• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.323-329
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• 2015

In this paper we applied pattern recognition approach to detect audio forgery. Classification of the microphone types and models can help determining the authenticity of the recordings. Canonical correlation analysis was applied to extract feature for microphone classification. We utilized the linear dependence between two near-silence regions. To utilize the advantage of multi-feature based canonical correlation analysis, we selected three commonly used features to capture the temporal and spectral characteristics. Using three different microphones, we tested the usefulness of multi-feature based characteristics of canonical correlation analysis and compared the results with single feature based method. The performance of classification rate was carried out using the backpropagation neural network. Experimental results show the promise of canonical correlation features for microphone classification.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.558-563
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• 2014

Sum-frequency generation spectra of a Langmuir monolayer on water surface at varying surface areas were studied with two-dimensional correlation analysis. Upon enlarging the area/molecule of the Langmuir monolayer, the sum-frequency spectra changed reflecting the conformation change of the alkyl chains of the molecules in the monolayer. These changes stood out more clearly by employing two-dimensional correlation analysis of the above sum-frequency spectra. Features not very pronounced in the original spectra such as closely-spaced spectral bands can also be easily distinguished in the two-dimensional correlation spectra.

• Asian Journal of Turfgrass Science
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• v.22 no.1
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• pp.1-12
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• 2008

Remote sensing using multispectral radiometry may be a useful tool to detect drought stress in turf. The objective of this research was to investigate the correlation between drought stress and multispectral reflectance (MSR) from the turf canopy. St. Augustinegrass (Stenotaphrum secundatum[Walt.] Kuntze.) cultivars 'Floratam' and 'Palmetto', 'SeaIsle 1' seashore paspalum Paspalum vaginatum Swartz.), 'Empire' zoysiagrass (Zoysia japonica Steud.), and 'Pensacola' bahiagrass (Paspalum notatumFlugge) were established in lysimeters in the University of Florida Envirotron greenhouse facility in Gainesville. Irrigation was applied at 100%, 80%, 60%, or 40% of evapotranspiration (ET). Weekly evaluations included: a) shoot quality, leaf rolling, leaf firing b) soil moisture, chlorophyll content index; c) photosynthesis and d) multispectral reflectance. All the measurements were correlated with MSR data. Drought stress affected the infrared spectral region more than the visible spectral region. Reflectance sensitivity to water content of leaves was higher in the infrared spectral region than in the visible spectral region. Grasses irrigated at 100% and 80% of ET had no differences in normalized difference vegetation indices (NDVI), leaf area index (LAI), and stress indices. Grasses irrigated at 60% and 40% of ET had differences in NDVI, LAI, and stress indices. All measured wavelengths except 710nm were highly correlated (P < 0.0001) with turf visual quality, leaf firing, leaf rolling, soil moisture, chlorophyll content index, and photosynthesis. MSR could detect drought stress from the turf canopy.

• Journal of the Korean Chemical Society
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• v.52 no.4
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• pp.369-379
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• 2008

• Bulletin of the Korean Space Science Society
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• 1999.04a
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• pp.27-27
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• 1999

No Abstract, See Full Text

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.357-367
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• 2012

This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.

• Journal of the Korean Magnetic Resonance Society
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• v.3 no.2
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• pp.140-148
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• 1999

Using 1H magnetic resonance spectroscopy (MRS), we quantitatively evaluated correlation representing linear relationship between the metabolite peak area ratios associated with poor shimming conditions. The inadequate shimming due to linear shim offsets directly affected overall MR spectral quality as well as peak area for each metabolite. Three major peaks such as N-acetylaspartate (NAA), creatine (Cr,) choline (Cho) were used as a reference for data analysis. Despite considerable variations of metabolite peak area, a significant correlation between the metabolite peak area ratios relative to Cr was established while the correlation between the peak area ratios relative to Cho and NAA was not. The present study suggested that metabolite peak area ratios based on the metabolite of Cr could be an acceptable quantification method even under the poor shimming in clinical MRS examination.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1722-1732
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• 1997

In this paper, we propose a coding method of remotely sensed satellite image data using region classification and interband correlation. This method classifies each pixel vector consider spectral characteristics. Then we perform the classified intraband VQ to remove spatial (intraband redundancy for a reference band image. To remove interband redundancy effectively, we perform the classified interband prediction for the band images that the high correlation spectrally and perform the classified interband VQ for the remaining band images. Experiments on LANDSAT TM image show that the coding efficiency of the proposed method is better than that of the conventional Gupta's method. Especially, this method removes redundancies effectively for satellite iamge including various geographical objects and for and images that have low interband correlation.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.325-329
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• 2012

We will report our recent study on the properties of more than 1,600 galaxies detected by the AKARI All-Sky Survey with physical quantities based on optical and 21-cm observations, to understand the physics determining the infrared spectral energy distribution (Totani et al., 2011). We discover a tight linear correlation for normal star-forming galaxies between the radiation field strength of dust heating (corresponding to dust temperature) and the galactic-scale infrared radiation field, $L_{TIR}/R^2$. This is the tightest correlation of dust temperature ever known, and the dispersion along the mean relation is 13% in dust temperature. This relation can be explained physically by a thin layer of heating sources embedded in a thicker, optically-thick dust screen. We also find that the number of galaxies sharply drops when galaxies become optically thin against dust-heating radiation, indicating that a feedback process to galaxy formation (e.g., by the photoelectric heating) is working when dust-heating radiation is not self-shielded on a galactic scale. We discuss implications from these findings for the $M_{H_I}$ -size relation, the Kennicutt-Schmidt relation, and galaxy formation in the cosmological context.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.1-11
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• 2015

In this paper, the transmission of an improper-complex second-order stationary data sequence is considered over a strictly band-limited frequency-selective channel. It is assumed that the transmitter employs linear modulation and that the channel output is corrupted by additive proper-complex cyclostationary noise. Under the average transmit power constraint, the problem of minimizing the mean-squared error at the output of a widely linear receiver is formulated in the time domain to find the optimal transmit and receive waveforms. The optimization problem is converted into a frequency-domain problem by using the vectorized Fourier transform technique and put into the form of a double minimization. First, the widely linear receiver is optimized that requires, unlike the linear receiver design with only one waveform, the design of two receive waveforms. Then, the optimal transmit waveform for the linear modulator is derived by introducing the notion of the impropriety frequency function of a discrete-time random process and by performing a line search combined with an iterative algorithm. The optimal solution shows that both the periodic spectral correlation due to the cyclostationarity and the symmetric spectral correlation about the origin due to the impropriety are well exploited.