Abstract:
A loop antenna includes first and second loops that are formed with respective conductive wires. In this case, the second loop is formed with a double loop having current paths of opposite directions.
Abstract:
Provided is a system for predicting disease based on biosignal data and medical knowledge base convergence. The system includes a first system unit configured to receive, from a user terminal, biosignal data collected from at least one sensor for sensing a biosignal, and calculate a disease score from the biosignal data based on a pre-trained prediction model, a second system unit configured to provide medical knowledge data for the first system unit, analyze a query input from the user terminal to provide a corresponding response, and augment the medical knowledge data based on the query and response; and a unified distributed repository that includes a database for enqueuing the biosignal data, a manager database for storing additional information of a user, and a medical knowledge base for storing predetermined medical knowledge data.
Abstract:
Provided is an engine container configured by a workflow engine framework for a cross-domain extension, including a plurality of operators configured to interwork with a plurality of representational state transfer (REST) application programming interfaces (APIs), respectively, a runner configured to sequentially call the plurality of operators according to a request from a client, and a controller configured to control an operation of the plurality of operators and the runner, wherein each operator operates in a pipeline manner to call a corresponding REST API using uniform resource locator (URL) information transferred from the runner and to transfer a processing result obtained by processing data provided through the corresponding called REST API to a next operator.
Abstract:
Provided are an infrastructure apparatus and method of providing collaboration between thing devices. Since a plurality of thing devices located in a specific space share an experience where the plurality of thing devices have performed a collaboration service, each of the thing devices may search for peripheral thing devices for performing the collaboration service without intervention of a center server and may generate a collaboration group including the found thing devices, and tasks for performing through negotiation may be autonomously distributed to the thing devices included in the collaboration group, thereby providing autonomous collaboration between the thing devices.
Abstract:
Provided are an apparatus and method for detecting an anomaly in a plant pipe using multiple meta-learning. When a multi-sensor data stream about a plant pipe is received, each of a plurality of meta-learning modules for processing different packet section ranges, extracts one or more preset types of features from sensor data of packet section ranges set according to trend from an arbitrary reception time point, generates 2D image features of the features according to multi-sensor-specific times, generates 3D volume features by accumulating the 2D image features in a depth direction according to multiple sensors, and learns the 3D volume features in parallel through multi-sensor-specific learning modules. Results of the learning of the meta-learning modules are aggregated, and it is determined whether there is an anomaly in a plant pipe according to a learning result selected based on an optimal combination of multiple features, multiple sensors, and multiple packet sections.
Abstract:
Provided are an apparatus and method for detecting an anomaly in a plant pipe using multiple meta-learning. When a multi-sensor data stream about a plant pipe is received, each of a plurality of meta-learning modules for processing different packet section ranges, extracts one or more preset types of features from sensor data of packet section ranges set according to trend from an arbitrary reception time point, generates 2D image features of the features according to multi-sensor-specific times, generates 3D volume features by accumulating the 2D image features in a depth direction according to multiple sensors, and learns the 3D volume features in parallel through multi-sensor-specific learning modules. Results of the learning of the meta-learning modules are aggregated, and it is determined whether there is an anomaly in a plant pipe according to a learning result selected based on an optimal combination of multiple features, multiple sensors, and multiple packet sections.
Abstract:
An omnidirectional antenna is provided. The omnidirectional antenna includes a spiral antenna including a substrate, at least one upper antenna pattern formed on the substrate, and at least one lower antenna pattern formed under the substrate and connected to the upper antenna pattern; and a monopole antenna that supports the spiral antenna and that is connected to the spiral antenna. Therefore, by forming an omnidirectional antenna in a spiral antenna having an upper antenna pattern and a lower antenna pattern at an upper surface and a lower surface, respectively, of a substrate, three-dimensional current flow is available and thus omnidirectional radiation characteristics may be exhibited.
Abstract:
A multi-channel wireless network acquires reference time information that is commonly applied to all multi-channels and acquires packet receiving time information of a received packet on each channel basis based on the reference time information by spreading and applying the reference time information to each channel.
Abstract:
A receiving apparatus for an RFID reader estimates channel coefficients for each of a plurality of receiving antennas based on tag response signals received via a plurality of receiving antennas, compensates the tag response signals received via the plurality of receiving antennas based on the channel coefficients estimated for each of a plurality of channel estimators, combines the compensated tag response signals for each of the plurality of receiving antennas to generate a combined signal, and detect bits in the combined signal.
Abstract:
A virtual sensor generation apparatus of a sensor network sets a communication connection to a sensor node at a periphery of a smart device, generates a logical sensor corresponding to a physical sensor that is connected to the sensor node, generates a virtual sensor with the logical sensor, and provides an application service to a user using the virtual sensor.