• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.369-378
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• 2018

Purpose: The aim of this study was to construct a saponin content-predicting model using shortwave infrared imaging spectroscopy. Methods: The experiment used a shortwave imaging spectrometer and ENVI spectral acquisition software sampling a spectrum of 910 nm-2500 nm. The corresponding preprocessing and mathematical modeling analysis was performed by Unscrambler 9.7 software to establish a ginsenoside nondestructive spectral testing prediction model. Results: The optimal preprocessing method was determined to be a standard normal variable transformation combined with the second-order differential method. The coefficient of determination, $R^2$, of the mathematical model established by the partial least squares method was found to be 0.9999, while the root mean squared error of prediction, RMSEP, was found to be 0.0043, and root mean squared error of calibration, RMSEC, was 0.0041. The residuals of the majority of the samples used for the prediction were between ${\pm}1$. Conclusion: The experiment showed that the predicted model featured a high correlation with real values and a good prediction result, such that this technique can be appropriately applied for the nondestructive testing of ginseng quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.191-199
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• 2006

In this paper, we propose a method to implement a predistorter of the $rho$-th order inverse filter structure to prevent signal distortion and spectral re-growth due to the high PAPR (peak-to-average ratio) of the OFDM signals and the non-linearity of high-power amplifiers. We model the memory-less non-linearity of the high-power amplifier with a polynomial model and utilize the inverse of the model, the $rho$-th order inverse filter, for the predistorter. Once the non-linearity is modeled with a polynomial, since we can determine the $rho$-th order inverse filter only with the coefficients of the polynomial, large memory is not required. To update the coefficients of the non-linear high-power amplifier model, we can use LMS or RLS algorithms. The convergence speed is high since the number of coefficients is small, and the computation is simple since manipulation of complex numbers is not necessary.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.475-487
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• 2011

In this paper, we present a systematic method to derive spectrum of high-order pulse and a novel design of e-Learning system that deals with deriving the spectrum using concept-based branching method. Spectrum of high-order pulse can be derived using conventional methods including 'Consecutive Differentiations' or 'Convolutions', however, their complexity of calculation should be too high to be used as the order of the pulse increase. We develop a recursive algorithm according to the order of pulse, and then derive the formula of spectrum connected to the order with a newly designed look-up table. Moving along, we design an e-Learning content for studying the procedure of deriving high-order pulse spectrum described above. In this authoring, we use the concept-based object branching method including conventional page or title-type branching in sequential playing. We design all four Content-pages divided into 'Modeling', 'Impulse Response and Transfer Function', 'Parameters' and 'Look-up Table' by these conceptual objects. And modules and sub-modules are constructed hierarchically as conceptual elements from the Content-pages. Students can easily approach to the core concepts of the analysis because of the effects of our new teaching method. We offer step-by-step processes of the e-Learning content through unit-based branching scheme for difficult modules and sub-modules in our system. In addition we can offer repetitive learning processes for necessary block of given learning objects. Moreover, this method of constructing content will be considered as an advanced effectiveness of content itself.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.671-674
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• 2005

Atmospheric correction over the ocean part is more important than that over the land because the signal from the ocean is very small about one tenth of that reflected from land. In this study, the Spectral Shape Matching Method (SSMM) developed by Ahn and Shanmugam (2004) is evaluated using Landsat imagery acquired over the highly turbid Saemangeum Coastal Area. The result of SSMM is compared with COST model developed by Chavez (1991 and 1997). In principle, SSMM is simple and easy to implement on any satellite imagery, relying on both field and image properties. To assess the potential use of these methods, several field campaigns were conducted in the Saemangeum coastal area corresponding with Landsat-7 satellite's overpass on 29 May 2005. In-situ data collected from the coastal waters of Saemangeum using optical instruments (ASD field spectroradiometer) consists of ChI, Ap, SS, aooM, F(d). In order to perform SSMM, we use the in-situ water-leaving radiance spectra from clear oceanic waters to estimate the the path radiance from total signal recorded at the top of the atmosphere (TOA), due to the reason that the shape of clear water-leaving radiance spectra is nearly stable than turbid water-leaving radiance spectra. The retrieved water-leaving radiance after subtraction of path signal from TOA signal in this way is compared with that estimated by COST model. The result shows that SSMM enabled retrieval of water-leaving radiance spectra that are consistent with in-situ data obtained from Saemangeum coastal waters. The COST model yielded significantly high errors in these areas.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.994-1003
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• 1994

In this paper, a scheme of noise cancellation using spectral subreaction method with single input in an autombile noise environment is proposed. In order to remove the changing automonile noise components form the noisy speech signal, the noise of various states is analyzed and its characteristics are presented. For the decision of speech/nonspeech and the estimation of noise spectrum, a classification function is proposed on the basis of noise analysis. This function presents the precise decision of speech/nonspeech and the optimal estimation of noise spectrum with less computation. As the result of the estimation of noise spectrum by the proposed classification function, the clean speech signal is extracted from the noisy speech signal with high signal-to-ratio.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.151.2-151.2
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• 2011

IGRINS (Immersion GRating INfrared Spectrometer) will provide the spectra with high-resolution and an instantaneous spectral coverage of H and K band in NIR region. Therefore, it is expected that the wide coverage of wavelength would make a production of an extensive NIR high-resolution spectra of standard stars as a prior program of IGRINS. As a counter part of these NIR spectra, we have planned to obtain the high-resolution spectra of those standard stars in optical band. These optical high-resolution spectra would give us an opportunity to produce the library of high-resolution stellar spectra covering from optical to NIR band, and to confirm the method to determine the stellar parameters and chemical abundances from the NIR high-resolution spectra. Before using the NIR high-resolution spectra, we have tested the method to determine the stellar parameters by comparing between the observed spectra and the synthetic spectra in optical band. In order to make the synthetic spectra, we have used the Kurucz ATLAS9 model grids and the SYNTH code described by Fiorella Castelli (http://wwwuser.oat.ts.astro.it/castelli/). For the cross-check against the parameters that would be derived from the NIR spectra, the stellar parameters such as effective temperature and surface gravity were determined using the optical spectra of the solar-like stars, as preliminary results.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.377-391
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• 2018

In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2223-2225
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• 2005

In this work, experimental investigation has been mainly done. For this purpose, UHF sensor has been designed and fabricated to detect the partial discharges produced from the 10 artificial defects introduced into the real scale 70kV GIS mock-up under the high voltage at the well shielded room. And also, in order to verify the applicability of the proposed method at the site, the proposed CAPD (chaos analysis of partial discharge) is combined with spectral analysis method in order to identify the nature of the above 10 defects. The PD pattern recognition of each defect has been fulfilled by applying self developed artificial neural network soft ware. The result shows that the recognition rate is reached to be 80% by newly proposed method while the traditional PRPD analysis method leads us to obtain 41%. In consequence, it can be pointed out that the proposed method seems likely to be applicable to the real GIS at the site.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.85-95
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• 2012

In this thesis, we develop a spectral analysis scheme to eliminate the spurious peaks generated in HRR Millimeterwave Seeker based on FMICW system. In contrast to FMCW system, FMICW system generates spurious peaks in the spectrum of its IF signal, caused by the periodic discontinuity of the signal. These peaks make the accuracy of the system depend on the previously estimated range if a band pass filter is utilized to eliminate them and noise floor go to high level if random interrupted sequence is utilized and in case of using staggering process, we must transmit several waveforms to obtain overlapped information. Using the spectral analysis one of the schemes such as IAA(Iterative Adaptive Approach) and SPICE(SemiParametric Iterative Covariance-based Estimation method) which were introduced recently, the spurious peaks can be eliminated effectively. In order to utilize IAA and SPICE, since we must distinguish between reliable data and unreliable data and only use reliable data, STFT(Short Time Fourier Transform) is applied to the distinguishment process.