• Journal of Information Processing Systems
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• v.4 no.1
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• pp.9-16
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• 2008

This paper describes the design and implementation of a two-tier DBMS for handling massive data and providing faster response time. In the present day, the main requirements of DBMS are figured out using two aspects. The first is handling large amounts of data. And the second is providing fast response time. But in fact, Traditional DBMS cannot fulfill both the requirements. The disk-oriented DBMS can handle massive data but the response time is relatively slower than the memory-resident DBMS. On the other hand, the memory-resident DBMS can provide fast response time but they have original restrictions of database size. In this paper, to meet the requirements of handling large volumes of data and providing fast response time, a two-tier DBMS is proposed. The cold-data which does not require fast response times are managed by disk storage manager, and the hot-data which require fast response time among the large volumes of data are handled by memory storage manager as snapshots. As a result, the proposed system performs significantly better than disk-oriented DBMS with an added advantage to manage massive data at the same time.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1747-1758
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• 2016

In this paper, we propose a new fast Hough transform to improve the processing time and line detection of Hough transform that is widely used in various vision systems. First, for the fast processing time, we reduce the number of features by using multi-statistical methods and also reduce the dimension of angle through six separate directions. Next, for improving the line detection, we effectively detect the lines of various directions by designing the line detection method which detects line in proportion to the number of features in six separate directions. The proposed method was evaluated with previous methods and obtained the excellent results. The processing time was improved in about 20% to 50% and line detection was performed better in various directions than conventional methods with experimental images.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.11
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• pp.804-815
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• 1988

Real-time image processing algorithms to detect position and orientation of rectangular type electronic components are developed. The position detection algorithm is implemented with the use of projection method which is insensitive to noise. Also dynamic thresholding method of projection is employed in order to distinguish between the boundary of a component and any marking on the component. The orientation is determined by Hough transform of boundary candidates of a component, which is obtained a priori by a simple edge detection method. For real-time processing of both position and orientation for a component which is not aligned well, parallel processing method of image data is proposed and tested in real-time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5694-5711
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• 2017

The technology of cloud computing is growing very quickly, thus it is required to manage the process of resource allocation. In this paper, load balancing algorithm based on honey bee behavior (LBA_HB) is proposed. Its main goal is distribute workload of multiple network links in the way that avoid underutilization and over utilization of the resources. This can be achieved by allocating the incoming task to a virtual machine (VM) which meets two conditions; number of tasks currently processing by this VM is less than number of tasks currently processing by other VMs and the deviation of this VM processing time from average processing time of all VMs is less than a threshold value. The proposed algorithm is compared with different scheduling algorithms; honey bee, ant colony, modified throttled and round robin algorithms. The results of experiments show the efficiency of the proposed algorithm in terms of execution time, response time, makespan, standard deviation of load, and degree of imbalance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.171-171
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• 2000

We have developed m innovative surface inspection system for automated quality control for steel products in POSCO. We had ever installed the various kinds of surface inspection systems, such as a linear CCD and a laser typed surface inspection systems at cold rolled strips production lines. But, these systems cannot fulfill the sufficient detection and classification rate, and real time processing performance. In order to increase detection and classification rate, we have used the Dark, Bright and Transition Field illumination and area type CCD camera, and fur the real time image processing, parallel computing has been used. In this paper, we introduced the automatic surface inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms and its performance obtained at the production line.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2015.11a
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• pp.289-290
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• 2015

In this experiment, nitriding treatment has been performed at $400^{\circ}C$ with various $N_2$ content and with changing processing time on AISI 420 martensitic stainless steel to investigate the expanded martensite layer (${\alpha}^{\prime}_N$ layer) formation behavior. Nitriding was implemented with changing $N_2$ content from 10% to 25% for 15 hrs and processing time was changed from 4hr to 15hr at 25% $N_2$ content. After treatment, the behavior of the ${\alpha}^{\prime}_N$ layer was investigated by optical microscopy, X-ray diffraction, and micro-hardness testing. Potentiodynamic polarization test was also used to evaluate the corrosion resistance of the samples. It was found that the surface hardness and ${\alpha}^{\prime}_N$ layer thickness increases with increasing $N_2$ percentage and processing time. Although their corrosion behaviors are worse than the bare sample.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.260-264
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• 1987

Algorithms to detect in real-time both position and orientation of rectangular type electronic components are developed for industrial vision. In order to conduct detection in real-time, parallel processing algorithm of image date which uses several control processor is proposed. Image processing area is divided into several regions which can be processed by each cpu. As a result, processing time is improved when two control processors are used and real-time pattern recognition of not-well-aligned components is accomplished.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.547-549
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• 2021

In Artificial Intelligence analysis, the process of creating a model and verifying it is a task that requires computational processing time because it is Batch Processing performed with already generated data. We need to model, validate, and predict real-time data, such as stocks and defense information, with data generated directly in front of us. As a solution to this, we solve it by applying techniques to segment the data required for artificial intelligence modeling tasks in order of time processing and distribute the data across multiple processes.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1988-1995
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• 2000

In this paper, we have proposed the contrast control method for improving image quality. The proposed method can be easily applied to the FPD (flat panel display) which requires real-time processing because of its lower hardware complexity that the conventional methods. In addition, it can flexibly control the contrast of input image by arraying the weight values that control the contrast range. Visual test and standard deviation of their histograms have been introduced to evaluate the results of proposed method and the original images. The functional operation of he proposed method has been verified using the SYNOPSYS VHDL tool and computer simulation. Its results show that he proposed method might be very suitable for real-time processing on the FPD.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.952-965
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• 1993

A simulation modeling is necessary for the optimal design of a rice processing plant, which consists of a facility (a silo system) of rice drying and storage and a rice mill plant. In a rice processing plant, the production scheduling and the decision on capcity of each unit based on a queuing theory is very important and difficult. In this study a process-oriented simulation model was developed for the design of a rice drying and storage system with SLAMSYSTEM. The simulation model is capable of simulating virtually all the processing activities and provides work schedules which minimize total processing time , mean flow time and bottleneck of the plant system and estimate drying time for a batch in a drying silo. Model results were used for determination the size and capacity of each processing unit and for analyzing the performance of the plant . The developed model was actually applied to construct a grain silo system for rice drying and storage.