• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.482-484
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• 1998

Abstract : Multimedia data now one of the widely used information in all the fields as the fast developments of computer techniques have been made. Traditional database systems based on textual information have limitations when applied to multimedia information. This is because simple textual descriptions are ambiguous and inadequate for searching multimedia information for multimedia databases and digital libraries. Thus, especially for image data, which is one of the important multimedia information types, which can retrieve and browse image data on the basis of pictorial queries. Therefore, this paper presents an efficient method for describing texture information in image data.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.8
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• pp.369-374
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• 2006

Due to development of internet network environments and data compression techniques, the size and amount of multimedia data has greatly increased. They are compressed before transmission or storage. Dealing with these compressed data such as video retrieval or indexing requires decompression procedure in most cases. This causes additional computations and increases the processing time. In various applications a histogram is one of the most frequently used tools. Efficiency of extracting such histograms will drop down if decompression is involved. We propose a novel scheme for extracting histograms from images that are transformed into the compressed domain by 8x8 DCT(Discrete Cosine Transform). In this scheme an averaged version of original image is obtained by a simple linear combination of DCT coefficients with the sets of coefficients we designed.

• Journal of the Korea Society for Simulation
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• v.11 no.3
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• pp.35-48
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• 2002

In the work presented here, we describe a method to extract TrueType features for supporting letter recognition. Even if variously existing document processing techniques have been challenged, almost few methods are capable of recognize a letter associated with its TrueType features supporting OCR free, which boost up fast processing time for image text retrieval. By reviewing the mechanism generating digital fonts and birth of TrueType, we realize that each TrueType is drawn by its contour of the glyph table. Hence, we are capable of deriving the segment with density for a letter with a specific TrueType, defined by the number of occurrence over a segment width. A certain number of occurrence appears frequently often due to the fixed segment width. We utilize letter recognition by comparing TrueType feature library of a letter with that from input word images. Experiments have been carried out to justify robustness of the proposed method showing acceptable results.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.19-29
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• 2013

Insights from the recent wealth of popular books on neuroscience are offered to suggest a strengthening of theory in information science. Information theory has traditionally neglected the human dimension in favour of 'scientific' theory often derived from the Shannon-Weaver model. Neuroscientists argue in excitingly fresh ways from the evidence of case studies, non-intrusive experimentation and the measurements that can be obtained from technologies that include electroencephalography, positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). The way in which the findings of neuroscience intersect with ideas such as those of Kahneman on fast and slow thinking and Csikszentmihalyi on flow, is tentatively explored as lines of connection with information science. It is argued that the beginnings of a theoretical underpinning for current web-based information searching in relation to established information retrieval methods can be drawn from this.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.241-248
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• 2006

Web is greatly contributing in providing a variety of information. Especially, as media for the purpose of development and education of human resources, the role of web is important. Furthermore, E-Learning through web plays an important role for each enterprise and an educational institution. Also, above all, fast and various searches are required in order to manage and search a great number of educational contents in web. Therefore, most of present information is composed in HTML, so there are lots of restrictions. As a solution to such restriction, XML a standard of Web document, and its various search functions is being extended and studied variously. This paper proposes a search system able to search XML in E-Learning or var ious contents of non-XML using mobile device PDA.

• Structural Engineering and Mechanics
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• v.12 no.3
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• pp.297-312
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• 2001

The accurate finite element (FE) simulation of reinforced concrete (RC) slabs, having different boundary conditions and subjected to uniformly distributed loading, has led to the use of the developed FE models for generating results of ultimate loads from predictions of 'computer-model' RC slabs having different material and geometric properties. Equations derived from these results constitute the primary database of an intelligent computer-aided-design (CAD) system developed for accurate and fast information retrieval on arbitrary slabs. The system is capable of generating a secondary database through systems of interpolation and can be used for design assistance purposes.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.11a
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• pp.110-121
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• 2001

The interest in suction piles by the oil industry was risen in the middle of 1980's. Recently, suction piles have been applied increasingly in offshore engineering due to its low cost, simplicity, efficiency, and reliability. Suction piles have normally been used as anchors of floating structures and foundations of marine structures in deep-water locations. Suction piles have several technical advantages over conventional piles and anchors; fast and easy installation at any depth of water, extremely large resistance due to its huge size, and easy retrieval by applying a positive suction pressure inside the pile, etc. Daewoo E&C Co., Ltd. has conducted a series of field suction pile installation and loading tests inside the Okpo harbor located in Geojedo and the Onsan harbor in Ulsan, Korea, during the summer of 2001, which may provide additional validation of the analytical solutions previously developed by the US Naval Facilities Engineering Service Center. This is a brief description of the general mechanisms of suction pile installation and loading capacity based on the study conducted by the US Navy and Daewoo E&C Co., Ltd.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.492-494
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• 1993

CMAC (Cerebeller Model Articulation Controller) is kind of Neural Networks that imitate the human cerebellum. For storage and retrieval of learned data, the input of CMAC is used as a key to determine the memory location. he learned information is distributively stored in physical memory. The learning of CMAC is very fast and converged well, therefore, it effects the application of Pattern Recognition. Through the our experiment of Pattern Recognition, we will prove that CMAC is very suitable for On-line real time processing and incremental learning of Neural Networks.

• Language and Information
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• v.9 no.1
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• pp.69-92
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• 2005

Pattern recognition in cognitive agents is based on (i) the uninterpreted input data (e.g. parameter values) provided by the agent's hardware devices and (ii) and interpreted patterns (e.g. templates) provided by the agent's memory. Computationally, the task consists in finding the memory data corresponding best to the input data, for any given input. Once the best fitting memory data have been found, the input is recognized by applying to it the interpretation which happens to be stored with the memorized pattern. This paper presents a fast converging procedure which starts from a few initially recognized items and then analyzes the remainder of the input by systematically checking for items shown by memory to have been related to the initial items in previous encounters. In this way, known patterns are tried first, and only when they have been exhausted, an elementary exploration of the input is commenced. Efficiency is improved further by choosing the candidate to be tested next according to frequency.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.139-151
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• 2020

Entity name recognition is a part of information extraction that extracts entity names from documents and classifies the types of extracted entity names. Entity name recognition technologies are widely used in natural language processing, such as information retrieval, machine translation, and query response systems. Various deep learning-based models exist to improve entity name recognition performance, but studies that compared and analyzed these models on Korean data are insufficient. In this paper, we compare and analyze the performance of CRF, LSTM-CRF, BiLSTM-CRF, and BERT, which are actively used to identify entity names using Korean data. Also, we compare and evaluate whether embedding models, which are variously used in recent natural language processing tasks, can affect the entity name recognition model's performance improvement. As a result of experiments on patent data and Korean corpus, it was confirmed that the BiLSTM-CRF using FastText method showed the highest performance.