a result of said customers receiving controlled-use resources designated for said merchants.
    Type: Grant
    Filed: March 11, 2021
    Date of Patent: May 17, 2022
    Assignee: BANK OF AMERICA CORPORATION
    Inventors: Robertson Walters Greenbacker, Brian Wallace Borneman, Justin Riley duPont, Tony England, Timothy Stephen Nurse, Stephen Philip Selfridge
  • Patent number: 11188646
    Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.
    Type: Grant
    Filed: October 24, 2019
    Date of Patent: November 30, 2021
    Assignee: Cylance Inc.
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Yaroslav Oliinyk, Ryan Permeh
  • Publication number: 20210256350
    Abstract: A system is provided for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.
    Type: Application
    Filed: December 18, 2020
    Publication date: August 19, 2021
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Eric Petersen, Ming Jin, Ryan Permeh
  • Patent number: 11074494
    Abstract: In one respect, there is provided a system for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.
    Type: Grant
    Filed: November 7, 2016
    Date of Patent: July 27, 2021
    Assignee: Cylance Inc.
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Eric Petersen, Ming Jin, Ryan Permeh
  • Patent number: 10922604
    Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more instruction sequences. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: training, based at least on training data, a machine learning model to detect one or more predetermined interdependencies amongst a plurality of tokens in the training data; and providing the trained machine learning model to enable classification of one or more instruction sequences. Related methods and articles of manufacture, including computer program products, are also provided.
    Type: Grant
    Filed: November 7, 2016
    Date of Patent: February 16, 2021
    Assignee: Cylance Inc.
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Eric Petersen, Ming Jin, Ryan Permeh
  • Patent number: 10810470
    Abstract: Centroids are used for improving machine learning classification and information retrieval. A plurality of files are classified as malicious or not malicious based on a function dividing a coordinate space into at least a first portion and a second portion such that the first portion includes a first subset of the plurality of files classified as malicious. One or more first centroids are defined in the first portion that classify files from the first subset as not malicious. A file is determined to be malicious based on whether the file is located within the one or more first centroids.
    Type: Grant
    Filed: August 7, 2019
    Date of Patent: October 20, 2020
    Assignee: Cylance Inc.
    Inventors: Jian Luan, Matthew Wolff, Brian Wallace
  • Patent number: 10637874
    Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.
    Type: Grant
    Filed: November 7, 2016
    Date of Patent: April 28, 2020
    Assignee: Cylance Inc.
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andrew Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Yaroslav Oliinyk, Ryan Permeh
  • Patent number: 10611592
    Abstract: An automatic loader for delivering vertically stacked media to a hopper of a feeder. The automatic loader includes a powered conveying device, actuated plates, a first sensor, and a second sensor. The first sensors detects a height of the vertically stacked media that is in the hopper, and the second sensor detects a separation between the hopper and the vertically stacked media that is in a staging area of the conveying device. Based on signals generated by the first and second sensors, the conveying device automatically delivers the vertically stacked media that is in the staging area to the hopper of the feeder.
    Type: Grant
    Filed: May 30, 2018
    Date of Patent: April 7, 2020
    Assignee: Walco Systems
    Inventor: Robert Brian Wallace
  • Publication number: 20200057853
    Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.
    Type: Application
    Filed: October 24, 2019
    Publication date: February 20, 2020
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Yaroslav Oliinyk, Ryan Permeh
  • Patent number: 10503901
    Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.
    Type: Grant
    Filed: November 7, 2016
    Date of Patent: December 10, 2019
    Assignee: Cylance Inc.
    Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Yaroslav Oliinyk, Ryan Permeh
  • Publication number: 20190362196
    Abstract: Centroids are used for improving machine learning classification and information retrieval. A plurality of files are classified as malicious or not malicious based on a function dividing a coordinate space into at least a first portion and a second portion such that the first portion includes a first subset of the plurality of files classified as malicious. One or more first centroids are defined in the first portion that classify files from the first subset as not malicious. A file is determined to be malicious based on whether the file is located within the one or more first centroids.
    Type: Application
    Filed: August 7, 2019
    Publication date: November 28, 2019
    Inventors: Jian Luan, Matthew Wolff, Brian Wallace
  • Patent number: D993650
    Type: Grant
    Filed: August 4, 2021
    Date of Patent: August 1, 2023
    Assignee: BE WOOD, LLC
    Inventor: Brian Wallace