• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.191-196
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• 2013

In this paper, the interaural intensity difference (IID)-based sounr source separation method in closely spaced stereo omnidirectional microphones is proposed. First, in order to improve the channel separability, a minimum variance distortionless response (MVDR) beamformer is employed to increase the intensity difference between stereo channels. After that, IID-based sound source separation method is applied. In order to evaluate the performance of the proposed method, source-to-distortion ratio (SDR), source-to-interference ratio (SIR), and sources-to-artifacts ratio (SAR), which are defined as objective evaluation criteria in stereo audio source separation evaluation campaign (SASSEC), are measured. As a result, it was shown from the objective evaluation that the proposed method outperforms a sound source separation method without applying a beamformer.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.98-103
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• 2001

The binaural auditory system of human has the capability of differentiating the direction and distance of sound sources. This feature is well characterised in terms of the inter-aural intensity difference (IID), the inter-aural time difference (ITD) and/or the spectral shape difference (SSD) arising from the acoustic transfer of a sound source to the outer ears. This paper proposes an effective way of extracting the three sound perception factors (IID, ITD, SSD) from the head-related transfer functions (HRTF's) that depends on the direction and distance of the acoustic source from the listener. It includes the estimation method of the equivalent ITD and 1/3-octave band-based IID factors and their usage to locate a sound source in space. Subjective and objective tests were carried out to examine the effectiveness of the proposed methodology and its applicability to real sound systems. Those experimental results are illustrated in this paper.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.61-73
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• 2016

We consider the wild bootstrap Ljung-Box (LB) test for autocorrelation in residuals of fitted multivariate time series models. The asymptotic chi-square distribution under the IID assumption is traditionally used for the LB test; however, size distortion tends to occur in the usage of the LB test, due to the conditional heteroskedasticity of financial time series. In order to overcome such defects, we propose the wild bootstrap LB test for autocorrelation in residuals of fitted vector autoregressive and error correction models. The simulation study and real data analysis are conducted for finite sample performance.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.603-611
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• 1996

In this article we consider a sequential procedure for the fixed width interval estimation of the means of two mutually independent linear processes. It is shown that the proposed stopping rule is asymptotically efficient as in iid samples (cf. Robbins, Simons and Starr(l967)).

• Journal of the Korean Statistical Society
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• v.32 no.3
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• pp.213-224
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• 2003

We give an overview of results which have appeared or will appear elsewhere demonstrating that by suitably modifying the bootstrap principle, its applicability can be greatly enhanced. Although we state our results for the iid case, extensions are, at least heuristically, easy.

• Korean Journal of Plant Resources
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• v.14 no.3
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• pp.247-250
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• 2001

Two naturalized taxa in Jeju such as Tradescantia flumiensis Vell., and Lotus tenuis Wald. et Kit. ex WiIId. are newly recorded. Short descriptions and illustrations for these taxa are provided.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.231-243
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• 1997

In this paper we investigate weak convergence of the intergral processes whose index set is the non-compact infinite time interval. Our first goal is to develop the empirical central limit theorem as random elements of [0, .infty.) for an integral process which is constructed from iid variables. In developing the weak convergence as random elements of D[0, .infty.), we will use a result of Ossiander(4) whose proof heavily depends on the total boundedness of the index set. Our next goal is to establish the empirical central limit theorem for the Kaplan-Meier integral process as random elements of D[0, .infty.). In achieving the the goal, we will use the above iid result, a representation of State(6) on the Kaplan-Meier integral, and a lemma on the uniform order of convergence. The first result, in some sense, generalizes the result of empirical central limit therem of Pollard(5) where the process is regarded as random elements of D[-.infty., .infty.] and the sample paths of limiting Gaussian process may jump. The second result generalizes the first result to random censorship model. The later also generalizes one dimensional central limit theorem of Stute(6) to a process version. These results may be used in the nonparametric statistical inference.

• Food Science of Animal Resources
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• v.43 no.4
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• pp.625-638
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• 2023

Among various biological agents, bacteriocins are important candidates to control Listeria monocytogenes which is a foodborne pathogen. In this study, a novel bacteriocin, named agilicin C7, was isolated from Ligilactobacillus agilis C7 showing inhibitory activity against L. monocytogenes. Agilicin C7 biosynthesis gene was characterized by bioinformatics analyses and heterologously expressed in Escherichia coli for further study. The anti-listeria activity of recombinant agilicin C7 (r-agilicin C7) was lost by proteases and α-amylase, suggesting that agilicin C7 is a glycoprotein. r-Agilicin C7 has wide pH and thermal stability and is also stable in various organic solvents. It destroyed L. monocytogenes by damaging the integrity of the cell envelope. These properties of r-agilicin C7 indicate that agilicin C7 is a novel amylase-sensitive anti-listerial Class IId bacteriocin. Physicochemical stability and inhibitory activity against L. monocytogenes of r-agilicin C7 suggest that it can be applied to control L. monocytogenes in the food industry, including dairy and meat products.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.119-130
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• 2003

SP data have been widely used in assessing new transport policies and transport related plans. However, one of criticisms of using SP is that respondents may show different reaction between hypothetical experiments and real life. In order to overcome the problem, combination of SP and RP data has been suggested and the combined methods have been being developed. The purpose of this paper is to suggest a new SP and RP combined method using error component method and to verify the method. The error component method decomposes IID extreme value error into non-IID error component(s) and an IID error component. The method estimates both of component parameters and utility parameters in order to obtain relative variance of SP data and RP data. The artificial SP and RP data was created by using simulation and used for the analysis, and the estimation results of the error component method were compared with those of existing SP and RP combined methods. The results show that regardless of data size, the parameters of the error component method models are similar to those assumed parameters much more than those of the existing SP and RP combined models, indicating usefulness of the error component method. Also the values of time for error component method are more similar to those assumed values than those of the existing combined models. Therefore, we can conclude that the error component method is useful in combining SP and RP data and more efficient than the existing methods.

• Journal of the Korean Statistical Society
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• v.15 no.2
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• pp.97-106
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• 1986

Assume that $X_1, X_2, \cdots, X_N$ are iid p-dimensional normal random vectors ($p \geq 3$) with unknown covariance matrix. The problem of estimating multivariate normal mean vector in an empirical Bayes situation is considered. Empirical Bayes estimators, obtained by Bayes treatmetn of the covariance matrix, are presented. It is shown that the estimators are minimax, each of which domainates teh maximum likelihood estimator (MLE), when the loss is nonsingular quadratic loss. We also derive approximate credibility region for the mean vector that takes advantage of the fact that the MLE is not the best estimator.