Mahesh Iyer Ramachandran

US Patent:

6711619, Mar 23, 2004

Filed:

Dec 15, 1999

Appl. No.:

09/464351

Inventors:

Bharath Chandramohan - Mountain View CA
Mahesh Ramachandran - San Jose CA

Assignee:

Hewlett-Packard Development Company, L.P. - Houston TX

International Classification:

G06F 1516

US Classification:

709229, 709203, 709219, 709231, 709232, 707 10

Abstract:

A method, system, and apparatus for distributing and using portions of a computer-based application over a network, such as the internet. The present embodiment executes streamed chunks of code associated with an application on demand by binary emulation. Therefore the present invention enables execution of applications on network-based computer systems thereby enabling flexible distribution and use of executable code over a network. By streaming the transmission of non-sequentially ordered code chunks the present embodiment enables overlapping of streaming and execution of code chunks and reduces network latency effects of the past. The present embodiment may also speculatively stream the code chunks associated with the application to further reduce network latency effects associated with transmission of the code chunks.

US Patent:

20210243069, Aug 5, 2021

Filed:

May 18, 2020

Appl. No.:

16/876723

Inventors:

- San Jose CA, US
Mahesh RAMACHANDRAN - San Jose CA, US
Bhanu Pratap SINGH - Fremont CA, US

Assignee:

OPSRAMP, INC. - San Jose CA

International Classification:

H04L 12/24
G06F 9/54
G06N 3/08
G06K 9/62

Abstract:

Alert correlation plays an important role in IT event management. It helps reduce the number of alerts that IT staff have to act upon. The disclosure describes a method, a computer program product that applies a machine driven deep learning model to effectively correlate alerts caused by a common root cause. In addition, this method of correlation provides the user the context of the root cause. Therefore, it helps the user to quickly identify, understand and resolve the problem thereby reducing the mean time to identification and resolution. Alerts that are caused by the same root cause therefor come together. In the machine learning world, language sequence models are doing very well on learning the sequence patterns between words. For example, the machine can learn the subtle difference between choice of words and the order of words in order to fake a person's writing. The disclosed embodiments use similar technology but apply it on IT resource and application monitoring alerts across private and public clouds to learn the alert's sequence pattern. Once the sequence model is trained with alert sequences, the model is fed with a stream of new alerts, the model then identifies the two or more alerts that are together or clustered. Clustered alerts are often caused by the same root cause and should be correlated as one unit of work to understand cause, impact and resolution.

US Patent:

20200033943, Jan 30, 2020

Filed:

Oct 2, 2019

Appl. No.:

16/591382

Inventors:

- San Diego CA, US
Mahesh RAMACHANDRAN - Santa Clara CA, US

International Classification:

G06F 3/01
G06K 9/00
G06F 3/147
G06F 3/0481
G06K 9/22

Abstract:

Methods and apparatus relating to enabling augmented reality applications using eye gaze tracking are disclosed. An exemplary method according to the disclosure includes displaying an image to a user of a scene viewable by the user, receiving information indicative of an eye gaze of the user, determining an area of interest within the image based on the eye gaze information, determining an image segment based on the area of interest, initiating an object recognition process on the image segment, and displaying results of the object recognition process.

US Patent:

20180253145, Sep 6, 2018

Filed:

May 2, 2018

Appl. No.:

15/969430

Inventors:

- San Diego CA, US
Mahesh RAMACHANDRAN - San Jose CA, US

International Classification:

G06F 3/01
G06K 9/00
G06F 3/147
G06K 9/22
G06F 3/0481
G06K 9/32

Abstract:

Methods and apparatus relating to enabling augmented reality applications using eye gaze tracking are disclosed. An exemplary method according to the disclosure includes displaying an image to a user of a scene viewable by the user, receiving information indicative of an eye gaze of the user, determining an area of interest within the image based on the eye gaze information, determining an image segment based on the area of interest, initiating an object recognition process on the image segment, and displaying results of the object recognition process.