• Horticultural Science & Technology
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• v.34 no.1
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• pp.163-171
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• 2016

We investigated the intensity and pattern of the scent produced by diploid and tetraploid Cymbidium flowers, using an electronic nose with 6 metal oxide sensors (MOS). The MOS responses were evaluated by principal component analysis, discriminant function analysis, and sensor data. These analyses revealed that tetraploid flowers had a stronger scent than diploid flowers in Cymbidium Golden Elf 'Sundust'. Furthermore, among the different flower parts-column, lip, and petals-the column produced the strongest scent. There was no significant difference between the flowering periods of diploid and tetraploid potted Cymbidium Golden Elf 'Sundust' and Cymbidium Elma 'Orient Toyo' grown in a greenhouse. Moreover, there were no significant differences between the number of flowers per flower stem and the length of flower stems on the diploid and tetraploid plants of these two Cymbidium cultivars. This study provides potentially useful information for the breeding of polyploidy Cymbidium in the floriculture industry.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.71-96
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• 2023

This study aimed to investigate key research areas in the field of Library and Information Science (LIS) by analyzing trends and identifying emerging topics. To facilitate the research, a collection of 40,897 author keywords from 11,252 papers published in the past 30 years (1993-2022) in five journals was gathered. In addition, keyword analysis, as well as Principal Component Analysis (PCA) and correlation analysis were conducted, utilizing variables such as the number of articles, number of authors, ratio of co-authored papers, and cited counts. The findings of the study suggest that two topics are likely to develop as promising research areas in LIS in the future: machine learning/algorithm and research impact. Furthermore, it is anticipated that future research will focus on topics such as social media and big data, natural language processing, research trends, and research assessment, as they are expected to emerge as prominent areas of study.

• The KIPS Transactions:PartB
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• v.13B no.6 s.109
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• pp.601-606
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• 2006

The image data amount that used in medical institution with great development of medical technology is increasing rapidly. Therefore, people need automation method that use image processing description than macrography of doctors for analysis many medical image. In this paper. we propose that acquire texture information to using GLCM about liver area of abdomen CT image, and automatically detects liver tumor using PCA from this data. Method by one feature as intensity of existent liver humor detection was most but we changed into 4 principal component accumulation images using GLCM's texture information 8 feature. Experiment result, 4 principal component accumulation image's variance percentage is 89.9%. It was seen this compare with liver tumor detecting that use only intensity about 92%. This means that can detect liver tumor even if reduce from dimension of image data to 4 dimensions that is the half in 8 dimensions.

• YAKHAK HOEJI
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• v.49 no.1
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• pp.74-79
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• 2005

Metabonomic analysis has been recognized as a powerful approach for characterizing metabolic changes in biofluids due to toxicity, disease process or environmental influences. To investigate the possibility of relating metabolic changes with $^{1}H-NMR$ spectra, urine samples from Sprague-Dawley rats treated with various dietary restrictions or toxic substances (nicotine) were analysed using $^{1}H-NMR$ spectroscopy and pattern recognition techniques. Dietary restrictions-given to male rats were normal diet and high fat diet and fasting. The nicotine urine samples were collected from SD rats administered with nicotine (25 mg/kg) at the various time intervals. $^{1}H-NMR$ spectra of all urine samples were acquired at 400 MHz on a VARIAN spectrometer. To establish the presence of any intrinsic class-related patterns or clusters in each NMR data, methods of PCA (principal component analysis) and soft independent modeling of class analogy (SIMCA) analysis were used, and the results from these analyses were compared to each other. In all cases of dietary conditions and nicotine treatment, SIMCA analysis gave better results for the discrimination of NMR spectra of urine samples than PCA.

• Korean Journal of Plant Taxonomy
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• v.41 no.3
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• pp.223-229
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• 2011

The taxonomy of the Isodon excisus complex has been ambiguous and problematic because the morphological characters, especially characters related to the leaf distinguishing subgroups of the complex in the original descriptions, are variable. To elucidate the taxonomic structure of the I. excisus complex in Korea, 34 characters were measured from 70 OTUs representing different locations and analyzed by principal component analysis (PCA). The analysis showed that principle component axis 1, 2, 3 (PC1, PC2, PC3) represents 52.0% of the total variance and characters showing high loading values for PC1 were leaf shape, density of non-glandular hairs on the lower surface of the leaf, and characters related to the teeth of the leaf. The length of apical tooth and the angle between two widest points of the leaf were highly correlated to PC2 and PC3, respectively. Three-dimensional scatter plotting of OTUs for PC1, PC2, and PC3 axis showed that the areas of previously recognized three subgroups of I. excisus completely overlapped. Our result supported that just one taxon, I. excisus var. excisus, should be recognized in the complex at the variety level.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.15-21
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• 2010

In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, the research about the signal compression is not enough than a signal alignment and a noise reduction; even though that can reduce considerably the computation time for the power analysis. But, the existing compression method can sometimes reduce the performance of the power analysis because those are the unsophisticated method not considering the characteristic of the signal. In this paper, we propose the new PCA (principal component analysis)-based signal compression method, which can block the loss of the meaningful factor of the original signal as much as possible, considering the characteristic of the signal. Also, we prove the performance of our method by carrying out the experiment.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.196-199
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• 2008

Lineament is defined generally as a linear feature or pattern on interpretation of a satellite image and indicates the geological structures such as faults and fractures. For this reason, a lineament extraction and analysis using remote sensing images have been widely used for mapping large areas. The Gyeong-gang Fault is a NNE trending structure located in Gangwon-do and Kyeonggi-do district. However, a few geological researches on that fault have been carried out and its trace or continuity is ambiguous. In this study, we investigate the geologic features at Gyeong-gang Fault Zone using LANDSAT ETM+ satellite image and SRTM digital elevation model. In order to extract the characteristics of geologic features effectively, we transform the LANDSAT ETM+ image using Principal Component Analysis (PCA) and create a shade relief from SRTM data with various illumination angles. The results show that it is possible to identify the dimensions and orientations of the geologic features at Gyeong-gang Fault Zone using remote sensing data. An aerial photograph interpretation and a field work will be future tasks for more accurate analysis in this area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2919-2937
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• 2020

Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme's optimized implementation performed well at high speeds.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.555-567
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• 2014

Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric system is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-classification fusion that is based on the similarity of the maximum of matching scores. The proposed solution enhances biometric recognition performances based on suitable feature selection and reduction, such as principal component analysis (PCA) and linear discriminant analysis (LDA), as much as not all of the feature vectors components support the performance improvement degree.

• Bulletin of the Korean Chemical Society
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• v.32 no.5
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• pp.1547-1553
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• 2011

An effective analytical method of gas chromatography/mass spectrometry (GC/MS) was developed for the rapid determination of essential oils in the crude extract of Acorus species (Acorus gramineus, Acorus tatarinowii, and Acorus calamus). Major phenypropanoids (${\beta}$,${\alpha}$-asarone isomers, euasarone, and methyleugenol) and ${\beta}$-caryophyllene in Acorus species were used as marker compounds and determined for the quality control of herbal medicines. To extract marker compounds, various extraction techniques such as solvent immersion, mechanical shaking, and sonication were compared, and the greatest efficiency was observed with sonication extraction using petroleum ether. The dynamic range of the GC/MS method depended on the specific analyte; acceptable quantification was obtained between 10 and 2000 ${\mu}g/mL$ for ${\beta}$-asarone, 10 and 500 ${\mu}g/mL$ for ${\alpha}$-asarone, 10 and 200 ${\mu}g/mL$ for methyleugenol, and between 5 and 100 ${\mu}g/mL$ for ${\beta}$-caryophyllene. The method was deemed satisfactory by inter- and intra-day validation and exhibited both high accuracy and precision, with a relative standard deviation < 10%. Overall limits of detection were approximately 0.34-0.83 ${\mu}g/mL$, with a standard deviation (${\sigma}$)-to-calibration slope (s) ratio (${\sigma}$/s) of 3. The limit of quantitation in our experiments was approximately 1.13-3.20 ${\mu}g/mL$ at a ${\sigma}$/s of 10. On the basement of method validation, 20 samples of Acorus species collected from markets in Korea were monitored for the quality control. In addition, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed on the analytical data of 20 different Acorus species samples in order to classify samples that were collected from different regions.