• 제목/요약/키워드: The Other Error

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Practical Treatment of Path -Delay Error by Terrain Model in Mobile Wireless Location

  • Kim, Wuk;Lee, Jang-Gyu;Jee, Gyu-In
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.58-58
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    • 2001
  • This paper shows a practical approach that is robust to the errors causing path-delay in mobile wireless location, and analyzes its performance by comparing with other methods. NLOS(non-line-of-sight) error and multipath are two big sources of positioning error in wireless location. Contrary to GPS(global positioning system), they result from the terrestrial propagation of a signal. Especially, since LOS(line-of-sight) path between a transceiver and a receiver is blocked by intermediate buildings and topography, NLOS causes a signal to be reflected and diffracted. This path-delay error is very localized, and so, it is not easy to be estimated and mitigated. To treat such localized error, therefore ...

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위그너-빌 분포함수의 계산시 창문함수의 적용에 의한 바이어스 오차 (The Bias Error due to Windows for the Wigner-Ville Distribution Estimation)

  • 박연규;김양한
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 1995년도 추계학술대회논문집; 한국종합전시장, 24 Nov. 1995
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    • pp.80-85
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    • 1995
  • Too see the effects of finite record on the estimation of WVD in practice, a window which has time varying length is examined. Its length increases linearly with time in the first half of the record, and decreases from the center of the record. The bias error due to this window decreases inversely proportionally to the window length as time increases in the first half. In the second half, the bias error increases and the resolution decreases as time increases. The bias error due to the smoothing of WVD, which is obtained by two-dimensional convolution of the true WVD and the smoothing window, which has fixed lengths along time and frequency axes, is derived for arbitrary smoothing window function. In the case of using a Gaussian window as a smoothing window, the bias error is found to be expressed as an infinite summation of differential operators. It is demonstrated that the derived formula is well applicable to the continuous WVD, but when WVD has some discontinuities, it shows the trend of the error. This is a consequence of the assumption of the derivation, that is the continuity of WVD. For windows other than Gaussian window, the derived equation is shown to be well applicable for the prediction of the bias error.

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Error Concealment Based on Multiple Representation for Wireless Transmission of JPEG2000 Image

  • ;이원영;양태욱;지성택;이경현
    • 한국통신학회논문지
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    • 제33권1C호
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    • pp.68-78
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    • 2008
  • The transmission of multimedia information over error-prone channels such as wireless networks has become an important area of research. In this paper, we propose two Error Concealment(EC) schemes for wireless transmission of JPEG2000 image. The Multiple Representation(MR) is employed as the preprocessing in our schemes, whereas the main error concealing operation is applied in wavelet domain at receiver side. The compressed code-stream of several subsampled versions of original image is transmitted over a single channel with random bit errors. In the decoder side, the correctly reconstructed wavelet coefficients are utilized to recover the corrupted coefficients in other sub-images. The recovery is carried out by proposed basic(MREC-BS) or enhanced(MREC-ES) methods, both of which can be simply implemented. Moreover, there is no iterative processing during error concealing, which results a big time saving. Also, the simulation results confirm the effectiveness and efficiency of our proposed schemes.

신경회로망의 예측제어기를 이용한 보일러의 온도제어에 관한 연구 (On the Temperature Control of Boiler using Neural Network Predictive Controller)

  • 엄상희;이권순;배종일
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.798-800
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    • 1995
  • The neural network predictive controller(NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output(Neural Network Predictor) and the other one is for control the plant(Neural Network Controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and prediction error. The NNP forecasts the future output based upon the current control input and the estimated control output. The method is applied to the control of temperature in boiler systems. The proposed NNPC is compared with the other conventional control methods such as PID controller, neural network controller with specialized learning architecture, and one-step-ahead controller. The computer simulation and experimental results show that the proposed method has better performances than the other methods.

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Bayesian smoothing under structural measurement error model with multiple covariates

  • Hwang, Jinseub;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • 제28권3호
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    • pp.709-720
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    • 2017
  • In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.

화학공정산업의 인적오류 제어 방법 (A method of human error management in chemical process industries)

  • 조영도;박교식;박희준
    • 한국가스학회지
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    • 제7권2호
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    • pp.42-47
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    • 2003
  • 화학공정산업에서 화재, 폭발, 독성물질 누출의 대형사고로 인한 막대한 인적 물적 손실을 효과적으로 방지하기 위하여 기계적 오류와 연계하여 사람의 행동을 동적으로 제어하는 것이 필요하다. 석유화학공단을 비롯한 에너지산업시설에서의 대형사고는 기계적인 결함과 더불어 사람의 행동과 관련되어 있음에도 불구하고, 대부분의 연구는 시스템의 위험을 감소시키기 위하여 안전장치의 결함과 인간의 행동에 대하여 서로 연계를 지우지 않고 독립적으로 연구를 수행하여 왔다 본 연구에서는 화학공정산업의 안전을 향상시키기 위한 방법을 제시하기 위하여 기계적 고장과 인적오류를 동시에 고려하여 인적오류를 제어하고, 중요한 수행영향인자에 대하여 고찰하였다.

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Index of Union와 다른 정확도 측도들 (Index of union and other accuracy measures)

  • 홍종선;최소연;임동휘
    • 응용통계연구
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    • 제33권4호
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    • pp.395-407
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    • 2020
  • 최적분류점에 대한 대부분의 정확도 측도들은 두 종류의 누적분포함수와 확률밀도함수를 기반으로 정의하거나 또는 ROC 곡선과 AUC를 기반으로 정의하는 방법으로 구분하는데, Unal (2017)은 두 가지 방법을 혼합하여 누적분포함수와 AUC를 모두 고려하는 정확도 측도 Index of Union (IU) 통계량을 제안하였다. 본 연구에서는 IU 통계량을 포함한 열 개의 정확도 측도들을 여섯 종류의 범주로 구분하여 각 범주에 속하는 측도들을 비교하면서 IU의 장점을 연구한다. 다양한 정규혼합분포를 설정하여 각각의 측도들에 대응하는 최적분류점들을 구하고 각 분류점에 대응하는 제1종과 제2종 오류 그리고 두 종류의 오류합을 구해서 오류들의 크기를 비교하면서 분류정확도 측도들의 판별력을 비교하면서 IU의 성격과 특징을 탐색한다. 두 종류 분포들의 평균 차이가 증가할수록 IU 통계량의 제1종 오류와 오류합의 크기가 최고의 분류정확도를 갖는 제2범주의 정확도 측도의 오류에 수렴하는 것을 발견하였다. 그러므로 IU는 모형의 판별력을 평가하는 정확도 측도로 활용할 수 있다.

Comparsion of Dst forecast models during intense geomagnetic storms (Dst $\leq$ -100 nT)

  • Ji, Eun-Young;Moon, Yong-Jae;Lee, Dong-Hun
    • 천문학회보
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    • 제35권2호
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    • pp.51.2-51.2
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    • 2010
  • We have investigated 63 intense geomagnetic storms (Dst $\leq$ -100 nT) that occurred from 1998 to 2006. Using these events, we compared Dst forecast models: Burton et al. (1975), Fenrich and Luhmann (1998), O'Brien and McPherron (2000a), Wang et al. (2003), and Temerin and Li (2002, 2006) models. For comparison, we examined a linear correlation coefficient, RMS error, the difference of Dst minimum value (${\Delta}$peak), and the difference of Dst minimum time (${\Delta}$peak_time) between the observed and the predicted during geomagnetic storm period. As a result, we found that Temerin and Li model is mostly much better than other models. The model produces a linear correlation coefficient of 0.94, a RMS (Root Mean Square) error of 14.89 nT, a MAD (Mean Absolute Deviation) of ${\Delta}$peak of 12.54 nT, and a MAD of ${\Delta}$peak_time of 1.44 hour. Also, we classified storm events as five groups according to their interplanetary origin structures: 17 sMC events (IP shock and MC), 18 SH events (sheath field), 10 SH+MC events (Sheath field and MC), 8 CIR events, and 10 nonMC events (non-MC type ICME). We found that Temerin and Li model is also best for all structures. The RMS error and MAD of ${\Delta}$peak of their model depend on their associated interplanetary structures like; 19.1 nT and 16.7 nT for sMC, 12.5 nT and 7.8 nT for SH, 17.6 nT and 15.8 nT for SH+MC, 11.8 nT and 8.6 nT for CIR, and 11.9 nT and 10.5 nT for nonMC. One interesting thing is that MC-associated storms produce larger errors than the other-associated ones. Especially, the values of RMS error and MAD of ${\Delta}$peak of SH structure of Temerin and Li model are very lower than those of other models.

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3차원 안면자동인식기(3D-AFRA)의 Software 정밀도 검사 : 형상측정프로그램 오차분석 (A Software Error Examination of 3D Automatic Face Recognition Apparatus(3D-AFRA) : Measurement of Facial Figure Data)

  • 석재화;송정훈;김현진;유정희;곽창규;이준희;고병희;김종원;이의주
    • 사상체질의학회지
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    • 제19권3호
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    • pp.51-61
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    • 2007
  • 1. Objectives The Face is an important standard for the classification of Sasang Constitutions. We are developing 3D Automatic Face Recognition Apparatus(3D-AFRA) to analyse the facial characteristics. This apparatus show us 3D image and data of man's face and measure facial figure data. So We should examine the Measurement of Facial Figure data error of 3D Automatic Face Recognition Apparatus(3D-AFRA) in Software Error Analysis. 2. Methods We scanned face status by using 3D Automatic Face Recognition Apparatus(3D-AFRA). And we measured lengths Between Facial Definition Parameters of facial figure data by Facial Measurement program. 2.1 Repeatability test We measured lengths Between Facial Definition Parameters of facial figure data restored by 3D-AFRA by Facial Measurement program 10 times. Then we compared 10 results each other for repeatability test. 2.2 Measurement error test We measured lengths Between Facial Definition Parameters of facial figure data by two different measurement program that are Facial Measurement program and Rapidform2006. At measuring lengths Between Facial Definition Parameters, we uses two measurement way. The one is straight line measurement, the other is curved line measurement. Then we compared results measured by Facial Measurement program with results measured by Rapidform2006. 3. Results and Conclusions In repeatability test, standard deviation of results is 0.084-0.450mm. And in straight line measurement error test, the average error 0.0582mm, and the maximum error was 0.28mm. In curved line measurement error test, the average error 0.413mm, and the maximum error was 1.53mm. In conclusion, we assessed that the accuracy and repeatability of Facial Measurement program is considerably good. From now on we complement accuracy of 3D-AFRA in Hardware and Software.

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선박 건조 과정에서 발생하는 치수 오차 분석을 위한 가중 포인트 정합 방법 (A Weighted Points Registration Method to Analyze Dimensional Errors Occurring during Shipbuilding Process)

  • 권기연
    • 한국CDE학회논문집
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    • 제21권2호
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    • pp.151-158
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    • 2016
  • It is important to analyze dimensional errors occurring during shipbuilding process. A ship is constructed by assembling blocks and installing outfits in assembled ship structure. Blocks and outfits have a main direction that has greater importance than other directions from the view point of dimensional error. Therefore, a main direction should have a greater weighting factor than other directions in order to achieve meaningful inspection results. In this paper, a modified point registration method based on iterative closest point (ICP) is proposed. In this method, a user determines one or two main directions among x, y, and z directions, and then each main direction is made to have a greater weighting factor than other directions. For points registration, mapping between measured points and design points are performed by the modified ICP in which weighting factor assigned to each main direction is considered.