Chung Yong Kim

54856574, Jan 23, 1996

May 11, 1994

8/240995

Chung B. Kim - Walnut Creek CA

A41F 100

24543

Four embodiments are disclosed of a garment-hanger clip having a central portion adapted to be received with a garment to be hung and manually bendable wing portions adapted to be manually bent into close confrontation with the opposite sides of the central portion in order to engage the garment with prongs raised on said central portion and to maintain the garment in engagement with those prongs.

20220293395, Sep 15, 2022

Mar 12, 2021

17/199729

- Santa Clara CA, US
Changhun LEE - San Jose CA, US
Kyeong-Tae LEE - Livermore CA, US
Chung Hoan KIM - San Jose CA, US
Youngmin SHIN - San Jose CA, US

H01J 37/32
G03F 7/42

A method for recovering ashing rate in a plasma processing chamber includes positioning a substrate in a processing volume of a processing chamber, wherein the substrate has a silicon chloride residue formed thereon. The method further includes evaporating the silicon chloride residue from the substrate. The method further includes depositing the evaporated silicon chloride on one or more interior surfaces in the processing volume. The method further includes exposing the deposited silicon chloride to an oxidizing environment to convert the deposited silicon chloride to a silicon oxide passivation layer. The oxidizing environment can comprise an oxygen-containing plasma, oxygen radicals, or a combination thereof

20230099334, Mar 30, 2023

Sep 30, 2021

17/491068

- Mountain View CA, US
Yu Zheng - Milpitas CA, US
Eamonn Michael Doherty - Mountain View CA, US
Brian Clair Williammee - Santa Cruz CA, US
Kevin Joseph Malta - San Francisco CA, US
Chung Eun Kim - San Mateo CA, US
Xu Dong - Sunnyvale CA, US

B60W 60/00
B60W 30/18
B60W 40/06
G06N 20/00

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a pull-over location using machine learning. One of the methods includes obtaining data specifying a target pull-over location for an autonomous vehicle travelling on a roadway. A plurality of candidate pull-over locations in a vicinity of the target pull-over location are identified. For each candidate pull-over location, an input that includes features of the candidate pull-over location is processed using a machine learning model to generate a respective likelihood score representing a predicted likelihood that the candidate pull-over location is an optimal location. The features of the candidate pull-over location include one or more features that compare the candidate pull-over location to the target pull-over location. Using the respective likelihood scores, one of the candidate pull-over locations is selected as an actual pull-over location for the autonomous vehicle.