• Title/Summary/Keyword: Improved estimator

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A Proposed Algorithm and Sampling Conditions for Nonlinear Analysis of EEG (뇌파의 비선형 분석을 위한 신호추출조건 및 계산 알고리즘)

  • Shin, Chul-Jin;Lee, Kwang-Ho;Choi, Sung-Ku;Yoon, In-Young
    • Sleep Medicine and Psychophysiology
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    • v.6 no.1
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    • pp.52-60
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    • 1999
  • Objectives: With the object of finding the appropriate conditions and algorithms for dimensional analysis of human EEG, we calculated correlation dimensions in the various condition of sampling rate and data aquisition time and improved the computation algorithm by taking advantage of bit operation instead of log operation. Methods: EEG signals from 13 scalp lead of a man were digitized with A-D converter under the condition of 12 bit resolution and 1000 Hertz of sampling rate during 32 seconds. From the original data, we made 15 time series data which have different sampling rate of 62.5, 125, 250, 500, 1000 hertz and data acqusition time of 10, 20, 30 second, respectively. New algorithm to shorten the calculation time using bit operation and the Least Trimmed Squares(LTS) estimator to get the optimal slope was applied to these data. Results: The values of the correlation dimension showed the increasing pattern as the data acquisition time becomes longer. The data with sampling rate of 62.5 Hz showed the highest value of correlation dimension regardless of sampling time but the correlation dimension at other sampling rates revealed similar values. The computation with bit operation instead of log operation had a statistically significant effect of shortening of calculation time and LTS method estimated more stably the slope of correlation dimension than the Least Squares estimator. Conclusion: The bit operation and LTS methods were successfully utilized to time-saving and efficient calculation of correlation dimension. In addition, time series of 20-sec length with sampling rate of 125 Hz was adequate to estimate the dimensional complexity of human EEG.

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Automatic velocity analysis using bootstrapped differential semblance and global search methods (고해상도 속도스펙트럼과 전역탐색법을 이용한 자동속도분석)

  • Choi, Hyung-Wook;Byun, Joong-Moo;Seol, Soon-Jee
    • Geophysics and Geophysical Exploration
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    • v.13 no.1
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    • pp.31-39
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    • 2010
  • The goal of automatic velocity analysis is to extract accurate velocity from voluminous seismic data with efficiency. In this study, we developed an efficient automatic velocity analysis algorithm by using bootstrapped differential semblance (BDS) and Monte Carlo inversion. To estimate more accurate results from automatic velocity analysis, the algorithm we have developed uses BDS, which provides a higher velocity resolution than conventional semblance, as a coherency estimator. In addition, our proposed automatic velocity analysis module is performed with a conditional initial velocity determination step that leads to enhanced efficiency in running time of the module. A new optional root mean square (RMS) velocity constraint, which prevents picking false peaks, is used. The developed automatic velocity analysis module was tested on a synthetic dataset and a marine field dataset from the East Sea, Korea. The stacked sections made using velocity results from our algorithm showed coherent events and improved the quality of the normal moveout-correction result. Moreover, since our algorithm finds interval velocity ($\nu_{int}$) first with interval velocity constraints and then calculates a RMS velocity function from the interval velocity, we can estimate geologically reasonable interval velocities. Boundaries of interval velocities also match well with reflection events in the common midpoint stacked sections.

Feature-based Non-rigid Registration between Pre- and Post-Contrast Lung CT Images (조영 전후의 폐 CT 영상 정합을 위한 특징 기반의 비강체 정합 기법)

  • Lee, Hyun-Joon;Hong, Young-Taek;Shim, Hack-Joon;Kwon, Dong-Jin;Yun, Il-Dong;Lee, Sang-Uk;Kim, Nam-Kug;Seo, Joon-Beom
    • Journal of Biomedical Engineering Research
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    • v.32 no.3
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    • pp.237-244
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    • 2011
  • In this paper, a feature-based registration technique is proposed for pre-contrast and post-contrast lung CT images. It utilizes three dimensional(3-D) features with their descriptors and estimates feature correspondences by nearest neighborhood matching in the feature space. We design a transformation model between the input image pairs using a free form deformation(FFD) which is based on B-splines. Registration is achieved by minimizing an energy function incorporating the smoothness of FFD and the correspondence information through a non-linear gradient conjugate method. To deal with outliers in feature matching, our energy model integrates a robust estimator which discards outliers effectively by iteratively reducing a radius of confidence in the minimization process. Performance evaluation was carried out in terms of accuracy and efficiency using seven pairs of lung CT images of clinical practice. For a quantitative assessment, a radiologist specialized in thorax manually placed landmarks on each CT image pair. In comparative evaluation to a conventional feature-based registration method, our algorithm showed improved performances in both accuracy and efficiency.

Development of an Efficiency Calibration Model Optimization Method for Improving In-Situ Gamma-Ray Measurement for Non-Standard NORM Residues (비정형 공정부산물 In-Situ 감마선 측정 정확도 향상을 위한 효율교정 모델 최적화 방법 개발)

  • WooCheol Choi;Tae-Hoon Jeon;Jung-Ho Song;KwangPyo Kim
    • Journal of Radiation Industry
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    • v.17 no.4
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    • pp.471-479
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    • 2023
  • In In-situ radioactivity measurement techniques, efficiency calibration models use predefined models to simulate a sample's geometry and radioactivity distribution. However, simplified efficiency calibration models lead to uncertainties in the efficiency curves, which in turn affect the radioactivity concentration results. This study aims to develop an efficiency calibration optimization methodology to improve the accuracy of in-situ gamma radiation measurements for byproducts from industrial facilities. To accomplish the objective, a drive mechanism for rotational measurement of an byproduct simulator and a sample was constructed. Using ISOCS, an efficiency calibration model of the designed object was generated. Then, the sensitivity analysis of the efficiency calibration model was performed, and the efficiency curve of the efficiency calibration model was optimized using the sensitivity analysis results. Finally, the radiation concentration of the simulated subject was estimated, compared, and evaluated with the designed certification value. For the sensitivity assessment of the influencing factors of the efficiency calibration model, the ISOCS Uncertainty Estimator was used for the horizontal and vertical size and density of the measured object. The standard deviation of the measurement efficiency as a function of the longitudinal size and density of the efficiency calibration model decreased with increasing energy region. When using the optimized efficiency calibration model, the measurement efficiency using IUE was improved compared to the measurement efficiency using ISOCS at the energy of 228Ac (911 keV) for the nuclide under analysis. Using the ISOCS efficiency calibration method, the difference between the measured radiation concentration and the design value for each simulated subject measurement direction was 4.1% (1% to 10%) on average. The difference between the estimated radioactivity concentration and the design value was 3.6% (1~8%) on average when using the ISOCS IUE efficiency calibration method, which was closer to the design value than the efficiency calibration method using ISOCS. In other words, the estimated radioactivity concentration using the optimized efficiency curve was similar to the designed radioactivity concentration. The results of this study can be utilized as the main basis for the development of regulatory technologies for the treatment and disposal of waste generated during the operation, maintenance, and facility replacement of domestic byproduct generation facilities.