• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3378-3393
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• 2014

We have witnessed the rapid development of information technology in recent years. One of the key phenomena is the fast, near-exponential increase of data. Consequently, most of the traditional data classification methods fail to meet the dynamic and real-time demands of today's data processing and analyzing needs--especially for continuous data streams. This paper proposes an improved incremental learning algorithm for a large-scale data stream, which is based on SVM (Support Vector Machine) and is named DS-IILS. The DS-IILS takes the load condition of the entire system and the node performance into consideration to improve efficiency. The threshold of the distance to the optimal separating hyperplane is given in the DS-IILS algorithm. The samples of the history sample set and the incremental sample set that are within the scope of the threshold are all reserved. These reserved samples are treated as the training sample set. To design a more accurate classifier, the effects of the data volumes of the history sample set and the incremental sample set are handled by weighted processing. Finally, the algorithm is implemented in a cloud computing system and is applied to study user behaviors. The results of the experiment are provided and compared with other incremental learning algorithms. The results show that the DS-IILS can improve training efficiency and guarantee relatively high classification accuracy at the same time, which is consistent with the theoretical analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.871-874
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• 2007

Stream data need a efficient data management with high reliability and real time processing. The characteristics of these data are a large volume, a short report interval and asynchronous report time. The typical queries of these systems consist of the current query to search the latest signal value, the snapshot query to search the signal value of a past time, the historical query to search the signal value of a past time to current. This paper proposes the efficient method to manage the above signals by using a file structured database in QNX operating systems. The query model to accommodate various query for stream data is proposed. The proposed methods are applied to reactive protection system to verify their usefulness. The COM(Cabinet Operator Module) based on the QNX employs file database that adopts a delta version and a buffering method for the resource limit of a small storage and a low computing power.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.287-292
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• 2001

Multimedia service systems should have efficient capacity to serve the growing clients and new data. In the general streaming services, users can endure the small amount of time delay at the beginning of service. But they want to have good quality of service. A streaming server tries to transfer video files to clients from a repository of files in real time. The server must guarantee concurrent and uninterrupted delivery of each video stream requested from clients. To achieve its purpose, many stream servers adopt multi-processors, sufficient memory, and RAID or SAN in their systems. In this paper, we propose a Linux-based parallel media streaming server. It is superior to the other systems in the storing structure, fault-tolerance, and service capacity. Since this system supports the web interlace, users can operate easily through the www. This system uses unique striping policy to distribute multimedia files into the parallel storage nodes. If a service request occurs, each storage node transmits striped files concurrently to the client. Its performance is better than the single media streaming service because of the parallel architecture.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.486-488
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• 2004

The SRI (Super Resolution Imager) uses the CCD (Charge coupled device) detector that is used to convert the light into electronic data. The purpose of the SRI is to obtain data for high resolution images by converting incoming light into digital stream of pixel data. The SRI has a high resolution, so this electronic system needs more fast imaging data processing, detector control and data transmission systems. This report describes the required system specification and manufactured electronic system for satellite.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1379-1386
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• 2017

As the Internet of Things evolves, various IoT services are provided. IFTTT is an abbreviation for If This Then That and refers to a service that links different web-based services. This paper proposes a system that generates and manages rules that combine the possibility of IFTTT service and the real-time event processing according to the concept of IoT service. Conventional database-based data processing methods are burdened to process a lot of data of IoT devices coming in real-time. The IoT device's data can be classified into formal data such as the amount of power, temperature value and position information, and informal data such as video or image data. Thus, this system classifies the data stream of IoT devices coming in real-time using the CEP engine Esper into a file signature table, classifies the formal/informal data, and shows the condition of the device data defined by the user and the service to be provided by applying the service.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.181-184
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• 2000

In this paper, we described a design of the input buffer system for efficiently dealing with MPEG audio bitstream to demux header and side information, audio data. In order to overcome the limitations of fixed-word manipulation in bitstream demuxing, we proposed a new variable length bit retrieval system with FSM sequencer supporting MPEG audio frame format, and serial buffer demuxing audio stream, FIFO circular buffer including header and side information.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.43-54
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• 2009

As R&D(Research and Development) is going on actively to develop technologies for the ubiquitous computing environment, which Is the human-oriented future computing environment, GIS dealing with spatio-temporal data is emerging as a promising technology. This also increases the necessity of the middleware for providing services to give interoperability in various heterogeneous environments. The core technologies of the middleware are real-time processing technology of data streams coming unceasingly from positioning systems and data stream processing technology developed for non-spatio-temporal data. However, it has problems in processing queries on spatio-temporal data efficiently. Accordingly, this paper designed and implemented the spatio-temporal middleware that provides interoperability between a mobile spatio-temporal DBMS(DataBase Management System) and a server spatio-temporal MMDBMS(Main Memory DataBase Management System). The spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real-time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. In addition, it manages session for the connection of each spatio-temporal DBMS and manages resources for its stable operation. Finally, this paper proved the usability of the spatio-temporal middleware by applying it to a real-time position tracking system.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.184-186
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• 2015

본 논문에서는 PTAM을 위한 새로운 분산 스트림 프로세싱 시스템을 제안한다. PTAM은 하나의 시스템에서 동작하도록 설계되었다. 이는 PTAM이 가지고 있는 한계점을 말해주는 부분인데, PTAM은 Bundle Adjustment의 계산 부하가 커지는 경우에 map을 구축하는데 있어 많은 시간과 리소스가 필요하다. 이에 하둡을 통해 계산 부하를 분산하고, PE(Processing Element)를 Xeon phi 시스템을 통해 동작되는 시스템을 제안한다.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.79-88
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• 2009

The volume of memory to store real-time data stream is varied dynamically. Continuous queries processing the data stream must manage the storage volume dynamically. In previous research, according to current volume of data a general memory manager which allocates and releases memory by a page unit is researched.However, the method frequently executes page allocation and release to store data stream. Moreover, particularly delayed queries can monopolize many of pages because the method directly allocates pages when a query has not enough memory. Focusing on the problems in memory management systems, this research proposes a memory management method which reduces the frequency of allocation and release and uniformly distributes pages for queries. The method can reduce the frequency of allocation and release through allocation based on utilization ratio of pages in each query and prevent memory monopoly through memory allocation which considers query delay.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1384-1397
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• 2007

This paper proposes fast storage techniques for hybrid query of data streams. DSMS(Data Stream Management System) have been researched for processing data streams that have busting income. To process hybrid query that retrieve both current incoming data streams and past data streams data streams have to be stored into disk. But due to fast input speed of data stream and memory and disk space limitation, the main research is not about querying to stored data streams but about querying to current incoming data streams. Proposed techniques of this paper use circular buffer for maximizing memory utility and for make non blocking insertion possible. Data in a disk is compressed to maximize the number of data in the disk. Through experiences, proposed technique show that bursting insertion is stored fast.