• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.497-501
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• 2008

In this paper we present a method for continuous EEG classification, where we employ nonnegative tensor factorization (NTF) to determine discriminative spectral features and use the Viterbi algorithm to continuously classily multiple mental tasks. This is an extension of our previous work on the use of nonnegative matrix factorization (NMF) for EEG classification. Numerical experiments with two data sets in BCI competition, confirm the useful behavior of the method for continuous EEG classification.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.253-253
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• 2011

ZnTe semiconductor is very attractive a material for optoelectronic devices in the visible green spectral region because of it has direct bandgap of 2.26 eV. The prototypes of ZnTe light emitting diodes (LEDs) have been reported [1], showing that their green emission peak closely matches the most sensitive region of the human eye. The optoelectronic properties of ZnTe:O film allow to expect a large optical gain in the intermediate emission band, which emission band lies about 0.4-0.6 eV below the conduction band of ZnTe [2]. So, the ZnTe system is useful for the production of high-efficiency multi-junction solar cells [2,3]. In this work, the ZnTe:O thin films were deposited on Al2O3 substrates by using the radio frequency magnetron sputtering system. Three sets of samples were prepared using argon and oxygen as the sputtering gas. The deposition chamber was pre-pumped down to a base pressure of 10-7 Torr before introducing gas. The deposition pressure was fixed at 10-3 Torr throughout this work. During the ZnTe deposition, the substrate temperature was 300 oC. The optical properties were also investigated by using the ultraviolte-visible (UV-Vis) spectrophotometer.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.1
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• pp.68-83
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• 2020

This study suggests a method to predict the color appearance of textiles that shifts depending on illumination variations. The suggested method allows the calculations of lightness, chroma, and hue appearance values from the spectral reflectance values of the textile and illuminant. The accuracy of the method was evaluated through numerical and statistical comparisons between the predicted and the measured color appearance values of 24 fabric samples under CIE standard illuminant D65. As a result, there were excellent agreements between the two data sets with the error values close to zero. The predicted color appearance values of 24 samples under two illuminating (color temperature-luminance) conditions, 2700 K-100 cd/㎡ and 6500 K-100 cd/㎡, were then compared to prove the significant effect of illumination on the color appearance of textiles. The color appearance values were also compared with spectrophotometrically measured physical color attributes, that is, true colors of the samples. The physical color attributes of samples were unchanged; however, differences in color appearance under different conditions were generally much larger than the suprathreshold color difference tolerances discussed in the color science literature. Finally, the magnitude of the illumination effect depending on the physical color attributes of samples was also analyzed.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.49-54
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• 2000

Conventional methods for measuring winds provide wind velocity observations over limited area and time period. The use of satellite imagery for measuring wind velocity overcomes some of these limitations by providing wide area and near condinuous coverage. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP models. GMS-5 provides full disk images at hourly intervals. At four times each day - 0500, 1100, 1700, 2300 hours UTC-a series of three images is received, separated by thirty minutes, centered at the four times. The current wind system generates winds from sets of 3 infrared(IR) images, separated by an hour, four times a day. It also produces visible(VIS) and water vapor(WV) image-based winds from half-hourly imagery four times a day. The derivation of wind from satellite imagery involves the identification of suitable cloud targets. tracking the targets on sequential images, associating a pressure height with the derived wind vector, and quality control. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.65-78
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• 2008

This study compares the relative accuracy and consistency of four split-window land surface temperature (LST) algorithms (Becker and Li, Kerr et ai., Price, Ulivieri et al.) using 24 sets of Terra (Aqua)/Moderate Resolution Imaging Spectroradiometer (MODIS) data, observed ground grass temperature and air temperature over South Korea. The effective spectral emissivities of two thermal infrared bands have been retrieved by vegetation coverage method using the normalized difference vegetation index. The intercomparison results among the four LST algorithms show that the three algorithms (Becker-Li, Price, and Ulivieri et al.) show very similar performances. The LST estimated by the Becker and Li's algorithm is the highest, whereas that by the Kerr et al.'s algorithm is the lowest without regard to the geographic locations and seasons. The performance of four LST algorithms is significantly better during cold season (night) than warm season (day). And the LST derived from Terra/MODIS is closer to the observed LST than that of Aqua/MODIS. In general, the performances of Becker-Li and Ulivieri et al algorithms are systematically better than the others without regard to the day/night, seasons, and satellites. And the root mean square error and bias of Ulivieri et al. algorithm are consistently less than that of Becker-Li for the four seasons.

• Bulletin of the Korean Chemical Society
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• v.21 no.4
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• pp.393-400
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• 2000

2,2￠-Dihydroxyazobenzene (DHAB) was attached to poly(ethylenimine) (PEI) to obtain DHAB-PEI. Spectral titration revealed that uranyl, Fe(III), Cu(II), and Zn(II) ion form 1 : 1-type complexes with DHAB attached to PEI. Formation constants for the metal complexes formed by the DHAB moieties of DHAB-PEI were mea-sured by using various competing ligands. The results indicated thatthe concentrations of uranyl, Fe(III), and Cu(II) ions can be reduced to 10 -16 -10 -23 M at p 8 with DHAB-PEI when the concentration of the DHAB moiety is 1 residue M. By using cyanuric chloride as the coupling reagent, DHAB-PEI was immobilized on Sephadex G-25 resin to obtain DHAB-PEI-Seph. Binding of uranyl,Fe(III), Cu(II), and Zn(II) ion by DHAB-PEI-Seph was characterized by using competing ligands. A new method has been developed for characteriza-tion of metal sequestering ability of a chelating resin. Formation constants and metal-binding capacity of two sets of binding sites on the resin were estimated for each metal ion. DHAB-PI-Seph was applied to recovery of metals such as uranium,Fe, Cu, Zn, Pb, V, Mn, and W from seawater. The uranium recovery from seawaterby DHAB-PEI-Seph does not meet the criterion for economical feasibility partlydue to interference by Fe and Zn ions. The seawater used in the experiment was contaminated by Fe and Zn and, therefore, the efficiency of uranium extractionfrom seawater with DHAB-PEI-Seph could be improved if the experiment is carried out in a cleaner sea.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2396-2406
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• 2021

The Pacific Earthquake Engineering Research (PEER) Center has been developing a performance-based earthquake engineering (PBEE) methodology, which is based on explicit determination of performance, e.g., monetary losses, in a probabilistic manner where uncertainties in earthquake ground motion, structural response, damage estimation, and losses are explicitly considered. To carry out the PEER PBEE procedure for a component of the nuclear power plant (NPP) such as the cable tray system, hazard curve and spectra were defined for two hazard levels of the ground motions, namely, operation basis earthquake, and safe shutdown earthquake. Accordingly, two sets of spectral compatible ground motions were selected for dynamic analysis of the cable tray system. In general, the PBEE analysis of the cable tray in NPP was introduced where the resulting floor motions from the time history analysis (THA) of the NPP structure should be used as the input motion to the cable tray. However, for simplicity, a finite element model of the cable tray was developed for THA under the effect of the selected ground motions. Based on the structural analysis results, fragility curves were generated in terms of specific engineering demand parameters. Loss analysis was performed considering monetary losses corresponding to the predefined damage states. Then, overall losses were evaluated for different damage groups using the PEER PBEE methodology.

• Earthquakes and Structures
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• v.23 no.2
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• pp.115-128
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• 2022

One common method to select input ground motions to predict dynamic behavior of structures subjected to seismic excitation requires spectral acceleration (S_a) match target mean response spectrum. However, dispersion of ground motions, which explicitly affects the structural response, is rarely discussed in this method. Generally, selecting ground motions matching target mean and variance has been utilized as an appropriate method to predict reliable seismic response. The goal of this paper is to investigate the impact of target spectra variance of ground motions on structural seismic response. Two sets of ground motions with different target variances (zero variance and minimum variance larger than inherent variance of the target spectrum) are selected as input to two different structures. Structural responses at different heights are compared, in terms of peak, mean and dispersion. Results show that increase of target spectra variance tends to increase peak floor acceleration, peak deformation and dispersions of response of interest remarkably. To short-period structures, dispersion increase ratios of seismic response are close to that of S_a of input ground motions at the first period. To long-period structures, dispersions of floor acceleration and floor response spectra increase more significantly at the bottom, while dispersion increase ratios of IDR and deformation are close to that of S_a of input ground motions at the first period. This study could further provide useful information on selecting appropriate ground motion to predict seismic behavior of different types of structures.

• Phonetics and Speech Sciences
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• v.15 no.2
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• pp.53-59
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• 2023

Detection of children with autism spectrum disorder (ASD) based on speech has relied on predefined feature sets due to their ease of use and the capabilities of speech analysis. However, clinical impressions may not be adequately captured due to the broad range and the large number of features included. This paper demonstrates that the knowledge-driven speech features (KDSFs) specifically tailored to the speech traits of ASD are more effective and efficient for detecting speech of ASD children from that of children with typical development (TD) than a predefined feature set, extended Geneva Minimalistic Acoustic Standard Parameter Set (eGeMAPS). The KDSFs encompass various speech characteristics related to frequency, voice quality, speech rate, and spectral features, that have been identified as corresponding to certain of their distinctive attributes of them. The speech dataset used for the experiments consists of 63 ASD children and 9 TD children. To alleviate the imbalance in the number of training utterances, a data augmentation technique was applied to TD children's utterances. The support vector machine (SVM) classifier trained with the KDSFs achieved an accuracy of 91.25%, surpassing the 88.08% obtained using the predefined set. This result underscores the importance of incorporating domain knowledge in the development of speech technologies for individuals with disorders.

• Near Infrared Analysis
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• v.2 no.1
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• pp.59-66
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• 2001

Nowadays, medical diagnostics is efficiently supported by clinical chemistry and near infrared spectroscopy is becoming a new dimension, which has shown high potential to provide valuable information for diagnosis. The investigation was carried out to study the influence of mammary gland inflammation, called mastitis, on cow´s milk spectra and milk composition measured by near infrared spectroscopy (NIRS). Milk somatic cell counts (SCC) in milk were used as a measure of mammary gland inflammation. Naturally occurred variations with milk composition within lactation and in the process of milking were included in the experimental design of this study. Time series of unhomogenized, raw milk spectral data were collected from 3 cow along morning and evening milking, for 5 consecutive months, within their second lactation. In the time of the trial, the investigated cows had periods with mammary gland inflammation. Transmittance spectra of 258 milk samples were obtained by NIRSystem 6500 spectrophotometer in 1100-2400 nm region. Calibration equations for the examined milk components were developed by PLS regression using 3 different sets of samples: samples with low somatic cell count (SCC), samples with high SCC and combined data set. The NIR calibration and prediction of individual cow´s milk fat, protein, and lactose were highly influenced by the presence of mil samples from animals with mammary gland inflammation in the data set. The best accuracy of prediction (i.e. the lower SEP and the higher correlation coefficient) for fat, protein and lactose was obtained for equations, developed when using only “healthy” samples, with low SCC. The standard error of prediction increased and correlation coefficient decreased significantly when equations for low SCC milk were used to predict examined components in “mastitis” samples with high SCC, and vice versa. Combined data set that included samples from healthy and mastitis animals could be used to build up regression models for screening. Further use of separate model for healthy samples improved milk composition measurement. Regression vectors for NIR mild protein measurement obtained for “healthy” and “mastitic” group were compared and revealed differences in 1390-1450 nm, 1500-1740 nm and 1900-2200 nm regions and thus illustrated post-secretory breakdown of milk proteins by hydrolytic enzymes that occurred with mastitis. For the first time it has been found that monitoring the spectral differences in water bands at 1440 nm and 1912 nm could provide valuable information for inflammation diagnosis.