Abstract:
A system for managing a disaster based on a grid and an operating method of the system are disclosed. The operating method includes generating one or more models respectively corresponding to one or more sensors, acquiring and storing one or more of one or more pieces of sensing information sensed by the one or more sensors, event information determined based on the one or more pieces of sensing information, and status information of the one or more sensors, in the one or more models, based on multidimensional spatial information based on a grid on which the one or more sensors are disposed, information stored in the one or more models, and disaster information related to the multidimensional spatial information, creating grid-based data to monitor a disaster situation associated with the information stored in the one or more models and/or the multidimensional spatial information, and outputting the created grid-based data.
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 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:
A wireless access point apparatus for configuring a multiple data security tunnel, and a system having the same and a method thereof, and more particularly, a technology associated with a wireless access point apparatus that supports a wireless secure throughout all layers in a wireless network section. The wireless access point apparatus for configuring a multiple data security tunnel includes: a control security tunnel managing unit managing a control security tunnel that transfers policies and authentication information for wireless network access control and management; and a multiple data security tunnel managing unit creating a data security tunnel for each of a plurality of wireless terminals, while, creating and managing the multiple data security tunnel for each of application services of the plurality of wireless terminals.
Abstract:
In a scheduling apparatus, a packet start time with respect to an input packet is calculated, and a slot corresponding to the packet start time is selected from a scheduler including a plurality of slots. Whether to store the packet in the selected slot in consideration of the number of packets stored in the selected slot and the number of packets corresponding to virtual ports corresponding to the input packet is determined, and here, the virtual port is an output port of a switch device which is connected to the outside and does not have a scheduling function.