Patents by Inventor Lijuan Luo

Lijuan Luo 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).

  • Deep learning based identification of difficult to test nodes
    Patent number: 11574097
    Abstract: Techniques to improve the accuracy and speed for detection and remediation of difficult to test nodes in a circuit design netlist. The techniques utilize improved netlist representations, test point insertion, and trained neural networks.
    Type: Grant
    Filed: April 15, 2021
    Date of Patent: February 7, 2023
    Assignee: NVIDIA CORP.
    Inventors: Harbinder Sikka, Kaushik Narayanun, Lijuan Luo, Karthikeyan Natarajan, Manjunatha Gowda, Sandeep Gangundi
  • DEEP LEARNING BASED IDENTIFICATION OF DIFFICULT TO TEST NODES
    Publication number: 20210295169
    Abstract: Techniques to improve the accuracy and speed for detection and remediation of difficult to test nodes in a circuit design netlist. The techniques utilize improved netlist representations, test point insertion, and trained neural networks.
    Type: Application
    Filed: April 15, 2021
    Publication date: September 23, 2021
    Applicant: NVIDIA Corp.
    Inventors: Harbinder Sikka, Kaushik Narayanun, Lijuan Luo, Karthikeyan Natarajan, Manjunatha Gowda, Sandeep Gangundi
  • Deep learning based identification of difficult to test nodes
    Patent number: 11010516
    Abstract: Techniques to improve the accuracy and speed for detection and remediation of difficult to test nodes in a circuit design netlist. The techniques utilize improved netlist representations, test point insertion, and trained neural networks.
    Type: Grant
    Filed: August 9, 2019
    Date of Patent: May 18, 2021
    Assignee: NVIDIA Corp.
    Inventors: Harbinder Sikka, Kaushik Narayanun, Lijuan Luo, Karthikeyan Natarajan, Manjunatha Gowda, Sandeep Gangundi
  • FUNGICIDAL FERTILIZER COMPOSITION COMPRISING POTASSIUM PHOSPHITE AND GAMMA-POLY-GLUTAMIC ACID
    Publication number: 20210078917
    Abstract: A fungicidal fertilizer composition is provided, which has active ingredients compromising ?-poly-glutamic acid and potassium phosphite. A method for preparing the composition and use thereof are further provided. Experimental results indicate that the composition promotes crop health, improves crop yield, prevents and controls crop diseases.
    Type: Application
    Filed: September 10, 2018
    Publication date: March 18, 2021
    Applicant: JIANGSU HUIFENG BIO AGRICULTURE CO., LTD.
    Inventors: Hangen ZHONG, Hongjin JI, Shaojie TAI, Lijuan LUO
  • COMPOSITE FERTILIZER CONTAINING MAGNESIUM AMMONIUM PHOSPHATE AND POLYGLUTAMIC ACID
    Publication number: 20210017094
    Abstract: A composite fertilizer containing magnesium ammonium phosphate and polyglutamic acid. A weight ratio of the polyglutamic acid to the magnesium ammonium phosphate is 1:100 to 10000, preferably 1:200 to 8000. An experimental result indicates that the composite fertilizer can well regulate the growth of crops, improve the disease resistance and stress tolerance, promote the healthy effect of the crops, and increase the yield of the crops.
    Type: Application
    Filed: February 2, 2019
    Publication date: January 21, 2021
    Applicant: JIANGSU HUIFENG BIO AGRICULTURE CO., LTD.
    Inventors: Hangen ZHONG, Hongjin JI, Ming ZHANG, Lijuan LUO, Ying WANG, Ying WANG, Jianfeng WEI
  • Deep learning testability analysis with graph convolutional networks
    Patent number: 10657306
    Abstract: Techniques to improve the accuracy and speed for detection and remediation of difficult to test nodes in a circuit design netlist. The techniques utilize improved netlist representations, test point insertion, and trained neural networks.
    Type: Grant
    Filed: July 24, 2019
    Date of Patent: May 19, 2020
    Assignee: NVIDIA Corp.
    Inventors: Yuzhe Ma, Haoxing Ren, Brucek Khailany, Harbinder Sikka, Lijuan Luo, Karthikeyan Natarajan
  • DEEP LEARNING BASED IDENTIFICATION OF DIFFICULT TO TEST NODES
    Publication number: 20200151289
    Abstract: Techniques to improve the accuracy and speed for detection and remediation of difficult to test nodes in a circuit design netlist. The techniques utilize improved netlist representations, test point insertion, and trained neural networks.
    Type: Application
    Filed: August 9, 2019
    Publication date: May 14, 2020
    Applicant: NVIDIA Corp.
    Inventors: Harbinder Sikka, Kaushik Narayanun, Lijuan Luo, Karthikeyan Natarajan, Manjunatha Gowda, Sandeep Gangundi
  • Deep Learning Testability Analysis with Graph Convolutional Networks
    Publication number: 20200151288
    Abstract: Techniques to improve the accuracy and speed for detection and remediation of difficult to test nodes in a circuit design netlist. The techniques utilize improved netlist representations, test point insertion, and trained neural networks.
    Type: Application
    Filed: July 24, 2019
    Publication date: May 14, 2020
    Applicant: NVIDIA Corp.
    Inventors: Yuzhe Ma, Haoxing Ren, Brucek Khailany, Harbinder Sikka, Lijuan Luo, Karthikeyan Natarajan
  • BREAKWATER
    Publication number: 20100215435
    Abstract: A breakwater, in which the surface thereof facing the sea (H) is a curved surface rendering the cross section of the breakwater a trapezoid with curved side (ABCDEFG) which comprises a shorter top side (EF), a longer bottom side (AG), and a curved side (ABCDE) facing the sea (H). The curve profile is similar to a recumbent concaved-up parabola.
    Type: Application
    Filed: April 7, 2008
    Publication date: August 26, 2010
    Inventors: Gushi Luo, Lijuan Luo