• Title/Summary/Keyword: Polynomial fitting model

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Effects of element composition in soil samples on the efficiencies of gamma energy peaks evaluated by the MCNP5 code

  • Ba, Vu Ngoc;Thien, Bui Ngoc;Loan, Truong Thi Hong
    • Nuclear Engineering and Technology
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    • v.53 no.1
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    • pp.337-343
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    • 2021
  • In this work, self-absorption correction factor related to the variation of the composition and the density of soil samples were evaluated using the p-type HPGe detector. The validated MCNP5 simulation model of this detector was used to evaluate its Full Energy Peak Efficiency (FEPE) under the variation of the composition and the density of the analysed samples. The results indicates that FEPE calculation of low gamma ray is affected by the composition and the density of soil samples. The self-absorption correction factors for different gamma-ray energies which was fitted as a function of FEPEs via density and energy and fitting parameters as polynomial function for the logarithm neper of gamma ray energy help to calculate quickly the detection efficiency of detector. Factor Analysis for the influence of the element composition in analysed samples on the FEPE indicates the FEPE distribution changes from non-metal to metal groups when the gamma ray energy increases from 92 keV to 238 keV. At energies above 238 keV, the FEPE primarily depends only on the metal elements and is significantly affected by aluminium and silicon composition in soil samples.

Study of RF Impairments in Wideband Chirp Signal Generator (광대역 첩 신호 발생기를 위한 RF 불균형 연구)

  • Ryu, Sang-Burm;Kim, Joong-Pyo;Yang, Jeong-Hwan;Won, Young-Jin;Lee, Sang-Kon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.12
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    • pp.1205-1214
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    • 2013
  • Recently spaceborne SAR systems are increasing image resolution and frequency. As a high quality image resolution, the wider bandwidth is required and a wideband signal generator with RF component is very complicated and RF impairments of device is increased. Therefore, it is very important to improve performance by reducing these errors. In this study, the transmission signal of the wideband signal generator is applied to the phase noise, IQ imbalance, ripple gain, nonlinear model of high power amplifier. And we define possible structures of wideband signal generator and measure the PSLR and ISLR for the performance assesment. Also, we extract error of the amplitude and phase from the waveform and use a quadratic polynomial curve fitting and examine the performance change due to nonlinear device. Finally, we apply a high power amplifier predistortion method for non-linear error compensation. And we confirm that distortion in the output of the amplifier by intermodulation component is decreased by 15 dB.

CHALLENGING APPLICATIONS FOR FT-NIR SPECTROSCOPY

  • Goode, Jon G.;Londhe, Sameer;Dejesus, Steve;Wang, Qian
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.4112-4112
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    • 2001
  • The feasibility of NIR spectroscopy as a quick and nondestructive method for quality control of uniformity of coating thickness of pharmaceutical tablets was investigated. Near infrared spectra of a set of pharmaceutical tablets with varying coating thickness were measured with a diffuse reflectance fiber optic probe connected to a Broker IFS 28/N FT-NIR spectrometer. The challenging issues encountered in this study included: 1. The similarity of the formulation of the core and coating materials, 2. The lack of sufficient calibration samples and 3. The non-linear relationship between the NIR spectral intensity and coating: thickness. A peak at 7184 $cm^{-1}$ was identified that differed for the coating material and the core material when M spectra were collected at 2 $cm^{-1}$ resolution (0.4 nm at 7184 $cm^{-1}$). The study showed that the coating thickness can be analyzed by polynomial fitting of the peak area of the selected peak, while least squares calibration of the same data failed due to the lack of availability of sufficient calibration samples. Samples of coal powder and solid pieces of coal were analyzed by FT-NIR diffuse reflectance spectroscopy with the goal of predicting their ash content, percentage of volatile components, and energy content. The measurements were performed on a Broker Vector 22N spectrometer with a fiber optic probe. A partial least squares model was constructed for each of the parameters of interest for solid and powdered sample forms separately. Calibration models varied in size from 4 to 10 PLS ranks. Correlation coefficients for these models ranged from 86.6 to 95.0%, with root-mean-square errors of cross validation comparable to the corresponding reference measurement methods. The use of FT-NIR diffuse reflectance measurement techniques was found to be a significant improvement over existing measurement methodologies in terms of speed and ease of use, while maintaining the desired accuracy for all parameters and sample forms.(Figure Omitted).

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A Study on Pseudo-Range Correction Modeling in order to Improve DGNSS Accuracy (DGNSS 위치정확도 향상을 위한 PRC 보정정보 모델링에 관한 연구)

  • Sohn, Dong Hyo;Park, Kwan Dong
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.4
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    • pp.43-48
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    • 2015
  • We studied on pseudo-range correction(PRC) modeling in order to improve differential GNSS(DGNSS) accuracy. The PRC is the range correction information that provides improved location accuracy using DGNSS technique. The digital correction signal is typically broadcast over ground-based transmitters. Sometimes the degradation of the positioning accuracy caused by the loss of PRC signals, radio interference, etc. To prevent the degradation, in this paper, we have designed a PRC model through polynomial curve fitting and evaluated this model. We compared two quantities, estimations of PRC using model parameters and observations from the reference station. In the case of GPS, the average is 0.1m and RMSE is 1.3m. Most of GPS satellites have a bias error of less than ${\pm}1.0m$ and a RMSE within 3.0m. In the case of GLONASS, the average and the RMSE are 0.2m and 2.6m, respectively. Most of satellites have less than ${\pm}2.0m$ for a bias error and less than 3.0m for RMSE. These results show that the estimated value calculated by the model can be used effectively to maintain the accuracy of the user's location. However;it is needed for further work relating to the big difference between the two values at low elevation.