• Bulletin of the Korean Chemical Society
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• v.25 no.12
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• pp.1840-1844
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• 2004

The mass spectra of benzophenones, 2-benzoylthiophenes, 2-benzoylpyrroles, and 2-benzoylfurans which have substituents at the m- and p-positions of the benzoyl ring were analyzed to find correlations against the Hammett substituent parameter ${\sigma}\;and\;{\sigma}^+$. The slopes of the plots of the intensities of the fragments from the heterocycles against those of the benzene gave sets of meaningful values for the indices of aromaticity of the heterocycles: benzene 1.00; thiophene 0.94, pyrrole 0.82, and furan 0.74.

• Wind and Structures
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• v.3 no.1
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• pp.1-10
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• 2000

Recently, an efficient and practical method has been developed for the generation of univariate non-Gaussian wind pressure time histories on low building roofs; this methodology requires intermittent exponential random numbers for the simulation. On the other hand, the conventional spectral representation scheme with random phase is found suitable for the generation of univariate Gaussian wind pressure time histories on low building roofs; this simulation scheme requires uniform random numbers. The dependency of these simulation methodologies on the random number generator is one of the items affecting the accuracy of the simultion result; therefore, an attempt has been made to investigate the issue. This note presents the observed sensitivity of random number sets in repetitive simulations of Gaussian and non-Gaussian wind pressures.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1052-1054
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• 2003

RAZAKSAT is a second micro-satellite mission by Malaysian Satellite Program and is expected for launch in June 2004. Designed to orbit the earth at low-equatorial orbit, RAZAKSAT will meet Malaysia’s immediate needs to rapid data acquisition (real time and more repetitions) to address many operational issues of remote sensing applications, which require availability of current data sets. RAZAKSAT will be among the first remote sensing satellite to orbit the earth at low inclination along the equator, 9$^{\circ}$ with 685km altitude, hence, allows optimal geographical information and environment change within equatorial region be observed with a unique revisit characteristics. The satellite primary payload is MAC, a push-broom type camera with 2.5m of ground sampling distance (GSD) in panchromatic band and 5m of GSD in four multi-spectral bands. This paper describes on the variation of illumination anticipated from simulated RAZAKSAT image, examine its implication to its ground leaving radiances for major applications.

• Communications of the Korean Mathematical Society
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• v.21 no.2
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• pp.253-259
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• 2006

Let T be a bounded linear operator on a Banach space X. And let ${{\rho}T}(X)$ be the local resolvent set of T at $x\;{\in}\;X$. Then we prove that a complex number ${\lambda}$ belongs to ${{\rho}T}(X)$ if and only if there is a sequence $\{x_{n}\}$ in X such that $x_n\;=\;(T - {\lambda})x_{n+1}$ for n = 0, 1, 2,..., $x_0$ = x and $\{{\parallel}x_n{\parallel}^{\frac{1}{n}}\}$ is bounded.

• Earthquakes and Structures
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• v.12 no.4
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• pp.389-395
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• 2017

In this paper a simple approach is presented for spectral matching of ground motions utilizing the wavelet transform and a recently developed metaheuristic optimization technique. For this purpose, wavelet transform is used to decompose the original ground motions to several levels, where each level covers a special range of frequency, and then each level is multiplied by a variable. Subsequently, the vibrating particles system (VPS) algorithm is employed to calculate the variables such that the error between the response and target spectra is minimized. The application of the proposed method is illustrated through modifying 12 sets of ground motions. The results achieved by this method demonstrate its capability in solving the problem. The outcomes of the VPS algorithm are compared to those of the standard colliding bodies optimization (CBO) to illustrate the importance of the enhancement of the algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.204-207
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• 2013

Music genre classification is an essential component for music information retrieval system. There are two important components to be considered for better genre classification, which are audio feature extraction and classifier. This paper incorporates two different kinds of features for genre classification, timbral texture and rhythmic content features. Timbral texture contains several spectral and Mel-frequency Cepstral Coefficient (MFCC) features. Before choosing a timbral feature we explore which feature contributes less significant role on genre discrimination. This facilitates the reduction of feature dimension. For the timbral features up to the 4-th order central moments and the covariance components of mutual features are considered to improve the overall classification result. For the rhythmic content the features extracted from beat histogram are selected. In the paper Extreme Learning Machine (ELM) with bagging is used as classifier for classifying the genres. Based on the proposed feature sets and classifier, experiment is performed with well-known datasets: GTZAN databases with ten different music genres, respectively. The proposed method acquires the better classification accuracy than the existing approaches.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. 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. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.445-455
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• 2011

A probabilistic classification framework is presented that can combine temporal contextual information derived from an existing land-cover map in order to improve the classification accuracy of land-cover classes that can not be discriminated well when using spectral information only. The transition probability is computed by using the existing land-cover map and training data, and considered as a priori probability. By combining the a priori probability with conditional probability computed from spectral information via a Bayesian combination rule, the a posteriori probability is finally computed and then the final land-cover types are determined. The method presented in this paper can be adopted to any probabilistic classification algorithms in a simple way, compared with conventional classification methods that require heavy computational loads to incorporate the temporal contextual information. A case study for crop classification using time-series MODIS data sets is carried out to illustrate the applicability of the presented method. The classification accuracies of the land-cover classes, which showed lower classification accuracies when using only spectral information due to the low resolution MODIS data, were much improved by combining the temporal contextual information. It is expected that the presented probabilistic method would be useful both for updating the existing past land-cover maps, and for improving the classification accuracy.

• Journal of the Korean earth science society
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• v.31 no.6
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• pp.541-554
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• 2010

Fifteen min-microtremor data sets were collected at 136 sites from a coastal area of Kunsan and 117 sites from an inland area of Jeonju located in SW Korea, and were analyzed for the HVSR (Horizontal to Vertical Spectral Ratio) of the sites. The microtremor spectra of the coastal area have stronger energy in the lower frequency range from 1-6 Hz than those of the coastal area. This result can be attributed to the effect of the waves and tides in the Keum river and the Yellow sea. Twenty four hours of measurement of the microtremor indicated that the microtremor spectrum correlates with the human activities, but the microtremor HVSR peak was observed consistently at the characteristic frequency for the site. The HVSR peaks were grouped into 4 types -"single peak", "double peak", "broad peak" or "no peak"- based on their shapes. More than 90% of the data sets exhibit peak frequencies ($F_0$) which can be easily identified. The distribution of $F_0$ reveals a close relationship with the topography and local geology of the areas, exhibiting high F0s in the hillside areas and low $F_0s$ in the reclaimed land area. While the amplitudes of microtremor HVSR peak frequencies are less than 4 in the downstream of the inland area, those of the recently reclaimed land in the coastal area are extremely high (more than 10). The results of this study indicate that detailed HVSR studies are essential for the earthquake hazard reduction of reclaimed lands.

• Geophysics and Geophysical Exploration
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• v.5 no.3
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• pp.157-168
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• 2002

Improved procedures were implemented in the production of the lithospheric magnetic anomaly map from Magsat satellite magnetometer data of East Asia between $90^{\circ}E-150^{\circ}E$ and $10^{\circ}S-50^{\circ}N$. Procedures included more effective selection of the do·it and dawn tracks, ring current correction, and separation of core field and external field effects. External field reductions included an ionospheric correction and pass-by-pass correlation analysis. Track-line noise effects were reduced by spectral reconstruction of the dusk and dawn data sets. The total field magnetic anomalies were differentially-reduced-to-the-pole to minimize distortion s between satellite magnetic anomalies and their geological sources caused by corefield variations over the study area. Aeromagnetic anomalies were correlated with Magsat magnetic anomalies at the satellite altitude to test the lithospheric veracity of anomalies in these two data sets. The aeromagnetic anomalies were low-pass filtered to eliminate high frequency components that may not be shown at the satellite altitude. Although the two maps have a low CC of 0.243, there are many features that are directly correlated (peak-to-peak and trough-to-trough). The low CC between the two maps was generated by the combination of directly- and inversely-correlative anomaly features between them. It is very difficult to discriminate directly, inversely, and nully correlative features in these two anomaly maps because features are complicatedly correlated due to the depth and superposition of the anomaly sources. In general, the lithospheric magnetic components were recovered successfully from satellite magnetometer observations and correlated well with aeromagnetic anomalies in the study area.