• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.989-998
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• 2013

We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1785-1796
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• 1993

Thanks to the data processing facilities of modern digital computers, the performances of radar has been promoted greatly as one of the main components of command and control systems along with the computer communications. In this study, radar data integrating and processing systems were designed for the data processing of various information from many kinds of radar in a single data processing system. The performance of the data integrating system was analyzed by applying queueing theory. A radar data integrating network was designed for synchronous relational operations among the information processing systems and the transmission characteristics were also analysed by specific models for each system. The designed data integrating systems can be divided into a simplex type and a distributed multiplex type.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.643-645
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• 2015

Real life has been actively utilizing storage from anywhere automobiles and Aviation field etc to the development of storage. Recent Big Data is stored as a number of data storage and data distribution processing emerged in research has been actively conducted to process the data. But many bottlenecks or processing speed slows down when you request the data at the same time a problem arises. In this paper consider should be used in the field of big data storing and processing large amounts of data, the process data more efficiently when the number of data request and data suggest that the weight-effective, manageable data processing system algorithm.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.54-60
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• 2018

In this paper, we analyze the trends of deep-learning based plant data processing technologies. In recent years, the deep-learning technology has been widely applied to various AI tasks, such as vision (image classification, image segmentation, and so on) and natural language processing because it shows a higher performance on such tasks. The deep-leaning method is also applied to plant data processing tasks and shows a significant performance. We analyze and show how the deep-learning method is applied to plant data processing tasks and related industries.

• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.82-87
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• 2003

Post-processing programs play an important role in the CFD data visualization and analysis. A variety of post-processing softwares have been developed and are being used in the CFD community. Developing a good quality of post-processing program requires dedication and efforts. In this paper an experience obtained through previous studies and developing post-processing programs are introduced which includes data structure and visualization algorithms.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.526-528
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• 2004

This paper describes the SAR data processing S/W package it will be able to process the SAR image. This package constructs the several modules: SAR Image processing module, measuring module of surface displacement using differential interferometric SAR method, classification module using the POLSAR data, SAR Focusing module. In this paper, briefly describe the algorithm that is adopted to the functions, and module architecture.

• International Journal of Contents
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• v.17 no.3
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• pp.74-83
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• 2021

A location-aware algorithm is proposed in this study to optimize the system performance of distributed systems for processing big data with low data reliability and application performance. Compared with previous algorithms, the location-aware data block placement algorithm uses data block placement and node data recovery strategies to improve data application performance and reliability. Simulation and actual cluster tests showed that the location-aware placement algorithm proposed in this study could greatly improve data reliability and shorten the application processing time of I/O interfaces in real-time.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1375-1384
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• 2004

Streaming data processing is an area of interest with much research under way. There has been increasing attention on the demands for efficient processing of streaming data produced in the application areas such as monitoring and sensor network. We have developed a continuous query processing system for streaming data and evaluated its performance in this paper. XML, the standard for data exchange on the web, is used as the model for the streaming data and the XQuery appended with a time interval is adopted as the query language for expressing con-tinuous queries. In the proposed system, the result is produced through background processing and materialized for reute in subsequent query processing. Through a detailed set of performance experiments, we shoed the effectiveness of the proposed system.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.11
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• pp.25-39
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• 1992

Due to the data processing development by the computer, the early warning system recently has made a remarkable evolution in its functions and performance as a component of the communication and control system which is also supported by the computer communication and intelligence system. In this paper it is presented that a integrated data processing system is designed to integrate the information sent from the various radar systems which constitute an early warning system. The suggested system model of this paper is devided into two types of structures, the centralized model and the distributed model, according to the data processing algorithm. We apply the queueing theory to analyse the performance of the designed models and the OPNET system kernel to make the analysing program with C language. From the analysis of the queueing components by applying the analysis programs to the designed systems, we got the tendancies and characteristics of both models, that is, a fast data processing performance of the distributed model and a stable data processing capability of the centralized model.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.316-320
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• 1987

This paper deals with expert system for power system fault restoration and accompanying numerical data processing. Nowadays, expert system which is a branch or artificial intelligence expands its application area to many fields. And it requires computer language for A.I. to be versatile. Expert system for power system handles numerous numerical data and language for A.I. has its deficiency in numerical data processing. However some recent version of the A.I. language rind ways of overcoming this dilemma by giving the way or linking conventional algorithmic languages to them. This study presents numerical data processing routines described in Turbo prolog which is run in IBM PC and linking numerical data processing routines written in Turbo C to Turbo prolog.