Ihor R. Lemischka - Princeton NJ, US Christoph Schaniel - Princeton NJ, US Feng Li - Plainsboro NJ, US Xenla Schafer - Princeton NJ, US Patrick J. Paddison - Oyster Bay NY, US
Assignee:
The Trustees of the University of Princeton - Princeton University - Princeton NJ
International Classification:
C07H 21/04 A01N 63/00 C12N 15/74
US Classification:
536 231, 4353201, 424 932, 424 9321
Abstract:
The present invention relates to methods and compositions for assaying embryonic stem cell maintenance. In particular, the present invention provides reporter constructs for stem cell pluripotency and differentiation and cells and organisms containing such constructs.
A Shock absorbing support system isolates vibrations that would otherwise pass through the important instrument mounted on the vibration source. The isolation includes springs and dampers under the bottom of the instrument while dampers around tops of the instrument. The combination of the springs and the dampers results in a dissipation of kinetic energy caused by vibrations that would otherwise pass through the instrument and cause significant dynamic load and damages to the support and the instrument.
Stereo-Image Quality And Disparity/Depth Indications
Izzat Izzat - Plainsboro NJ, US Feng Li - Newark DE, US
Assignee:
THOMSON LICENSING - ISSY LES MOULINEAUX
International Classification:
H04N 13/04 H04N 13/02
US Classification:
348 47, 348 54, 348E13026, 348E13074
Abstract:
A variety of implementations are described. At least one implementation modifies one or more images from a stereo-image pair in order to produce a new image pair that has a different disparity map. The new disparity map satisfies a quality condition that the disparity of the original image pair did not. In one particular implementation, a first image and a second image that form a stereo image pair are accessed. A disparity map is generated for a set of features from the first image that are matched to features in the second image. The set of features is less than all features in the first image. A quality measure is determined based on disparity values in the disparity map. The first image is modified, in response to the determined quality measure, such that disparity for the set of features in the first image is also modified.
Automatic Demand-Driven Resource Scaling For Relational Database-As-A-Service
- Redmond WA, US Feng LI - Bellevue WA, US Vivek NARASAYYA - Redmond WA, US Arnd Christian KÖNIG - Kirkland WA, US
International Classification:
G06Q 10/06 G06F 11/34 G06F 16/21
Abstract:
Architecture that enables a Database-as-a-Service (DaaS) to auto-scale container sizes on behalf of tenants. An abstraction is provided that enables tenants to reason about monetary budget and query latency, rather than resource provisioning. An auto-scaling module automatically determines a container size for a subsequent billing interval based on telemetry that comprises latencies (e.g., waits), resource utilizations, and available budget, for example. A set of robust signals are derived from database engine telemetry and combined to significantly improve accuracy of resource demand estimation for database workloads. In a more specific implementation, resource demands can be estimated for arbitrary SQL (structured query language) workloads in a relational database management system (RDBMS).
- Redmond WA, US Feng Li - Bellevue WA, US Manoj A. Syamala - Issaquah WA, US Vivek R. Narasayya - Redmond WA, US
International Classification:
G06F 15/173 G06F 12/02 G06F 3/06
Abstract:
A server system may include a cluster of multiple computers that are networked for high-speed data communications. Each of the computers has a remote direct memory access (RDMA) network interface to allow high-speed memory sharing between computers. A relational database engine of each computer is configured to utilize a hierarchy of memory for temporary storage of working data, including in order of decreasing access speed (a) local main memory, (b) remote memory accessed via RDMS, and (c) mass storage. The database engine uses the local main memory for working data, and additionally uses the RDMA accessible memory for working data when the local main memory becomes depleted. The server system may include a memory broker to which individual computers report their available or unused memory, and which leases shared memory to requesting computers.
Automatic Demand-Driven Resource Scaling For Relational Database-As-A-Service
- Redmond WA, US Feng Li - Bellevue WA, US Vivek Narasayya - Redmond WA, US Arnd Christian König - Kirkland WA, US
Assignee:
MICROSOFT CORPORATION - Redmond WA
International Classification:
G06Q 10/06 G06Q 20/14
Abstract:
Architecture that enables a Database-as-a-Service (DaaS) to auto-scale container sizes on behalf of tenants. An abstraction is provided that enables tenants to reason about monetary budget and query latency, rather than resource provisioning. An auto-scaling module automatically determines a container size for a subsequent billing interval based on telemetry that comprises latencies (e.g., waits), resource utilizations, and available budget, for example. A set of robust signals are derived from database engine telemetry and combined to significantly improve accuracy of resource demand estimation for database workloads. In a more specific implementation, resource demands can be estimated for arbitrary SQL (structured query language) workloads in a relational database management system (RDBMS).
Jun 2013 to 2000 Senior Algorithm EngineerMitsubishi Electric Research Labs Cambridge, MA Nov 2011 to Jun 2013 Adjunct Member Research ScientistUniversity of Delaware Newark, DE Aug 2006 to Oct 2011 Research AssistantMitsubishi Electric Research Labs Cambridge, MA Jun 2011 to Aug 2011 Research InternThomson Corporate Research Princeton, NJ Feb 2009 to May 2009 Research Intern, TechnicolorMicrosoft Research Asia
Jul 2008 to Oct 2008 Research InternPacific Research & Development Ltd
Apr 2006 to Jul 2006 Technical Marketing Engineer, Intel AsiaIntel China Software Center
Sep 2005 to Mar 2006 Software Engineering Intern
Education:
University of Delaware Newark, DE Sep 2011 Ph.D. in Computer ScienceShanghai Jiao Tong University Mar 2006 M.EFuzhou University Jul 2003 B.E. in Electrical Engineering
Aug 2011 to 2000 Research Assistant, Missouri S&TSinopec Shengli Oilfield Company
Sep 2009 to Mar 2011 Software engineerVictorySoft Co., Ltd
Jun 2009 to Aug 2009 Summer Intern as software engineerQilu Software Design Competition
Jun 2006 to Aug 2006 Software developer
Education:
China University of Petroleum Qingdao, CN Jul 2011 M.S. in Computer EngineeringQilu Univ. of Technology Jinan, CN Jul 2008 B.S. in Science and TechnologyMissouri Univ. of Science and Technology Rolla, MO Ph.D. in Computer Science
Aug 2007 to 2000 Graduate Research AssistantTsinghua University
Aug 2005 to May 2007 Graduate Research Assistant
Education:
Georgia Institute of Technology Atlanta, GA 2007 to 2012 Ph.D. in TransportationTsinghua University 2007 M.S. in Civil EngineeringTsinghua University 2001 to 2005 B.S. in Civil Engineering
Medical School Tufts University School of Medicine Graduated: 2002
Description:
Dr. Li graduated from the Tufts University School of Medicine in 2002. He works in Tyler, TX and specializes in Gastroenterology. Dr. Li is affiliated with Mother Francis Hospital.
Baidu - Sofeware Development Engineer (2011) Alstom China Technology Center - Sofeware Development Engineer (2009-2011) EMC R&D Center - Sofeware Development Engineer Intern (2008-2008)
Education:
Fudan University - Master, Computer Science, National University of Singapore - Research Assistant, Sichuan University - Computer Science
Tagline:
To be or not to be
Feng Li
Work:
Nanyang Technological University - PhD Student
Education:
Nanyang Technological University - Computer Engineering, Shandong University - Computer Science and Technology, Shandong Normal University - Computer Science and Technology