Abstract: The present invention relates to a device and method of predicting disease by using elderly cohort data, and more particularly, to a device and method of predicting disease by using elderly cohort data and an elderly disease prediction model applied thereto, which may predict an outbreak possibility of an elderly disease including cerebral stroke by using cohort data of 60 or more-year-old persons.

Abstract: Provided are a data processing apparatus and method for merging and processing deterministic knowledge and non-deterministic knowledge. The data processing apparatus and method may efficiently process various real-time and large-scale data to convert the data into knowledge by merging and processing non-deterministic knowledge and also deterministic knowledge perceived by an expert. Thus, it is possible to adaptively operate in accordance with a dynamically changing application service environment by converting a conversion rule for converting collected data generated from an application service system into semantic data, a context awareness rule for perceiving context information from given information, and a user query for searching for knowledge information into knowledge and gradually augmenting the knowledge information in accordance with an application service environment.

Abstract: A method of filtering content including privacy information in an Internet of things (IoT) terminal includes generating, by the processor, content management data prescribing a mapping relationship between pieces of content, a kind of a network, and a plurality of applications and storing the content management data in a content management data storage unit, based on a user input, the content management data prescribing a security policy associated with external transmission of the pieces of content, and when an external transmission request message corresponding to specific content of the pieces of content is received from the specific application, determining, by the processor, whether to allow external transmission of the specific content in response to the external transmission request message, based on the security policy prescribed in the content management data.

Abstract: A workflow engine framework for creating a single-domain adaptive and a cross-domain adaptive workflow performing platform is disclosed. The workflow engine framework includes: a resource management unit configured to manage resources including engine components and workflow property specification components; a system configuration unit configured to create an engine by assembling the property specification components; and a system control unit configured to drive and execute one or more engines. Further the workflow engine framework is allocated to each of two or more different signal domains and forms a cross-domain adaptive workflow engine framework.

Abstract: A workflow engine framework for creating a single-domain adaptive and a cross-domain adaptive workflow engine platform is disclosed. The single-domain adaptive workflow engine framework is allocated to each of two or more different signal domains and forms a cross-domain adaptive workflow engine framework. Here, the single-domain adaptive workflow engine framework includes a resource management unit configured to manage resources including engine components and workflow property specification components; a system configuration unit configured to create an engine by assembling the property specification components; and a system control unit configured to drive and execute one or more engines.

Abstract: An automatic configuration device, for an Internet-of-Things (IoT) device, which operates a data analysis-based automation system includes when various types of IoT devices are registered in a system, a data analysis-based automation system for supporting both use of functions of the IoT devices and an effective analysis of collected data.

Abstract: A method of filtering content including privacy information in an Internet of things (IoT) terminal includes generating, by the processor, content management data prescribing a mapping relationship between pieces of content, a kind of a network, and a plurality of applications and storing the content management data in a content management data storage unit, based on a user input, the content management data prescribing a security policy associated with external transmission of the pieces of content, and when an external transmission request message corresponding to specific content of the pieces of content is received from the specific application, determining, by the processor, whether to allow external transmission of the specific content in response to the external transmission request message, based on the security policy prescribed in the content management data.

Abstract: Provided is an apparatus and method for hierarchically providing a context-aware service by real-time user behavior analysis, autonomously collecting information required for the context-aware service using a smart device, and autonomously configuring the service. The apparatus for hierarchical context awareness and device autonomous configuration through a real-time user behavior analysis includes a fast context aware engine configured to receive user data, infer a context, and provide a primary response context aware service, and a fine context aware engine configured to provide a secondary response context aware service using context information inferred by the fast context aware engine and machine learning prediction data, wherein the fast context aware engine reconfigures a resource of a smart device to suit a service.

Abstract: A method and an apparatus for communication between peer devices in which a cyclic-superframe including a plurality of superframes is used are provided. The method may include: receiving a discovery request command frame including information about a first cyclic-superframe for a peering period at an active contention access period (CAP) of the plurality of superframes; transmitting, to a peer device that has transmitted the discovery request command frame, a discovery response command frame corresponding to the discovery request command frame; and performing the peering period with the peer device based on the first cyclic-superframe.

Abstract: An apparatus/method for extracting multiple features from time series data collected from a plurality of sensors and for performing transfer learning on them. There is provided an apparatus including: a multi-feature extraction unit for extracting multiple features from a data stream for each sensor inputted from the plurality of sensors; a transfer-learning model generation unit for extracting useful multi-feature information from a learning model which has finished pre-learning, for the multiple features for forwarding the extracted multi-feature information to a multi-feature learning unit to generate a learning model that performs transfer learning on the multiple features; and the multi-feature learning unit for receiving learning variables from the learning model for each of the multiple features and for performing parallel learning for the multiple features, to calculate and output a loss. In addition, there is provided an apparatus for detecting leaks in plant pipelines.

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 automatic configuration device, for an Internet-of-Things (IoT) device, which operates a data analysis-based automation system includes when various types of IoT devices are registered in a system, a data analysis-based automation system for supporting both use of functions of the IoT devices and an effective analysis of collected data.

Abstract: The present invention is directed to providing a total periodic de-identification management apparatus capable of setting de-identification and degrees of adequacy of non-identified data as unit components, providing work flow information so that an operator can select desired unit components, and performing de-identification to correspond to total periodic work flow parsing information including the combination of the unit components selected by the operator.

Abstract: A workflow engine framework for creating a single-domain adaptive and a cross-domain adaptive workflow performing platform is disclosed. The workflow engine framework includes: a resource management unit configured to manage resources including engine components and workflow property specification components; a system configuration unit configured to create an engine by assembling the property specification components; and a system control unit configured to drive and execute one or more engines. Further the workflow engine framework is allocated to each of two or more different signal domains and forms a cross-domain adaptive workflow engine framework.

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: A method and an apparatus for communication between peer devices in which a cyclic-superframe including a plurality of superframes is used are provided. The method may include: receiving a discovery request command frame including information about a first cyclic-superframe for a peering period at an active contention access period (CAP) of the plurality of superframes; transmitting, to a peer device that has transmitted the discovery request command frame, a discovery response command frame corresponding to the discovery request command frame; and performing the peering period with the peer device based on the first cyclic-superframe.

Abstract: Provided is a data meta-scaling method. The data meta-scaling method optimizes an abbreviation criterion for abbreviating data through continuous knowledge augmentation in various dimensions which enable expression of data in a process of performing machine learning.

Abstract: Provided are a self-learning system and method for automatically performing machine learning (ML). The self-learning system includes a memory configured to store an ML knowledge database (DB) in which ML knowledge is stored and a program for automatically performing ML based on request information of a user, and a processor configured to execute the program stored in the memory. Here, when executing the program, the processor creates or recommends at least one workflow corresponding to the request information of the user based on the ML knowledge stored in the ML knowledge DB and generates an execution code for performing the created or recommended workflow.

Abstract: Provided are a data processing apparatus and method for merging and processing deterministic knowledge and non-deterministic knowledge. The data processing apparatus and method may efficiently process various real-time and large-scale data to convert the data into knowledge by merging and processing non-deterministic knowledge and also deterministic knowledge perceived by an expert. Thus, it is possible to adaptively operate in accordance with a dynamically changing application service environment by converting a conversion rule for converting collected data generated from an application service system into semantic data, a context awareness rule for perceiving context information from given information, and a user query for searching for knowledge information into knowledge and gradually augmenting the knowledge information in accordance with an application service environment.

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.