• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.330-336
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• 2011

In this paper, we propose a new method to improve the performance of supervector linear kernel SVM (Support Vector Machine) for speaker identification. This method is based on splitting one training datum into several pieces of utterances. We use four different databases for evaluating performance and use PCA (Principal Component Analysis), GKPCA (Greedy Kernel PCA) and KMDA (Kernel Multimodal Discriminant Analysis) for feature enhancement. As a result, the proposed method shows improved performance for speaker identification using supervector linear kernel SVM.

• Journal of Construction Engineering and Project Management
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• v.2 no.4
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• pp.11-19
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• 2012

Construction supply chain management (CSCM) has become one of the critical factors that determine the success of a construction project as it becomes increasingly complicated and mega-sized. Particularly for high-rise or mega-sized building construction, just-in-time supply chain management is required due to lack of storage space and effective logistics for construction components and materials at a construction site. Despite the fact that research and development of radio frequency identification (RFID) and wireless sensor network (WSN) technology have been performed, construction project managers still need to carry mobile devices and check material and component flow at each stage of the supply chain process. This research proposes that the equipment used in the construction supply chain process, such as movers, trailers, gates, and hoists, can become main actors in the supply chain process using RFID and WSN technologies. And the proposed equipment and process focused on a solution to the redundancy identification problem, which has been observed in operations that use RFID/WSN-based processes for construction logistics. This paper also presents issues identified through verification and validation of the research results and proposes further studies.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.200-206
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• 2024

Computing music similarity is an indispensable component in developing music search service. This paper proposes a relevance weight of each chromagram vector for cover song identification in computing a music similarity function in order to boost identification accuracy. We derive a music similarity function using the relevance weight based on the probabilistic relevance model, where higher relevance weights are assigned to less frequently-occurring discriminant chromagram vectors while lower weights to more frequently-occurring ones. Experimental results performed on two cover music datasets show that the proposed music similarity improves the cover song identification performance.

• Journal of Microbiology and Biotechnology
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• v.29 no.4
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• pp.548-557
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• 2019

Staphylococcus species have a ubiquitous habitat in a wide range of foods, thus the ability to identify staphylococci at the species level is critical in the food industry. In this study, we performed rapid identification of Staphylococcus species using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry (MALDI-TOF MS). MALDI-TOF MS was evaluated for the identification of Staphylococcus reference strains (n = 19) and isolates (n = 96) from various foods with consideration for the impact of sample preparation methods and incubation period. Additionally, the spectra of isolated Staphylococcus strains were analyzed using principal component analysis (PCA) and a main spectra profile (MSP)-based dendrogram. MALDI-TOF MS accurately identified Staphylococcus reference strains and isolated strains: the highest performance was by the EX method (83.3~89.5% accuracy) at species level identification (EDT, 70.3~78.9% accuracy; DT, less than 46.3~63.2% accuracy) of 24-h cultured colonies. Identification results at the genus level were 100% accurate at EDT, EX sample preparation and 24-h incubation time. On the other hand, the DT method showed relatively low identification accuracy in all extraction methods and incubation times. The analyzed spectra and MSP-based dendrogram showed that the isolated Staphylococcus strains were characterized at the species level. The performance analysis of MALDI-TOF MS shows the method has the potential ability to discriminate between Staphylococcus species from foods in Korea. This study provides valuable information that MALDI-TOF MS can be applied to monitor microbial populations and pathogenic bacteria in the food industry thereby contributing to food safety.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.87-92
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• 2007

Recently, developments of process monitoring system in order to detect and diagnose process abnormalities has got the spotlight in process systems engineering. Normal data obtained from processes provide available information of process characteristics to be used for modeling, monitoring, and control. Since modern chemical and environmental processes have high dimensionality, strong correlation, severe dynamics and nonlinearity, it is not easy to analyze a process through model-based approach. To overcome limitations of model-based approach, lots of system engineers and academic researchers have focused on statistical approach combined with multivariable analysis such as principal component analysis (PCA), partial least squares (PLS), and so on. Several multivariate analysis methods have been modified to apply it to a chemical process with specific characteristics such as dynamics, nonlinearity, and so on.This paper discusses about missing value estimation and sensor fault identification based on process variable reconstruction using dynamic PCA and canonical variate analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.491-499
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• 2001

In this paper, the scheme of an efficient fuzzy rule generation and fuzzy system construction using GA(genetic algorithm) and FCM(fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. In the structure identification, input data is transformed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, a set fuzzy rules are generated for a given criterion by FCM clustering algorithm . In the parameter identification premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this one can systematically obtain the valid number of fuzzy rules which shows satisfying performance for the given problem. Finally, we applied the proposed method to the Box-Jenkins data and rice taste data modeling problems and obtained a better performance than previous works.

• Horticultural Science & Technology
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• v.17 no.1
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• pp.23-28
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• 1999

To examine taxonomic relationships among 53 plums derived from Prunus cerasifera, P. domestica, and P. salicina, principal component analysis (PCA) and cluster analysis on 27 morphological characters were conducted. Of 27 characters, leaf size, leaf shape, and leaf hair were useful characters for plum identification and understanding of taxonomic relationships among them. Leaf length, petiole length, number of leaf nectaries, leaf shape, leaf base, and date of full blooming showed the clear differences between P. salicina group and P. domestica group. Results of cluster analysis using scores of the first three principal components indicated that 53 plums could be grouped into P. salicina-P. cerasifera, P. domestica, and P. spinosa phenon at 1.0 of average distance in UPGMA. Although PCA was useful for rough classification of plums, much more characters were needed for the exact classification.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.128-141
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• 2015

Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: instability and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to validate the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

• Journal of the Korean Society of Propulsion Engineers
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• v.9 no.4
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• pp.81-88
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle). In order to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. When the performance analysis is performed at far away operation conditions from the design point, in case of use of e component map by the traditional scaling method, the error of the performance analysis results is greatly increasing. In the other hand, if in case of use of the compressor map generated by the proposed GAs scheme, the performance analysis results are closely met with those by the performance deck, EEPP.

• YAKHAK HOEJI
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• v.34 no.4
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• pp.277-281
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• 1990

The isolation and identification of an antibacterial component, from Polygoni Radix against a cariogenic bacterium Streptococcus mutans OMZ 176, were carried out for development of anticariogenic agents. The bioactive component was identified to be emodin. The minimal inhibitory concentration (MIC) of emodin was $100\;{\mu}g/ml$ against S. mutans OMZ 176. The bioactive component emodin weakly inhibited ${\beta}-lactamase$ activity with the inhibition ratio of 1.7, 4.3 and 7.6% at the concentration of 50, 100, and 200 uM, respectively. Emodin exhibited slight phototoxicity when analysed by the photohemolysis method.