Li I Zhou

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.

20120011200, Jan 12, 2012

Jul 5, 2011

13/176498

Xinyan Zhang - Nanjing, CN
Li Zhou - Bellevue WA, US

ROXBEAM MEDIA NETWORK CORPORATION - Beijing

G06F 15/16

709204

One embodiment of the present invention provides a peer-to-peer (P2P) data-storage system. The system includes a P2P network, a file upload module configured to receive a file uploaded by a user, a file processing module configured to disassemble the received file into a plurality of file blocks and select a plurality of peer nodes from the P2P network, and a file distribution module configured to distribute the file blocks to the selected peer nodes. A respective file block is distributed to a respective peer node.

59493453, Sep 7, 1999

May 27, 1997

8/863377

Richard D. Beckert - Lake Stevens WA
Mark M. Moeller - Des Moines WA
Li Zhou - Bellevue WA

Microsoft Corporation - Redmond WA

G08B 500

34081541

A vehicle computer system includes a display device that is configurable for viewing by a driver of a vehicle while the vehicle is moving. The display device is responsive to a processor that executes application programs in conjunction with an operating system. A plurality of sensors are used to indicate the position of the display device, to indicate vehicle motion, and to indicate the state of a chosen vehicle control such as a parking brake. Application programs open display windows in conjunction with the operating system. In opening a window, an application program can indicate whether the window will contain driving-related information. The operating system monitors the sensors and prevents the display of non-driving-related windows to the driver when the vehicle is in motion or when it has the potential for motion. Specifically, the operating system in such a situation hides any windows that have not been specified as being driving-related. Initially, all windows are assumed to contain non-driver related information; hence, they are hidden until it is determined what type of information they display.

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.

20210312260, Oct 7, 2021

Jul 4, 2017

16/316095

- Redmond WA, US
Baoxun WANG - Redmond WA, US
Shuang PENG - Redmond WA, US
Min ZENG - Redmond WA, US
Li ZHOU - Redmond WA, US

MICROSOFT TECHNOLOGY LICENSING, LLC - Redmond WA

G06N 3/04
G06F 40/30

Non-limiting examples of the present disclosure describe a convolutional neural network (CNN) architecture configured to evaluate conversational relevance of query-response pairs. A CNN model is provided that can include a first branch, a second branch, and multilayer perceptron (MLP) layers. The first branch includes convolutional layers with dynamic pooling to process a query. The second branch includes convolutional layers with dynamic pooling to process candidate responses for the query. The query and the candidate responses are processed in parallel using the CNN model. The MLP layers are configured to rank query-response pairs based on conversational relevance.

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.

20200005243, Jan 2, 2020

Jun 27, 2018

16/020640

- Redmond WA, US
Viman Deb - San Jose CA, US
Manish Baldua - San Jose CA, US
Shidong Yan - Newark CA, US
Li Zhou - Sunnyvale CA, US
Tao Zheng - Redwood City CA, US

Microsoft Technology Licensing, LLC - Redmond WA

G06Q 10/10
G06Q 10/06

The disclosed embodiments provide a system for processing data. During operation, the system stores, in a repository, a set of configurable rules for managing hiring workflows in an applicant tracking system, wherein each configurable rule in the set of configurable rules includes a trigger representing activity associated with an online network, a condition to be evaluated in response to the trigger, and an action to be performed when the condition is met. Next, the system matches recent activity associated with a candidate in an applicant tracking system to the trigger in a configurable rule from the repository. Next, the system evaluates the condition from the configurable rule using attributes associated with the candidate. When the condition is met by the attributes, the system automatically performs the action specified in the configurable rule to advance the candidate through the hiring workflow in the applicant tracking system.