• Phonetics and Speech Sciences
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• v.10 no.2
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• pp.7-14
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• 2018

The paper investigates the acoustic characteristics of English fricatives in the TIMIT corpus, with a special focus on the role of voicing in rendering fricatives in American English. The TIMIT database includes 630 talkers and 2,342 different sentences, and comprises more than five hours of speech. Acoustic analyses are conducted in the domain of spectral and temporal properties by treating gender, voicing, and place of articulation as independent factors. The results of the acoustic analyses revealed that acoustic signals interact in a complex way to signal the gender, place, and voicing of fricatives. Classification experiments using a multiclass support vector machine (SVM) revealed that 78.7% of fricatives are correctly classified. The majority of errors stem from the misclassification of /θ/ as [f] and /ʒ/ as [z]. The average accuracy of gender classification is 78.7%. Most errors result from the classification of female speakers as male speakers. The paper contributes to the understanding of the effects of voicing and gender on fricatives in a large-scale speech corpus.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.89-97
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• 2005

Application of proper orthogonal decomposition (POD) and continuous wavelet transform (CWT) is introduced to study wind speed and building roof pressures of flow separation region. In this study, a detailed analysis of the approach wind flow, wind-induced building pressure and the relation between the two fields was carried out using the POD technique and CWT analysis. The results show potential of the application of POD and CWT in characterization of spatio-temporal and spectral properties of the approach wind and its induced dynamic pressure events. Some of findings resulting from the application of this analysis can be summarized as follows: (1) The POD first principal coordinate of the roof pressure in the separated shear layer is closely correlated with the longitudinal component of oncoming flow. (2) The CWT analysis suggests that the extreme peak pressure in the separated shear layer is due to condensed large-scale eddy motions.

• The Korean Journal of Ecology
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• v.20 no.6
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• pp.423-438
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• 1997

The structure and variation of the mating call in Rana nigromaculata was studied in a population at Da-rak, Chong-won, Chung-buk (36$\circ$ 37' latitude, 127$\circ$ 21' longitude) in Korea. The mating call consists of 3 to 8 pulse groups divided by clear silent intervals. Each pulse group is also composed of fine pulses. Temperature and body size affect the temporal and spectral characteristics of the mating call. Pulse, pulse group repetition rate and dominant frequency rise with increasing temperature, whereas pulse grouprepetition rate and dominant frequency decrease with increasing body size. A playback experiment was designed to establish the effect of a potential intruder on male calling. During the stimulus periods, resident males markedly decreased the pulse repetition rate, and icreased the rate of pulse groups, dominant frequency, and the number of call groups. This results indicate that this species responds in a graded fashion when interacting with other individuals.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.507-519
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• 2023

Multi-temporal optical images have been utilized for time-series monitoring of croplands. However, the presence of clouds imposes limitations on image availability, often requiring a cloud removal procedure. This study assesses the applicability of various machine learning algorithms for effective cloud removal in optical imagery. We conducted comparative experiments by focusing on two key variables that significantly influence the predictive performance of machine learning algorithms: (1) land-cover types of training data and (2) temporal variability of land-cover types. Three machine learning algorithms, including Gaussian process regression (GPR), support vector machine (SVM), and random forest (RF), were employed for the experiments using simulated cloudy images in paddy fields of Gunsan. GPR and SVM exhibited superior prediction accuracy when the training data had the same land-cover types as the cloud region, and GPR showed the best stability with respect to sampling fluctuations. In addition, RF was the least affected by the land-cover types and temporal variations of training data. These results indicate that GPR is recommended when the land-cover type and spectral characteristics of the training data are the same as those of the cloud region. On the other hand, RF should be applied when it is difficult to obtain training data with the same land-cover types as the cloud region. Therefore, the land-cover types in cloud areas should be taken into account for extracting informative training data along with selecting the optimal machine learning algorithm.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.58.3-59
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• 2018

We investigate velocity oscillations in a solar quiet region by using the spectral data of the $H{\alpha}$ and Ca II $8542{\AA}$ lines. The data were acquired by the Fast Imaging Solar Spectrograph installed at the 1.6 m Goode Solar Telescope of Big Bear Solar Observatory. According to Chae & Litvinenko (2018)'s theoretical work, there is a correlation between dominant period of the oscillations and the temperature of the temperature minimum region in a non-isothermal atmosphere. In our study, we measure the temporal variations of the intensity and the line of sight Doppler velocity, and find out the relations between the intensity and dominant period of the oscillations. In addition, we investigate oscillations in a few distinct regions and discuss regional characteristics of the oscillations.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.425-431
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• 2005

This paper describes the method of using IKONOS imagery in the development of agriculture-related data inventories. Temporally different three images of panchromatic (1m resolution) and multi-spectral bands (4m resolution) were used to obtain the distribution and characteristics of rice, pear, grape, red pepper, garlic, and reservoir surface area with the field surveys. The result of this study suggests the utility of KOMPSAT-II, which increases the use of the crop and water resources data in rural areas by accumulating temporal data inventories.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.9-16
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• 2015

Various approaches to process active sonar signals are under study, but there are many problems to be considered. The sonar signals are distorted by the underwater environment, and the spatio-temporal and spectral characteristics of active sonar signals change in accordance with the aspect of the target even though they come from the same one. And it has difficulties in collecting actual underwater data. In this paper, we synthesized active target echoes based on ray tracing algorithm using target model having 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to synthesized target echoes to extract feature vector. Recognition experiment was performed using probabilistic neural network classifier.

• Phonetics and Speech Sciences
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• v.1 no.2
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• pp.15-22
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• 2009

Prominence of speech, which is often called 'accent,' affects the fluency of speaking American English greatly. In this paper, we present an accurate prominence detection method that can be utilized in computer-aided language learning (CALL) systems. We employed pitch movement, overall syllable energy, 300-2200 Hz band energy, syllable duration, and spectral and temporal correlation as features to model the prominence of speech. After the features for vowel syllables of speech were extracted, prominent syllables were classified by SVM (Support Vector Machine). To further improve accuracy, the differences in characteristics of neighboring syllables were added as additional features. We also applied a speech recognizer to extract more precise syllable boundaries. The performance of our prominence detector was measured based on the Intonational Variation in English (IViE) speech corpus. We obtained 84.9% accuracy which is about 10% higher than previous research.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• v.4 no.1
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• pp.44-50
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• 2001

Existing surface defects in structural members often act as sites of fatigue crack initiation, and if undetected, these cracks may grow through the thickness of the member, leading to catastrophic failure of the structure. Thus, in-service monitoring of fatigue cracks through reliable and effective nondestructive techniques is an important ingredient in the leak-before-break (LBB) design and safe operation of defects critical structures. An advanced, waveform-based, acoustic emission (AE) technique has been used in this paper to study the characteristics of the signals emanating from the initiation, growth and through-the -thickness penetration of surface fatigue crack in a 6061 aluminum plate. The goal of this experimental study is to determine whether the evolution of the fatigue crocks could be identified from the properties of the waveforms produced during the tests. The AE waveform signals detected at different stages of crack growth was found to have different temporal and spectral characteristics. The data analysis technique presented here can be applied to real-time monitoring of the initiation and propagation of fatigue cracks in structural components.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.371-384
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• 2015

Although GOCI has potential for land surface monitoring, there have been only a few cases for land applications. It might be due to the lack of reliable land products derived from GOCI data for end-users. To use for land applications, it is often essential to provide cloud-free composite over land surfaces. In this study, we proposed a cloud detection method that was very important to make cloud-free composite of GOCI reflectance and vegetation index. Since GOCI does not have SWIR and TIR spectral bands, which are very effective to separate clouds from other land cover types, we developed a multi-temporal approach to detect cloud. The proposed cloud detection method consists of three sequential steps of spectral tests. Firstly, band 1 reflectance threshold was applied to separate confident clear pixels. In second step, thick cloud was detected by the ratio (b1/b8) of band 1 and band 8 reflectance. In third step, average of b1/b8 ratio values during three consecutive days was used to detect thin cloud having mixed spectral characteristics of both cloud and land surfaces. The proposed method provides four classes of cloudiness (thick cloud, thin cloud, probably clear, confident clear). The cloud detection method was validated by the MODIS cloud mask products obtained during the same time as the GOCI data acquisition. The percentages of cloudy and cloud-free pixels between GOCI and MODIS are about the same with less than 10% RMSE. The spatial distributions of clouds detected from the GOCI images were also similar to the MODIS cloud mask products.