Electronics and Telecommunications Research Institute

Jae Hun Choi

Seon Hee Park

Soo Jun Park

Hwin Dol Park

Myung Eun Lim

Kwang Hyo Chung

Dae Hee Kim

Hyung Wook Noh

Do Hyeun Kim

Seunghwan Kim

Myung-Eun Lim

Sun Lee Bang

YongWon Jang

Youngwoong Han

Seung Hwan Kim

Do Hyun Kim

Chang-Geun Ahn

Jong Min Park

Chang Geun Ahn

Yong Won Jang

Ho-Youl Jung

Chang-geun Ahn

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.

Device and method for anomaly detection of gas sensor

Disclosed is a time-series data processing device that includes a preprocessor, a learner, and a predictor. The preprocessor generates time-series interval data based on a time interval of time-series data, generates feature interval data based on a time interval of each of features of the time-series data, and preprocesses the time-series data. The learner generates a weight group of a prediction model for generating a prediction result based on the time-series interval data, the feature interval data, and the preprocessed time-series data. The predictor generates a time-series weight, which depends on a feature weight of each of the features and a time flow of the time-series data, based on the time-series interval data, the feature interval data, and the preprocessed time-series data and generates a prediction result based on the feature weight and the time-series weight.

Device for processing time series data having irregular time interval and operating method thereof

Disclosed is a device which includes a data manager, a learner, and a predictor. The data manager generates output data based on time-series data, receives device prediction results corresponding to the output data from the prediction devices, and calculates device errors based on the difference between device prediction results and time-series data. The learner may adjust a parameter group of a prediction model for generating device weights, based on device prediction results and device errors. The predictor generates the ensemble result of first and second device prediction results based on device weights.

Device for ensembling data received from prediction devices and operating method thereof

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.

Apparatus for controlling gas flow rates at multi-ports

Provided is a device for ensembling data received from prediction devices and a method of operating the same. The device includes a data manager, a learner, and a predictor. The data manager receives first and second device prediction results from first and second prediction devices, respectively. The learner may adjust a weight group of a prediction model for generating first and second item weights, first and second device weights, based on the first and second device prediction results. The first and second item weights depend on first and second item values, respectively, of the first and second device prediction results. The first device weight corresponds to the first prediction device, and the second device weight corresponds to the second prediction device. The predictor generates an ensemble result of the first and second device prediction results, based on the first and second item weights and the first and second device weights.

Disclosed are a gas detection intelligence training system and an operating method thereof. The gas detection intelligence training system includes a mixing gas measuring device that collects an environmental gas from a surrounding environment, generates a mixing gas based on the collected environmental gas and a target gas, senses the mixing gas by using a first sensor array and a second sensor array under a first sensing condition and a second sensing condition, respectively, and generates measurement data based on the sensed results of the first sensor array and the second sensor array, and a detection intelligence training device including a processor that generates an ensemble prediction model based on the measurement data.

Gas detection intelligence training system and operating method thereof

The image processing device includes a voxel extractor, a learner, and a predictor. The voxel extractor extracts a target voxel and neighboring voxels adjacent to the target voxel from a 3D image. The learner generates vectors corresponding to the target voxel and the neighboring voxels, respectively, generates vector weights corresponding to each of the vectors, based on the vectors and a parameter group, and adjusts the parameter group, based on an analysis result of the target voxel generated by applying the vector weights to the vectors. The predictor generates vectors corresponding to the target voxel and the neighboring voxels, respectively, generates correlation weights among the vectors by applying a parameter group to the vectors, generates vector weights corresponding to each of the vectors by applying the correlation weights to the vectors, and generates an analysis result of the target voxel by applying the vector weights to the vectors.

Image processing device and calcification analysis system including the same

An apparatus and method for assisting medication are disclosed. The apparatus includes a medication box and a medication service device. The medication box includes a plurality of containers each storing a paper bag of medication, and discharges a paper bag of medication from a corresponding one of the containers using a rotational force of an electric motor, and detects whether the stored paper bag of medication is present or is discharged. The medication service device includes a situation detector detecting a status of a user based on user identification and signal strength included in a radio frequency signal, and a status of the medication box, a situation recognizer recognizing a medication situation, and a service executor generating a service for medication. The user who has to regularly take a paper bag of medication for a long time can be assisted to take an accurate dose of medication on time.

Medication service apparatus, medication box, and apparatus and method for assisting medication

The present invention discloses a medication history management system and method. The medication management system includes: a mobile terminal; a medicine storage apparatus which is operably connected to the mobile terminal and stores medicines; and a medication management server which is connected to the mobile terminal via a network, provides a medicine loading request message for requesting a user to load a medicine in the medicine storage apparatus to the user through the mobile terminal when the user who must take the medicine will go out, and provides a medication request message for requesting the user to take the medicine stored in the medicine storage apparatus to the user through the mobile terminal when it is time to take the medicine.

Medication history management system and method

An apparatus and method for assisting medication are capable of assisting medication of users who have to regularly take medications in daily life. The apparatus includes a medication box having a plurality of containers, each of which stores a dose of medication to be taken at one time according to a medication schedule, a radio frequency (RF) transmitter carried on a user and transmitting an RF signal, an RF receiver receiving the RF signal from the RF transmitter, and a controller controlling medication assisting. Thus, the apparatus checks a spatial-temporal situation of the user, i.e. an medication, notification or information situation, using the received RF signal, and creating and providing medication service corresponding to the checked situation.

Apparatus and method for assisting medication, medication box, and medication storage container

A context aware system and a context aware method thereof perform a reasoning to be aware of contexts in ubiquitous environments. The context aware method includes procedures of modeling a knowledge base describing context information including constraints; classifying the context information described in the knowledge base according to the constraints; filtering fact data having same constraints as input sensor data from the classified context data; storing only rules, which satisfy the filtered fact data and constraints, in an working memory; and inferring a service context by reasoning the stored fact data and rules. The method receives input sensor data, associated with a subject, continuously monitored and serviced by indoor sensors, performs a reasoning based upon the input sensor data, in order to be aware of the present contexts of the subject and also provide, in real-time, a service suitable for the present contexts, thereby promoting the convenience of life.

Context aware system and context aware method thereof

Provided are a method and apparatus for detecting bio-complexes that are important sub protein interaction networks using a rule-based template in large interaction networks present in a single species. The method includes (a) defining a rule-based template corresponding to a bio-complex to be detected by defining a node that consists of at least one protein, a triplet that consists of two defined nodes and a protein interaction relationship therebetween, and single and composite rules using the triplet and an operator; (b) analyzing the rules of the defined rule-based template by analyzing whether the protein corresponding to the node included in the defined rule-based template and the protein interaction relationship corresponding to the triplet are present in a protein interaction network; and (c) detecting a bio-complex in the protein interaction network by assessing the triplet included in the rules analyzed and the node included in the triplet using a protein interaction relationship and protein of the protein interaction networks.

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Daejeon, South Korea

Jae Hun Choi