• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.69-74
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• 2015

In this paper the patterns of information system is reduced so that control rules can guarantee fast response of queries in database. Generally an information system includes many kinds of necessary and unnecessary attribute. In particular, inconsistent information system is less likely to acquire the accuracy of response. Hence we are interested in the simple and understandable rules that can represent useful patterns by means of rough entropy and Bayesian posterior probability. We propose an algorithm which can reduce control rules to a minimum without inadequate patterns such that the implication between condition attributes and decision attributes is measured through the framework of rough entropy. Subsequently the validation of the proposed algorithm is showed through test information system of new employees appointment.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.93-100
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• 2009

In this paper, we propose a Difference Image Entropy based gaze direction recognition system. The Difference Image Entropy is computed by histogram levels using the acquired difference image of current image and reference images or average images that have peak positions from $-255{\sim}+255$ to prevent information omission. There are two methods about the Difference Image Entropy based gaze direction. 1) The first method is to compute the Difference Image Entropy between an input image and average images of 45 images in each location of gaze, and to recognize the directions of user's gaze. 2) The second method is to compute the Difference Image Entropy between an input image and each 45 reference images, and to recognize the directions of user's gaze. The reference image is created by average image of 45 images in each location of gaze after receiving images of 4 directions. In order to evaluate the performance of the proposed system, we conduct comparison experiment with PCA based gaze direction system. The directions of recognition left-top, right-top, left-bottom, right-bottom, and we make an experiment on that, as changing the part of recognition about 45 reference images or average image. The experimental result shows that the recognition rate of Difference Image Entropy is 97.00% and PCA is 95.50%, so the recognition rate of Difference Image Entropy based system is 1.50% higher than PCA based system.

• Journal of IKEEE
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• v.17 no.3
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• pp.352-359
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• 2013

This paper proposes an entropy coding unit for H.264/AVC baseline profile. Entropy coding requires code tables for macroblock encoding. There are patterns in codewords of each code tables. In this paper, the patterns between codewords are analyzed to reduce the hardware cost. The entropy coding unit consists of Exp-Golomb unit and CAVLC unit. The Exp-Golomb unit can process five code types in a single unit. It can perform Exp-Golomb processing using only two adders. While typical CAVLC units use various code tables which require large amounts of resources, the sizes of the tables are reduced to about 40% or less of typical CAVLC units using relationships between table elements in the proposed CAVLC unit. After the Exp-Golomb unit and the CAVLC unit generate code values, the entropy unit uses a small size shifter for bit-stream generation while typical methods are barrel shifters.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.73-76
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• 2000

본 논문은 표준완성형코드를 표준으로 허프만 부호를 생성하기 위해 부호화 효율이 가장 높은 곳에서 예외 부호화를 통해 최적의 허프만 부호를 얻는다. 현재 우리나라의 DTV는 한글문자를 압축하지 않고 전송하는 형태이며, 본격적인 데이터 방송이 시작되면 한글 데이터가 차지하는 전송량으로 인한 심각한 문제가 야기된다. 본 논문에서는 데이터 방송에서 문제가 되는 전송량을 줄이기 위해 한글 전용 최적의 허프만 부호를 생성하여 일련의 해결책을 찾고자 하며 영문 위주인 데이터 압축기술을 한글에 맞게 적용하여 DTV 방송용 한글 전용 압축부호를 만드는데 있다.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.109-114
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• 2015

This paper presents a computational model on the transfer of airborne fine particles to analyze the similarities and influences among the 25 districts in Seoul by quantifying a time series data collected from each district. The properties of each district are driven with the model of a time series of the fine particle concentrations, and the calculation of edge-based weights are carried out with the transfer entropies between all pairs of the districts. We applied a modularity-based graph clustering technique to detect the communities among the 25 districts. The result indicates the discovered clusters correspond to a high transfer-entropy group among the communities with geographical adjacency or high in-between traffic volumes. We believe that this approach can be further extended to the discovery of significant flows of other indicators causing environmental pollution.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.87-94
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• 2004

The feature subset selection is used as a preprocessing step of a teaming algorithm. If collected data are irrelevant or redundant information, we can improve the performance of learning by removing these data before creating of the learning model. The feature subset selection can also reduce the search space and the storage requirement. This paper proposed a new feature subset selection algorithm that is using the heuristic function based on entropy to evaluate the performance of the abstracted feature subset and feature selection. The ACS algorithm was used as a search method. We could decrease a size of learning model and unnecessary calculating time by reducing the dimension of the feature that was used for learning.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.10
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• pp.947-954
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• 2009

Starting from the Eu's GH(Generalized Hydrodynamic) theory, the multi-species GH numerical solver is developed in this research and its computatyional behaviors are examined for the hypersonic rarefied flow over an axisymmetric body. To improve the accuracy of the developed multi-species GH solver, various slip-wall boundary conditions are tested and the computed results are compared. Additionally, in order to validate the entropy characteristics of the GH equation, the entropy production and entropy generation rates of the GH equation are investigated in the 1-dimensional normal shock structure test at a high Knudsen number.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.774-777
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• 2017

사진에는 의도하지 않은 노이즈나 찍는 과정 중에 발생한 실수나 문제로 원치 않게 가려진 부분이 있을 수 있는데, 이미지 완성 어플리케이션은 사용자가 전문적인 프로그램이나 전문가의 도움 없이 노이즈나 가려진 부분을 제거할 수 있도록 하였다. 본 논문에서는 GAN(Generative Adversial Network) 모델에 노이즈가 있는 사진을 입력으로 넣어 노이즈가 제거 된 사진을 생성하도록 하였고, 생성 된 사진과 기존 이미지가 자연스럽게 합성 될 수 있도록 보정을 하여 완성 된 이미지를 출력하는 어플리케이션을 제안한다. GAN 분류 모델의 시그모이드 교차-엔트로피와 생성이미지와 원본이미지간의 평균 제곱 오차를 함께 최소화 하도록 생성 모델을 학습시켰고, 낮은 평균 제곱 오차를 가지는 완성 이미지를 생성 할 수 있었다. 이미지 보정을 통해 생성 된 이미지와 입력 이미지와의 밝기 차이를 해소시켜 좀 더 자연스러운 완성 이미지 결과를 얻을 수 있었다.

• Journal of Energy Engineering
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• v.22 no.2
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• pp.120-127
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• 2013

This study investigated the characteristics of heat transfer and pressure drop for cross-flow heat exchanger of premixed combustion system. The premixed burner was in front of a heat exchanger, and the number of heat exchanger modules was changed to investigate the characteristics of NOx and CO emissions with various equivalence ratios. In addition, the effectiveness, entropy generation and pressure drop were calculated by various number of heat exchanger modules and the performance of heat exchanger was analyzed by the exergy loss.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.27-34
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• 2006

In this study, we propose this new algorithm that generates score function in ICA(Independent Component Analysis) using entropy theory. To generate score function, estimation of probability density function about original signals are certainly necessary and density function should be differentiated. Therefore, we used kernel density estimation method in order to derive differential equation of score function by original signal. After changing formula to convolution form to increase speed of density estimation, we used FFT algorithm that can calculate convolution faster. Proposed score function generation method reduces the errors, it is density difference of recovered signals and originals signals. In the result of computer simulation, we estimate density function more similar to original signals compared with Extended Infomax and Fixed Point ICA in blind source separation problem and get improved performance at the SNR(Signal to Noise Ratio) between recovered signals and original signal.