• Title/Summary/Keyword: Real variance

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Empirical model of over-all ship's magnetism (총체적 선체현장의 실험모델)

  • 박길현;정태권;이상집
    • Journal of the Korean Institute of Navigation
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    • v.13 no.3
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    • pp.1-20
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    • 1989
  • In order to provide a basic information to locate the sensor of remote-indicating magnetic compass onboard, an empirical model for the over-all ship's magnetism was developed based on the periodicity of the observed magnetic field around the vessels. The values of model parameters were determined by least-square method and optimum numbers of them were fixed using Akaike's information criterion theory, and also an approximation method to determine parameter was proposed based on the symmetrical characteristic of observed data versus ship's length. The confidence level of the newly developed models was tested by analysis of variance method. The agreement between the modelled and real values was found to be remarkably accurate.

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The Design and Implementation of Adaptive Contrast Enhancement Device for High Resolution LCD TV (고해상도 LCD TV를 위한 적응형 콘트라스트 향상 장치의 설계 및 구현)

  • Seo, Burm-Suk;Kwon, Byung-Heon;Hwang, Byung-Won
    • Journal of Advanced Navigation Technology
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    • v.11 no.3
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    • pp.319-328
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    • 2007
  • In this paper we implemented the Real Time Contrast Enhancer for image quality enhancement of moving picture. Also we proposed adaptive contrast control method that use mean and variance of input video signal. The Designed the contrast Enhancer is measured in comparison with conventional pictures and interfaced to 30inch TFT LCD TV.

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Estimation of Conditional Kendall's Tau for Bivariate Interval Censored Data

  • Kim, Yang-Jin
    • Communications for Statistical Applications and Methods
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    • v.22 no.6
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    • pp.599-604
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    • 2015
  • Kendall's tau statistic has been applied to test an association of bivariate random variables. However, incomplete bivariate data with a truncation and a censoring results in incomparable or unorderable pairs. With such a partial information, Tsai (1990) suggested a conditional tau statistic and a test procedure for a quasi independence that was extended to more diverse cases such as double truncation and a semi-competing risk data. In this paper, we also employed a conditional tau statistic to estimate an association of bivariate interval censored data. The suggested method shows a better result in simulation studies than Betensky and Finkelstein's multiple imputation method except a case in cases with strong associations. The association of incubation time and infection time from an AIDS cohort study is estimated as a real data example.

A Study on Crack Fault Diagnosis of Wind Turbine Simulation System (풍력발전기 모사 시스템에서의 균열 결함 진단에 대한 연구)

  • Bae, Keun-Ho;Park, Jong-Won;Kim, Bong-Ki;Choi, Byung-Oh
    • Journal of Applied Reliability
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    • v.14 no.4
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    • pp.208-212
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    • 2014
  • An experimental gear-box was set-up to simulate the real situation of the wind-turbine. Artificial cracks of different sizes were machined into the gear. Vibration signals were acquired to diagnose the different crack fault conditions. Time-domain features such as root mean square, variance, kurtosis, normalized 6th central moments were used to capture the characteristics of different crack conditions. Normal condition, 1 mm crack condition, 2mm crack condition, 6mm crack condition, and tooth fault condition were compared using ANFIS and DAG-SVM methods, and three different DAG-SVM models were compared. High-pass filtering improved the success rates remarkably in the case of DAG-SVM.

Visual Bean Inspection Using a Neural Network

  • Kim, Taeho;Yongtae Do
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.644-647
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    • 2003
  • This paper describes a neural network based machine vision system designed for inspecting yellow beans in real time. The system consists of a camera. lights, a belt conveyor, air ejectors, and a computer. Beans are conveyed in four lines on a belt and their images are taken by a monochrome line scan camera when they fall down from the belt. Beans are separated easily from their background on images by back-lighting. After analyzing the image, a decision is made by a multilayer artificial neural network (ANN) trained by the error back-propagation (EBP) algorithm. We use the global mean, variance and local change of gray levels of a bean for the input nodes of the network. In an our experiment, the system designed could process about 520kg/hour.

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Study on Enumerating the Degree of Similarity in Pairs of the Stnadardized Scores and Lower and Upper tail Probabilites using the Folded Normal Distribution (동형고사에서 표준점수차의 확률분포를 이용한 상사성의 측정과 평가치 산정에 관한 연구)

  • 홍석강
    • The Mathematical Education
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    • v.39 no.2
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    • pp.167-177
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    • 2000
  • In this thesis we concerned with the degree of similarity in pairs of scores having a common mean and variance could express similarity in terms of the absolute difference between the standardized scores. We particulary discussed the distribution of absolute differences between pairs of T scores among many standardized scores and demonstrated the procedures for calculating the lower limit of Med(│d│) values i. e. the maximum possible similarity with medians and correlation coefficients of the equivalent form tests by using the folded normal distribution, although other researchers expressed the degree of similarity using only the standard normal distribution. We also described many cases how to use those techniques and to apply effectively them in real evaluation fields.

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Bayesian Outlier Detection in Regression Model

  • Younshik Chung;Kim, Hyungsoon
    • Journal of the Korean Statistical Society
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    • v.28 no.3
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    • pp.311-324
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    • 1999
  • The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for an outlier problem and also analyze it in linear regression model using a Bayesian approach. Then we use the mean-shift model and SSVS(George and McCulloch, 1993)'s idea which is based on the data augmentation method. The advantage of proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability. The MCMC method(Gibbs sampler) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data and a real data.

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Clipping Value Estimate for Iterative Tree Search Detection

  • Zheng, Jianping;Bai, Baoming;Li, Ying
    • Journal of Communications and Networks
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    • v.12 no.5
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    • pp.475-479
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    • 2010
  • The clipping value, defined as the log-likelihood ratio (LLR) in the case wherein all the list of candidates have the same binary value, is investigated, and an effective method to estimate it is presented for iterative tree search detection. The basic principle behind the method is that the clipping value of a channel bit is equal to the LLR of the maximum probability of correct decision of the bit to the corresponding probability of erroneous decision. In conjunction with multilevel bit mappings, the clipping value can be calculated with the parameters of the number of transmit antennas, $N_t$; number of bits per constellation point, $M_c$; and variance of the channel noise, $\sigma^2$, per real dimension in the Rayleigh fading channel. Analyses and simulations show that the bit error performance of the proposed method is better than that of the conventional fixed-value method.

Maintenance Scheduling Using PSO Algorithm for Power Plants (PSO알고리즘을 이용한 전력계통의 발전기 예방정비계획 수립)

  • Park, Young-Soo;Jeong, Hee-Myung;Park, Jong-Kook;Kim, Jin-Ho;Park, June-Ho
    • Proceedings of the KIEE Conference
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    • 2007.11b
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    • pp.237-239
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    • 2007
  • This paper focuses on maintenance scheduling using PSO algorithm for power plants from an economic (operating cost) and reliable(variance of operating reserve margin) point of view. We also apply regional reserve margin and transfer capability to maintenance scheduling problem. The proposed method has been applied to IEEE-RTS(1996) with 32-generators and a real -world large scale power system with 291 generators.

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Wafer Map Image Analysis Methods in Semiconductor Manufacturing System (반도체 공정에서의 Wafer Map Image 분석 방법론)

  • Yoo, Youngji;An, Daewoong;Park, Seung Hwan;Baek, Jun-Geol
    • Journal of Korean Institute of Industrial Engineers
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    • v.41 no.3
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    • pp.267-274
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    • 2015
  • In the semiconductor manufacturing post-FAB process, predicting a package test result accurately in the wafer testing phase is a key element to ensure the competitiveness of companies. The prediction of package test can reduce unnecessary inspection time and expense. However, an analysing method is not sufficient to analyze data collected at wafer testing phase. Therefore, many companies have been using a summary information such as a mean, weighted sum and variance, and the summarized data reduces a prediction accuracy. In the paper, we propose an analysis method for Wafer Map Image collected at wafer testing process and conduct an experiment using real data.