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 a method of allocating resources in a wireless local area network (WLAN) system and the WLAN system including an access point (AP) to allocate a resource for communication between a relay and a station associated with the relay, the relay to allocate a restricted access window (RAW) or a slot for communication with a station based on the allocated resource, and the station to communicate with the relay based on the allocated RAW or the allocated slot.

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 a system and method for controlling a workflow across domains on the basis of a hierarchical engine framework. Inventive workflow control makes it possible to configure a flexible hierarchical engine framework and provide a workflow service with low latency. Also, the system and method make it possible to control a workflow by building an engine and a data pipeline across domains.

Abstract: Provided are a method of allocating resources in a wireless local area network (WLAN) system and the WLAN system including an access point (AP) to allocate a resource for communication between a relay and a station associated with the relay, the relay to allocate a restricted access window (RAW) or a slot for communication with a station based on the allocated resource, and the station to communicate with the relay based on the allocated RAW or the allocated slot.

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: A method of configuring a multi-superframe is provided. The method includes setting at least one parameter for configuring the multi-superframe, and configuring the multi-superframe corresponding to the at least one parameter, wherein the at least one parameter includes a superframe order (SO), a beacon order (BO), and a multi-superframe order (MO), in a form of positive integers, and the setting includes setting the MO to have a value higher than the BO.

Abstract: Provided are a method of allocating resources in a wireless local area network (WLAN) system and the WLAN system including an access point (AP) to allocate a resource for communication between a relay and a station associated with the relay, the relay to allocate a restricted access window (RAW) or a slot for communication with a station based on the allocated resource, and the station to communicate with the relay based on the allocated RAW or the allocated slot.

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 are a method of allocating resources in a wireless local area network (WLAN) system and the WLAN system including an access point (AP) to allocate a resource for communication between a relay and a station associated with the relay, the relay to allocate a restricted access window (RAW) or a slot for communication with a station based on the allocated resource, and the station to communicate with the relay based on the allocated RAW or the allocated slot.

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 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 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 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: Provided are a method of allocating resources in a wireless local area network (WLAN) system and the WLAN system including an access point (AP) to allocate a resource for communication between a relay and a station associated with the relay, the relay to allocate a restricted access window (RAW) or a slot for communication with a station based on the allocated resource, and the station to communicate with the relay based on the allocated RAW or the allocated slot.

Abstract: Provided is a small switchable directional control antenna that can perform direction control according to shapes and sizes of various devices. The antenna includes a dielectric layer, a radiation patch formed on a side of the dielectric layer, a ground plane formed on a side of the dielectric layer opposite to the side on which the radiation patch is formed and configured to have a plurality of slots formed at edges thereof, and a control module insulated from the ground plane and configured to control electrical connection between the radiation patch and the ground plane.

Abstract: Provided are a method of allocating resources in a wireless local area network (WLAN) system and the WLAN system including an access point (AP) to allocate a resource for communication between a relay and a station associated with the relay, the relay to allocate a restricted access window (RAW) or a slot for communication with a station based on the allocated resource, and the station to communicate with the relay based on the allocated RAW or the allocated slot.