Li Zhou

7958094, Jun 7, 2011

Jun 25, 2008

12/145814

Daniel Edward Grack - Fountain Valley CA, US
Lauren Anne Mayes - Laguna Beach CA, US
Bao Quoc Vu - Mission Viejo CA, US
Li Zhou - Irvine CA, US

International Business Machines Corporation - Armonk NY

G06F 7/00
G06F 17/30

707662, 707692, 707754

A method and system for the management of deletion requests for related documents in a content management system. When a user requests to delete a related document associated with a record in the content management system, the request determines whether there are other documents associated with the record, collects the documents and determines if any of the collected documents are parent documents, removes the association between each collected document and the record, and initiates a deletion process to delete the parent documents.

8326978, Dec 4, 2012

Feb 5, 2010

12/701137

Sunil Bharadwaj - Beaverton OR, US
Stephen A. Byrd - San Jose CA, US
David L. Merbach - Rochester MN, US
Kevin J. Webster - Lake Worth FL, US
Li Zhou - San Jose CA, US

International Business Machines Corporation - Armonk NY

G06F 15/173

709224, 709223

The present disclosure provides techniques for updating fabric alert definitions defined for a fiber channel or other fabric-based network within a storage management system. One embodiment provides techniques for detecting fabric merges, fabric segmentations, and principal switch changes of the fabric and modifying fabric alert definitions as a result of these changes. Thus, any alert definitions scoped by fabric will remain relevant even after fabric structural changes, and duplicate and/or redundant alerts may be reduced within the storage management system. In a further embodiment, detection of fabric changes is performed by first storing relationships between fabrics and switches, and comparing the current relationships between the fabrics and the switches against the stored relationships. Upon recognition of changes within the fabrics, the fabric alert definitions may be automatically analyzed and updated.

20070032890, Feb 8, 2007

Mar 21, 2006

11/385065

Li Zhou - Cupertino CA, US
Eduardo Misawa - Stillwater OK, US

G05B 19/04

700063000, 700304000, 702113000

According to a preferred aspect of the instant invention, there is provided a system and method of robust vibration suppression which might be used in many subject matters, but which is preferably used in connection with computer controlled electromechanical devices such as disk drive arms. In a first preferred embodiment, a Gaussian waveform is selected as a velocity profile, with its integral and derivatives providing position and acceleration/jerk profiles respectively. According to another preferred embodiment, the movement velocity profile will be selected to be a member of the prolate spheroid family of waveforms. This family of functions has certain optimal properties with respect to the frequency domain concentration of energy for a given time-domain length time series. The movement of a flexible arm that is performed according to the invention will be one that has minimal or reduced residual vibration after it has reached its destination.

20130163436, Jun 27, 2013

Dec 4, 2012

13/693291

International Business Machines Corporation - Armonk NY, US
Stephen A. Byrd - San Jose CA, US
David L. Merbach - Rochester MN, US
Kevin J. Webster - Lake Worth FL, US
Li Zhou - San Jose CA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

H04L 12/24

370241

For automatic updates to fabric alert definitions, a method monitors fabric alert definitions defined for a storage area network having a plurality of switches and a plurality of fabrics. The fabric alert definitions define alert conditions within the storage area network relevant to events occurring within one or more of the plurality of fabrics. The method further detects one or more changes to the plurality of fabrics by discovering relationships between each fabric and each switch within the storage area network and comparing current relationships against previous relationships. In addition, the method automatically modifies fabric alert definitions having a reference to changed fabrics responsive to detection of the one or more changes to the plurality of fabrics.

20220343336, Oct 27, 2022

Apr 22, 2021

17/237827

- Redmond WA, US
Li Zhou - Sunnyvale CA, US
Cheng Deng - Santa Clara CA, US
Yu Wang - Sunnyvale CA, US

G06Q 30/00
G06Q 10/10
G06N 20/00
G06F 17/18

Described herein is a technique for establishing an overall company-level confidence score based on analyzing data from various data sources. The overall score is derived using a machine learned model that takes as input a set of sub-scores, with each sub-score representing a measure of how frequently a domain name occurs within the same data record as a company name. The model used to combine the several sub-scores is trained using training data that includes a variety of sub-scores for company and domain names that have already been verified to be associated with one another.

20230004815, Jan 5, 2023

Jul 1, 2021

17/365803

- Northridge CA, US
Francesca Piccinini - Los Angeles CA, US
Li Zhou - Pasadena CA, US
Chi A Tran - Falcon Heights MN, US
Farhad Batmanghelich - San Jose CA, US
Juan Enrique Arguelles Morales - Los Angeles CA, US
Anuj M. Patel - Porter Ranch CA, US
Sarkis D. Aroyan - Northridge CA, US

G06N 3/08
A61B 5/145
A61B 5/00

An example method for calibrating a glucose sensor includes determining, by one or more processors, a set of electrical parameters for the glucose sensor of a plurality of glucose sensors and determining, by the one or more processors, a cluster for the glucose sensor based on the set of electrical parameters. Each cluster of the plurality of clusters identifies respective configuration information. In this example, the method includes configuring, by the one or more processors, the glucose sensor to determine a glucose level of a patient based on configuration information identified by the determined cluster.

20200234244, Jul 23, 2020

Jan 23, 2019

16/255195

Li Zhou - Sunnyvale CA, US
Chong Zhang - Mountain View CA, US
Andrew Walter Chimka - San Francisco CA, US
Kevin Chuang - San Francisco CA, US
Kumaresh Pattabiraman - Sunnyvale CA, US
Yixiao Lu - San Jose CA, US
Chen Qian - Fremont CA, US
George Pearman - Menlo Park CA, US

G06Q 10/10

Disclosed are systems, methods, and non-transitory computer-readable media for providing profiles with limited permission level functionality in the network. In response to receiving a request to post the new employment listing, a collaboration system updates a permission list of the employment listing to provide a first user account with an administrator permission level in relation to the employment listing. The administrator permission level provides a first function and a second function in relation to the employment listing. The collaboration system receives a request to tag a second user account to the employment listing and updates the permission list to provide the second user account with a limited permission level in relation to the employment listing. The limited permission level provides the second user account with permission to perform the first function in relation to the employment listing but does not provide permission to perform the second function.

20200202303, Jun 25, 2020

Dec 21, 2018

16/230079

- Redmond WA, US
Li Zhou - Sunnyvale CA, US
Andrew Walter Chimka - San Francisco CA, US
Kevin Chuang - San Francisco CA, US
Kumaresh Pattabiraman - Sunnyvale CA, US
Yixiao Lu - Sunnyvale CA, US
Nadeem Anjum - Santa Clara CA, US
George Pearman - Menlo Park CA, US
Hsiang Lin - Sunnyvale CA, US

G06Q 10/10
G06F 16/33
G06F 16/29
H04L 29/08

Disclosed are systems, methods, and non-transitory computer-readable media for identifying profiles in a network based on relevance scores. A relevancy system identifies a set of candidate user profiles based on user profiles that correspond to users that are members of a first organization. For each candidate user profile, the relevancy system determines scores indicating a relevance level of the respective candidate user profile to an employment listing based on multiple relevance categories. The relevancy system applies weights to the scores and determined a relevance score for the candidate user profile based on the weighted relevancy scores. The weighs are determined based on historical hiring data and indicate a relative impact of each relevance category on hiring. The relevancy system selects a subset of the candidate user profiles based on the relevance scores and transmits notifications regarding the employment listing to the subset of the candidate user profiles.