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.
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.
Abstract:
Provided are a low power micro semiconductor gas sensor and a method of manufacturing the same. The micro semiconductor gas sensor includes a substrate having an air gap, a peripheral portion provided on the substrate and comprising electrode pads, a sensor portion comprising sensing electrodes connected from the electrode pads and a sensing film on the sensing electrodes and floating on the air gap, and a connection portion comprising conductive wires electrically connecting the electrode pads and the sensing electrodes to each other, and connecting the peripheral portion and the sensor portion to one another. In this case, the air gap penetrates the substrate, and a thermal isolation area extended from the air gap to a space between the peripheral portion and the sensor portion is provided.
Abstract:
A biosensor includes a solution chamber containing primary antibodies, secondary antibodies, and measuring substances, an injection fluid transfer unit for connection the solution chamber to an injection port, and a discharging transfer unit for connecting the solution chamber to a discharging port.
Abstract:
Provided are a search method and device in which, in order to search for health data having a multivariate (multi-dimensional) time-series characteristic with high calculation complexity for a search, a format of the health data is converted and a dimension of the health data is reduced through feature extraction to which a learning model is applied, so that the calculation complexity for the search may be remarkably reduced and the similar case search may be performed efficiently.
Abstract:
Provided is an ion beam treatment apparatus including the target. The ion beam treatment apparatus includes a substrate having a first surface and a second surface opposed to the first surface, and including a cone type hole decreasing in width from the first surface to the second surface to pass through the substrate, wherein an inner wall of the substrate defining the cone type hole is formed of a metal, an ion generation thin film attached to the second surface to generate ions by a laser beam incident into the cone type hole through the first surface and strengthen, and a laser that emits a laser beam to generate ions from the ion generation thin film and project the ions onto a tumor portion of a patient. The laser beam incident into the cone type hole is focused by the cone type hole and is strengthened.
Abstract:
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.
Abstract:
Provided is a method for measuring a depth profile of a particle beam, the method including providing first sensors in a first direction in auditory organs of a human body, providing second sensors in a second direction that intersects with the first direction on a top of a head and in a mouth of the human body, providing a particle beam into the head of the human body, detecting an acoustic signal generated by the particle beam through the first and second sensors, and calculating a depth profile of the first and second directions of the particle beam corresponding to a Bragg peak position of the particle beam in the head using the acoustic signal.
Abstract:
Provided are a search method and device for searching for a case similar to user's health data at high-speed from large scale multi-dimensional time series health data. The method includes preprocessing health data inputted through an interface circuit, performing a multi-dimensional feature extraction learning based on machine learning on the preprocessed health data, and generating one or more feature extraction models for dimension reduction based on the multi-dimensional feature extraction learning.
Abstract:
The inventive concept relates to a method and apparatus for predicting health data values through the generation of a health data pattern. The inventive concept provides a health data value prediction method and apparatus. The health data value prediction method and apparatus may select health data values and important health characteristics associated with the health data values from big data on a plurality of pieces of time-series health information. The health data value prediction method and apparatus may form a health data value prediction model that has repetitively learned the pattern, and accurately predict a user's health data value through the prediction model.