• Title/Summary/Keyword: variance component

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Optimal Design of Partially Accelerated Life Testing for Multi-Component Mixed Systems

  • Park, Hee-Chang;Jeng, Kwang-Man;Kim, Min-Hwan
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.87-95
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    • 2002
  • In this paper we consider optimal designs of partially accelerated life testing which is devised for multi-component mixed systems with the considerably long lifetime. Test items are run at both use condition and accelerated condition until a specified censoring time. The optimal criterion for the sample-proportion allocated to accelerated condition is to minimize asymptotic variance of the maximum likelihood estimators of the acceleration factor and hazard rates.

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Chemical and Sensory Characterization of Korean Commercial Rice Wines (Yakju)

  • Lee, Seung-Joo;Kwon, Young-Hee;Kim, Hye-Ryun;Ahn, Byung-Hak
    • Food Science and Biotechnology
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    • v.16 no.3
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    • pp.374-380
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    • 2007
  • Chemical and sensory profiles of 5 Korean commercial rice wines (yakju) were developed using descriptive, physicochemical, and volatile analyses. Color, 6 aroma, and 5 taste attributes of these rice wines were evaluated by a panel of 13 judges. Sample wines were analyzed for titratable acidity, ethanol content, pH, Hunter colorimeter value, organic acids, and free sugars. Volatile analysis of the samples revealed the presence of 2 acids, 7 alcohols, 19 esters, and 5 miscellaneous compounds. Based on principal component analysis of the descriptive data, rice wines were primarily separated along the first principal component, which accounted for 57% of the total variance between the rice wines with high intensities of 'color' and 'sweet aroma' versus 'ginseng' aroma.

Analysis of Sewage Plant Operation by Statistical Approach (통계방법에 의한 하수처리장 운전분석)

  • 이찬형;문경숙
    • Journal of Environmental Health Sciences
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    • v.28 no.3
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    • pp.34-38
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    • 2002
  • Statistical analysis between sewage plant operating parameters and the effluent quality was performed. We extracted two factors from principal component analysis of operating parameters and effluent quality from each plant. The total variance of 84.7%, 79.2% was explained by the two factors at SB plant and SC plant, respectively. The factors were identified at SB plant in the following order 1) the oxidation of organic material by aeration basin microbe,2) biomass in aeration basin and at SC plant 1) the oxidation of organic material by aeration basin microbe, 2) thickening of acti-vated sludge. These results suggested that the control of microbial composition might be critical on the improvement of the effluent quality and plant operating efficiency because most of the factors were related with microbes.

Test in Unbalanced Panel Regression Model with Nuisance Parameter (장애모수가 존재하는 불균형 패널회귀모형에서의 검정법)

  • 이재원;정병철;송석헌
    • The Korean Journal of Applied Statistics
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    • v.17 no.3
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    • pp.547-556
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    • 2004
  • This paper consider the testing problem of variance component for the unbalanced two-way error component model with nuisance parameter. We derive the one-sided LM test statistic for testing zero individual(time) effects assuming that the other time-specific(individual) effects are present. Using the Monte Carlo experiments, the computational more demanding LR test slightly underestimates the nominal size and has the low powers relative to LM test statistic.

Optimal Designs of Partially Constant-Stress Life Testing For Three-Component Mixed Systems

  • Park, Hee-Chang;Jeng, Kwang-Man;Kim, Min-Hwan
    • 한국데이터정보과학회:학술대회논문집
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    • 2002.06a
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    • pp.155-167
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    • 2002
  • In this paper we consider optimal designs of partially constant-stress life testing which is deviced for three-component mixed systems with the considerably long time. Mixed systems are jointed serial system with parallel system. Test items are run at both use condition and accelerated condition until a specified censoring time. The optimal criterion for the sample-proportion allocated to accelerated condition is to minimized asymptotic variance of the maximum likelihood estimators of the acceleration factor and hazard rates.

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High Compression synthetic High Coding Using Edge Sharpening (에지 선명화에 의한 고압축 Synthetic High 부호화)

  • 정성환;김남철
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.9
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    • pp.1410-1419
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    • 1989
  • In this paper, we present a new synthetic high coding method which gives high image compression ratio. Given an image, only its low-pass component is transmitted by DCT coding` the high-pass component is not transmitted but synthesized using edge sharpening on the reconstructed low-pass image at the receiver. For the DCT coding which is used to encode the low-pass image, we used an improved version of Cox's variance estimator. Also, introduced are new image quality measures called GSNR and EPR which emphasize perceptual aspects of image quality. Experimental results show that the performance of the proposed synthetic high coding is better in various quality measures than that of Cox's adaptive transform coding. Also, it yields acceptable image quality with neither apparent block effect nor visible granular noise even at high compression ratio of about 30:1.

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Chip Disposal State Monitoring in Drilling Using Neural Network (신경회로망을 이용한 드릴공정에서의 칩 배출 상태 감시)

  • , Hwa-Young;Ahn, Jung-Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.6
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    • pp.133-140
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    • 1999
  • In this study, a monitoring method to detect chip disposal state in drilling system based on neural network was proposed and its performance was evaluated. If chip flow is bad during drilling, not only the static component but also the fluctuation of dynamic component of drilling. Drilling torque is indirectly measured by sensing spindle motor power through a AC spindle motor drive system. Spindle motor power being measured drilling, four quantities such as variance/mean, mean absolute deviation, gradient, event count were calculated as feature vectors and then presented to the neural network to make a decision on chip disposal state. The selected features are sensitive to the change of chip disposal state but comparatively insensitive to the change of drilling condition. The 3 layerd neural network with error back propagation algorithm has been used. Experimental results show that the proposed monitoring system can successfully recognize the chip disposal state over a wide range of drilling condition even though it is trained under a certain drilling condition.

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An Application of the Monte Carlo Method to the Economical Circuit Design in Consideration of the Drift Reliability (표류신뢰도를 고려한 경제적 회로 설계에 대한 몬테칼로법의 적용)

  • Kyun-Hyon Tchah
    • 전기의세계
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    • v.24 no.5
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    • pp.72-80
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    • 1975
  • In this paper an application of the Monte Carlo method to optimum circuit design is discussed. T. Tsuda and T. Kiyono's algorithm based on the Monte Carlo method for solving multiple simul-taneous nonlinear equations is generalized to apply it to finding solutions of the constrained nonlinear optimization problem. The generalized algorithm derived here is directly applied to economical circuit design. In the cirsuit design, the object function is a cost function which is related to the cost of each circuit component. The constraint is the variance of the total system expressed by the variances of each circuit component. The design is to be determined so that the circuit has specified drift reliability with minimum cost. A practical example of economical circuit design and a general nonlinear function minimization is presented with food results.

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Optimal input cross-power spectra in shake table testing of asymmetric structures

  • Ammanagi, S.;Manohar, C.S.
    • Earthquakes and Structures
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    • v.9 no.5
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    • pp.1115-1132
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    • 2015
  • The study considers earthquake shake table testing of bending-torsion coupled structures under multi-component stationary random earthquake excitations. An experimental procedure to arrive at the optimal excitation cross-power spectral density (psd) functions which maximize/minimize the steady state variance of a chosen response variable is proposed. These optimal functions are shown to be derivable in terms of a set of system frequency response functions which could be measured experimentally without necessitating an idealized mathematical model to be postulated for the structure under study. The relationship between these optimized cross-psd functions to the most favourable/least favourable angle of incidence of seismic waves on the structure is noted. The optimal functions are also shown to be system dependent, mathematically the sharpest, and correspond to neither fully correlated motions nor independent motions. The proposed experimental procedure is demonstrated through shake table studies on two laboratory scale building frame models.

Dynamic state estimation for identifying earthquake support motions in instrumented structures

  • Radhika, B.;Manohar, C.S.
    • Earthquakes and Structures
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    • v.5 no.3
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    • pp.359-378
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    • 2013
  • The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.