-
161.
公开(公告)号:US11655564B2
公开(公告)日:2023-05-23
申请号:US16506062
申请日:2019-07-09
Inventor: Sang Ouk Kim , Taeyeong Yun , In Ho Kim , Hong Ju Jung
CPC classification number: D01F9/145 , D01G13/00 , D10B2101/12 , D10B2401/16
Abstract: Provided are a graphene-based fiber in which a liquid-crystalline aromatic compound is intercalated into a graphene-based material, a graphene-based carbon fiber obtained by carbonizing the graphene-based fiber, and a method of manufacturing the same.
-
162.
公开(公告)号:US20230154069A1
公开(公告)日:2023-05-18
申请号:US18054794
申请日:2022-11-11
Inventor: JongChul YE , Hyungjin CHUNG
CPC classification number: G06T11/006 , G06T5/002 , G06T2207/20084 , G06T2207/20081
Abstract: A magnetic resonance imaging (MRI) recovery method using a score-based diffusion model and an apparatus thereof are provided. The MRI recovery method using the score-based diffusion model, which is performed by a computer, is implemented, including training a continuous time-dependent score function with denoising score matching and sampling data from a conditional distribution given the measurements, leveraging the learned score function, and recovering an image.
-
公开(公告)号:US20230153993A1
公开(公告)日:2023-05-18
申请号:US17557010
申请日:2021-12-20
Inventor: Kyoung Gyun LEE , Seok Jae LEE , Nam Ho BAE , Dong Gee RHO , Tae Jae LEE , Moon Keun LEE , Yoo Min PARK
CPC classification number: G06T7/0012 , H04N5/2256 , C12Q1/686 , B01L7/52 , G06T2207/30072 , G06T2207/20084 , G06T2207/30242 , B01L2300/18
Abstract: A method for providing quantitative information for targets and a device using the same according to an exemplary embodiment of the present disclosure are provided. A quantitative information providing method for targets according to the exemplary embodiment of the present disclosure includes flowing a plurality of microdroplets into a chamber or a channel including a detection region acquiring a single layer of microdroplets in which the plurality of microdroplets is present as a single layer, and providing quantitative data of targets based on the single layer image of the microdroplets, and the detection region has a height which is one time to about two times of a diameter of the plurality of microdroplets and is defined as a region in which the plurality of microdroplets is dispersed in a plurality of columns to fill the detection region.
-
164.
公开(公告)号:US20230153598A1
公开(公告)日:2023-05-18
申请号:US17976945
申请日:2022-10-31
Inventor: Yang-Kyu CHOI , Inkyu PARK , Joon-Kyu HAN , Mingu KANG
Abstract: The present disclosure relates to a gas-responsive neuron module including a resistive gas sensor for sensing gaseous molecules and converting the sensed gaseous molecules into an electrical signal, and a single transistor neuron composed of a source, a drain, and a gate, and a gas sensing system for sensing gas including the same, for implementing a high-integration and low-power neuromorphic electronic nose.
-
165.
公开(公告)号:US20230150813A1
公开(公告)日:2023-05-18
申请号:US18056291
申请日:2022-11-17
Inventor: Jeung Ku KANG , Min Gyu PARK , Jong Hui CHOI , Dong Won KIM
CPC classification number: C01B3/0063 , B82Y30/00 , B82Y40/00 , C01B3/0084 , C01B3/0094
Abstract: The present disclosure relates to a composite for hydrogen storage formed through lithiation and a method of preparing the same.
-
公开(公告)号:US20230149915A1
公开(公告)日:2023-05-18
申请号:US16970682
申请日:2020-05-29
Inventor: Hyunjoo LEE , Gihun KWON
CPC classification number: B01J37/00 , C07C2/84 , B01J23/63 , B01J6/001 , C07C2523/63
Abstract: Disclosed are: a catalyst for oxidative coupling of methane, the catalyst comprising palladium supported on a cerium palladium solid solution; and a method for oxidative coupling using the same, wherein highly oxidative Pd/CePdO and CePdO catalysts can be used in the production of C2 hydrocarbon compounds through oxidative coupling of methane, hereinafter OCM) at low temperatures.
-
公开(公告)号:US11651214B2
公开(公告)日:2023-05-16
申请号:US16764677
申请日:2018-11-13
Inventor: Hyun Soo Choi , Chang D. Yoo , Sung Hun Kang , Jun Yeong Kim , Sung Jin Kim
CPC classification number: G06N3/08 , G06F18/217 , G06N3/045 , G06N20/20
Abstract: An artificial intelligence (AI) system capable of simulating functions of a human brain, such as recognition and judgment, by using the machine learning algorithm such as deep learning, and an application thereof are provided. A method of learning multi-modal data according to the AI system and an application thereof includes: obtaining first context information representing a characteristic of a first signal and second context information representing a characteristic of a second signal by using a first learning network model; obtaining hidden layer information based on the first context information and the second context information by using a second learning network model; obtaining a correlation value representing a relation degree between the hidden layer information by using the second learning network model; and learning the hidden layer information in which the correlation value is derived as a maximum value.
-
公开(公告)号:US11649517B2
公开(公告)日:2023-05-16
申请号:US16083713
申请日:2017-09-20
Inventor: Changheui Jang , Hyunmyung Kim , Gokul Obulan Subramanian , Jin Woo Heo , Ho Jung Lee , Sunghoon Hong , Chaewon Kim
IPC: C21D9/46 , C21D6/00 , C21D8/02 , C22C38/02 , C22C38/04 , C22C38/06 , C22C38/48 , C22C38/50 , C22C38/18
CPC classification number: C21D9/46 , C21D6/004 , C21D8/0205 , C21D8/0226 , C21D8/0236 , C21D8/0263 , C22C38/02 , C22C38/04 , C22C38/06 , C22C38/18 , C22C38/48 , C22C38/50 , C21D2211/001 , C21D2211/004 , C21D2211/005
Abstract: The present disclosure relates to a high-strength Fe—Cr—Al—Ni multiplex stainless steel and a manufacturing method therefor. The multiplex stainless steel comprises 35 to 67 wt % of iron (Fe), 13 to 30 wt % of chrome (Cr), 15 to 30 wt % of nickel (Ni), and 5 to 15 wt % of aluminum (Al) and has a multiplex structure in which an austenite phase accounting for high ductility, a ferrite phase accounting for high strength, and an NiAl(B2) phase providing both strength and high-temperature steam oxidation resistance, exist in combination. The multiplex stainless steel can secure necessary fabricability and mechanical strength even if for/in a thin state, can maintain integrity as a structural member in a normal operation condition of a light-water reactor thanks to the formation of a chrome oxide layer thereon, and can form a stable oxide layer including alumina under a high-temperature steam environment, which is plausible in a high-temperature nuclear accident, thereby providing exceptionally improved resistance to serious accidents.
-
169.
公开(公告)号:US20230142820A1
公开(公告)日:2023-05-11
申请号:US17969006
申请日:2022-10-19
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Yang-Kyu CHOI , Joon-Kyu HAN
IPC: G06N3/063
CPC classification number: G06N3/063
Abstract: According to an embodiment of the present disclosure, a neuron circuit may be provided. The neuron circuit includes a biristor that includes a collector electrode receiving a constant input current from a first synapse circuit and an emitter electrode connected with a ground and outputs a collector signal through the collector electrode, and a voltage divider that is enabled by the collector signal, performs voltage division on an operating voltage by using values of resistances included therein, and outputs an output voltage corresponding to a result of the voltage division to a second synapse circuit.
-
公开(公告)号:US11645508B2
公开(公告)日:2023-05-09
申请号:US16002614
申请日:2018-06-07
Inventor: Sungju Hwang , Haebum Lee , Donghyun Na , Eunho Yang
Abstract: A method for generating a trained model is provided. The method for generating a trained model includes: receiving a learning data; generating an asymmetric multi-task feature network including a parameter matrix of the trained model which permits an asymmetric knowledge transfer between tasks and a feedback matrix for a feedback connection from the tasks to features; computing a parameter matrix of the asymmetric multi-task feature network using the input learning data to minimize a predetermined objective function; and generating an asymmetric multi-task feature trained model using the computed parameter matrix as the parameter of the generated asymmetric multi-task feature network.
-
-
-
-
-
-
-
-
-