• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.1-8
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• 2010

The researches about gaze recognition which current user gazes and finds the location have increasingly developed to have many application. The gaze recognition of existence all about researches have got problems because of using equipment that Infrared(IR) LED, IR camera and head-mounted of high price. This study propose and implement the gaze recognition system based on SVM using a single PC Web camera. The proposed system that divide the gaze location of 36 per 9 and 4 to recognize gaze location of 4 direction and 9 direction recognize user's gaze. Also, the proposed system had apply on image filtering method using difference image entropy to improve performance of gaze recognition. The propose system was implements experiments on the comparison of proposed difference image entropy gaze recognition system, gaze recognition system using eye corner and eye's center and gaze recognition system based on PCA to evaluate performance of proposed system. The experimental results, recognition rate of 4 direction was 94.42% and 9 direction was 81.33% for the gaze recognition system based on proposed SVM. 4 direction was 95.37% and 9 direction was 82.25%, when image filtering method using difference image entropy implemented. The experimental results proved the high performance better than existed gaze recognition system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.985-987
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using individual average difference. In order to accurately recognize an user' s emotion, the proposed model utilizes the difference between the average of the given input physiological signals and the average of each emotion state' signals rather than only the input signal. For the purpose of alleviating data sparse -ness, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of physiological signals based on a second rather than the longer total emotion response time. With the aim of easily constructing the model, it utilizes a simple average difference calculation technique and a maximum entropy model, one of well-known machine learning techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.35-44
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• 2004

In this paper, we design an efficient VLSI architecture of entropy coding algorithm in JPEG2000. Entropy coder is a context-based binary arithmetic encoder, and composed of a Context Extractor(CE) and an Arithmetic Coder(AC). We speed-up CE by skipping no-operation bits in coding passes, and AC is to be performed based on MQ coder. Because of using Qe value associated with each allowed context and probability estimation, MQ coder is a multiplication free coder that reduces computation loads and makes simple the structure of arithmetic coder. We have developed and synthesized the VHDL models of CE and AC pairs using Xilinx FPGA technology. The proposed architecture operates up to 30MHz.

• Journal of the Korean Geographical Society
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• v.30 no.3
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• pp.207-229
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• 1995

The characteristics of weather and climate in South Korea has great influences on the annual variation pattern and the appearance of the prevailing weather. The purpose of this paper is to induce the quantity of the weather entropy and annual variation pattern using the information theory and the principal component analysis. And author tried to classify the region according to the variation of its space scale, The raw materials used for this study are the daily cloudiness and precipitation during the years 1990-1994 at 69 stations in South Korea. It is divided into four classes of fine, clear, cloudy and rainy. The rcsults of this study can be summarized as follows: 1. Thc characteristics of annual variation pattern of weather entropy can be chiefly divided into five categories and the accumulated contributory rate of these is 73.1%. 2. Annual variation pattern of the first principal component reaches smaller in May, April and September than national average, and becomes greater when the winter comes. This weather entropy's quantity(Rs1) is positive in most area to the western sife of Soback Mountains and negative in most seaside area to the eastern side of Soback Mountains. 3. The characteristics of annual variation pattern of the second principal component shows that the entropy is more smaller in summer than national average and the rest of seasons shows larger, especially in January, May and September. This weather entropy's quantity(Rs2) is positive in most Honam Inland area to the western side of Soback Mountains and negative in most Youngnam Inland area to the eastern side of Soback Mountains. 4. Eight type regions (S1-S11) are classified based on the occurrences of minimum weather entropy in South Korea, and annual variation pattern of weather entropy by principal component analysis may be classified into sixteen type regions (Rs1-Rs9). Putting these things together, South Korea can be classifieed into thirty one type regions (Rs1S7-Rs9S10).

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.148-148
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• 2011

Riemann 문제는 천수방정식과 같은 쌍곡선형 방정식과 단일한 도약에 의해 불연속인 어떤 점의 좌 우에서 상수인 자료로 구성되는 초기치 문제로서 그 해법은 Godunov 방법과 같이 정확해에 의하면 정확 Riemann 해법, 근사 기법에 의하면 근사 Riemann 해법으로 불린다. 지금까지 이용되는 근사 Riemann 해법으로는 1981년에 P. L. Roe가 제안한 Roe의 선형화 기법과 1983년에 A. Harten, P. D. Lax, 그리고 B. van Leer가 제안한 HLL 기법의 수정 기법들이다. 최대 및 최소 파속만 고려하는 것으로 알려진 HLL 기법은 1988년에 B. Einfeldt의 제안에 의해 두 파속의 결정에서 Roe의 선형화 기법에 따른 고유치와 비교하는 것으로 수정되었다(HLLE 기법). 또한, 1994년에 E. F. Toro 등은 접촉파를 고려하기 위해 선형화된 지배방정식의 정확해로부터 중앙 파속을 고려하는 기법을 제안하였고, 이를 HLLC 기법으로 불렀다. 2002년에 T. Linde는 중앙 파속을 평가하기 위해 일반화된(수학적) 엔트로피 함수를 도입하였으며, van Leer는 이를 HLLL 기법으로 불렀다. 이 기법에서는 접촉파의 평가를 위해 보존변수에 대한 일반화된 엔트로피 함수로부터 중앙 파속이 유도되며, 이것과 특성 속도의 비교를 통해 최대 및 최소 파속이 결정된다. 따라서 이 기법에서는 모든 파속이 초기치로부터 결정되므로 HLLE 기법과 달리 Roe의 선형화 기법과 완전히 결별되고 HLLC 기법과 달리 정확해에 의존되지 않는 점에서 HLLL 기법은 모태인 HLL 기법의 온전한 계승으로 볼 수 있다. HLLL 기법은 여러 분야에 적용된 바 있으나, 수공학 분야에 적용된 사례는 알려진 바 없다. 이는 천수방정식에 대한 (물리적) 엔트로피 함수가 명확하지 않기 때문인 것으로 보인다. 이 연구에서는 보존변수로부터 정의되는 총 에너지를 일반화된 엔트로피 함수로 간주하여 모형을 구성하고, 정확해가 알려진 1차원 문제에 대해 적용성을 검토하였다. 정확해가 알려진 경우에 대해 모의한 결과, 1차 정도 수치해의 한계에도 불구하고, HLLL 기법의 결과는 대체로 정확해와 잘 일치하였으며 그 외의 HLL-형 기법의 그것에 비해 우수한 것으로 나타났다. 특히, 물이 빠져 바닥이 드러나는 상태에 대한 접촉 파속의 추정에서 Riemann 불변량을 이용하는 HLLC 기법에 비해 물이 빠지는 전선을 더 정확하게 포착하는 HLLL 기법의 결과는 매우 고무적이었다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.664-666
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• 2005

막횡단 단백질(Transmembrane Protein)은 약물표적(drug target)으로 신약개발로 대표되는 바이오 산업에서 중요한 연구대상이 되고 있다. 막횡단 단백질의 구조는 실험적 기법 또는 컴퓨터 모델링 기술을 이용하여 연구되고 있으며 컴퓨터 모델링 방법 중에서는 Hidden Markov Mode(HMM)에 기반한 시스템들이 좋은 성능을 보이고 있다. 그런데 이러한 시스템들은 구조형성에 관여하는 단백질의 다양한 특성에 대한 지식은 많이 고려하고 있지 않다. 만약 이러한 특성들이 고려된다면 구조 예측에 효과적인 보다 지능적인 모델을 만드는데 도움을 줄 수 있을 것이다. 본 논문은 단백질의 특성과 관련한 다양한 정보들을 융합하는데 효율적인 최대엔트로피모델(Maximum Entropy Model)을 이용하여 막횡단 단백질의 서열(sequence)로부터 막횡단 지역을 예측하는 방법을 제시하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.246-249
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• 2007

In numerical analysis for phase change material, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be used without modelling. In this study applicability of neural networks in modelling superheated vapor region of water was examined by comparing with the quadratic spline. neural network consists of an input layer with 2 nodes, two hidden layers and an output layer with 3 nodes. Quadratic spline interpoation method was also applied for comparison. Neural network model revealed smaller percentage error to quadratic spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the superheated range of the steam table.

• Proceedings of the Korean Society for Information Management Conference
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• 1999.08a
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• pp.17-20
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• 1999

내용기반 이미지 검색에서는 이미지의 하위 영역을 구분하는 방식에 대하여 다양한 접근이 이루어져 왔다. 그중 한 가지가 Stricker와 Dimai가 제안한, 이미지를 다섯개의 영역으로 나누고 그 가운데 주재 객체가 위치할 것을 가정하여 높은 가중치를 부여하는 방법인데, 본 연구에서는 이와 같은 가정이 타당할 것인가를 S.K. Chang의 PIM(Picture Information Measure) 엔트로피를 계산하여 검증하려 하였다. 실험결과 이미지의 중앙과 그 외부 영역 사이에는 유의미한 차이가 존재하는 것으로 나타났으며, 따라서 Stricker와 Dimai의 방식을 지지할 수 있을 것으로 결론 내릴 수 있다.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.1036-1046
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• 2011

MPEG and VCEG have constituted a collaboration team called JCT-VC(Joint Collaborative Team on Video Coding) and have been developing HEVC(High Efficiency Video Coding) standard. All transform coefficients in a TU(Transform Unit) have been equally quantized according to the quantization and inverse quantization method which is used in HEVC standard. Such an equal quantization is not efficient because the transformed coefficients in the TU are not eqully distributed. Furthermore, the quantized coefficients which is positioned in later scanning order cannot be efficient due to the entropy scanning method. We suggest an algorithm that transform coefficients are quantized at different values according to the position in TU considering a scanning order of entropy encoding to improve the coding efficiency. The principle of this algorithm is that quantization and inverse quantization are carried out according to the scanning order which is in accordance with the statistical characteristic of distribution of quantized transform coefficients. The proposed algorithm shows on the average of 0.34% Y BD-rate compression rate improvement.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.133-143
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• 2011

In this paper, a complexity-balancing algorithm is proposed for distributed video coding based on entropy coding. In order to reduce complexity of DVC-based decoders, the proposed method employs an entropy coder instead of channel coders and the complexity-balancing method is designed to improve RD performance with minimal computational complexity. The proposed method performs motion estimation in the decoder side and transmits the estimated motion vectors to the encoder. The proposed encoder can perform more accurate refinement using the transmitted motion vectors from the decoder. During the motion refinement, the optimal predicted motion vectors are decided by the received motion vector and the predicted motion vectors and complexity load of block is allocated by adjusting the search range based on the difference between the received motion vector and the predicted motion vectors. The computational complexity of the proposed encoder is decreased 11.9% compared to the H.264/AVC encoder and that of the proposed decoder are reduced 99% compared to the conventional DVC decoder.