• Title/Summary/Keyword: Discrete observations

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Classification of a binary group variable with dependece structure (종속구조를 가진 집단변수의 판별-분류에 관한 연구)

  • 황선영;나은정
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.177-184
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    • 1998
  • Most of the research on discrimination and classification analysis has been directed to the situation where the data consist of independent observations. However, it is often the case in practice that a dependence structure between objects does exist, in particular, for the time series data. This article is handling such a case and is concerned with the problem of classifying new object when the dependence can be modelled by a discrete time series via conditional autologistic transition probability.

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Measure of Effectiveness Analysis of Passive SONAR System for Detection (수동소나시스템에서 탐지효과도 분석)

  • Cho, Jung-Hong;Kim, Jea-Soo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.3
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    • pp.272-287
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    • 2012
  • The optimal use of sonar systems for detection is a practical problem in a given ocean environment. In order to quantify the mission achievability in general, measure of effectiveness(MOE) is defined for specific missions. In this paper, using the specific MOE for detection, which is represented as cumulative detection probability(CDP), an integrated software package named as Optimal Acoustic Search Path Planning(OASPP) is developed. For a given ocean environment and sonar systems, the discrete observations for detection probability(PD) are used to calculate CDP incorporating sonar and environmental parameters. Also, counter-detection probability is considered for vulnerability analysis for a given scenario. Through modeling and simulation for a simple case for which an intuitive solution is known, the developed code is verified.

Tracking Filter Design for a Maneuvering target Using Jump Processes

  • Lim, Sang-Seok
    • Journal of Electrical Engineering and information Science
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    • v.3 no.3
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    • pp.373-384
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    • 1998
  • This paper presents a maneuvering target model with the maneuver dynamics modeled as a jump process of Poisson-type. The jump process represents the deterministic maneuver(or pilot commands) and is described by a stochastic differential equation driven by a Poisson process taking values a set of discrete states. Employing the new maneuver model along with the noisy observations described by linear difference equations, the author has developed a new linear, recursive, unbiased minimum variance filter, which is structurally simple, computationally efficient, and hence real-time implementable. Futhermore, the proposed filter does not involve a computationally burdensome technique to compute the filter gains and corresponding covariance matrices and still be able to track effectively a fast maneuvering target. The performance of the proposed filter is assessed through the numerical results generated from the Monte-Carlo simulation.

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NEW VARIABLE STARS IN THE REGION OF THE OPEN CLUSTER M38 (NGC 1912) II (산개성단 M38(NGC 1912) 영역의 새로운 변광성 II)

  • Jeon, Young-Beom
    • Publications of The Korean Astronomical Society
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    • v.25 no.2
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    • pp.31-49
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    • 2010
  • Next to Paper I (Jeon 2009a), time-series BV CCD images of the open cluster M38 were taken for 4 nights on December, 2009. The observations have been carried out for total 27 nights. In addition to the 20 variable stars in the Paper I, the discovery of 44 new variable stars has been presented in this paper: $6{\delta}$ Scuti stars, $2{\gamma}$ Doradus stars, 18 eclipsing binaries and 18 semi-long periodic and/or slow irregular type variable stars. For the V photometry of the ${\delta}$ Scuti and ${\gamma}$ Doradus stars, multi-frequency analysis was performed using the Discrete Fourier Transform and linear least-square fitting. The period search for the eclipsing binaries and the semi-long periodic and/or slow irregular type variable stars was performed by phase fitting method. As a result, the periods for 23 variable stars among the 44 ones were defined.

A Theoretical Study on the Dispersion of Elastic Waves in Particulate Composites (입자복합재료 내부의 탄성파 분산에 관한 이론적 연구)

  • 김진연;이정권
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.7
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    • pp.1697-1704
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    • 1994
  • Elastic wave propagation in discrete random medium studies to predict dynamic effective properties of composite materials containing spherical inclusions. A self-consistent method is proposed which is analogous to the well-known coherent potential approximation. Three conditions that must be satisfied by two effective elastic moduli and effective density are derived for the time without limit of frequency. The derived self-consistency conditions have the physical meaning that the scattering of coherent wave by the constituents in effective medium is vanished on the average. The frequency-dependent complex effective wave speed and coherent attenuation can be obtained by solving the derived self-consistency conditions numerically. The wave speed and attenuation obtained from present theory are shown to be in the better agreements with previous experimental observations than the previous theory.

The Effective Temperature of the N Stars (탄소성(炭素星)(N성(星))의 유효온도)

  • Lee, Young-Bom
    • Journal of The Korean Astronomical Society
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    • v.8 no.1
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    • pp.11-14
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    • 1975
  • Photoelectric observations were made of four N stars (HD 51208, HD 75021, V 1942 Sgr, and RU Vir) at careful1y chosen discrete wavelengths between $7000{\AA}\;and\;11000{\AA}$ with $30{\AA}$ bandpass width. Their effective temperatures have been derived by fitting the black-body radiation curve to the observed continuum intensities at $7800{\AA},\;9000{\AA}\;and\;10800{\AA}$. The resulting temperature ranges from $2500^{\circ}K\;to\;2900^{\circ}K.$. It is probable that almost all the N stars belong to this range of temperature. However, the temperatures of very red N stars can not be well determined due to large variability and redistribution of their radiation energy arising from the graphite shells around them.

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Bayesian Multiple Change-Point Estimation and Segmentation

  • Kim, Jaehee;Cheon, Sooyoung
    • Communications for Statistical Applications and Methods
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    • v.20 no.6
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    • pp.439-454
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    • 2013
  • This study presents a Bayesian multiple change-point detection approach to segment and classify the observations that no longer come from an initial population after a certain time. Inferences are based on the multiple change-points in a sequence of random variables where the probability distribution changes. Bayesian multiple change-point estimation is classifies each observation into a segment. We use a truncated Poisson distribution for the number of change-points and conjugate prior for the exponential family distributions. The Bayesian method can lead the unsupervised classification of discrete, continuous variables and multivariate vectors based on latent class models; therefore, the solution for change-points corresponds to the stochastic partitions of observed data. We demonstrate segmentation with real data.

Comparison of Three Evolutionary Algorithms: GA, PSO, and DE

  • Kachitvichyanukul, Voratas
    • Industrial Engineering and Management Systems
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    • v.11 no.3
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    • pp.215-223
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    • 2012
  • This paper focuses on three very similar evolutionary algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). While GA is more suitable for discrete optimization, PSO and DE are more natural for continuous optimization. The paper first gives a brief introduction to the three EA techniques to highlight the common computational procedures. The general observations on the similarities and differences among the three algorithms based on computational steps are discussed, contrasting the basic performances of algorithms. Summary of relevant literatures is given on job shop, flexible job shop, vehicle routing, location-allocation, and multimode resource constrained project scheduling problems.

Decentralized Moving Average Filtering with Uncertainties

  • Song, Il Young
    • Journal of Sensor Science and Technology
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    • v.25 no.6
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    • pp.418-422
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    • 2016
  • A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

A Generalization of the Discrete Feedback Adjustment by Rational Subgrouping

  • Park, Changsoon;Moonsup Song;Lee, Jaeheon
    • Journal of the Korean Statistical Society
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    • v.27 no.2
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    • pp.237-249
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    • 1998
  • Process adjustment has been widely used in production processes in order to set the output characteristic as close as to the target. Box and Kramer(1992) developed a feedback adjustment control procedure for process adjustment. We generalize their procedure by using a rational subgrouping of sequential observations. In this paper the feedback control rule of the rational subgrouping is proposed and the overall expected cost is evaluated. Also properties of the proposed control scheme are illustrated and compared to Box and Kramer's in the context of the expected cost.

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