Patents by Inventor Minh Hoang
Minh Hoang 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).
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Publication number: 20240133718Abstract: The disclosure is directed to apparatus and methods for detection of out of position (OOP) components in a carrier tape forming machine. An apparatus includes cross track sensors coupled to the bus interface circuitry, the cross track sensors configured to detect OOP components prior to overlaying the components on the carrier tape with cover tape, optical sensors to detect the OOP components on the carrier tape after overlaying with cover tape and prior to sealing and to detect reflections from OOP components seated on the carrier tape, an amplifier coupled to the optical sensors to amplify signals generated by the optical sensors and set a range for determining whether the components are OOP, and relays to receive indications of detected OOP components, and a controller coupled to the relays to stop the carrier tape forming machine as a function of signals received by the relays.Type: ApplicationFiled: October 19, 2022Publication date: April 25, 2024Applicant: Intel CorporationInventors: Ngoc Duy VU, Nguyen Hoang Tan LE, Minh Anh Khoa NGUYEN
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Patent number: 11960832Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).Type: GrantFiled: April 20, 2022Date of Patent: April 16, 2024Assignee: Docugami, Inc.Inventors: Andrew Paul Begun, Steven DeRose, Taqi Jaffri, Luis Marti Orosa, Michael B. Palmer, Jean Paoli, Christina Pavlopoulou, Elena Pricoiu, Swagatika Sarangi, Marcin Sawicki, Manar Shehadeh, Michael Taron, Bhaven Toprani, Zubin Rustom Wadia, David Watson, Eric White, Joshua Yongshin Fan, Kush Gupta, Andrew Minh Hoang, Zhanlin Liu, Jerome George Paliakkara, Zhaofeng Wu, Yue Zhang, Xiaoquan Zhou
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Publication number: 20240119298Abstract: In aspects of the disclosure, a method comprises training, by a computing system, a dynamics model of a cooperative multi-agent reinforcement learning (c-MARL) environment. The method further comprises processing, by the computing system, a perturbation optimizer to generate a state perturbation of the c-MARL environment, based on the dynamics model. The method further comprises selecting one or more agents of the c-MARL system as having enhanced vulnerability. The method further comprises attacking, by the computing system, the c-MARL system based on the state perturbation and the selected one or more agents.Type: ApplicationFiled: September 23, 2022Publication date: April 11, 2024Inventors: Nhan Huu Pham, Lam Minh Nguyen, Jie Chen, Thanh Lam Hoang, Subhro Das
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Patent number: 11954085Abstract: A computer implemented method performs data skipping in a hierarchically organized computing system. A group of processor units determines leaf node data sketches for data in leaf nodes in the hierarchically organized computing system. The leaf node data sketches summarize attributes of data in the leaf nodes. The group of processor units aggregates the leaf node data sketches at intermediate nodes in the hierarchically organized computing system to form aggregated data sketches at the intermediate nodes and retains data sketches received at the intermediate nodes from a group of child nodes to form retained data sketches. The retained data sketches are one of leaf node data sketches and the aggregated data sketches. The group of processor units searches the data using the retained data sketches and the data skipping within the hierarchically organized computing system in response to queries made to the intermediate nodes in the hierarchically organized computing system.Type: GrantFiled: September 22, 2022Date of Patent: April 9, 2024Assignee: International Business Machines CorporationInventors: Mudhakar Srivatsa, Raghu Kiran Ganti, Joshua M. Rosenkranz, Linsong Chu, Tuan Minh Hoang Trong, Utpal Mangla, Satishkumar Sadagopan, Mathews Thomas
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Publication number: 20240104075Abstract: A computer implemented method performs data skipping in a hierarchically organized computing system. A group of processor units determines leaf node data sketches for data in leaf nodes in the hierarchically organized computing system. The leaf node data sketches summarize attributes of data in the leaf nodes. The group of processor units aggregates the leaf node data sketches at intermediate nodes in the hierarchically organized computing system to form aggregated data sketches at the intermediate nodes and retains data sketches received at the intermediate nodes from a group of child nodes to form retained data sketches. The retained data sketches are one of leaf node data sketches and the aggregated data sketches. The group of processor units searches the data using the retained data sketches and the data skipping within the hierarchically organized computing system in response to queries made to the intermediate nodes in the hierarchically organized computing system.Type: ApplicationFiled: September 22, 2022Publication date: March 28, 2024Inventors: MUDHAKAR SRIVATSA, RAGHU KIRAN GANTI, Joshua M. Rosenkranz, Linsong Chu, Tuan Minh HOANG TRONG, Utpal Mangla, SATISHKUMAR SADAGOPAN, Mathews Thomas
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Publication number: 20230390397Abstract: A method and system for sterilizing an iodine antiseptic solution is disclosed. The iodine antiseptic solution can comprise iodine crystals and/or povidone-iodine (PVP-I). The method includes providing the iodine antiseptic solution to a closed container. And during a sterilization cycle, the method further includes heating the iodine antiseptic solution in the closed container to a sterilization temperature sufficient to generate free elemental iodine in the closed container. The method further includes applying a positive pressure in the closed container to pressurize the free elemental iodine to produce sterilized iodine within the closed container.Type: ApplicationFiled: May 24, 2023Publication date: December 7, 2023Inventors: Minh HOANG, Bryan Garrett DAVIS
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Patent number: 11822880Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).Type: GrantFiled: August 5, 2020Date of Patent: November 21, 2023Assignee: Docugami, Inc.Inventors: Andrew Begun, Steven DeRose, Taqi Jaffri, Luis Marti Orosa, Michael Palmer, Jean Paoli, Christina Pavlopoulou, Elena Pricoiu, Swagatika Sarangi, Marcin Sawicki, Manar Shehadeh, Michael Taron, Bhaven Toprani, Zubin Rustom Wadia, David Watson, Eric White, Joshua Yongshin Fan, Kush Gupta, Andrew Minh Hoang, Zhanlin Liu, Jerome George Paliakkara, Zhaofeng Wu, Yue Zhang, Xiaoquan Zhou
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Patent number: 11816428Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).Type: GrantFiled: August 5, 2020Date of Patent: November 14, 2023Assignee: Docugami, Inc.Inventors: Andrew Begun, Steven DeRose, Taqi Jaffri, Luis Marti Orosa, Michael Palmer, Jean Paoli, Christina Pavlopoulou, Elena Pricoiu, Swagatika Sarangi, Marcin Sawicki, Manar Shehadeh, Michael Taron, Bhaven Toprani, Zubin Rustom Wadia, David Watson, Eric White, Joshua Yongshin Fan, Kush Gupta, Andrew Minh Hoang, Zhanlin Liu, Jerome George Paliakkara, Zhaofeng Wu, Yue Zhang, Xiaoquan Zhou
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Publication number: 20230177240Abstract: Systems and methods for semi-discrete modeling of progressive damage and failure in composite laminate materials are disclosed. An example method includes receiving, from a user, a fibrous strip width and a fibrous strip spacing, and creating a finite-element (FE) mesh by: generating, using a structured hex meshing algorithm, a plurality of fibrous strips along a fiber direction based on the fibrous strip width and the fibrous strip spacing, and generating, using a free hex-dominated advancing front meshing algorithm, a bulk element between each of the plurality of fibrous strips. The FE mesh may define a portion of a composite laminate material. The example method includes determining a predicted mechanical response of the composite laminate material by: generating a constitutive model corresponding to the composite laminate material based on the FE mesh, and inputting a stress value or a strain value to the constitutive model to generate the predicted mechanical response.Type: ApplicationFiled: November 15, 2022Publication date: June 8, 2023Inventors: Minh Hoang Nguyen, Anthony M. Waas
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Publication number: 20230169408Abstract: A system, computer program product, and method are provided for distributed data workflow semantics. A pipeline, such as a machine learning (ML) pipeline, is implemented over a data flow graph (DFG) with nodes configured to support rich semantics. The rich semantics include two or more operational semantics, and at least one lineage semantic to selectively combine features that trace lineage to a common input object. The lineage semantic is leveraged to associate training and testing data set pairs in cross validation of the trained ML models produced from parallelizing the selection of ML pipelines.Type: ApplicationFiled: November 30, 2021Publication date: June 1, 2023Applicant: International Business Machines CorporationInventors: Carlos Henrique Andrade Costa, RAGHU KIRAN GANTI, MUDHAKAR SRIVATSA, Linsong Chu, Joshua M. Rosenkranz, Tuan Minh HOANG TRONG
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Publication number: 20230153489Abstract: Systems and methods for semi-discrete modeling of delamination migration in composite laminate materials are disclosed. An example method includes receiving a specimen geometry and a specimen stacking sequence. The example method also includes creating a finite-element (FE) mesh that defines a composite laminate material by: generating, using a mesh generation tool, a plurality of plies shaped according to the specimen geometry, and connecting the plies together based on the stacking sequence by placing cohesive elements between each adjacent pair of plies. The example method also includes determining a predicted mechanical response of the composite laminate material by: generating a constitutive model corresponding to the composite laminate material based on the FE mesh, and inputting a strain value to the constitutive model to generate the predicted mechanical response.Type: ApplicationFiled: November 15, 2022Publication date: May 18, 2023Inventors: Minh Hoang Nguyen, Anthony M. Waas
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Patent number: 11532086Abstract: Systems and methods that facilitate determining interaction between medications and the brain using a brain measure and a brain model. Hidden nervous system states are difficult to predict, diagnose, and treat with therapeutic medications. A Dual Neural Machine Translation (d-NMT) algorithmic system that utilizes sets of parameters for a relapsing-remitting MS model based on patient medical records and adjusts a method of parameterization to produce a model that can match patients' medical records and medical images. These parameters are can be used by a therapeutic determining model to recommend therapies, doses, and time courses accurately.Type: GrantFiled: February 20, 2020Date of Patent: December 20, 2022Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: James R Kozloski, Viatcheslav Gurev, Tuan Minh Hoang Trong, Adamo Ponzi
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Patent number: 11514238Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).Type: GrantFiled: August 5, 2020Date of Patent: November 29, 2022Assignee: Docugami, Inc.Inventors: Andrew Paul Begun, Steven DeRose, Taqi Jaffri, Luis Marti Orosa, Michael Palmer, Jean Paoli, Christina Pavlopoulou, Elena Pricoiu, Swagatika Sarangi, Marcin Sawicki, Manar Shehadeh, Michael Taron, Bhaven Toprani, Zubin Rustom Wadia, David Watson, Eric White, Joshua Yongshin Fan, Kush Gupta, Andrew Minh Hoang, Zhanlin Liu, Jerome George Paliakkara, Zhaofeng Wu, Yue Zhang, Xiaoquan Zhou
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Publication number: 20220369644Abstract: An antimicrobial solution for a medical device having a chamber defined by a wall, the chamber being configured to be includes water, and an amount of iodine in the water sufficient to generate free elemental iodine when introduced into the chamber of the medical device. The free elemental iodine is configured to diffuse through the wall of the chamber and/or be embedded in the wall of the chamber of the medical device to form an antimicrobial polymer on the wall of the chamber.Type: ApplicationFiled: April 2, 2022Publication date: November 24, 2022Inventors: Minh HOANG, Bryan Garrett DAVIS
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Patent number: 11507740Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).Type: GrantFiled: August 5, 2020Date of Patent: November 22, 2022Assignee: Docugami, Inc.Inventors: Andrew Begun, Steven DeRose, Taqi Jaffri, Luis Marti Orosa, Michael Palmer, Jean Paoli, Christina Pavlopoulou, Elena Pricoiu, Swagatika Sarangi, Marcin Sawicki, Manar Shehadeh, Michael Taron, Bhaven Toprani, Zubin Rustom Wadia, David Watson, Eric White, Joshua Yongshin Fan, Kush Gupta, Andrew Minh Hoang, Zhanlin Liu, Jerome George Paliakkara, Zhaofeng Wu, Yue Zhang, Xiaoquan Zhou
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Publication number: 20220245335Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).Type: ApplicationFiled: April 20, 2022Publication date: August 4, 2022Inventors: Andrew Paul Begun, Steven DeRose, Taqi Jaffri, Luis Marti Orosa, Michael B. Palmer, Jean Paoli, Christina Pavlopoulou, Elena Pricoiu, Swagatika Sarangi, Marcin Sawicki, Manar Shehadeh, Michael Taron, Bhaven Toprani, Zubin Rustom Wadia, David Watson, Eric White, Joshua Yongshin Fan, Kush Gupta, Andrew Minh Hoang, Zhanlin Liu, Jerome George Paliakkara, Zhaofeng Wu, Yue Zhang, Xiaoquan Zhou
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Patent number: 11392763Abstract: Machine learning, artificial intelligence, and other computer-implemented methods are used to identify various semantically important chunks in documents, automatically label them with appropriate datatypes and semantic roles, and use this enhanced information to assist authors and to support downstream processes. Chunk locations, datatypes, and semantic roles can often be automatically determined from what is here called “context”, to wit, the combination of their formatting, structure, and content; those of adjacent or nearby content; overall patterns of occurrence in a document, and similarities of all these things across documents (mainly but not exclusively among documents in the same document set).Type: GrantFiled: August 5, 2020Date of Patent: July 19, 2022Assignee: DOCUGAMI, INC.Inventors: Andrew Paul Begun, Steven DeRose, Taqi Jaffri, Luis Marti Orosa, Michael Palmer, Jean Paoli, Christina Pavlopoulou, Elena Pricoiu, Swagatika Sarangi, Marcin Sawicki, Manar Shehadeh, Michael Taron, Bhaven Toprani, Zubin Rustom Wadia, David Watson, Eric White, Joshua Yongshin Fan, Kush Gupta, Andrew Minh Hoang, Zhanlin Liu, Jerome George Paliakkara, Zhaofeng Wu, Yue Zhang, Xiaoquan Zhou
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Patent number: 11372113Abstract: Methods, non-transitory computer readable medium and devices that initiating determination of navigation with an initial heading while in motion and without waiting for a stationary phase. Ongoing position-dependent data and/or velocity-dependent data of an object is/are received from a Global Navigation Satellite System (GNSS) receiver system or a position fixing system and from an inertial measurement unit (IMU). A weight associated with each of a plurality of filters is iteratively determined in an adaptive estimation model based on a match between position data and velocity data for each of the plurality of the filters conditioned by filter heading data for each of the plurality of the filters and the ongoing obtained position data and the velocity data of the object.Type: GrantFiled: April 17, 2020Date of Patent: June 28, 2022Assignee: Orolia USA Inc.Inventor: Gia Minh Hoang
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Publication number: 20210325546Abstract: Methods, non-transitory computer readable medium and devices that initiating determination of navigation with an initial heading while in motion and without waiting for a stationary phase. Ongoing position-dependent data and/or velocity-dependent data of an object is/are received from a Global Navigation Satellite System (GNSS) receiver system or a position fixing system and from an inertial measurement unit (IMU). A weight associated with each of a plurality of filters is iteratively determined in an adaptive estimation model based on a match between position data and velocity data for each of the plurality of the filters conditioned by filter heading data for each of the plurality of the filters and the ongoing obtained position data and the velocity data of the object.Type: ApplicationFiled: April 17, 2020Publication date: October 21, 2021Inventor: Gia Minh Hoang
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Publication number: 20210264603Abstract: Systems and methods that facilitate determining interaction between medications and the brain using a brain measure and a brain model. Hidden nervous system states are difficult to predict, diagnose, and treat with therapeutic medications. A Dual Neural Machine Translation (d-NMT) algorithmic system that utilizes sets of parameters for a relapsing-remitting MS model based on patient medical records and adjusts a method of parameterization to produce a model that can match patients' medical records and medical images. These parameters are can be used by a therapeutic determining model to recommend therapies, doses, and time courses accurately.Type: ApplicationFiled: February 20, 2020Publication date: August 26, 2021Inventors: James R Kozloski, Viatcheslav Gurev, Tuan Minh Hoang Trong, Adamo Ponzi