• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.6
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• pp.394-404
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• 2013

In the present study, the characteristics of spectral peakedness parameter $Q_p$, bandwidth parameter ${\varepsilon}$, and spectral width parameter ${\nu}$ were analyzed as a first step to define the swell waves quantitatively. For the analysis, the joint probability density function of significant wave heights and peak periods were newly developed. The MCMC(Markov Chain Monte Carlo) simulations have been performed to generate the significant wave heights and peak periods from the developed probability density functions. Applying the simulated significant wave heights and peak periods to the theoretical wave spectrum models, the spectral shapes parameters were obtained and analyzed. Among the spectral shape parameters, only the spectral peakedness parameter $Q_p$, is shown to be independent with the significant wave height and peak wave period. It also best represents the peakedness of the spectral shape, and henceforth $Q_p$ should be used to define the swell waves with a wave period. For the field verification of the results, wave data obtained from Hupo port and Ulleungdo were analyzed and results showed the same trend with the MCMC simulation results.

• Animal Bioscience
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• v.36 no.2
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• pp.256-263
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• 2023

Objective: Feed molecular structures can affect its availability to gastrointestinal enzymes which impact its digestibility and absorption. The molecular spectroscopy-attenuated total reflectance Fourier transform infrared vibrational spectroscopy (ATR-FTIR) is an advanced technique that measures the absorbance of chemical functional groups on the infrared region so that we can identify and quantify molecules and functional groups in a feed. The program aimed to reveal the association of intrinsic molecular structure with nutrient supply to animals from canola feedstocks and co-products from bio-oil processing. The objective of this study was to characterize special intrinsic carbohydrate and protein-related molecular structure spectral profiles of feedstock and co-products (meal and pellets) from bio-oil processing from two source origins: Canada (CA) and China (CH). Methods: The samples of feedstock and co-products were obtained from five different companies in each country arranged by the Canola Council of Canada (CCC). The molecular structure spectral features were analyzed using advanced vibrational molecular spectroscopy-ATR-FTIR. The spectral features that accessed included: i) protein-related spectral features (Amide I, Amide II, α-helix, β-sheet, and their spectral intensity ratios), ii) carbohydrate-related spectral features (TC1, TC2, TC3, TC4, CEC, STC1, STC2, STC3, STC4, TC, and their spectral intensity ratios). Results: The results showed that significant differences were observed on all vibrationally spectral features related to total carbohydrates, structural carbohydrates, and cellulosic compounds (p<0.05), except spectral features of TC2 and STC1 (p>0.05) of co-products, where CH meals presented higher peaks of these structures than CA. Similarly, it was for the carbohydrate-related molecular structure of canola seeds where the difference between CA and CH occurred except for STC3 height, CEC and STC areas (p>0.05). The protein-related molecular structures were similar for the canola seeds from both countries. However, CH meals presented higher peaks of amide I, α-helix, and β-sheet heights, α-helix:β-sheet ratio, total amide and amide I areas (p<0.05). Conclusion: The principal component analysis was able to explain over 90% of the variabilities in the carbohydrate and protein structures although it was not able to separate the samples from the two countries, indicating feedstock and coproducts interrelationship between CH and CA.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.1-10
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• 2022

As the volume of marine hazardous and noxious substances (HNSs) transported in domestic and overseas seas increases, the risk of HNS spill accidents is gradually increasing. HNS leaked into the sea causes destruction of marine ecosystems, pollution of the marine environment, and human casualties. Secondary accidents accompanied by fire and explosion are possible. Therefore, various types of HNSs must be rapidly detected, and a control strategy suitable for the characteristics of each substance must be established. In this study, the ground HNS spill experiment process and application result of detection algorithms were presented based on hyperspectral remote sensing. For this, styrene was spilled in an outdoor pool in Brest, France, and simultaneous observation was performed through a hyperspectral sensor. Pure styrene and seawater spectra were extracted by applying principal component analysis (PCA) and the N-Findr method. In addition, pixels in hyperspectral image were classified with styrene and seawater by applying spectral matching techniques such as spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), and spectral angle mapper (SAM). As a result, the SDS and SSV techniques showed good styrene detection results, and the total extent of styrene was estimated to be approximately 1.03 m². The study is expected to play a major role in marine HNS monitoring.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.201-212
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• 2003

Recently, the ability of earthquake detection in the Kyungsang Basin of southeastern Korean Peninsula is greatly improved since seismic stations including seismic network of KIGAM(Korea Institute of Geoscience and Mineral Resources) have been significantly increased. However, a large number of signals from explosions are recorded because of frequent medium to large chemical explosions. The discrimination between natural earthquakes and explosions in the Basin has become an important issue. High frequency local records from 43 earthquakes and 43 explosions with comparable magnitude are selected to establish a reliable discrimination technique in the Basin. Several discrimination techniques in spectral domain using spectral amplitude ratios among Pg, Sg, and Lg waves are widely examined with tile selected data. Among them the Pg/Lg spectral ratio method is appeared to be a good discrimination technique to improve the discrimination power. Multivariate discriminant analysis is also applied to the Pg/Lg spectral ratios. The discrimination power of the Pg/Lg ratios for distance corrected three component record compared to uncorrected vertical component one shows distinct improvement. In the frequency band 4 to 14 Hz, Pg/Lg spectral ratio for distance corrected three component record provides discrimination power with a total misclassification probability of only 0.89%.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3124-3124
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• 2001

The development and evolution of near infra-red spectroscopic (NIS) calibrations for high-moisture materials is an expensive proposition. Such investment is suspect unless the instrument, or instruments, on which calibrations were developed can be preserved intact or re-standardized as component replacements occurs. The objective of this paper is to detail the changes in performance of a six-year old instrument after maintenance in years five and six resulted in collection of spectral data that was increasingly removed from the calibration population. Calibrations for the analysis of mature sugarcane stalks, a high-moisture material, were developed successfully in 1995 using a broad sample population in terms of genetics, and spectral and temporal variation. The spectral library was further broadened in 1996. In 1997, 1999, 1999, and 2000, additional samples constituting 10% of the laboratories throughput were subjected to full component analyses using routine laboratory techniques. These samples were primarily random samples, but were complemented with samples that were significant for the spectral H statistic or for the component t statistic. In 1998, an additional calibration was developed for populations consisting of samples of either mature stalks (culms) or sucker culms. Substantial additional samples numbers were collected for this calibration in 1999 and 2000. Attempts to standardize the scanning spectrophotometer used for these calibrations with a second similar instrument in 1999 failed because the instruments were optically different, and standardization could not account for this. Maintenance adjustments were made to the remote reflectance probe of the original instrument in 1999, and replacement of its PbS detectors was done in 2000. Spectral data collected in 1999 and 2000 yielded spectral populations that were increasingly removed from the respective spectral populations on which the calibrations were developed. The mature stalk calibrations benefited marginally from evolutionary calib.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.39-54
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• 2012

The objective of this study is to propose efficient data fusion techniques feasible to the KOMPSAT-2 satellite images. The most widely used image fusion techniques, which are the high-pass filter (HPF), the intensity-hue-saturation-based (modified IHS), the pan-sharpened, and the wavelet-based methods, was applied to four KOMPSAT - 2 satellite images having different regional and seasonal characteristics. Each fusion result was compared and analyzed in spatial and spectral features, respectively. Quality evaluation of image fusion techniques was performed in both quantitative and visual analysis. The quantitative analysis methods used for this study were the relative global dimensional error (spatial and spectral ERGAS), the spectral angle mapper index (SAM), and the image quality index (Q4). The results of quantitative and visual analysis indicate that the pan-sharpened method among the fusion methods used for this study relatively has the suitable balance between spectral and spatial information. In the case of the modified IHS method, the spatial information is well preserved, while the spectral information is distorted. And also the HPF and wavelet methods do not preserve the spectral information but the spatial information.

• Journal of KIISE
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• v.43 no.6
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• pp.686-691
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• 2016

In this paper, we introduced the adaptive spectral co-clustering, a spectral clustering for multiview data, especially data with more than three views. In the adaptive spectral co-clustering, the performance is improved by sharing information from diverse views. For the efficiency in information sharing, a co-training approach is adopted. In the co-training step, a set of parameters are estimated to make all views in data maximally independent, and then, information is shared with respect to estimated parameters. This co-training step increases the efficiency of information sharing comparing with ordinary feature concatenation and co-training methods that assume the independence among views. The adaptive spectral co-clustering was evaluated with synthetic dataset and multi lingual document dataset. The experimental results indicated the efficiency of the adaptive spectral co-clustering with the performances in every iterations and similarity matrix generated with information sharing.

• Journal of the Optical Society of Korea
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• v.20 no.4
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• pp.515-523
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• 2016

Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm does not make full use of this characteristic sparseness, the compressive sensing algorithm can make full use of it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuit algorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficient is introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used to select the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation on the MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy based on the DOMP algorithm is higher than for the other three methods. The root-mean-square error and color difference decreases with an increasing number of principal components. The reconstruction error decreases as the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improve the accuracy of color-information replication effectively, and high-accuracy color-information reproduction can be realized.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.39-46
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• 2001

In this paper we propose a new method that can be estimation the spectral power distribution of the light source from three-band images. the light source is estimated by dividing the reflected spectral power distribution of the maximum achromatic region(L(λ)) by the corresponding surface reflectance(Ο(λ)). In order to obtain reflected spectral power distribution of the maximum achromatic region from three-bend images, a modified gray world assumption algorithm is adapted. And the maximum surface reflectance is estimated using the principal component analysis method along with achromatic population. The achromatic population is created from a set of given Munsell color chips whose chroma vector is less than threshold. Cumulative contribution ratio of principal components from the first to the third for classified achromatic population was about 99.75%. The reconstruction of illumination spectral power distribution by using achromatic population and three-band digital images captured under various light source was examined, and evaluated by RMSE between the original and reconstructed illumination spectral power distribution. This work was supported by grant No (2000-1-30200-005-3) from the Basic Research Program of the Korea Science & Engineering Foundation.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.1
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• pp.1-11
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• 2000

The hybrid coding algorithm for multi-spectral image obtained from satellite is discussed. As the spatial and spectral resolution of satellite image are rapidly increasing, there are enormous amounts of data to be processed for computer processing and data transmission. Therefore an efficient coding algorithm is essential for multi-spectral image processing. In this paper, VQ(vector quantization), quadtree decomposition, and DCT(discrete cosine transform) are combined to compress the multi-spectral image. VQ is employed for predictive coding by using the fact that each band of multi-spectral image has the same spatial feature, and DCT is for the compression of residual image. Moreover, the image is decomposed into quadtree structure in order to allocate the data bit according to the information content within the image block to improve the coding efficiency. Computer simulation on Landsat TM image shows the validity of the proposed coding algorithm.