• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5280-5287
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• 2014

This paper proposes a method in which classes are grouped as a hierarchical tree structure for the effective classification of the Raman spectra. As experimental data, the Raman spectra of 28 chemical compounds were obtained, and pre-treated with noise removal and normalization. The spectra that induced a classification error were grouped into the same class and the hierarchical structure class was composed. Each high and low class was classified using a PCA-MAP method. According to the experimental results, the classification of 100% was achieved with 2.7 features on average when the proposed method was applied. Considering that the same classification rates were achieved with 6 features using the conventional method, the proposed method was found to be much better than the conventional one in terms of the total computational complexity and practical application.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.48 no.1
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• pp.34-42
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• 2016

In this study, we classified three copying papers and Korean, Chinese, and Japanese traditional papers using IR and/or NIR spectra and principal component analysis. Various chemicals are used when producing fine papers. In this case, the IR method to analyze functional groups is suitable for the classification of paper. On the other hand, NIR analysis is more suitable for the classification of traditional papers, as it uses nearly raw materials (pulp). Therefore, principal component analysis using IR and NIR depending on the paper production process will be the classification tool of paper.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.4
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• pp.65-77
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• 2007

Site response analyses were performed based on equivalent linear technique using shear wave velocity profiles of 162 sites collected around the Korean peninsula. The site characteristics, particularly the shear wave velocities and the depth to the bedrock, are compared to those in the western United States. The results show that the site-response coefficients based on the mean shear velocity of the top 30m ($V_{S30}$) suggested in the current code underestimates the motion in short-period ranges and overestimates the motion in mid-period ranges. The current Korean code based on UBC is required to be modified considering site characteristics in Korea for the reliable estimation of site amplification. From the results of numerical estimations, new regression curves were derived between site coefficients ($F_{a}\;and\;F_{v}$) and the fundamental site periods, and site coefficients were grouped based on site periods with reasonable standard deviations compared to site classification based on $V_{S30}$. Finally, new site classification system and modification of design response spectra are recommended considering geotechnical characteristics in Korea.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1248-1248
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• 2001

Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and considerable compositional changes in milk, reducing milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm and chemometric method for classification to detect milk from mastitic cows was investigated. A total of 189 milk samples from 7 Holstein cows were collected for 27 days, consecutively, and analyzed for somatic cells (SCC). Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in the spectral range from 1100 to 2500nm. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. The classification of the samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two concentration of SCC - 200 000 cells/ml and 300 000 cells/ml, respectively, were used as thresholds fer separation of healthy and mastitis cows. The best detection accuracy was found for models, obtained using 200 000 cells/ml as threshold and smoothed absorbance data - 98.41% from samples in the calibration set and 87.30% from the samples in the independent test set were correctly classified. SIMCA results for classes, based on 300 000 cells/ml threshold, showed a little lower accuracy of classification. The analysis of changes in the loading of first PC factor for group of healthy milk and group of mastitic milk showed, that separation between classes was indirect and based on influence of mastitis on the milk components. The accuracy of mastitis detection by SIMCA method, based on NIR spectra of milk would allow health screening of cows and differentiation between healthy and mastitic milk samples. Having SIMCA models, mastitis detection would be possible by using only DIR spectra of milk, without any other analyses.

• Journal of the Korean Wood Science and Technology
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• v.47 no.4
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• pp.509-518
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• 2019

This study analyzed the effect of organic solvent extractives on the classification of wood species via near-infrared spectroscopy (NIR). In our previous research, five species of Korean softwood were classified into three groups (i.e., Cryptomeria japonica (cedar)/Chamaecyparis obtuse (cypress), Pinus densiflora (red pine)/Pinus koraiensis (Korean pine), and Larix kaempferi (Larch)) using an NIR-based principal component analysis method. Similar tendencies of extractive distribution were observed among the three groups in that study. Therefore, in this study, we qualitatively analyzed extractives extracted by an organic solvent and analyzed the NIR spectra in terms of the extractives' chemical structure and band assignment to determine their effect in more detail. Cedar/cypress showed a similar NIR spectra patterns by removing the extractives at 1695, 1724, and 2291 nm. D-pinitol, which was detected in cedar, contributed to that wavelength. Red pine/Korean pine showed spectra changes at 1616, 1695, 1681, 1705, 1724, 1731, 1765, 1780, and 2300 nm. Diterpenoids and fatty acid, which have a carboxylic group and an aliphatic double bond, contributed to that wavelength. Larch showed a catechin peak in gas chromatography and mass spectroscopy analysis, but it exhibited very small NIR spectra changes. The aromatic bond in larch seemed to have low sensitivity because of the 1st overtone of the O-H bond of the sawdust cellulose. The three groups sorted via NIR spectroscopy in the previous research showed quite different compositions of extractives, in accordance with the NIR band assignment. Thus, organic solvent extractives are expected to affect the classification of wood species using NIR spectroscopy.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.33-39
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• 2007

Hyperspectral remote sensing data contain plenty of information about objects, which makes object classification more precise. In this paper, we proposed a new spectral similarity measure, called Spectral Mutual Information (SMI) for hyperspectral image classification problem. It is derived from the concept of mutual information arising in information theory and can be used to measure the statistical dependency between spectra. SMI views each pixel spectrum as a random variable and classifies image by measuring the similarity between two spectra form analogy mutual information. The proposed SMI was tested to evaluate its effectiveness. The evaluation was done by comparing the results of preexisting classification method (SAM, SSV). The evaluation results showed the proposed approach has a good potential in the classification of hyperspectral images.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.113-124
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• 2006

Despite the site classification method was improved in the previous study, the response spectrum would be required to be modified by adjusting the integration interval to calculate the site coefficients because the response spectra did not match well the average spectral accelerations obtained by site response analyses in the range of long periods. In this paper, new response spectra for each site categories were determined by adjusting the integration interval of long-period site coefficient $F_{v}$ from $0.4{\sim}2.0$ to $0.4{\sim}1.5$ second. It matched well the average spectral accelerations and new response spectrum, and it was also improved compared to the current site classification system.

• Current Optics and Photonics
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• v.6 no.1
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• pp.92-103
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• 2022

The development of midinfrared (mid-IR) quantum cascade lasers (QCLs) has enabled rapid high-contrast measurement of the mid-IR spectra of biological tissues. Several studies have compared the differences between the mid-IR spectra of colon cancer and noncancerous colon tissues. Most mid-IR spectrum classification studies have been proposed as machine-learning-based algorithms, but this results in deviations depending on the initial data and threshold values. We aim to develop a process for classifying colon cancer and noncancerous colon tissues through a deep-learning-based convolutional-neural-network (CNN) model. First, we image the midinfrared spectrum for the CNN model, an image-based deep-learning (DL) algorithm. Then, it is trained with the CNN algorithm and the classification ratio is evaluated using the test data. When the tissue microarray (TMA) and routine pathological slide are tested, the ML-based support-vector-machine (SVM) model produces biased results, whereas we confirm that the CNN model classifies colon cancer and noncancerous colon tissues. These results demonstrate that the CNN model using midinfrared-spectrum images is effective at classifying colon cancer tissue and noncancerous colon tissue, and not only submillimeter-sized TMA but also routine colon cancer tissue samples a few tens of millimeters in size.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.123-126
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• 1991

A generalization of null-spectrum for use in the estimation of directions of arrival of signal sources is considered in this paper. The upper and lower bounds of the generalized null-spectrum, the maximum and minimum null-spectra, are also derived. We observed that the maximum null-spectrum has higher resolution capability than other null-spectra including the two well-known null-spectra, the multiple signal classification null-spectrum and the Min-Norm null-spectrum.

• Earthquakes and Structures
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• v.15 no.1
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• pp.1-8
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• 2018

A new site classification system and site coefficients based on local site conditions in Korea were developed and implemented as a part of minimum design load requirements for general seismic design. The new site classification system adopted bedrock depth and average shear wave velocity of soil above the bedrock as parameters for site classification. These code provisions were passed through a public hearing process before it was enacted. The public hearing process recommended to modify the naming of site classes and adjust the amplification factors so that the level of short-period amplification is suitable for economical seismic design. In this paper, the new code provisions were assessed using dynamic centrifuge tests and by comparing the design response spectra (DRS) with records from 2016 Gyeongju earthquake, the largest earthquake in history of instrumental seismic observation in Korea. The dynamic centrifuge tests were performed to simulate the representative Korean site conditions, such as shallow depth to bedrock and short-period amplification characteristics, and the results corroborated with the new DRS. The Gyeongju earthquake records also showed good agreement with the DRS. In summary, the new code provisions are reliable for representing the site amplification characteristic of shallow bedrock condition in Korea.