• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1641-1648
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• 2017

Many researchers had examined the validity of using the high-to-low ratio between two fixed frequency band amplitudes (H/L-FFB) from the surface electromyography of a face and body as the first spectral index to assess muscle fatigue. Despite these studies, the disadvantage of this index is the lack of a criterion for choosing the optimal border frequency. We tested the potential of using the high-to-low ratio between two signal spectral moments (H/L-SSM), without fixed border frequencies, to evaluate muscle fatigue and predict endurance time ($T_{end}$), which was determined when the subject was exhausted and could no longer follow the fixed contraction cycle. Ten healthy participants performed five sets of voluntary isotonic contractions until they could only produce 10% and 20% of their maximum voluntary contraction (MVC). The $T_{end}$ values for all participants were $138{\pm}35s$ at 10% MVC and $69{\pm}20s$ at 20% MVC. Changes in conventional spectral indices, such as the mean power frequency (MPF), Dimitrov spectral index (DSI), H/L-FFB, and H/L-SSM, were extracted from surface EMG signals and were monitored using the initial slope computed every 10% of $T_{end}$ as a statistical indicator and compared as a predictor of $T_{end}$. Significant correlations were found between $T_{end}$ and the initial H/L-SSM slope as computed over 30% of $T_{end}$. In conclusion, initial H/L-SSM slope can be used to describe changes in the spectral content of surface EMG signals and can be employed as a good predictor of $T_{end}$ compared to that of conventional spectral indices.

• Proceedings of the KSRS Conference
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• v.1
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• pp.86-89
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• 2006

Ocean color remote sensing community currently uses the different solar irradiance spectra covering the visible and near-infrared in the calibration/validation and deriving products of ocean color instruments. These spectra derived from single and / or multiple measurements sets or models have significant discrepancies, primarily due to variation of the solar activity and uncertainties in the measurements from various instruments and their different calibration standards. Thus, it is prudent to examine model-to-model differences and select a standard reference spectrum that can be adopted in the future calibration and validation processes, particularly of the first Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meterological Satellite (COMS) planned to be launched in 2008. From an exhaustive survey that reveals a variety of solar spectra in the literature, only eight spectra are considered here seeing as reference in many remote sensing applications. Several criteria are designed to define the reference spectrum: i.e., minimum spectral range of 350-1200nm, based completely or mostly on direct measurements, possible update of data and less errors. A careful analysis of these spectra reveals that the Thuillier 2004 spectrum seems to be very identical compared to other spectra, primarily because it represents very high spectral resolution and the current state of the art in solar irradiance spectra of exceptionally low uncertainty ${\sim}0.1%.$ This study also suggests use of the Gueymard 2004 spectrum as an alternative for applications of multispectral/multipurpose satellite sensors covering the terrestrial regions of interest, where it provides spectral converge beyond 2400nm of the Thuillier 2004 spectrum. Since the solar-activity induced spectral variation is about less than 0.1% and a large portion of this variability occurs particularly in the ultraviolet portion of the electromagnetic spectrum that is the region of less interest for the ocean color community, we disregard considering this variability in the analysis of solar irradiance spectra, although determine the solar constant 1366.1 $Wm^{-2}$ to be proposed for an improved approximation of the extraterrestrial solar spectrum in the visible and NIR region.

• Journal of Animal Environmental Science
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• v.20 no.3
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• pp.117-124
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• 2014

The objectives were to assess the use of near-infrared reflectance spectroscopy (NIRS) as a tool for estimating nutrient compositions of corn kernel, and to apply an NIRS-based indium gallium arsenide array detector to the system for collecting spectra and analyzing calibration equations using equipments designed for field application. Partial Least Squares Regression (PLSR) was employed to develop calibration equations based on representative data sets. The kennard-stone algorithm was applied to induce a calibration set and a validation set. As a result, the method for structuring a calibration set significantly affected prediction accuracy. The prediction of chemical composition of corn kernel resulted in the following (kennard-stone algorithm: relative) moisture ($R^2=0.82$, RMSEP=0.183), crude protein ($R^2=0.80$, RMSEP=0.142), crude fat ($R^2=0.84$, RMSEP=0.098), crude fiber ($R^2=0.74$, RMSEP=0.098), and crude ash ($R^2=0.81$, RMSEP=0.048). Result of this experiment showed the potential of NIRS to predict the chemical composition of corn kernel.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.369-376
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• 2002

This paper presents a method to enhance the performance of supervised classification by separating the spectral signature of the training data sets for each class. Using clustering technique, a training data set is divided into several subsets which show a pattern of the normal distribution with small value of spectral variances. Then a supervised classification is applied with the divided training data set as training data for the temporary subclasses of the original class. The proposed method is applied to a Landsat TM image of Busan area for the applicability test. The result shows that the proposed method produces better classified results than the conventional statistical classification methods. It is expected that the proposed method will reduce the effort and expense for selecting the training data set for each class in an area which has spectrally homogeneous signature.

• Journal of The Korean Astronomical Society
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• v.54 no.5
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• pp.139-155
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• 2021

We present an updated version of the multilayer spectral inversion (MLSI) recently proposed as a technique to infer the physical parameters of plasmas in the solar chromosphere from a strong absorption line. In the original MLSI, the absorption profile was constant over each layer of the chromosphere, whereas the source function was allowed to vary with optical depth. In our updated MLSI, the absorption profile is allowed to vary with optical depth in each layer and kept continuous at the interface of two adjacent layers. We also propose a new set of physical requirements for the parameters useful in the constrained model fitting. We apply this updated MLSI to two sets of Hα and Ca II line spectral data taken by the Fast Imaging Solar Spectrograph (FISS) from a quiet region and an active region, respectively. We find that the new version of the MLSI satisfactorily fits most of the observed line profiles of various features, including a network feature, an internetwork feature, a mottle feature in a quiet region, and a plage feature, a superpenumbral fibril, an umbral feature, and a fast downflow feature in an active region. The MLSI can also yield physically reasonable estimates of hydrogen temperature and nonthermal speed as well as Doppler velocities at different atmospheric levels. We conclude that the MLSI is a very useful tool to analyze the Hα line and the Ca II 8542 line spectral daya, and will promote the investigation of physical processes occurring in the solar photosphere and chromosphere.

• Journal of The Korean Astronomical Society
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• v.43 no.2
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• pp.41-54
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• 2010

We report relative proper motion measurements of $H_{2}O$ masers in massive star-forming region W51 Main, based on data sets of VLBI observations for $H_{2}O$ masers at 22 GHz with Japanese VERA telescopes from 2003 to 2006. Data reductions and single-beam imaging analysis are to measure internal kinematics of maser spots and eventually to estimate the three-dimensional kinematics of $H_{2}O$ masers in W51 Main. Average space motions and proper motion measurements of $H_{2}O$ masers are given both graphical and in table formats. We find in this study that W51 Main appears to be associated with hyper-compact H II region with multiple massive proto-stars whose spectral types are of late O.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.59-65
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• 2003

The merging of different scales or multi-sensor image data is becoming a widely used procedure of the complementary nature of various data sets. Ideally, the merging method should not distort the characteristics of the high-spatial and high-spectral resolution data used. To present an effective merging method for survey of reclaimed land using the high-resolution (6.6 m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSA T-l) and the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data, this paper compares the results of Intensity Hue Saturation (IHS) and Principal Component Analysis (PCA) methods. The comparison is made by statistical and visual evaluation of three-color combination images of IHS and PCA results based on spatial and spectral characteristics. The use of MODIS bands 1, 2, and 3 with a contrast stretched EOC panchromatic image as a substitute for intensity was found to be particularly effective in this study.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.32 no.5
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• pp.14-25
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• 2000

In this investigation, a wavelet transform analysis was used to decompose beta-radiographic formation images into spectral and spatial components. Conventional formation analysis may use spectral analysis, based on Fourier transformation or variance vs. zone size, to describe the grammage distribution of features such as flocs, streaks and mean fiber orientation. However, these methods have limited utility for the analysis of statistically stationary data sets where variance is not uniform with position, e.g. paper machine CD profiles (especially those that contain streaks). A continuous wavelet transform was used to analyze formation data arrays obtained from radiographic imaging of handsheets and cross machine paper samples. The response of the analytical method to grammage, floc size distribution, mean fiber orientation an sensitivity to feature localization were assessed. From wavelet analysis, the change in scale of grammage variation as a function of position was used to demonstrate regular and isolated differences in the formed structure.

• Journal of the Chungcheong Mathematical Society
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• v.24 no.1
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• pp.19-34
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• 2011

A bounded linear operator T on a complex Banach space X is said to have property (I) provided that T has Bishop's property (${\beta}$) and there exists an integer p > 0 such that for a closed subset F of ${\mathbb{C}}$ ${X_T}(F)={E_T}(F)=\bigcap_{{\lambda}{\in}{\mathbb{C}}{\backslash}F}(T-{\lambda})^PX$ for all closed sets $F{\subseteq}{\mathbb{C}}$, where $X_T$(F) denote the analytic spectral subspace and $E_T$(F) denote the algebraic spectral subspace of T. Easy examples are provided by normal operators and hyponormal operators in Hilbert spaces, and more generally, generalized scalar operators and subscalar operators in Banach spaces. In this paper, we prove that if T has property (I), then the quasi-nilpotent part $H_0$(T) of T is given by $$KerT^P=\{x{\in}X:r_T(x)=0\}={\bigcap_{{\lambda}{\neq}0}(T-{\lambda})^PX$$ for all sufficiently large integers p, where ${r_T(x)}=lim\;sup_{n{\rightarrow}{\infty}}{\parallel}T^nx{\parallel}^{\frac{1}{n}}$. We also prove that if T has property (I) and the spectrum ${\sigma}$(T) is finite, then T is algebraic. Finally, we prove that if $T{\in}L$(X) has property (I) and has decomposition property (${\delta}$) then T has a non-trivial invariant closed linear subspace.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.25-36
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• 2014

Multispectral image classification of individual tree species is often difficult because of the spectral similarity among species. In this study, we attempted to analyze the suitability of hyperspectral image to classify coniferous tree species. Several image sets and classification methods were applied and the classification results were compared with the ones from multispectral image. Two airborne hyperspectral images (AISA, CASI) were obtained over the study area in the Gwangneung National Forest. For the comparison, ETM+ multispectral image was simulated using hyperspectral images as to have lower spectral resolution. We also used the transformed hyperspectral data to reduce the data volume for the classification. Three supervised classification schemes (SAM, SVM, MLC) were applied to thirteen image sets. In overall, hyperspectral image provides higher accuracies than multispectral image to discriminate coniferous species. AISA-dual image, which include additional SWIR spectral bands, shows the best result as compared with other hyperspectral images that include only visible and NIR bands. Furthermore, MNF transformed hyperspectral image provided higher classification accuracies than the full-band and other band reduced data. Among three classifiers, MLC showed higher classification accuracy than SAM and SVM classifiers.