Patents by Inventor Hamed AL-RAWESHIDY

Hamed AL-RAWESHIDY 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).

  • Patent number: 11950122
    Abstract: A device may receive software logs identifying raw data and may convert the raw data to a text format, to generate text data. The device may extract pre-log data from the text data and may remove files with less than a threshold quantity of lines from the text data to generate modified text data. The device may extract UE data from the modified text data and may decode RRC messages in the modified text data to generate decoded RRC messages. The device may extract marker data from the modified text data and may remove files associated with timestamps and test cases from the modified text data to generate further modified text data. The device may extract test case data from the further modified text data and may generate final data that includes the pre-log data, the UE data, the decoded RRC messages, the marker data, and the test case data.
    Type: Grant
    Filed: October 1, 2021
    Date of Patent: April 2, 2024
    Assignee: VIAVI Solutions Inc.
    Inventors: Sayed Taheri, Faris Muhammad, Hamed Al-Raweshidy, Srini Challa
  • Publication number: 20230419104
    Abstract: In some implementations, a device may obtain a training corpus, from a set of pre-processed log data, associated with an alphanumeric format. The device may encode the training corpus to obtain encoded data using a set of tokens. The device may calculate a sequence length based on a statistical parameter associated with the training corpus. The device may generate a set of input sequences and a set of target sequences based on the encoded data, where each input sequence and each target sequence has a length equal to the sequence length. The device may generate a training data set based on combining the set of input sequences and the set of target sequences. The device may train a deep neural network (DNN) using the training data set and based on one or more hyperparameters to obtain a set of embedding tensors associated with an embedding layer of the DNN.
    Type: Application
    Filed: June 28, 2022
    Publication date: December 28, 2023
    Inventors: Sayed TAHERI, Faris MUHAMMAD, Hamed AL-RAWESHIDY, Srini CHALLA
  • Publication number: 20230107148
    Abstract: A device may receive software logs identifying raw data and may convert the raw data to a text format, to generate text data. The device may extract pre-log data from the text data and may remove files with less than a threshold quantity of lines from the text data to generate modified text data. The device may extract UE data from the modified text data and may decode RRC messages in the modified text data to generate decoded RRC messages. The device may extract marker data from the modified text data and may remove files associated with timestamps and test cases from the modified text data to generate further modified text data. The device may extract test case data from the further modified text data and may generate final data that includes the pre-log data, the UE data, the decoded RRC messages, the marker data, and the test case data.
    Type: Application
    Filed: October 1, 2021
    Publication date: April 6, 2023
    Inventors: Sayed TAHERI, Faris MUHAMMAD, Hamed AL-RAWESHIDY, Srini CHALLA