-
公开(公告)号：US20240320525A1
公开(公告)日：2024-09-26
申请号：US18678657
申请日：2024-05-30
Inventor： Dae Seon CHOI , Yoon Soo AN
IPC: G06N5/04
CPC classification number: G06N5/04
Abstract: disclosure An AI model inference apparatus includes: a processor; and a memory connected to the processor, wherein the memory stores program instructions executed by the processor to use an output value of a target model to determine whether the target model corresponds to any of a graybox environment or a blackbox environment, input the same data as the target model to a plurality of AI models included in a candidate model group to acquire the output value, process output values of each of the plurality of AI models differently according to the environment of the target model to acquire a first feature or a second feature, and input the output values of each of the plurality of AI models and the first feature or the second feature to a pre-trained model type classifier to determine the AI model corresponding to the target model.
-
132.发明公开公开(公告)号：US20240320196A1
公开(公告)日：2024-09-26
申请号：US18224578
申请日：2023-07-21
Inventor： Jiwoong Kim , Hyokyeong Kim , Sohyun Park
IPC: G06F16/21
CPC classification number: G06F16/211
Abstract: A system for constructing a database for a structure and a property of a material based on big data includes an input module that receives chemical information about the material based on the big data, a controller that obtains information about the structure and the property of the material by modeling the chemical information about the material based on quantum mechanics and calculating elastic constants, a database constructing module that constructs a database for the information about the structure and the property, and an output module that outputs the information about the structure and the property in the database with respect to a model selected through the modeling.
-
133.发明公开公开(公告)号：US20240242088A1
公开(公告)日：2024-07-18
申请号：US18219691
申请日：2023-07-09
Inventor： Min Hae KWON , Mi Ru KIM , Hyo Seon KYE
IPC: G06N3/098
CPC classification number: G06N3/098
Abstract: Provided is a method of personalized federated learning performed by an electronic device. The method is performed by an electronic device including one or more processors, a communication circuit which communicates with an external device, and one or more memories storing at least one instruction executed by the one or more processors. The method may include, by the one or more processors, training a local model using local data, in which the local model as an artificial neural network model includes a first parameter set corresponding to a global parameter set and a second parameter set corresponding to a local parameter set, transmitting the first parameter set to the external device, receiving a 1-1st parameter set for renewing the first parameter set from the external device, changing the first parameter set included in the local model to the 1-1st parameter set, and training the local model including the 1-1st parameter set.
-
134.发明公开公开(公告)号：US20240241800A1
公开(公告)日：2024-07-18
申请号：US18219642
申请日：2023-07-07
Inventor： Min Hae KWON , Mi Ru KIM
IPC: G06F11/14
CPC classification number: G06F11/1471
Abstract: Provided is an anomaly detection method performed by an electronic device. The method performed by an electronic device including one or more processors, a communication circuit which communicates with an external device, and one or more memories storing at least one instruction executed by the one or more processors may include: by the one or more processors, receiving target data for discriminating whether an anomaly occurs, in which the target data includes a value for each of a plurality of features; inputting a value for at least one important feature among the plurality of features into an anomaly detection model, in which the at least one important feature is determined by important feature information received from the external device; and determining whether the target data is abnormal based on an output of the anomaly detection model.
-
135.发明公开公开(公告)号：US20240236034A1
公开(公告)日：2024-07-11
申请号：US17928487
申请日：2022-05-17
Inventor： Young Han KIM , Kyoung Jae SUN
IPC: H04L61/2503 , H04L61/5007
CPC classification number: H04L61/2503 , H04L61/5007
Abstract: Provided is a method for managing an address for an application of a LISP (Locator ID Separation Protocol) network system in a distributed container-based virtualization environment, and the method comprises detecting, by a service discovery agent of a container platform, generation of an application in a corresponding cluster; querying, by the service discovery agent, a service IP address to be assigned to an application to be generated by transmitting a service name to a central control plane; searching, by the control plane, for a service IP address matching the service name and transmitting the service IP address to the service discovery agent; and transmitting, by the service discovery agent, the service IP address to a manager of the container platform to complete the generation of the application, and mapping the service IP address to a public IP for the generated application to register it in the control plane.
-
Patent Agency Ranking
136.发明公开公开(公告)号：US20240220636A1
公开(公告)日：2024-07-04
申请号：US18550865
申请日：2022-10-12
Inventor： Jeong Hyun YI , Haehyun CHO , Kyungmin SIM , Sunjun LEE , Geochang JEON
IPC: G06F21/57
CPC classification number: G06F21/577 , G06F2221/033
Abstract: Provided is a unit test case-based security design flaw detection method performed in a security design flaw detection apparatus for detecting a security design flaw of a software system, and the method comprises collecting a unit test case for the software system from an external device and preprocessing the unit test case; generating a first test case by testing whether the software system violates a security policy using the preprocessed unit test case; generating a second test case that is a data set for testing a function of the software system based on the first test case; and detecting a vulnerability of the software system by executing the second test case.
-
公开(公告)号：US20240215452A1
公开(公告)日：2024-06-27
申请号：US17798015
申请日：2022-02-21
Applicant: SEOUL NATIONAL UNIVERSITY R&DB FOUNDATION , FOUNDATION OF SOONGSIL UNIVERSITY - INDUSTRY COOPERATION
Inventor： Gyuchul Yi , Hongseok Oh
CPC classification number: H10N30/85 , G01L5/167 , H10N30/302 , H10N30/87
Abstract: An orthostatic hypotension screening system using a heart rate-based machine learning algorithm includes an input unit configured to receive a variable comprising at least one of a patient's age, blood pressure, an expiration (E)-inspiration (I) difference and an E:I ratio calculated from a heart rate, and a Valsalva ratio calculated according to a Valsalva method; and a determination unit configured to determine whether the patient has orthostatic hypotension according to a machine learning algorithm that is pre-trained based on the variable received through the input unit.
-
138.发明公开公开(公告)号：US20240202041A1
公开(公告)日：2024-06-20
申请号：US18515576
申请日：2023-11-21
Inventor： Young Han KIM , Tae Hoon KIM
IPC: G06F9/50
CPC classification number: G06F9/505 , G06F9/5072
Abstract: An apparatus, method, and system for automatically scaling dynamic computing resources based on predicted traffic patterns are disclosed. A system for automatically scaling dynamic computing resource based on a predicted traffic pattern comprises a prediction API for predicting resource according to a traffic request for each cluster configured on a workload server using a pre-trained machine learning model; and a prediction-based autoscaler for calculating required resource by comparing available resource for each cluster with the predicted resource, selecting an optimal flavor according to the calculated required resource, and generating a template corresponding to the selected optimal flavor.
-
公开(公告)号：US20240115956A1
公开(公告)日：2024-04-11
申请号：US18543568
申请日：2023-12-18
Inventor： Hyeon Suk Na , Min Gyu Jeon , Chi Yeon Hwang
IPC: A63F13/71 , A63F13/792
CPC classification number: A63F13/71 , A63F13/792 , A63F2300/408 , A63F2300/532
Abstract: Disclosed are a method for changing a game parameter and a client for performing same. The client comprises: a processor for executing a game program; and a transceiver for communicating with a blockchain node of a blockchain network storing a first blockchain, wherein the processor may authenticate a user account and perform a first event of the game program accessed by the user account, the transceiver may transmit, to the blockchain node, a completion signal of the first event including information about the client when the first event is completed and receive, from the blockchain node, a request signal for generating a second event, the processor may generate the second event on the basis of the request signal for generating the second event, and the transceiver may transmit, to the blockchain node, information about the second event.
-
公开(公告)号：US11909751B2
公开(公告)日：2024-02-20
申请号：US17528203
申请日：2021-11-17
Inventor： Minhae Kwon , Hyoseon Kye
CPC classification number: H04L63/1425 , H04L43/16 , H04L67/12
Abstract: An anomaly detection method includes searching for one principal component axis by analyzing a normal data set collected in time series from a plurality of IoT devices by using a principal component analysis technique, setting a center point of the principal component, receiving a currently measured measurement data set from the plurality of IoT devices, acquiring a linear transformation data set having a plurality of projection points as elements by projecting a plurality of measurement data which is each element in the measurement data set onto the principal component axis, calculating a Mahalanobis distance between the projection point and the central point, and detecting whether or not data of the IoT devices is abnormal by comparing the Mahalanobis distance calculated for each element with a threshold.
-
-
-
-
-
-
-
-
-
Search Results
398
records
(took 0.03 seconds)
