• Title/Summary/Keyword: a error model

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In-Flight Alignment of SDINS without Initial Heading Information (초기 기수각 정보가 필요 없는 SDINS의 운항중 정렬)

  • 홍현수;이장규;박찬국
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.6
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    • pp.524-532
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    • 2002
  • This paper presents a new in-flight alignment method for an SDINS under large initial heading error. To handle large heading error, a new attitude error model is introduced. The attitude errors are divided into heading error and leveling errors using a newly defined horizontal frame. Some navigation error dynamic models are derived from the attitude error model for indirect feedback filtering of the in-flight alignment system. A Kalman filter with Position measurement is designed to estimate navigation errors as the indirect feedback filter Simulation results show that the proposed in-flight alignment method reduces the heading error very quickly from more than 40deg to about 5deg so as to apply a refined navigation filter. The total alignment process including leveling mode and navigation mode in addition to the proposed one allows large initial values not only in heading error but also in leveling errors.

Statistical analysis of KNHANES data with measurement error models

  • Hwang, Jinseub
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.3
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    • pp.773-779
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    • 2015
  • We study a statistical analysis about the fifth wave data of the Korea National Health and Nutrition Examination Survey based on linear regression models with measurement errors. The data is obtained from a national population-based complex survey. To demonstrate the availability of measurement error models, two results between the general linear regression model and measurement error model are compared based on the model selection criteria which are Akaike information criterion and Bayesian information criterion. For our study, we use the simulation extrapolation algorithm for measurement error model and the jackknife method for the estimation of standard errors.

An Analysis of Human Factor and Error for Human Error of the Semiconductor Industry (반도체 산업에서의 인적오류에 대한 인적요인과 과오에 대한 분석)

  • Yun, Yong-Gu;Park, Beom
    • Proceedings of the Safety Management and Science Conference
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    • 2007.04a
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    • pp.113-123
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    • 2007
  • Through so that accident of semiconductor industry deduces unsafe factor of the person center on unsafe behaviour that incident history and questionnaire and I made starting point that extract very important factor. It served as a momentum that make up base that analyzes factors that happen based on factor that extract factor cause classification for the first factor, the second factor and the third factor and presents model of human error. Factor for whole defines factor component for human factor and to cause analysis 1 stage in human factor and step that wish to do access of problem and it do analysis cause of data of 1 step. Also, see significant difference that analyzes interrelation between leading persons about human mistake in semiconductor industry and connect interrelation of mistake by this. Continuously, dictionary road map to human error theoretical background to basis traditional accidental cause model and modern accident cause model and leading persons. I wish to present model and new model in semiconductor industry by backbone that leading persons of existing scholars who present model of existent human error deduce relation. Finally, I wish to deduce backbone of model of pre-suppression about accident leading person of the person center.

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GNSS Airborne Multipath Error Modeling Under UAV Platform and Operating Environment

  • Kim, Minchan;Kim, Kiwan;Lee, Dong-Kyeong;Lee, Jiyun
    • Journal of Positioning, Navigation, and Timing
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    • v.4 no.1
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    • pp.1-7
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    • 2015
  • In the case of an unmanned aerial vehicle (UAV) equipped with a GNSS sensor, a boundary line where the vehicle can actually exist can be calculated using a navigation error model, and safe navigation (e.g., precise landing and collision prevention) can be supported based on this boundary line. Therefore, for the safe operation of UAV, a model for the position error of UAV needs to be established in advance. In this study, the multipath error of a GNSS sensor installed at UAV was modeled through a flight test, and this was analyzed and compared with the error model of an existing manned aircraft. The flight test was conducted based on a scenario in which UAV performs hovering at an altitude of 40 m, and it was found that the multipath error value was well bound by the error model of an existing manned aircraft. This result indicates that the error model of an existing manned aircraft can be used in operation environments similar to the scenario for the flight test. Also, in this study, a scenario for the operation of multiple UAVs was considered, and the correlation between the multipath errors of the UAVs was analyzed. The result of the analysis showed that the correlation between the multipath errors of the UAVs was not large, indicating that the multipath errors of the UAVs cannot be canceled out.

A study on the Pattern Recognition of the EMG signals using Neural Network and Probabilistic modal for the two dimensional Motions described by External Coordinate (신경회로망과 확률모델을 이용한 2차원운동의 외부좌표에 대한 EMG신호의 패턴인식에 관한 연구)

  • Jang, Young-Gun;Kwon, Jang-Woo;Hong, Seung-Hong
    • Proceedings of the KOSOMBE Conference
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    • v.1991 no.05
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    • pp.65-70
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    • 1991
  • A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

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The Error Structure of the CAPPI and the Correction of the Range Dependent Error due to the Earth Curvature (CAPPI 반사도의 오차구조 및 지구곡률효과로 인한 거리오차 보정)

  • Yoo, Chulsang;Yoon, Jungsoo
    • Atmosphere
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    • v.22 no.3
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    • pp.309-319
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    • 2012
  • It is important to characterize and quantify the inherent error in the radar rainfall to make full use of the radar rainfall. This study verified the error structure of the reflectivity and corrected the range dependent error in the CAPPI using a VPR (vertical profile of reflectivity) model. The error of the CAPPI to display the reflectivity data becomes bigger for the range longer than 100 km. This range dependent error, however, is significantly improved by corrected the CAPPI data using the VPR model.

A Proposition of Accident Causation Model for the Analysis of Human Error Accidents in Railway Operations (철도 분야의 인적 오류 사고 분석을 위한 사고발생 모형의 제안)

  • Kim, Dong-San;Baek, Dong-Hyun;Yoon, Wan-Chul
    • Journal of the Ergonomics Society of Korea
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    • v.29 no.2
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    • pp.241-248
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    • 2010
  • In accident analysis, it is essential to understand the causal pathways of the accident. Although numerous accident models have been developed to help analysts understand how and why an accident occurs, most of them do not include all elements related to the accident in various fields. Thus analysis of human error accidents in railway operations using these existing models may be possible, but inevitably incomplete. For a more thorough analysis of the accidents in railway operations, a more exhaustive model of accident causation is needed. This paper briefly reviews four recent accident causation models, and proposes a new model that overcomes the limitations of the existing models for the analysis of human error accidents in railway operations. In addition, the usefulness and comprehensiveness of the proposed model is briefly tested by explaining 12 railway accident cases with the model. The proposed accident causation model is expected to improve understanding of how and why an accident/incident occurs, and help prevent analysts from missing any important aspect of human error accidents in railway operations

Comparison of Confidence Intervals on Variance Component In a Simple Linear Regression Model with Unbalanced Nested Error Structure

  • Park, Dong Joon;Park, Sun-Young;Han, Man-Ho
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.459-471
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    • 2002
  • In applications using a linear regression model with nested error structure, one might be interested in making inferences concerning variance components. This article proposes approximate confidence intervals on the variance component of the primary level in a simple linear regression model with an unbalanced nested error structure. The intervals are compared using computer simulation and recommendations are provided for selecting an appropriate interval.

Error-robust model-based sampling in accounting (회계감사예에 적용시켜본 오차로버스터적 모델표본론)

  • 김영일
    • The Korean Journal of Applied Statistics
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    • v.6 no.1
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    • pp.29-40
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    • 1993
  • In a model-based sampling problem, it often happens that the functional form of variance of error terms in regression model cannot be specified in an exact form. The goal of error-robust sampling design will be to minimize the 'ill effects' resulting from a lack of knowledge of the error structure. A sampling criterion, which is optimal if it minimizes the average of an inefficiency measure when taken with respect to all candidate error structures, is proposed and a computer algorithm is developed for construction of optimal sampling plans. Auditing problem is of particular relevance because of the uncertainty that currently clouds specification of the error structure.

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Error Model and Accuracy Analysis of a Cubic Parallel Device

  • Lim, Seung-Reung;Park, Woo-Chun;Song, Jae-Bok;Daehie Hong
    • International Journal of Precision Engineering and Manufacturing
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    • v.2 no.4
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    • pp.75-80
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    • 2001
  • An error analysis is very important to estimate performance of a precision machine. This study proposes an error analysis for a new parallel device, a cubic parallel device. The cubic parallel manipulator has error sources including upper and lower universal joint errors due to the directional changes in the link and actuation errors. The maximum errors of the end effector are affected by the axial direction changes of each links and the clearances of the universal joints when the parallel manipulator is moving along a path. It is found that the changes of errors mostly occur at the positions where the directions of exerting link forces shift. The error analysis is based on an error model formed from the relation between the universal point errors and the end-effector accuracy. The analysis method can be also used in predicting the accuracy of other parallel devices.

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