• Journal of Korean Society of Archives and Records Management
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• v.10 no.1
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• pp.7-29
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• 2010

This article intends to establish a creation, management and preservation process of digital oral records. Because oral records is the work that will record memories of survivors, it is necessary of creating, managing and preserving reliable oral records; Oral records is the work that needs cooperations among interviewer, interviewee and cameraman, the formulation of systematic process can be called an essential issues. Moreover creating, managing and preserving digital oral records need the formulation of systematic process. Therefore this article establish creation process and management and preservation process of digital oral records based on examining a generic character of digital oral records.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.14-21
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• 1995

This paper presents a parallel sorting algorithm suitable for the SIMD multiprocessor. The algorithm finds pivots for partitioning the data into ordered subsets. The data can be evenly distributed to be sorted since it uses the probability theory. For n data elements to be sorted on p processors, when $n{\geq}p^2$, the algorithm is shown to be asymptotically optimal. In practice, sorting 8 million data items on 64 processors achieved a 48.43-fold speedup, while the PSRS required a 44.4-fold speedup. On a variety of shared and distributed memory machines, the algorithm achieved better than half-linear speedups.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.883-898
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• 1996

In this paper, we propose improved method to recognize the shape for enhancing the quality of the pattern recognition system by compressing the source images. In the proposed method, we reduced the data amount by skeletonizing the source images using mathematical morphology, and then matched patterns after accomplishing the translation and scale normalization, and rotation invariance on the transformed images. Through the scale normalization, it was possible for the shape recognition at minimum amount of the pixel by giving the weight to the skeleton pixel. As the source images was replaced by the skeleton images, it was possible to reduce the amount of data and computational loads dramatically, and so become much faster even with a smaller memory capacity. Through the experiment, we investigated the optimum scale factor and good result was proved when realizing the pattern recognition system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.1
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• pp.122-128
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• 2008

An word relay game contributes to rehabilitation and treatment of language disorders such as aphasia. As a computer is better than human in memorizing very large vocabularies, the computer has much advantage over people in word relay game. Such the game result in decrease the motivation of players and patients in treatment of language disorders. To make people to continue word relay and to be effective to remedy language disorders, the game need to be intelligent and familar with a person. This paper proposes an implementation of intelligent Korean word relay game, which considers characteristics of Korean word usage patterns. The gaem is intelligent in constructing vocabulary database and choosing an answer considering the level of player.

• 한국HCI학회:학술대회논문집
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• 2007.02b
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• pp.179-184
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• 2007

제품의 사용자 인터페이스를 개발하기 위해서는 해당 제품의 사용 행태를 정확하게 파악하는 것이 핵심적이다. 사용자 행태에 관한 정보를 수집하는 방법으로는 설문이나 개별/집단 면접 등이 흔히 사용되고 있으나, 이는 사용자들의 기억에 의존하는 간접적인 방법이기 때문에 그 정확성을 보장할 수 없다는 것이 단점으로 지적된다. 이 연구에서는 사용자 조작 로그(Log)를 기록, 수집하는 방법을 활용하여 가전 제품의 사용 행태에 대한 정보를 직접적으로 파악하였고 그 결과를 바탕으로 사용자 중심 인터페이스 디자인을 개발하고자 하였다. 디지털TV실사용자 가구들을 조사 대상으로 선발한 후 해당 가정의 실제 사용 환경에서 약 1개월간 사용 로그를 기록하였다. 로그 수집과 함께 면접 설문도 실시하였다. 수집된 로그를 통계적으로 분석하여 제품의 주요 기능별 사용 빈도와 패턴을 추출해 낼 수 있었다. 이 결과를 면접에서 대상자들이 응답한 내용과 비교하여 간접 조사 방법의 정확도를 검증해 보았다. 로그 분석 결과에서 도출된 사용 행태 데이터를 근거로 사용자 맞춤 인터페이스 기능을 제안하였다. 또한 각 가구별 결과를 2차 분석하여, 사용 행태 데이터를 기반으로 한 사용자 세분화(Segmentation)를 하였고 각 세그먼트(Segment)별 주요 특징을 도출해 낼 수 있었다. 이러한 여러 분석 결과는 가전 제품의 사용자 중심 인터페이스 개발에 사용 Log분석이 활용될 다양한 가능성과 유용성을 보여주었다.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.131-135
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• 2006

A seismic waveform inversion for prestack seismic data based on the Gauss-Newton method is presented. The Gauss-Newton method for seismic waveform inversion was proposed in the 80s but has rarely been studied. Extensive computational and memory requirements have been principal difficulties. To overcome this, we used different sizes of grids in the inversion stage from those of grids in the wave propagation simulation, temporal windowing of the simulation and approximation of virtual sources for calculating partial derivatives, and implemented this algorithm on parallel supercomputers. We show that the Gauss-Newton method has high resolving power and convergence rate, and demonstrate potential applications to real seismic data.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.824-830
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• 2003

RPA (Recursive Partition Averaging) method was proposed in order to improve the storage requirement and classification rate of the Memory Based Reasoning. That algorithm worked well in many areas, however, the major drawbacks of RPA are it's pattern averaging mechanism. We propose an adaptive OHC algorithm which uses the FPD(Feature-based Population Densimeter) to increase the classification rate of RPA. The proposed algorithm required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the RPA. Also, by reducing the number of stored patterns, it showed a excellent results in terms of classification when we compare it to the k-NN.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.291-295
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• 2008

In this paper, we propose an input image reduction method to solve the problems of Radon transform which is a line structure analysis tool to correct a rotated object through a vision system. First we extract an object image removed background from the input image. Then we also select a reduced object image as a final input mage of Radon transform from the object image by considering slope. Finally we extract a rotated angle by using Radon transform with the final input image and correct the rotated object with the angle. In experimental results, we could improve the process time of about 64%, reduce the memory space of about 18% and make progress the line detection rate of about 18%.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.63-68
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• 2018

Interests in face recognition area have been increasing due to diverse emerging applications. Face recognition algorithm from a two-dimensional source could be challenging in dealing with some circumstances such as face orientation, illuminance degree, face details such as with/without glasses and various expressions, like, smiling or crying. Hopfield Network capabilities have been used specially within the areas of recalling patterns, generalizations, familiarity recognitions and error corrections. Based on those abilities, a specific experimentation is conducted in this paper to apply the Redundant Parallel Hopfield Network on a face recognition problem. This new design has been experimentally confirmed and tested to be robust in any kind of practical situations.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1849-1857
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• 1999

We proposed the RPA (Recursive Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. This algorithm recursively partitions the pattern space until each hyperrectangle contains only those patterns of the same class, then it computes the average values of patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance. The proposed algorithm used 30~90% of memory space that is needed in the k-NN (k-Nearest Neighbors) classifier, and showed a comparable classification performance to the k-NN. Also, by reducing the number of stored patterns, it showed an excellent result in terms of classification time when we compare it to the k-NN.