• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.211-216
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• 2006

The Constrained Linear Spectral Unmixing(CLSU) is investigated for sub-pixel image processing, Its result is the abundance map which mean fractions of endmember existing in a mixed pixel. Compared to the Linear Spectral Unmixing using least square method, CLSU uses the NNLS (Non-Negative Least Square) algorithm to guarantee that the estimated fractions are constrained. But, CLSU gets Into difficulty in image processing due to select endmember at a user's disposition. In this study, endmember selection optimization method using entropy in the error-image analysis is proposed. In experiments which is used hyperion image, it is shown that our method can select endmember number than CLSU based on unsupervised endemeber selection.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.1
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• pp.1-7
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• 2009

To establish the Fourier-Transform Infra-Red spectrophotometry(FTIR) Direct-On-Filter(DOF) technique as a useful analytical method for quartz in respirable dust samples, an influence of the kaolinite should be corrected. Respirable dust, created in a dust chamber containing the standard material of quartz and kaolinite were collected using a cyclone equipped with a 25 mm, $0.8\;{\mu}m$ pore size DM filter as a collection medium. This study was designed to compare three methods of correction for kaolinite when quantifying the content of quartz, including the least square, the optimum choice and the spectral subtraction methods. The content of quartz in the respirable dust samples was overestimated by 6.2% when mixed with kaolinite(35.5% by weight). The content of quartz containing kaolinite(72.8% by weight) were overestimated by 32%. The spectral subtraction method underestimated the quartz content by 1.5%, while the other two correction methods, the optimum choice and the least square method, overestimated the quartz content by 1.9% to 6.4% and 0.04 to 1.1%, respectively. The results of this study are suggested that, when correcting for effects of kaolinite on quantitative analysis of quartz in respirable dust by FTIR direct-on-filter method, the least square method produce the most unbiased results be compared with those of other correction methods.

• Earthquakes and Structures
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• v.15 no.3
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• pp.263-273
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• 2018

Operational modal analysis is being widely used in aerospace, mechanical and civil engineering. Common research fields include optimal design and rehabilitation under dynamic loads, structural health monitoring, modification and control of dynamic response and analytical model updating. In many practical cases, influence of noise contamination in the recorded data makes it difficult to identify the modal parameters accurately. In this paper, an improved frequency domain method called Enhanced Least Square Complex Frequency (eLSCF) is developed to extract modal parameters from noisy recorded data. The proposed method makes the use of pre-defined approximate mode shape vectors to refine the cross-power spectral density matrix and extract fundamental frequency for the mode of interest. The efficiency of the proposed method is illustrated using an example five story shear frame loaded by random excitation and different noise signals.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.17 no.1
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• pp.21-30
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• 2007

To establish the Fourier-transform infra-red spectrophotometry (FTIR) direct-on-filter(DOF) technique as a useful analytical method for quartz in respirable dust samples, influence of the interference should be corrected. This study was designed to compare three methods of correction for cristobalite when quantifying the content of quartz, including the least square, the optimum choice and the spectral subtraction methods. Respirable dust, created in a dust chamber containing the standard material of quartz, cristobalite was collected using a cyclone equipped with a 25 mm, $0.8{\mu}m$ pore size DM filter as a collection medium. The quartz weights overestimated about 100% when mixed of cristobalite by measure using 799 cm-1 absorption peak of quartz. The quartz weights appeared over estimated by optimum choice, spectral subtraction and least square method in mixtures of 33% cristobalite were 90.3%, 60.1% and about 4.3%, respectively. The least square method have been adopted to correction methods of cristobalite and satisfactory results have been obtained. The results of this study suggest that, when correcting for effect of cristobalite on quantitative analysis of quartz in respirable dust by FTIR direct-on-filter method, the least square method produce the most unbiased results compared with those of other correction methods.

• Horticultural Science & Technology
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• v.34 no.2
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• pp.324-330
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• 2016

To determine whether FT-IR spectral analysis based on multivariate analysis for whole cell extracts can be used to discriminate between artichoke (Cynara cardunculus var. scolymus L.) plants at the metabolic level, leaves of ten artichoke plants were subjected to Fourier transform infrared(FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions reflect the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). PCA revealed separate clusters that corresponded to their species relationship. Thus, PCA could be used to distinguish between artichoke species with different metabolite contents. PLS-DA showed similar species classification of artichoke. Furthermore these metabolic discrimination systems could be used for the rapid selection and classification of useful artichoke cultivars.

• Journal of the Korean Geophysical Society
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• v.5 no.3
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• pp.233-245
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• 2002

The spectral-analysis-of-surface-waves (SASW) method is a nondestructive testing method based upon generation and detection of elastic stress waves. SASW is widely used as one of the techniques to determine stiffness profile in engineering geophysics. The essential steps involved are construction of an experimental dispersion curve from data collected in situ, and inversion of the dispersion curve to determine the stiffness profile. The main object of this study is to derive an analytical Jacobian for the inversion. If we set the subsurface to N homogeneous layer, it could save 2N times Jacobian calculation compared to numerical jacobian calculation during inversion. To reconstruct a stiffness profile, constrained damped least square method was applied for the inversion. The algorithm was tested for the numerical data and for the real asphalt and tunnel data, which were able to verify the stiffness profile. The stiffness profile reconstructed by the algorithm showed the possibility to appraise the soundness of tunnel with applications SASW.

• YAKHAK HOEJI
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• v.47 no.5
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• pp.261-265
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• 2003

Near-infrared (NIR) system was used to determine rapidly and simply indomethacin in buffer solution for a dissolution test of tablets and capsules. Indomethacin standards were prepared ranging from 10 to 50 ppm using the mixture of phosphate buffer (pH 7.2) and water (1 : 4). The near-infrared (NIR) transmittance spectra of indomethacin standard solutions were collected by using a quartz cell in 1 mm and 2 mm pathlength. Partial least square regression (PLSR) was explored to develop calibration models over the spectral range 1100∼1700 nm. The model using 1 mm quartz cell was better than that using 2 mm quartz cell. The PLSR models developed gave standard error of prediction (SEP) of 0.858 ppm. In order to validate the developed calibration model, routine analysis was performed using another standard solutions. The NIR routine analysis showed good correlation with actual values. Standard error of prediction (SEP) is 1.414 ppm for 7 indomethacin samples in routine analysis and its error was permeable in the regulation of Korean Pharmacopoeia (VII). These results show the potential use of the real time monitoring for indomethacin during a dissolution test.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.1-11
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• 2015

In this study, an online seed potato sorting system using a visible and near infrared (40 1100 nm) transmittance spectral technique and statistical model was evaluated for the nondestructive determination of infected and sound seed potatoes. Seed potatoes that had been artificially infected with Pectobacterium atrosepticum, which is known to cause a soil borne disease infection, were prepared for the experiments. After acquiring transmittance spectra from sound and infected seed potatoes, a determination algorithm for detecting infected seed potatoes was developed using the partial least square discriminant analysis method. The coefficient of determination($R^2_p$) of the prediction model was 0.943, and the classification accuracy was above 99% (n = 80) for discriminating diseased seed potatoes from sound ones. This online sorting system has good potential for developing a technique to detect agricultural products that are infected and contaminated by pathogens.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.4
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• pp.379-385
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• 2000

In order to evaluate the stability of permanent GPS arrays for obtaining high precision coordinates, spectral analysis uses the least square spectrum analysis to the coordinate variations of Suwon, Tsukuba and Sanghai stations. Permanent GPS observations at Suwon, Tsukuba and Sanghai have been more or less continuously carried out since 1994. Time series of the resulting coordinate variations are analyzed for long term repeatability and periodic behaviour.

• Journal of Plant Biotechnology
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• v.38 no.1
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• pp.9-14
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• 2011

To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves of nine commercial Orostachys plants were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA). The dendrogram based on hierarchical clustering analysis of these PLS-DA data separated the nine Orostachys species into five major groups. The first group consisted of O. iwarenge 'Yimge', 'Jeju', 'Jeongsun' and O. margaritifolius 'Jinju' whereas in the second group, 'Sacheon' was clustered with 'Busan,' both of which belong to O. malacophylla species. However, 'Samchuk', belong to O. malacophylla was not clustered with the other O. malacophylla species. In addition, O. minuta and O. japonica were separated to the other Orostachys plants. Thus we suggested that the hierarchical dendrogram based on PLS-DA of FT-IR spectral data from leaves represented the most probable chemotaxonomical relationship between commercial Orostachys plants. Furthermore these metabolic discrimination systems could be applied for reestablishment of precise taxonomic classification of commercial Orostachys plants.