• Title/Summary/Keyword: Markov-difference

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Small area estimations for disease mapping by using spatial model (질병지도 작성을 위해 공간모형을 이용한 소지역 추정)

  • An, Daeseong;Han, Junhee;Yoon, Taeho;Kim, Changhoon;Noh, Maengseok
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.1
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    • pp.101-109
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    • 2015
  • SMRs (standardized mortality rates) for major diseases, accidents, cancer are considered in small areas of administrative units such as Eup/Myeon/Dong from years 2005 to 2008. Due to small sample issue in small areas, the precision of directly estimated crude SMR for each area can be low. In this study, we consider the HGLM (hierarchical generalized linear model) with MRF (Markov random field) to account for the spatial correlations among the small areas. The effects of covariates for cause of mortality by Dongs in Seoul and disease maps based on the estimated SMR are presented. The results suggest how we analyze and interpret the difference in mortalities by small areas such as Dongs by revealing the spatial patterns.

Comparison of ICA Methods for the Recognition of Corrupted Korean Speech (잡음 섞인 한국어 인식을 위한 ICA 비교 연구)

  • Kim, Seon-Il
    • 전자공학회논문지 IE
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    • v.45 no.3
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    • pp.20-26
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    • 2008
  • Two independent component analysis(ICA) algorithms were applied for the recognition of speech signals corrupted by a car engine noise. Speech recognition was performed by hidden markov model(HMM) for the estimated signals and recognition rates were compared with those of orginal speech signals which are not corrupted. Two different ICA methods were applied for the estimation of speech signals, one of which is FastICA algorithm that maximizes negentropy, the other is information-maximization approach that maximizes the mutual information between inputs and outputs to give maximum independence among outputs. Word recognition rate for the Korean news sentences spoken by a male anchor is 87.85%, while there is 1.65% drop of performance on the average for the estimated speech signals by FastICA and 2.02% by information-maximization for the various signal to noise ratio(SNR). There is little difference between the methods.

A Beamforming Method for a Perturbed Linear Towed Array (비선형 형상 견인 어레이를 위한 빔형성 기법)

  • 김승일;도경철;오원천;윤대희;이충용
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.5
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    • pp.478-484
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    • 2002
  • Linear towed arrays (LTA) have a nonlinear shape due to tow vessel motion, ocean swells and currents. By reasons of nominally linear shape, various towed array shape estimation techniques have been developed since the perturbed shape cause the error in target detection. In this paper,, we propose the beamforming method for the perturbed LTA with simple structure. The proposed method linearizes a nonlinear phase of steering vector with position information measured by two reference sensors. It can be proved using some properties of Markov transition matrix, and iteration number of linearization process is decided by variance of cross phase difference. As a result of computer simulation in the ocean environment, beampattern of the proposed method is almost same with the ideal case in my type of array shape. In the signal-to-noise ratio (SNR) performance simlation, the DOA estimation performance of the proposed beamforming method is evaluated, and the comparison with Bartlett beamformer of the LTA shows that the proposed method can estimate. the spatial characteristic of sources more accuracy.

Difference State Number of CHMM Model to Improve the Performance of SCCRS (한국어 음성/문자 공용인식기의 성능향상을 위한 가변 상태수 CHMM모델의 구성)

  • Suk Soo-Young;Kim Min-Jung;Kim Kwang-Soo;Jung Ho-Youl;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.95-98
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    • 2002
  • 문자인식 또는 음성인식을 위해 사용되어지는 CHMM(Continuous Hidden Markov Model)모델은 일반적으로 모델의 상태수를 일정한 수로 고정하는 고정 상태수 모델 구조를 가지고 있으나, 이는 개별적인 인식 단위의 특성을 고려하지 않은 경우로써 이를 고려한 가변 상태수 모델을 사용할 경우 인식률 향상을 기대할 수 있다. 개별적인 인식 단위에 적합한 모델 상태수를 결정하는 방법으로 파라미터 히스토그램 방법과, BIC(Bayesian Information Criterion)방법을 사용하는 것이 대표적이다. 이들 방법들은 개별적인 인식단위의 우도값만을 향상시키기 위한 방법으로 전체인식률과 직접적으로 비례하지는 않는다. 따라서, 본 논문에서는 고정 상태수를 갖는 모델 적용 방법과 인식단위별 상태수 변화에 따른 인식률을 비교하였으며, 이를 바탕으로 각 모델별 상태수를 달리하는 가변 상태수 CHMM모델 구성 방법을 제안한다. 제안된 가변상태수 모델의 유효성을 확인하기 위해 음성/문자 공용인식기 중 필기체 문자 인식에 적용한 결과 제안한 LM(Local Maximum)으로 구성된 가변 상태수 모델이 MLE와 BIC로 구성된 모델과 인식률 면에서는 거의 동일한 성능을 유지하면서 전체 상태수는 MLE 모델에 비해 $31\%$, BIC로 구성된 모델에 비해 $22\%$ 감소를 나타내어 제안한 모델의 유효성을 확인할 수 있었다.

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Analysis of Cell Variation of ATM Transmission for the Poisson and MMPP Input Model in the TDMA Method (TDMA 방식에서 포아송 입력과 MMPP 입력 모델에 따른 ATM 전송의 셀 지연 변이 해석)

  • Kim, Jeong-Ho;Choe, Gyeong-Su
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.3
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    • pp.512-522
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    • 1996
  • To provide broadband ISDN service for the users in scattered locations, the application of satellite communications network is seriously considered. To trans mit ATM cells efficiently in satellite communications, it is effective to use TDM A method. However, it is necessary to have a method to compensate the cell delayvari-ation caused by the difference between TDMA and ATM. This paper optimized the cell control time(Tc) when traffic inputs have poisson or markov modulated poisson process by applying cell delay variation characteristics of time stamp method, which has the most advantages among compensation methods or cell delay variation. This paper also intorduces a method of reducing the cell clumping phenomena by adapting discrete time stamp method, including the analysis and evalutation of the range of required quality of CDV distribution by ATM transmission.The result of the experiment shows that CDV distribution-range can be controlled to 1.2$\times$Tc which reduces overall cell delay variation by discrrete time stamp method.

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Structural modal identification and MCMC-based model updating by a Bayesian approach

  • Zhang, F.L.;Yang, Y.P.;Ye, X.W.;Yang, J.H.;Han, B.K.
    • Smart Structures and Systems
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    • v.24 no.5
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    • pp.631-639
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    • 2019
  • Finite element analysis is one of the important methods to study the structural performance. Due to the simplification, discretization and error of structural parameters, numerical model errors always exist. Besides, structural characteristics may also change because of material aging, structural damage, etc., making the initial finite element model cannot simulate the operational response of the structure accurately. Based on Bayesian methods, the initial model can be updated to obtain a more accurate numerical model. This paper presents the work on the field test, modal identification and model updating of a Chinese reinforced concrete pagoda. Based on the ambient vibration test, the acceleration response of the structure under operational environment was collected. The first six translational modes of the structure were identified by the enhanced frequency domain decomposition method. The initial finite element model of the pagoda was established, and the elastic modulus of columns, beams and slabs were selected as model parameters to be updated. Assuming the error between the measured mode and the calculated one follows a Gaussian distribution, the posterior probability density function (PDF) of the parameter to be updated is obtained and the uncertainty is quantitatively evaluated based on the Bayesian statistical theory and the Metropolis-Hastings algorithm, and then the optimal values of model parameters can be obtained. The results show that the difference between the calculated frequency of the finite element model and the measured one is reduced, and the modal correlation of the mode shape is improved. The updated numerical model can be used to evaluate the safety of the structure as a benchmark model for structural health monitoring (SHM).

A Study of Reinforcement Learning-based Cyber Attack Prediction using Network Attack Simulator (NASim) (네트워크 공격 시뮬레이터를 이용한 강화학습 기반 사이버 공격 예측 연구)

  • Bum-Sok Kim;Jung-Hyun Kim;Min-Suk Kim
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.3
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    • pp.112-118
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    • 2023
  • As technology advances, the need for enhanced preparedness against cyber-attacks becomes an increasingly critical problem. Therefore, it is imperative to consider various circumstances and to prepare for cyber-attack strategic technology. This paper proposes a method to solve network security problems by applying reinforcement learning to cyber-security. In general, traditional static cyber-security methods have difficulty effectively responding to modern dynamic attack patterns. To address this, we implement cyber-attack scenarios such as 'Tiny Alpha' and 'Small Alpha' and evaluate the performance of various reinforcement learning methods using Network Attack Simulator, which is a cyber-attack simulation environment based on the gymnasium (formerly Open AI gym) interface. In addition, we experimented with different RL algorithms such as value-based methods (Q-Learning, Deep-Q-Network, and Double Deep-Q-Network) and policy-based methods (Actor-Critic). As a result, we observed that value-based methods with discrete action spaces consistently outperformed policy-based methods with continuous action spaces, demonstrating a performance difference ranging from a minimum of 20.9% to a maximum of 53.2%. This result shows that the scheme not only suggests opportunities for enhancing cybersecurity strategies, but also indicates potential applications in cyber-security education and system validation across a large number of domains such as military, government, and corporate sectors.

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A Comparison Study of Model Parameter Estimation Methods for Prognostics (건전성 예측을 위한 모델변수 추정방법의 비교)

  • An, Dawn;Kim, Nam Ho;Choi, Joo Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.25 no.4
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    • pp.355-362
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    • 2012
  • Remaining useful life(RUL) prediction of a system is important in the prognostics field since it is directly linked with safety and maintenance scheduling. In the physics-based prognostics, accurately estimated model parameters can predict the remaining useful life exactly. It, however, is not a simple task to estimate the model parameters because most real system have multivariate model parameters, also they are correlated each other. This paper presents representative methods to estimate model parameters in the physics-based prognostics and discusses the difference between three methods; the particle filter method(PF), the overall Bayesian method(OBM), and the sequential Bayesian method(SBM). The three methods are based on the same theoretical background, the Bayesian estimation technique, but the methods are distinguished from each other in the sampling methods or uncertainty analysis process. Therefore, a simple physical model as an easy task and the Paris model for crack growth problem are used to discuss the difference between the three methods, and the performance of each method evaluated by using established prognostics metrics is compared.

Genetic Variability Comparison of Wild Populations and Cultured Stocks of Flounder Paralichthys olivaceus Based on Microsatellite DNA Markers (넙치, Paralichthys olivaceus 자연 집단과 양식 집단의 유전학적 다양성 비교)

  • Jeong, Dal Sang;Noh, Jae Koo;Myeong, Jeong In;Lee, Jeong Ho;Kim, Hyun Choul;Park, Chul Ji;Min, Byung Hwa;Ha, Dong Soo;Jeon, Chang Young
    • Korean Journal of Ichthyology
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    • v.21 no.4
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    • pp.221-226
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    • 2009
  • Six microsatellite DNA markers were used to investigate the genetic variability between wild populations and cultured stocks of olive flounder Paralichthys olivaceus. The average of observed (Ho) and expected heterozygosity (He) ranged from 0.722 to 0.959, and from 0.735 to 0.937, respectively. There was no distinguishable difference between the wild populations and cultured stocks in terms of the observed and expected heterozygosities. However, number of alleles per locus differed markedly between the two fish groups: 19.7 to 21.8 for the wild populations and 12.0 to 14.7 for the cultured stocks. This result gives important information concerning the production of seedling for the improvement of genetic diversity in this species.

Derivation of the Instantaneous Unit Hydrograph and Estimation of the Direct Runoff by Using the Geomorphologic Parameters (지상인자에 의한 순간단위도 유도와 유출량 예측)

  • 천만복;서승덕
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.32 no.3
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    • pp.87-101
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    • 1990
  • The purpose of this study is to estimate the flood discharge and runoff volume at a stream by using geomorphologic parameters obtained from the topographic maps following the law of stream classification and ordering by Horton and Strahier. The present model is modified from Cheng' s model which derives the geomorphologic instantaneous unit hydrograph. The present model uses the results of Laplace transformation and convolution intergral of probability density function of the travel time at each state. The stream flow velocity parameters are determined as a function of the rainfall intensity, and the effective rainfall is calculated by the SCS method. The total direct runoff volume until the time to peak is estimated by assuming a triangular hydrograph. The model is used to estimate the time to peak, the flood discharge, and the direct runoff at Andong, Imha. Geomchon, and Sunsan basin in the Nakdong River system. The results of the model application are as follows : 1.For each basin, as the rainfall intensity doubles form 1 mm/h to 2 mm/h with the same rainfall duration of 1 hour, the hydrographs show that the runoff volume doubles while the duration of the base flow and the time to peak are the same. This aggrees with the theory of the unit hydrograph. 2.Comparisions of the model predicted and observed values show that small relative errors of 0.44-7.4% of the flood discharge, and 1 hour difference in time to peak except the Geomchon basin which shows 10.32% and 2 hours respectively. 3.When the rainfall intensity is small, the error of flood discharge estimated by using this model is relatively large. The reason of this might be because of introducing the flood velocity concept in the stream flow velocity. 4.Total direct runoff volume until the time to peak estimated by using this model has small relative error comparing with the observed data. 5.The sensitivity analysis of velocity parameters to flood discharge shows that the flood discharge is sensitive to the velocity coefficient while it is insensitive to the ratio of arrival time of moving portion to that of storage portion of a stream and to the ratio of arrival time of stream to that of overland flow.

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