• Communications of the Korean Mathematical Society
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• v.10 no.3
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• pp.653-659
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• 1995

We prove that two essentially normal elements of a type $II_{\infty}$ factor von Neumann algebra are unitarily equivalent up to the compact ideal if and only if they have the identical essential spectrum and the same index data. Also we calculate the spectrum and essential spectrum of a non-unitary isometry of von Neumann algebra.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.146-149
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• 2008

Simulation and signal conditioning on the time domain surface elevation records are conducted to verify the proposed Welch's method in non-directional ocean wave spectrum analysis. These spectrum data are further conditioned to provide wave characteristic that better describe the sea states. Comparison of significant wave height and zero crossing period between the proposed method and a reference toolkit are presented.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.560-568
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• 2000

The aims of this research were to investigate the preprocessing effect of spectrum data on prediction performance and to develop a robust model to predict SSC in intact apple. Spectrum data of 320 Fuji apples were measured with the on-line transmittance measurement system at the wavelength range of 550∼1100nm. Preprocess methods adopted for the tests were Savitzky Golay, MSC, SNV, first derivative and OSC. Several combinations of those methods were applied to the raw spectrum data set to investigate the relative effect of each method on the performance of the calibration model. PLS method was used to regress the preprocessed data set and the SSCs of samples, and the cross-validation was to select the optimal number of PLS factors. Smoothing and scattering corection were essential in increasing the prediction performance of PLS regression model and the OSC contributed to reduction of the number of PLS factors. The first derivative resulted in unfavorable effect on the prediction performance. MSC and SNV showed similar effect. A robust calibration model could be developed by the preprocessing combination of Savitzky Golay smoothing, MSC and OSC, which resulted in SEP= 0.507, bias=0.032 and R$^2$=0.8823.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.212-218
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• 2013

This paper presents an SVD(Singular Value Decomposition)-Pseudo Spectrum method for SAR (Synthetic Aperture Radar) imaging. The purpose of this work is to improve resolution and target separability of SAR images. This paper proposes SVD-Pseudo Spectrum method whose advantages are noise robustness, reduction of sidelobes and high resolution of spectral estimation. SVD-Pseudo Spectrum method uses Hankel Matrix of signal components and SVD (Singular Value Decomposition) method. In this paper, it is demonstrated that the SVD-Pseudo Spectrum method shows better performance than the matched filtering method and the conventional super-resolution based multiple signal classification (MUSIC) method in SAR image processing. The targets to be separated are modeled, and this modeled data is used to demonstrate the performance of algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1037-1044
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• 2020

Since radar wind profiler (RWP) provides wind field data with high time and space resolution in all weather conditions, their verification of the accuracy and quality is essential. The simultaneous wind measurement from rawinsonde is commonly used to evaluate wind vectors from RWP. In this study, the simulation algorithm which produces the spectrum and raw time series (I/Q) data from the average values of moments is presented as a step-by-step verification method for the signal processing algorithm. The possibility of the simulation algorithm was also confirmed through comparison with the raw data of LAP-3000. The Doppler power spectrum was generated by assuming the density function of the skew-normal distribution and by using the moment values as the parameter. The simulated spectrum was generated through random numbers. In addition, the coherent averaged I/Q data was generated by random phase and inverse discrete Fourier transform, and raw I/Q data was generated through the Dirichlet distribution.

• Bulletin of the Korean Chemical Society
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• v.33 no.10
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• pp.3391-3396
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• 2012

Two-dimensional infrared (2D-IR) spectroscopy can probe the fast structural evolution of molecules under thermal equilibrium. Vibrational frequency fluctuation caused by structural evolution produced the time-dependent line shape change in 2D-IR spectrum. A variety of methods has been used to connect the evolution of 2D-IR spectrum with Frequency-Frequency Correlation Function (FFCF), which connects the experimental observables to a molecular level description. Here, a new method to extract FFCF from 2D-IR spectra is described. The experimental observable is the time-dependent frequency shift of maximum peak position in the slice spectrum of 2D-IR, which is taken along the excitation frequency axis. The direct relation between the 2D-IR peak shift and FFCF is proved analytically. Observing the 2D-IR peak shift does not need the full 2D-IR spectrum which covers 0-1 and 1-2 bands. Thus data collection time to determine FFCF can be reduced significantly, which helps the detection of transient species.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1059-1065
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• 2020

In hospitals, nurses are subjectively determining the urine status to check the kidneys and circulatory system of patients whose statuses are related to patients with kidney disease, critically ill patients, and nursing homes before and after surgery. To improve this problem, this paper proposes a urine spectrum analysis system which clusters urine test results based on a hybrid machine learning model consists of unsupervised learning and supervised learning. The proposed system clusters the spectral data using unsupervised learning in the first part, and classifies them using supervised learning in the second part. The results of the proposed urine spectrum analysis system using a mixed model are evaluated with the results of pure supervised learning. This paper is expected to provide better services than existing medical services to patients by solving the shortage of nurses, shortening of examination time, and subjective evaluation in hospitals.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4067-4071
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• 2021

The ¹³C (α,n)¹⁶O reaction cross-section is important data for nuclear physics, astrophysical, and neutrino physics experiments, however, they exhibit uncertainties due to the discrepancies in the experimental data. In this study, using the Nedis-2m program code, the energy spectrum of α-induced neutrons in a thin carbon target was calculated and the corresponding reaction cross-section was refined in the alpha particle energy range of 5-8 MeV. The results were used to calculate the intensity and energy spectrum of background neutrons produced in the liquid scintillator of KamLAND. The results will be useful in a variety of astrophysical and neutrino experiments especially those based on LS or Gd-LS detectors.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.117-124
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• 2002

This research was conducted to develop a method to remove the effect of surface temperature of Shingo pears for sugar content measurement. Sugar content was measured by a near-infrared spectrum analysis technique. Reflected spectrum and sugar content of a pear were used for developing regression models. For the model development, reflected spectrums having wavelengths in the range of 654 to 1,052nm were used. To remove the effect of surface temperature, special sample preparation techniques and partial least square (PLS) regression models were proposed and tested. 71 Shingo pears stored in a cold storage, which had 2$^{\circ}C$ inside temperature, were taken out and left in a room temperature for a while. Temperature and reflected spectrum of each pear was measured. To increase the temperature distribution of samples, temperature and reflected spectrum of each pear was measured four times with one hour twenty minutes interval. During the experiment, temperature of pears increased up to 17 $^{\circ}C$. The total number of measured spectrum was 284. Three groups of spectrum data were formed according to temperature distribution. First group had surface temperature of 14$^{\circ}C$ and total number of 51. Second group consisted of the first and the fourth experiment data which contained the minimum and the maximum temperatures. Third group consisted of 155 data with normal temperature-distribution. The rest data set were used for model evaluation. Results shelved that PLS model I, which was developed by using the first data group, was inadequate for measuring sugar content of pears which had different surface temperatures from 14$^{\circ}C$. After temperature compensation, sugar content predictions became close to the measured values. Since using many data which had wide range of surface temperatures, PLS model II and III were able to predict sugar content of pears without additional temperature compensation. PLS model IV, which included the surface temperatures as an independent variable. showed slightly improved performance(R$^2$=0.73). Performance of the model could be enhanced by using samples with more wide range of temperatures and sugar contents.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.821-827
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• 2014

Many researches on the usage of shared spectrum have continuously been carried out to solve the recent frequency shortage problem and to use efficiently the spectrum without interference. Also, exponential mobile data growth and the solutions needed to address this challenge are parallel key objectives addressed in many countries. Spectrum policy innovation to meet this challenge is the ASA/LSA (Authorized Shared Access/Licensed Shared Access), which is the best access model to employ the small cell technology to meet this mobile traffic growth. Because 3.5 GHz bands is considered as the ASA/LSA frequency, in this paper, we propose the SAM(Spectrum Access Model) in 3~4 GHz bands to estimate the available ASA/LSA bands and to open more free spectrum. These results are utilized as the data to develop the SAM for the small cell and the open frequency in future.