• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.151-154
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• 2008

In this paper, this program which is Retrieval System using Image Gray-scale histogram and Edge features is used to reduce the errors incurred by inputting methods which are used in a current Retrieval System. The Retrieval Algorithm is proceeding with several steps which are extracting features of images quality, extracting edge features and refining images, analysing extracted features, retaining important information from analyzed features, retrieving retained information from database, extracting and comparing among images from retrieved database. The proposed Retrieval System is used for a fast retrieval with accuracy and it is confirmed through simulations.

• Journal of the Korea Computer Industry Society
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• v.6 no.2
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• pp.365-372
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• 2005

Generally, In a application program the core part for parallel processing is a loop. therefore exist data dependencies between the array index variables of a loop. The data dependence relations between statements which from variable or constant dependence distance are specially complex. Therefore extracting parallelism for those statements at compile time is very difficult. in this paper, among the proposed methods of extracting parallelism, analysis the unimodular method and non-unimodular method and grasping the merits and demerits of them. hereafter, this method will go far toward solving the effectively extracting parallelism of the loop.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.328-331
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• 2000

In this paper , we propose a texture feature extraction method of reduce the massive computational time on extracting texture, features of large sized medical such as MRI, CT-scan , and an index structure, called GLTFT, to speed up the retrieval performance. For these, the original image is transformed into a compressed image by Wavelet transform , and textural features such as contrast, energy, entropy, and homogeneity of the compressed image is extracted by using GLCM(Gray Level Co-occurrence Metrix) . The proposed index structure is organized by using the textural features. The processing in compressed domain can give the solution of storage space and the reduction of computational time of feature extracting . And , by GLTFT index structure, image retrieval performance can be expected to be improved by reducing the retrieval range . Our experiment on 270 MRIs as image database shows that shows that such expectation can be got.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.2
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• pp.43-45
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• 2000

In this study, present a method for extracting the BJT 1/f noise model parameters fabricated by BICMOS process. From the geometric analysis of the Kf, we show that Kf is in inverse proportion to emitter area. And it is extracting that $K=0.8\times10_{-20}, A_f=2, \alpha=1$ values.

• Bulletin of the Korean Mathematical Society
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• v.41 no.3
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• pp.573-587
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• 2004

Disentangling is the essential operation of Feynman's operational calculus for noncommuting operators. Thus formulas which simplify this operation are central to the subject. In a recent paper the procedure for 'extracting a linear factor' has been established in the setting of Feynman's operational calculus for time independent operators $A_1, ... , A_n$ and associated probability measures ${\mu}_1,..., {\mu}_n$. While the setting just described is natural in many circumstances, it is not natural for evolution problems. There the measures should not be restricted to probability measures and it is worthwhile to allow the operators to depend on time. The main purpose for this paper is to extend the procedure for extracting a linear factor to this latter setting. We should mention that Feynman's primary motivation for developing an operational calculus for noncommuting operators came from a desire to describe the evolution of certain quantum systems.m systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.2
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• pp.373-380
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• 1994

In this paper, we proposed a method of extracting optimum features of speech signal to adjust signal level. For extracting features of speech signal we used FRLS(Fast Recursive Least Square) algorithm, we adjusted each frames of equal to constant level, and extracted optimum features of speech signal by using equalized autocorrelation function proposed in this paper.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.2
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• pp.127-137
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• 1988

In this paper, the extracting method for the control subcode in digital audio systems is pressented. And also the subcode format to display on the screen and a extracting method of the control signals within the DAS information are described. The extracted control signal from DAS is analyzed in the microprocessor systems and the microprocessor systems generate the screen information and then transmit to the CRT controller by the proposed protool.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.327-335
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• 2000

The spent fuel rod extracting machine is automatically operated in high radioactive environment, so high reliability of operation is required. In this paper, to enhance the reliability of this machine by providing a close monitoring capability. a real time graphic simulation method is suggested. This method utilizes conventional IGRIP (Interactive Graphics Robot Instruction Program) 3D graphic simulation tool to visualize and simulate the 3D graphic model of this machine. Also, the dedicated protocol is defined for transmission of the operational data of the machine. The real time graphic simulation is realized by developing the socket module between a graphic workstation and a machine control computer through the TCP/IP network and by dividing the 3D graphic simulation GSL(Graphic Simulation Language) program as a small sized sub routine. The suggested method is implemented while automatically operating the rod extracting machine. The result of implementation shows that the real time 3D graphic simulation is well synchronized with the actual machine according to the operational data.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.262-265
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• 1999

This paper describes a new method for object extraction necessary for image tracking systems. The extraction method which this paper proposes here is that an M-array is set between a camera and the object and the obtained image including the object and M-array is pro-cessed for extracting the object. The image processing utilizes a characteristic of M-array which is robust to noise. When an M-array is overlapped on the object in background image, the object woud have a part of M-array, which is detected by use of partial correlation between the mosaic image of M-array and the standard M-array. Thus the shape and position of the object are extracted by extracting a common domain of width of high correlation value. Experiments are carried out by using an actual photo of Kumamoto city taken from an airplane as background, and by use of a rectangular and circular object. The results of experiment show a wide application of this method for practical image tracking systems.