Sigurd Wagner - Princeton NJ Yu Chen - Milpitas CA
Assignee:
The Trustees of Princeton University - Princeton NJ
International Classification:
H01L 2100
US Classification:
438154, 438151, 438153, 157 64, 157347
Abstract:
A p channel thin-film transistor (TFT) made of directly deposited microcrystalline silicon (uc-Si). The p TFT is integrated with its n channel counterpart on a single uc-Si film, to form a complementary metal-silicon oxide-silicon (CMOS) inverter of deposited uc-Si. The uc-Si channel material can be grown at lower temperatures by plasma-enhanced chemical vapor deposition in a process similar to the deposition. The p and n channels share the same uc-Si layer. The Figure shows the processing steps of manufacturing the TFT, where ( ) represents the uc-Si layer of the device.
Analytical Sensitivity Enhancement By Catalytic Transformation
A device and method for quantifying an impurity in an input gas stream. The device and method employ a catalyst to convert the impurity to a detectable species in an output gas stream, and the concentration of the detectable species is then measured by means of a detector.
Inverter Made Of Complementary P And N Channel Transistors Using A Single Directly-Deposited Microcrystalline Silicon Film
Sigurd Wagner - Princeton NJ, US Yu Chen - Pearland TX, US
International Classification:
H01L021/00 H01L021/84
US Classification:
438/154000
Abstract:
A p channel thin-film transistor (TFT) made of directly deposited microcrystalline silicon (c-Si). The p TFT is integrated with its n channel counterpart on a single c-Si film, to form a complementary metal-silicon oxide-silicon (CMOS) inverter of deposited c-Si. The c-Si channel material can be grown at lower temperatures by plasma-enhanced chemical vapor deposition in a process similar to the deposition of hydrogenated amorphous silicon. The p and n channels share the same c-Si layer.
Radio Access Network Control With Deep Reinforcement Learning
- Atlanta GA, US Wenjie Zhao - Princeton NJ, US Ganesh Krishnamurthi - Danville CA, US Huahui Wang - Bridgewater NJ, US Huijing Yang - Princeton NJ, US Yu Chen - Pittsburgh PA, US
International Classification:
G06N 3/08 G06N 3/04 H04W 24/08
Abstract:
A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.
Radio Access Network Control With Deep Reinforcement Learning
- Atlanta GA, US Wenjie Zhao - Princeton NJ, US Ganesh Krishnamurthi - Danville CA, US Huahui Wang - Bridgewater NJ, US Huijing Yang - Princeton NJ, US Yu Chen - Pittsburgh PA, US
International Classification:
G06N 3/08 G06N 3/04 H04W 24/08
Abstract:
A processing system including at least one processor may obtain operational data from a radio access network (RAN), format the operational data into state information and reward information for a reinforcement learning agent (RLA), processing the state information and the reward information via the RLA, where the RLA comprises a plurality of sub-agents, each comprising a respective neural network, each of the neural networks encoding a respective policy for selecting at least one setting of at least one parameter of the RAN to increase a respective predicted reward in accordance with the state information, and where each neural network is updated in accordance with the reward information. The processing system may further determine settings for parameters of the RAN via the RLA, where the RLA determines the settings in accordance with selections for the settings via the plurality of sub-agents, and apply the plurality of settings to the RAN.
Methods And Systems For Controlling The Shear Modulus Of Genomic Length Dsdna Molecules
Ezra S. ABRAMS - Newton MA, US Christian T. BOLES - Bedford MA, US Yu CHEN - Princeton NJ, US James STURM - Priceton NJ, US Robert AUSTIN - Princeton NJ, US - Beverly MA, US - Princeton NJ, US
International Classification:
B01L 3/00 G01N 27/447 G01N 15/14 C12Q 1/68
Abstract:
In some embodiments, a method for manipulating DNA molecules for use in a microfluidic device is provided, where the method may comprise providing a solution of a plurality of DNA molecules having a first radius of gyration under under a zero flow velocity, and maintaining the DNA molecules in a spherical shape under a flow velocity.
- Richmond VA, US - Princeton NJ, US - Baltimore MD, US Robert H. AUSTIN - Princeton NJ, US Joseph D'SILVA - Princeton NJ, US Yu CHEN - Princeton NJ, US
International Classification:
B01L 3/00 G01N 33/50 G01N 33/483
Abstract:
Described herein are improved microfluidic devices and methods for processing cells that can improve cell quality, streamline workflows, and lower costs. Applications include research and clinical diagnostics in cancer, infectious disease, and inflammatory disease, among other disease areas.
- Redmond WA, US Toby H. Walker - Wayne PA, US Zijian Zheng - Shoreline WA, US Yu Chen - Redmond WA, US Robert C. Wang - Redmond WA, US
Assignee:
Microsoft Technology Licensing, LLC - Redmond WA
International Classification:
G06F 17/30
Abstract:
The ranking quality of a ranked list may be evaluated. In an example embodiment, a method is implemented by a system to access log data, ascertain which entries of a ranked list are skipped, and determine a ranking quality metric from the skipped entries. More specifically, log data that reflects user interactions with a ranked list having multiple entries is accessed. The user interactions include at least indications of which of the multiple entries are selected entries. It is ascertained which entries of the multiple entries of the ranked list are skipped entries based on the selected entries. The ranking quality metric for the ranked list is determined responsive to the skipped entries.
Montefiore Medical Center Physical Medicine 111 E 210 St STE G78, Bronx, NY 10467 (718)9204133 (phone), (718)9202289 (fax)
Childrens Physicians Of Westchester 4350 Van Cortlandt Park E, Bronx, NY 10470 (347)2266437 (phone), (347)2266438 (fax)
John A Coleman School 317 North St, White Plains, NY 10605 (914)5974071 (phone), (914)3971765 (fax)
Education:
Medical School China Med Univ, Shenyang City, Liaoning, China Graduated: 1988
Procedures:
Neurological Testing Physical Medicine and Rehabilitation, Tests and Measurements Physical Therapy Evaluation
Languages:
English Spanish
Description:
Dr. Chen graduated from the China Med Univ, Shenyang City, Liaoning, China in 1988. She works in White Plains, NY and 2 other locations and specializes in Physical Medicine & Rehabilitation. Dr. Chen is affiliated with Montefiore Medical Center and Westchester Medical Center.
Dr. Chen graduated from the Taipei Med Coll, Taipei, Taiwan (385 04 Prior 1/71) in 1979. He works in Anaheim, CA and specializes in Family Medicine. Dr. Chen is affiliated with Kaiser Permanente Orange County Anaheim Medical Center.
Rush University Cancer Center 1725 W Harrison St STE 1010, Chicago, IL 60612 (312)9425904 (phone), (312)9423192 (fax)
Education:
Medical School Albert Einstein College of Medicine at Yeshiva University Graduated: 2010
Languages:
English Polish Spanish
Description:
Dr. Chen graduated from the Albert Einstein College of Medicine at Yeshiva University in 2010. She works in Chicago, IL and specializes in Radiation Oncology. Dr. Chen is affiliated with Rush University Medical Center.
Nov 2014 to 2000 Quantitative Analyst InternPriced a European
Feb 2014 to May 2014University Residences Tutoring Services, The Ohio State University Columbus, OH Sep 2010 to Dec 2012 TutorChina, Ltd Shenzhen, CN Jun 2012 to Aug 2012 Actuarial Analyst Intern
Education:
The State University of New Jersey New Brunswick, NJ Sep 2013 MS in FinanceThe Ohio State University Columbus, OH Apr 2000 to Sep 2009 BS in Mathematics