• Fire Science and Engineering
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• v.27 no.5
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• pp.38-43
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• 2013

An automatic spreading fire extinguisher usually installed in a closed area like a boiler room, a laundry store or a restaurant's kitchen room is one of the fire protection equipments. This extinguisher automatically discharges dry powder, extinguishing fire. As this extinguisher has the extinguishing capability applicable to the nominal protection area, objects outside the area cannot be properly extinguished. However only its number is being requested according to the floor area in the related laws, and the extinguishing capability depends on the distance from a fire source. In this study we tried to investigate the extinguishing capability of the automatic spreading fire extinguisher in accordance with horizontal separation distance from a fire source. It appeared that the maximum horizontal separation distance was about 30 cm for both class A and B fire to be certainly extinguished.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1024-1034
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• 2019

Preference for music is determined by a variety of factors, and identifying characteristics that reflect specific factors is important for music recommendations. In this paper, we propose a method to extract the singing voice related music features reflecting various musical characteristics by using a model learned for singer identification. The model can be trained using a music source containing a background accompaniment, but it may provide degraded singer identification performance. In order to mitigate this problem, this study performs a preliminary work to separate the background accompaniment, and creates a data set composed of separated vocals by using the proven model structure that appeared in SiSEC, Signal Separation and Evaluation Campaign. Finally, we use the separated vocals to discover the singing voice related music features that reflect the singer's voice. We compare the effects of source separation against existing methods that use music source without source separation.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.623-629
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• 2004

In this paper, a Efficient method for the mixed image separation is presented using independent component analysis and the new fast expectation-maximization(EM) algorithm. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme in various applications. However, it has been known that ICA does not establish good performance in source separation by itself. So, Innovation process which is one of the methods that were employed in image separation using ICA, which produces improved the mixed image separation. Unfortunately, the innovation process needs long processing time compared with ICA or EM. Thus, in order to overcome this limitation, we proposed new method which combined ICA with the New fast EM algorithm instead of using the innovation process. Proposed method improves the performance and reduces the total processing time for the Image separation. We compared our proposed method with ICA combined with innovation process. The experimental results show the effectiveness of the proposed method by applying it to image separation problems.

• Progress in Superconductivity and Cryogenics
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• v.25 no.3
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• pp.18-21
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• 2023

Pollution of the environment by micro-plastics is now a worldwide problem. Plastics are difficult to decompose and put a great load on the marine environment. Especially a plastic with a size of 5 mm or less is defined as micro-plastic and are carried by ocean currents over long distances, causing global pollution. These are not easily decomposed in the natural environment. In this paper, we aimed to experimentally demonstrate that micro-plastics in seawater can be continuously separated by electromagnetic Archimedes force. Using polyethylene particles of 3 mm in diameter as the separation target, a flow channel was fabricated and separation conditions were investigated by particle trajectory calculations for separation experiments. Based on the calculation results, a solenoid-type superconducting magnet was used as a source of magnetic field to conduct separation experiments of micro-plastics in seawater. Although a high separation rate was assumed in the simulation results, the experimental results did not show any significant improvement in the separation rate due to the electromagnetic Archimedes force. It was found that the gas generated by the electrolytic reaction may have inhibited the migration of the particles.

• Progress in Superconductivity and Cryogenics
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• v.21 no.2
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• pp.31-35
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• 2019

Andong-dam was built up in 1967 and it is one of the biggest dams in Korea. Previous studies showed that the sediments are highly contaminated with heavy metals such as arsenic, cadmium, and lead. Many research projects are going on to find out the source of the contamination, to evaluate the toxicities to ecosystem, to estimate the volume of sediment to be treated and to find out a good remediation method. Reports show that the sediment is highly contaminated and the main contamination source is supposed to be abandoned mines and a zinc refinery located upper stream of the river. A magnetic separation has been tested as a treatment method for the dredged sediment. Lab scale test showed that the magnetically captured portion is about 10% in weight but the contamination of heavy metal is much higher than the contamination of the passed portion. This indicates that a magnetic separation could be applied for the purpose of reduction of sediment to be treated and for increasing the volume of low toxic sediments which can be dumped as general waste. A magnetic separation using a HGMS has been tested for the sediment with variable magnetic field and the results showed the higher magnetic field increase the captured portion but the concentrating effect of heavy metal was weakened. Further study is needed to establish a useful technology and optimization between decontamination and reduction of sediment volume.

• MALSORI
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• no.48
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• pp.117-126
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• 2003

source of speech signal is actually composed of combination of periodic and aperiodic components, although it is often modeled to either one of those. In the paper an experiment which can separate periodic and aperiodic components from speech source. Linear predictive residual signal was used as a approximated vocal source the original speech to obtain the estimated aperiodic part. Iterative extrapolation method was used to compute the aperiodic part.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.70-76
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• 2012

The independent component analysis (ICA) technique is a source identification method that uses statistical independence to separate source signals from measured signals. It has been successfully applied to various fields such as medical care and communication. In this study, the ICA technique was adopted to analyze the vibration source contribution of plate structures. The theory of the ICA technique is introduced and the procedure of the vibration source contribution analysis based on the ICA technique is proposed. To investigate the applicability of the proposed method to plate structures, numerical examples are presented for a rectangular plate under harmonic force excitations. The results show that the proposed method could become an effective tool for the vibration source contribution analysis of a plate structure.

• ETRI Journal
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• v.34 no.6
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• pp.958-961
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• 2012

In this letter, we present a new algorithm for the harmonic and percussive separation of jazz music. Using a short-time Fourier transform and nonnegative matrix factorization, the signal is decomposed into rank components. Each component is then split into harmonic and percussive parts using masks calculated based on their tonalities. Finally, the harmonic and percussive parts are separated after applying the masks and a summation. We evaluate the algorithm based on real audio examples using both objective and subjective assessments. The proposed algorithm performs well for the separation of harmonic and percussive parts of jazz excerpts.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.2
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• pp.10-20
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• 2002

Various blind source separation (BSS) and independent component analysis (ICA) algorithms have been developed. However, comparison study for BSS/ICA algorithms has not been extensively carried out yet. The main objective of this paper is to compare various promising BSS/ICA algorithms in terms of several factors such as robustness to sensor noise, computational complexity, the conditioning of the mixing matrix, the number of sensors, and the number of training patterns. We propose several benchmarks which are useful for the evaluation of the algorithm. This comparison study will be useful for real-world applications, especially EEG/MEG analysis and separation of miked speech signals.

• Journal of The Korean Astronomical Society
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• v.27 no.2
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• pp.103-117
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• 1994

To extend the work of Gott, Park, and Lee (1989), statistical properties of gravitational lensing in a wide variety of cosmological models involving non-zero cosmological constant is investigated, using the redshifts of both lens and source and observed angular separation of images for gravitational lens systems. We assume singular isothermal sphere as lensing galaxy in homogenous and isotropic Friedmann­Lemaitre-Robertson- Walker universe, Schechter luminosity function, standard angular diameter distance formula and other galaxy parameters used in Fukugita and Turner (1991). To find the most adequate flat cosmological model and put a limit on the value of dimensionless cosmological constant $\lambda_0$, the mean value of the angular separation of images, probability distribution of angular separation and cumulative probability are calculated for given source and lens redshifts and compared with the observed values through several statistical methods. When there is no angular selection effect, models with highest value of $\lambda_0$ is preferred generally. When the angular selection effects are considered, the preferred model depends on the shape of the selection functions and statistical methods; yet, models with large $\lambda_0$ are preferred in general. However, the present data can not rule out any of the flat universe models with enough confidence. This approach can potentially select out best model. But at the moment, we need more data.