• International Journal of Advanced Culture Technology
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• 제8권3호
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• pp.275-279
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• 2020

Due to the recent rapid industrialization worldwide, the number of pediatric asthma patients is increasing. And the fine dust containing heavy metals is linked to the characteristics of high toxic lead due to the increase heating in factory operation and automobile driving. It is the reason of arsenic increasing. In the treatment of pediatric asthma patients, drug administration, oral drug entry, and HMPC (Home Management Plan of Care) are used. In this paper, we analyze the relationship between the onset of asthma and the method of prescription for specific childhood asthma in the United States using EM (Expectation Maximization) and MDL (Minimum Description Length) algorithms. And the association is also analyzed by comparing the nature of specific congestion between the past prevalence of digestive asthma and the recent prevalence of environmental pollution.

• ETRI Journal
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• 제32권5호
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.

• 한국음향학회지
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• 제29권1호
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• pp.56-61
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• 2010

본 논문에서는 HMM 기반의 연속음성인식에서 음향모델의 최적화 기법을 논한다. 대부분의 음성인식 시스템에서 HMM 상태별로 동일한 개수의 가우시안 성분 (mixture component)을 사용해 왔다. 그러나, 음향 모델링에 사용되는 데이터 샘플의 개수는 HMM상태별로 다르므로 이에 따른 최적화를 수행할 경우 모델 파라미터의 개수를 효과적으로 줄일 수 있을 뿐 아니라, 디코딩 단계에서 음성인식기의 속도 및 인식 성능 개선이 기대된다. 본 연구에서 제안한 방법은 기존에 알려진 MDL (minimum description length) 기반의 음향모델 최적화 방법에서 가우시안 성분들의 통합과정에 가우시안 성분의 가중치 정보 (mixture weight)를 반영하도록 개선하였다. 인식 실험 결과, 제안한 방법은 가우시안 성분의 가중치를 반영하지 않는 기존 방법에 비해 향상된 최적화 성능을 보임을 확인할 수 있었다.

• ETRI Journal
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• 제27권6호
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• pp.747-758
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• 2005

The problem of selection among competing models has been a fundamental issue in statistical data analysis. Good fits to data can be misleading since they can result from properties of the model that have nothing to do with it being a close approximation to the source distribution of interest (for example, overfitting). In this study we focus on the preference among models from a family of polynomial regressors. Three decades of research has spawned a number of plausible techniques for the selection of models, namely, Akaike's Finite Prediction Error (FPE) and Information Criterion (AIC), Schwartz's criterion (SCH), Generalized Cross Validation (GCV), Wallace's Minimum Message Length (MML), Minimum Description Length (MDL), and Vapnik's Structural Risk Minimization (SRM). The fundamental similarity between all these principles is their attempt to define an appropriate balance between the complexity of models and their ability to explain the data. This paper presents an empirical study of the above principles in the context of model selection, where the models under consideration are univariate polynomials. The paper includes a detailed empirical evaluation of the model selection methods on six target functions, with varying sample sizes and added Gaussian noise. The results from the study appear to provide strong evidence in support of the MML- and SRM- based methods over the other standard approaches (FPE, AIC, SCH and GCV).

• 한국통신학회논문지
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• 제15권10호
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• pp.842-849
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• 1990

본 논문에서는 array processing에서, sensor array를 통해 들어오는 source signal들의 개수를 결정하는 방법들을 판정의 정확도의 관점에서 연구 고찰한다. 첫번째 방법은 Akaike의 Akaike's Information Criterion(AIC)이고, 다른 하나는 Schwartz와 Rissanen의 Minimum Description Length(MDL)이다. 실용적인 측면에서 볼 때, 신호대잡음비 (S/N)가 매우 낮은 상태에서 얻어진 한정된 양의 data를 이용하여 제한된 갯수의 sensor들로 이루어진 array로 부터, 매우 근접해 있는 source signal들의 갯수를 예측해 내는 것은 대단히 중요한 일이다. 본 논문은 simulation 결과를 통하여, source signal들이 근접해 있을수록, array의 sensor 갯수가 줄어들수록, 이용할 data의 양이 한정될수록 또 S/N가 낮아질수록, AIC이 MDL에 비해서 높은 신뢰도를 가짐을 보여준다.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.974-986
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• 2016

Reversible image watermarking, a type of digital data hiding, is capable of recovering the original image and extracting the hidden message with precision. A number of reversible algorithms have been proposed to achieve a high embedding capacity and a low distortion. While numerous algorithms for the achievement of a favorable performance regarding a small embedding capacity exist, the main goal of this paper is the achievement of a more favorable performance regarding a larger embedding capacity and a lower distortion. This paper therefore proposes a reversible data hiding algorithm for which a novel piecewise 2D auto-regression (P2AR) predictor that is based on a rhombus-embedding scheme is used. In addition, a minimum description length (MDL) approach is applied to remove the outlier pixels from a training set so that the effect of a multiple linear regression can be maximized. The experiment results demonstrate that the performance of the proposed method is superior to those of previous methods.

• 한국전자통신학회논문지
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• 제16권4호
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• pp.617-624
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• 2021

도래각 추정, 간섭제거, 신호 수신 등을 위해 수신신호에 포함되는 신호의 개수를 정확히 파악하는 것이 필요하다. 대표적인 신호 개수 추정 알고리즘으로 AIC(: Akaike Information Criterion)와 MDL(: Minimum Description Length) 알고리즘이 있는데, 이들 알고리즘은 각 기준이 최소화되는 값을 찾아 신호의 개수를 추정한다. 수신기의 배열 안테나 요소 개수가 증가하면 추정 성능이 향상되지만, 최소값을 찾기 위해 모든 안테나 요소에 대한 기준값을 계산하여야 하므로 복잡도가 크게 증가한다. 이러한 문제를 해결하기 위해, 본 논문에서는 빔공간 처리를 통해 차원을 축소시켜 계산량을 줄이면서 효율적으로 신호의 개수를 추정할 수 있는 빔공간 기반의 AIC와 MDL 알고리즘을 제안한다. 또한, 다양한 시나리오 기반의 컴퓨터 시뮬레이션을 통해 제안된 알고리즘의 성능을 평가하고 분석한다.

• 한국산학기술학회논문지
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• 제13권2호
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• pp.817-821
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• 2012

본 논문에서는 환경음 인식에 GMM(Gaussain mixture model)을 이용할 때 MDL(minimum description length)와 BIC(Bayesian information criterion) 모델선택 기준을 이용하여 최적의 혼합모델 개수를 결정하는 방법에 대해 다루었다. 실험은 모두 9가지 종류의 환경음으로부터 12차 MFCC(mel-frequency cepstral coefficients) 특징 27747개를 추출하고 이를 GMM으로 분류하였다. 각 환경음 클래스의 최적 혼합모델 개수를 추정 하기위해 MDL과 BIC를 적용하고 그 결과를 고정 개수의 혼합모델을 사용한 경우와 비교하였다. 실험 결과에 따르면 혼합모델 선택 방법을 적용한 경우가 그렇지 않은 경우에 비해 거의 유사한 인식성능을 유지하면서 계산복잡도는 BIC와 MDL를 통해 각각 17.8%와 31.7%가 감소하는 것을 확인하였다. 이는 GMM을 이용한 환경음 인식에서 BIC와 MDL 적용을 통해 계산복잡도를 효과적으로 감소시킬 수 있음을 보여준다.

• 한국측량학회지
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• 제25권6_1호
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• pp.545-555
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• 2007

3D buildings are the most prominent feature comprising urban scene. A few of mega-cities in the globe are virtually reconstructed in photo-realistic 3D models, which becomes accessible by the public through the state-of-the-art online mapping services. A lot of research efforts have been made to develop automatic reconstruction technique of large-scale 3D building models from remotely sensed data. However, existing methods still produce irregular building polygons due to errors induced partly by uncalibrated sensor system, scene complexity and partly inappropriate sensor resolution to observed object scales. Thus, a geometric regularization technique is urgently required to rectify such irregular building polygons that are quickly captured from low sensory data. This paper aims to develop a new method for regularizing noise building outlines extracted from airborne LiDAR data, and to evaluate its performance in comparison with existing methods. These include Douglas-Peucker's polyline simplication, total least-squared adjustment, model hypothesis-verification, and rule-based rectification. Based on Minimum Description Length (MDL) principal, a new objective function, Geometric Minimum Description Length (GMDL), to regularize geometric noises is introduced to enhance the repetition of identical line directionality, regular angle transition and to minimize the number of vertices used. After generating hypothetical regularized models, a global optimum of the geometric regularity is achieved by verifying the entire solution space. A comparative evaluation of the proposed geometric regulator is conducted using both simulated and real building vectors with various levels of noise. The results show that the GMDL outperforms the selected existing algorithms at the most of noise levels.

• KIEAE Journal
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• 제3권2호
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• pp.51-58
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• 2003

The purpose of this study is to present rational methods of multi-criteria optimization of the shape of energy saving buildings. The object is to determine the optimum dimension of the shape of a building, based on the following criteria: minimum building costs (including the cost of materials and construction) and yearly heating costs. Mathematical model described heat losses and gains in a building during the heating season. It takes into consideration heat losses through wall, roof, floor and windows. Particular attention was paid to have a more detailed description of heat gains due to solar radiation. On the assumption that shape of building is rectangle in order to solve the problem, the proportions of wall length and building height are determined by using non-linear programing methods(Kuhn-Tucker Conditions). The results constitute information for designers on the optimum proportions of wall lengths, height, and the ratios of window to wall areas for energy saving buildings.