• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2001.05a
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• pp.144-145
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• 2001

Marine microalgae are used extensively in mariculture as food for marine animals, in particular larval and juvenile molluscs, crustaceans and fish. A wide range of microalgae has been tested, because not all species are equally successful in supporting growth of a particular animal. In addition, bioactivities of marine microalgae are recently investigated for the effective exploitation of unutilized marine resources. (omitted)

• East Asian Economic Review
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• v.22 no.4
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• pp.467-505
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• 2018

We propose a simple identification scheme for the causes of the violations of uncovered interest parity. Our method uses the serial dependence patterns of excess returns as a criterion for judging performance of economic models. We show that a mean reverting component in excess returns, representing a violation of uncovered interest parity, mainly contributes to generating different serial dependence patterns of excess returns: rational expectations risk premium models tend to generate negative serial dependence of excess returns, while expectational errors models tend to generate positive serial dependence.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.314.1-314.1
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• 2003

Examination was made of the urinary metabolite(s) of CKD-712, which is a chiral compound, named S-YS49 derived from higenamine (one component of Aconite spp.) derivatives. First of all. to analyze the metabolite(s) of CKD-712, a simple and sensitive detection method for CKD-712 was developed by using gas chromatography-mass spectrometry(GC/MS). (omitted)

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.33-42
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• 2005

Identifying color codes needs precise color information of their constituents, and is far from trivial because colors usually suffer severe distortions throughout the entire procedures from printing to acquiring image data. To accomplish accurate identification of colors, we need a reliable segmentation method to separate different color regions from each other, which would enable us to process the whole pixels in the region of a color statistically, instead of a subset of pixels in the region. Color image segmentation can be accomplished by performing edge detection on component image(s). In this paper, we separately detected edges on component images from RGB, HSI, and YIQ color models, and performed mathematical analyses and experiments to find out a pair of component images that provided the best edge image when combined. The best result was obtained by combining Y- and R-component edge images.

• Food Science of Animal Resources
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• v.36 no.6
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• pp.719-728
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• 2016

The aim of this study was to explore the volatile compounds of hind leg, foreleg, abdomen and Longissimus dorsi in both male and female Hyla rabbit meat by solid phase microextraction tandem with gas chromatography mass spectrometry, and to seek out the key odorants via calculating the odor activity value and principal component analysis. Cluster analysis is used to study the flavor pattern differences in four edible parts. Sixty three volatile compounds were detected, including 23 aldehydes, 4 alcohols, 5 ketones, 11 esters, 5 aromatics, 8 acids and 7 hydrocarbons. Among them, 6 aldehydes and 3 acids were identified as the potential key odorants according to the ratio of concentration and threshold. The contents of volatile compounds in male Hyla rabbit meat were significantly higher than those in female one (p<0.05). The results of principal component analysis showed that the first two principal component cumulative variance contributions reach 87.69%; Hexanal, octanal, 2-nonenal, 2-decenal and decanal were regard as the key odorants of Hyla rabbit meat by combining odor activity value and principal component analysis. Therefore volatile compounds of rabbit meat can be effectively characterized. Cluster analysis indicated that volatile chemical compounds of Longissimus dorsi were significantly different from other three parts, which provide reliable information for rabbit processing industry and for possible future sale.

• Journal of the Korean Wood Science and Technology
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• v.43 no.6
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• pp.701-713
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• 2015

A model was designed to identify wood species between Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc. using the near-infrared (NIR) spectroscopy in combination with principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). In the PCA using all of the spectra, Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc. could not be classified. In the PCA using the spectrum that has been measured in sapwood, however, Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc. could be identified. In particular, it was clearly classified by sapwood in radial section. And more, these two species could be perfectly identified using PLS-DA prediction model. The best performance in species identification was obtained when the second derivative spectra was used; the prediction accuracy was 100%. For prediction model, the $R_p{^2}$ value was 0.86 and the RMSEP was 0.38 in second derivative spectra. It was verified that the model designed by NIR spectroscopy with PLS-DA is suitable for species identification between Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.678-689
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• 2000

This paper describes an automatic summarization approach that constructs a summary by extracting sentences that are likely to represent the main theme of a document. As a way of selecting summary sentences, the system uses a model that takes into account lexical and statistical information obtained from a document corpus. As such, the system consists of two parts: the training part and the summarization part. The former processes sentences that have been manually tagged for summary sentences and extracts necessary statistical information of various kinds, and the latter uses the information to calculate the likelihood that a given sentence is to be included in the summary. There are at least three unique aspects of this research. First of all, the system uses a text component identification model to categorize sentences into one of the text components. This allows us to eliminate parts of text that are not likely to contain summary sentences. Second, although our statistically-based model stems from an existing one developed for English texts, it applies the framework to individual features separately and computes the final score for each sentence by combining the pieces of evidence using the Dempster-Shafer combination rule. Third, not only were new features introduced but also all the features were tested for their effectiveness in the summarization framework.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.149-153
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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 ordo 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. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method.

• The KIPS Transactions:PartD
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• v.17D no.3
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• pp.223-232
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• 2010

This study was carried out for the purpose of inquiring into the effect of composition and security activities for information security architecture on information asset protection and organizational performance in terms of general information security. This study made a survey on 300 workers in the government, public institutions and private companies, which it showed that management factors of risk identification and risk analysis, in general, have an usefulness to composition and security activities for information security architecture to prevent inside information leakage. And the understanding and training factors of IT architecture and its component were rejected, requiring the limited composition and security activities for information security architecture. In other words, from the reality, which most institutions and organizations are introducing and operating the information security architecture, and restrictively carrying out the training in this, the training for a new understanding of architecture and its component as an independent variable made so much importance, or it did not greatly contribute to the control or management activities for information security as the generalized process, but strict security activities through the generalization of risk identification and risk analysis management had a so much big effect on the significant organizational performance.

• Nuclear Engineering and Technology
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• v.43 no.3
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• pp.271-278
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• 2011

When performing fire PSA in a nuclear power plant, an event mapping method, using an internal event PSA model, is widely used to reduce the resources used by fire PSA model development. Feasible initiating events and component failure events due to fire are identified to transform the fault tree (FT) for an internal event PSA into one for a fire PSA using the event mapping method. A surrogate event or damage term method is used to condition the FT of the internal PSA. The surrogate event or the damage term plays the role of flagging whether the system/component in a fire compartment is damaged or not, depending on the fire being initiated from a specified compartment. These methods usually require explicit states of all compartments to be modeled in a fire area. Fire event scenarios, when using explicit identification, such as surrogate or damage terms, have two problems: (1) there is no consideration of multiple fire propagation beyond a single propagation to an adjacent compartment, and (2) there is no consideration of simultaneous fire propagations in which an initiating fire event is propagated to multiple paths simultaneously. The present paper suggests a fire propagation equation to identify all possible fire event scenarios for an explicitly treated fire event scenario in the fire PSA. Also, a method for separating fire events was developed to make all fire events a set of mutually exclusive events, which can facilitate arithmetic summation in fire risk quantification. A simple example is given to confirm the applicability of the present method for a $2{\times}3$ rectangular fire area. Also, a feasible asymptotic approach is discussed to reduce the computational burden for fire risk quantification.