• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.1-8
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• 2005

This paper describes a new objective methodology of seismic building damage assessment which is called Advanced Component Method(ACM). ACM is a major attempt to replace the conventional loss estimation procedure, which is based on subjective measures and the opinions of experts, with one that objectively measures both earthquake intensity and the response ol buildings. First, response of typical buildings is obtained analytically by nonlinear seismic static analysis, push-over analyses. The spectral displacement Is used as a measure of earthquake intensity in order to use Capacity Spectrum Method and the damage functions for each building component, both structural and non-structural, are developed as a function of component deformation. Examples of components Include columns, beams, floors, partitions, glazing, etc. A repair/replacement cost model is developed that maps the physical damage to monetary damage for each component. Finally, building response, component damage functions, and cost model were combined probabilistically, using Wonte Carlo simulation techniques, to develop the final damage functions for each building type. Uncertainties in building response resulting from variability in material properties and load assumptions were incorporated in the Latin Hypercube sampling technique. The paper also presents and compares ACM and conventional building loss estimation based on historical damage data and reported loss data.

• Journal of the korean society of oceanography
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• v.35 no.3
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• pp.129-152
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• 2000

The Cheju Current (CC), defined here as a mean eastward flow in the Cheju Strait, mostly carries water of high temperature and salinity originating from the Kuroshio in winter and spring, the Cheju Warm Current Water (CWCW). The strong core of the eastward component of the CC is found close to Cheju Island (Cheju-Do, hereafter) in winter and spring with a peak speed of about 17.0 cm/s. The eastward flow weakens towards the northern Cheju Strait, and a weak westward flow occurs occasionally close to the southern coast of Korea. The volume transport ranges from 0.37 to 0.45 Sv(1 Sv=10$^6$ m$^3$/s) in winter and spring. Seasonal thermocline and harocline are formed in summer and eroded in November. The occurrence of the CWCW is confined in the southern Cheju Strait close to Cheju-Do below the seasonal thermocline in summer and fall, and cold water occupies the lower layer north of the CWCW which is thought to be brought into the area from the area west of Cheju-Do along with the CWCW. Stratification acts to increase both the speed of the CC with a peak speed of greater than 30 cm/s and the vertical shear of the along-strait currents. The strong core of the CC detached from the coast of Cheju-Do and shifted to the north during the stratified seasons. The volume transport in summer and fall ranges 0.510.66 Sv, which is about 1.5 times larger than that in winter and spring. An annual cycle of the cross-strait sea level difference shows its maximum in summer and fall and minimum in winter and spring, whose tendency is consistent with the annual variability of the CC and its transport estimated from the ADCP measurements. Moored current measurements west of Cheju-Do indicate the clockwise turning of the CC, and the moored current measurements in the Cheju Strait for 1530 days show the low-frequency variability of the along-strait flow with a period of about 37 days.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.259-266
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• 2002

It is crucial to know spatial soil variability for precision farming. However, it is time-consuming, and difficult to measure spatial soil properties. Therefore, there are needs fur sensing technology to estimate spatial soil variability, and for electronic mapping technology to store, manipulate and process the sampled data. This research was conducted to develop a real-time soil organic matter sensor and an electronic mapping system. A soil organic matter sensor was developed with a spectrophotometer in the 900∼1,700 nm range. It was designed in a penetrator type to measure reflectance of soil at 15cm depth. The signal was calibrated with organic matter content (OMC) of the soil which was sampled in the field. The OMC was measured by the Walkeley-Black method. The soil OMCs were ranged from 0.07 to 7.96%. Statistical partial least square and principle component regression analyses were used as calibration methods. Coefficient of determination, standard error prediction and bias were 0.85 0.72 and -0.13, respectively. The electronic mapping system was consisted of the soil OMC sensor, a DGPS, a database and a makeshift vehicle. An algorithm was developed to acquire data on sampling position and its OMC and to store the data in the database. Fifty samples in fields were taken to make an N-fertilizer dosage map. Mean absolute error of these data was 0.59. The Kring method was used to interpolate data between sampling nodes. The interpolated data was used to make a soil OMC map. Also an N-fertilizer dosage map was drawn using the soil OMC map. The N-fertilizer dosage was determined by the fertilizing equation recommended by National Institute of Agricultural Science and Technology in Korea. Use of the N-fertilizer dosage map would increase precision fertilization up to 91% compared with conventional fertilization. Therefore, the developed electronic mapping system was feasible to not only precision determination of N-fertilizer dosage, but also reduction of environmental pollution.

• Atmosphere
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• v.24 no.2
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• pp.131-140
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• 2014

The "Barents Oscillation (BO)", first designated by Paul Skeie (2000), is an anomalous recurring atmospheric circulation pattern of high relevance for the climate of the Nordic Seas and Siberia, which is defined as the second Emperical Orthogonal Function (EOF) of monthly winter sea level pressure (SLP) anomalies, where the leading EOF is the Arctic Oscillation (AO). BO, however, did not attracted much interest. In recent two decades, variability of BO tends to increase. In this study, we analyzed the spatio-temporal structures of Atmospheric internal modes such as Arctic Oscillation (AO) and Barents Oscillation (BO) and examined how these are related with Arctic warming in recent decade. We identified various aspects of BO, not dealt in Skeie (2000), such as upper-level circulation and surface characteristics for extended period including recent decade and examined link with other surface variables such as sea-ice and sea surface temperature. From the results, it was shown that the BO showed more regionally confined spatial pattern compared to AO and has intensified during recent decade. The regional dipolelar structure centered at Barents sea and Siberia was revealed in both sea-level pressure and 500 hPa geopotential height. Also, BO showed a stronger link (correlation) with sea-ice and sea surface temperature especially over Barents-Kara seas suggesting it is playing an important role for recent Arctic amplification. BO also showed high correlation with Ural Blocking Index (UBI), which measures seasonal activity of Ural blocking. Since Ural blocking is known as a major component of Eurasian winter monsoon and can be linked to extreme weathers, we suggest deeper understanding of BO can provide a missing link between recent Arctic amplification and increase in extreme weathers in midlatitude in recent decades.

• Horticulture, Environment, and Biotechnology : HEB
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• v.59 no.6
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• pp.875-888
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• 2018

Tulip (Tulipa L.) is one of the most important ornamental geophytes in the world. Analysis of molecular variability of tulips is of great importance in conservation and parental lines selection in breeding programs. Of the 70 genic microsatellites, 15 highly polymorphic and reproducible markers were used to assess the genetic diversity, structure, and relationships among 280 individuals of 36 wild and cultivated tulip accessions from two countries: Iran and the Netherlands. The mean values of gene diversity and polymorphism information content were 0.69 and 0.66, respectively, which indicated the high discriminatory power of markers. The calculated genetic diversity parameters were found to be the highest in wild T. systola Stapf (Derak region). Bayesian model-based STRU CTU RE analysis detected five gene pools for 36 germplasms which corresponded with morphological observations and traditional classifications. Based on analysis of molecular variance, to conserve wild genetic resources in some geographical locations, sampling should be performed from distant locations to achieve high diversity. The unweighted pair group method with arithmetic mean dendrogram and principal component analysis plot indicated that among wild tulips, T. systola and T. micheliana Hoog exhibited the closest relationships with cultivated tulips. Thus, it can be assumed that wild tulips from Iran and perhaps other Middle East countries played a role in the origin of T. gesneriana, which is likely a tulip species hybrid of unclear origin. In conclusion, due to the high genetic variability of wild tulips, they can be used in tulip breeding programs as a source of useful alleles related to resistance against stresses.

• Korean Journal of Health Psychology
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• v.14 no.2
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• pp.277-292
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• 2009

This study investigated the responses of the autonomic nervous system of individuals with Type D personality during an acute stressful situation. Twenty-three female students of Type D personality and 23 female students with non-Type D personality. Stroop Color-Word Task was used to induce a stressful situation, heart rate variability (HRV) was used to measure the responses of the autonomic nervous system during the baseline, acute stress, recovery periods. To analyze the data, the repeated measures analysis of variance was used to compare the autonomic nervous system of the Type D group to that of the non-Type D group. Regression analysis is used to determine if the Type D scale and stress vulnerability predicted the activities of the autonomic nervous system during the baseline period. The results of this study demonstrated that the Type D group's normalized low frequency (LF norm) and ratio of low frequency to high frequency (LF/HF ratio) were higher than those for the non-Type D group, while its normalized high frequency (HF norm) was lower than that for the non-Type D group in all three periods. There were no statistically significant differences among the three periods in terms of LF norm, HF norm, and LF/HF ratio in the Type D group. The study demonstrated that the total scores of the Type DS-14 and scores of social inhibition and negative affect were independent predictors of LF norm and HF norm during the baseline. The Type D group showed increased activation of the sympathetic nervous system and/or decreased activation of the parasympathetic nervous system. These results support the hypothesis that the Type D personality is vulnerable to the stress. Also, the highly activated sympathetic and/or lowly activated parasympathetic nervous systems, which were observed in the Type D group during the baseline, indicated that the Type D individual is susceptible to psychosomatic disorders.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.55-64
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• 2019

Stress is accompanied by changes in the responses of the autonomic nervous system, and the heart rate variability (HRV) index is a quantitative marker that reflects autonomic responses induced by stressors. In this study, we observed changes in the autonomic responses induced by combinations of 30% oxygen administration and color light for stress relaxation. In all, 42 participants produced stress symptoms over the preceding two weeks, as rated on the stress response scale. After stress assessment, they were exposed to three therapeutic conditions, and electrocardiogram (ECG) signals were recorded before, during, and after therapy. The three therapy conditions consisted of only 30% oxygen administration with white light, a combination of 30% oxygen and orange light, and a combination of 30% oxygen and blue light. The HRV indices extracted from ECG signals were heart rate (HR), the standard deviation of the RR interval (SDNN), the mean square root of consecutive RR interval difference values (RMSSD), the low frequency component of HRV (LF), the high frequency component (HF), and the LF/HF ratio. These indicators were used to compare mean values before and after therapy. The results showed that HR and the LF/HF ratio were significantly lower after therapy than before it. In particular, the condition with 30% oxygen and blue light yielded significantly greater RMSSD and HF increases, as well as decreases in LF/HF ratio than in other two conditions. Our results suggest that therapy with 30% oxygen and blue light is the most effective for the relaxation of stress, which implies autonomic balance by parasympathetic activation.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.393-400
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• 2006

There are many feature extraction methods for face recognition. We need a new method to overcome the small sample problem that the number of feature variables is larger than the sample size for face image data. The paper considers partial least squares(PLS) as a new dimension reduction technique for feature vector. Principal Component Analysis(PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So, PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases shows that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.808-816
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• 2004

This paper proposes the method of implementation of practical online face verification system based on multiple feature combination and a similarity space. The main issue in face verification is to deal with the variability in appearance. It seems difficult to solve this issue by using a single feature. Therefore, combination of mutually complementary features is necessary to cope with various changes in appearance. From this point of view, we describe the feature extraction approaches based on multiple principal component analysis and edge distribution. These features are projected on a new intra-person/extra-person similarity space that consists of several simple similarity measures, and are finally evaluated by a support vector machine. From the experiments on a realistic and large database, an equal error rate of 0.029 is achieved, which is a sufficiently practical level for many real- world applications.