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1.发明公开公开(公告)号：US20230316156A1
公开(公告)日：2023-10-05
申请号：US18057080
申请日：2022-11-18
Inventor： Do Hyeun KIM , Myung Eun LIM , Jae Hun CHOI
IPC: G06N20/20
CPC classification number: G06N20/20
Abstract: Disclosed herein a method and apparatus for learning a multi-label ensemble based on multi-center prediction accuracy. According to an embodiment of the present disclosure, there is provided a multi-label ensemble learning method comprising: collecting a prediction value for learning data for each of a plurality of prediction models; calculating a prediction error of each of the prediction models using the prediction value of each of the prediction models and a correct answer prediction value; generating a weight label for each of the prediction models based on the prediction error; and learning an ensemble weight prediction model for predicting a weight of each of the prediction models using the weight label.
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2.发明申请公开(公告)号：US20220343160A1
公开(公告)日：2022-10-27
申请号：US17725172
申请日：2022-04-20
Inventor： Hwin Dol PARK , Jae Hun CHOI , Youngwoong HAN
IPC: G06N3/08
Abstract: Disclosed is a time series data processing device which includes a pre-processor that performs pre-processing on time series data to generate pre-processing data, and a learner that creates or updates a feature model through machine learning for the pre-processing data. The learner includes a time series irregularity learning model that learns time series irregularity of the pre-processing data, and a feature irregularity learning model that learns feature irregularity of the pre-processing data.
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公开(公告)号：US20220187262A1
公开(公告)日：2022-06-16
申请号：US17513567
申请日：2021-10-28
Inventor： YongWon JANG , Hwin Dol PARK , CHANG-GEUN AHN , Do Hyeun KIM , Seunghwan KIM , Hyung Wook NOH , Kwang Hyo CHUNG , Jae Hun CHOI
Abstract: Disclosed are a device and a method for anomaly detection of a gas sensor. The device includes a measuring unit that extracts a characteristic of a gas supplied from the outside, generates data based on the extracted characteristic, and outputs the data, and a data processing unit that receives the data, determines whether an error occurs in the data, and outputs an anomaly detection result based on a result of determining whether the error occurs in the data. The measuring unit performs a calibration operation or an environment adjusting operation before extracting the characteristic, and the data processing unit determines whether the error occurs in the data, based on machine learning.
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公开(公告)号：US20190221294A1
公开(公告)日：2019-07-18
申请号：US16213740
申请日：2018-12-07
Inventor： Ho-Youl JUNG , Hwin Dol PARK , Myung-Eun LIM , Jae Hun CHOI , Youngwoong HAN
Abstract: The inventive concept relates to a multi-dimensional time series data processing device, a health prediction system including the same, and a method of operating the time series data processing device. A time series data processing device according to an embodiment of the inventive concept includes a network interface, a data generator, a predictor, and a processor. The network interface receives the first time series data having the first type. The data generator generates second time series data having a second type based on the first time series data. The predictor generates prediction data based on the first time series data and the second time series data.
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公开(公告)号：US20140207386A1
公开(公告)日：2014-07-24
申请号：US13940182
申请日：2013-07-11
Inventor： Ho-Youl JUNG , Minho KIM , Myung-eun LIM , Jae Hun CHOI , Soo Jun PARK
IPC: G06F19/22
CPC classification number: G16B30/00
Abstract: Provided are a method of aligning a read sequence relative to a reference sequence using a seed and a read-sequence aligning apparatus using the same. The apparatus may include a seed generating unit producing seeds from read sequences, a representative seed selecting unit grouping the seeds into a plurality of seed clusters and selecting representative seeds from the plurality of seed clusters, a seed aligning unit aligning the representative seeds relative to a reference sequence, and a read-sequence aligning unit aligning the read sequences relative to the reference sequence, with reference to the alignment result of the representative seeds. The read sequence alignment may be performed using relationship between seeds, and thus, the sequencing may be performed with improved efficiency.
Abstract translation: 提供了使用种子和使用其的读取序列对准装置使读取序列相对于参考序列对准的方法。 该装置可以包括从读取序列产生种子的种子生成单元，将种子分组成多个种子群并从多个种子群中选择代表性种子的代表种子选择单元，将代表性种子相对于 参考序列，以及读取序列对齐单元，参考代表性种子的比对结果，相对于参考序列对准读取序列。 可以使用种子之间的关系来执行读取序列比对，因此，可以以提高的效率进行测序。
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Patent Agency Ranking
6.发明公开公开(公告)号：US20240192187A1
公开(公告)日：2024-06-13
申请号：US18509735
申请日：2023-11-15
Inventor： Jae Hun CHOI , Do Hyeun KIM , Hwin Dol PARK , Seunghwan KIM , Hyung Wook NOH , Chang-Geun ANH , YongWon JANG , Kwang Hyo CHUNG
IPC: G01N33/00
CPC classification number: G01N33/0034 , G01N33/0011 , G01N33/0062 , G01N2033/0019
Abstract: Disclosed is an artificial intelligence apparatus for detecting a target gas, which includes a mixed gas measurement unit that measures a mixed gas collected in a plurality of domains through a sensor array to generate sensing data including heterogeneous domain measurement data measured from the mixed gas collected in a domain different from the target gas and target domain measurement data measured from the mixed gas collected from the same domain as the target gas, a heterogeneous intelligence model deep learning unit that receives the heterogeneous domain measurement data to train a heterogeneous intelligence model, a target intelligence model deep learning unit that receives the heterogeneous intelligence model and the target domain measurement data to train a target intelligence model, and a target gas detection unit that determines whether an environmental gas includes the target gas using the target intelligence model.
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7.发明公开公开(公告)号：US20230229915A1
公开(公告)日：2023-07-20
申请号：US18155471
申请日：2023-01-17
Inventor： Hwin Dol PARK , Jae Hun CHOI , Young Woong HAN
IPC: G06N3/08
CPC classification number: G06N3/08
Abstract: Disclosed herein is a method and apparatus for predicting a future state and reliability based on time series data. In the method and the apparatus, a future state is predicted by preprocessing past state data and executing an algorithm based on the preprocessed past state data to generate a trained model, followed by preprocessing current state data and executing an algorithm based on the created trained model, the preprocessed current state data, and the preprocessed past state data.
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公开(公告)号：US20230176594A1
公开(公告)日：2023-06-08
申请号：US17716889
申请日：2022-04-08
Inventor： Kwang Hyo CHUNG , Chang Geun AHN , Do Hyun KIM , Seung Hwan KIM , Hyung Wook NOH , Hwin Dol PARK , Yong Won JANG , Jae Hun CHOI
CPC classification number: G05D7/0664 , F16L41/008 , F16L41/03
Abstract: Provided is a multi-port gas flow rate control apparatus. The multi-port gas flow rate control apparatus includes a gas supply chamber configured to supply a measurement gas input through one gas inflow channel while allowing the measurement gas to diverge into a plurality of flows, a plurality of gas divergence flow channels each having one side connected to the gas supply chamber and configured to transfer the measurement gas flowing through the gas supply chamber to a plurality of gas sensors, respectively, and a gas measurement chamber configured to accommodate the plurality of gas sensors, including the plurality of gas divergence flow channels configured to connect to the gas supply chamber to the plurality of gas sensors to transfer a gas outflow diverging through the gas supply chamber to the plurality of accommodated gas sensors, and configured to discharge the gas outflow sensed by the plurality of gas sensors.
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9.发明申请公开(公告)号：US20180150609A1
公开(公告)日：2018-05-31
申请号：US15812540
申请日：2017-11-14
Inventor： Minho KIM , YoungWon KIM , Donghun LEE , Jae Hun CHOI , Dae Hee KIM , Myung-eun LIM , Ho-Youl JUNG , Youngwoong HAN , Seunghwan KIM
CPC classification number: G16H50/20 , G06N3/04 , G06N5/048 , G06N20/00 , G16H10/60 , G16H50/50 , Y02A90/26
Abstract: The present disclosure herein relates to a future health trend forecasting system and a method thereof through a similar case cluster-based prediction model, and more specifically, to a server and a method thereof for extracting multiple associated feature similar case clusters that match a prediction query for the user's health information through a class prediction model and a future value prediction model for health features of a similar case cluster generated by cyclically clustering the target feature that is a health feature for personal health information and an associated feature of the target feature, predicting future health trends for each associated feature using multiple prediction models based on corresponding similar case clusters, and combining and outputting the prediction results.
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10.发明申请公开(公告)号：US20150261990A1
公开(公告)日：2015-09-17
申请号：US14480216
申请日：2014-09-08
Inventor： Dae Hee KIM , Ho Youl JUNG , Min Ho KIM , Myung Eun LIM , Jae Hun CHOI
CPC classification number: H03M7/70 , G06T9/00 , G06T2207/30072 , H03M7/40
Abstract: Provided are a method and apparatus for compressing DNA data based on a binary image. The method for compressing DNA data based on a binary image includes splitting DNA data including adenine (A), thymine (T), guanine (G), cytosine (C), and an indefinite base (N) into a plurality of binary images, determining a coding mode of each of the binary images according to characteristics of each of the binary images, and first coding each of the binary images based on the determined coding mode.
Abstract translation: 提供了一种基于二进制图像压缩DNA数据的方法和装置。 基于二值图像压缩DNA数据的方法包括将包括腺嘌呤（A），胸腺嘧啶（T），鸟嘌呤（G），胞嘧啶（C））和不定碱（N）的DNA数据分解成多个二值图像， 根据每个二进制图像的特性确定每个二进制图像的编码模式，并且基于所确定的编码模式对每个二进制图像进行编码。
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