• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.377-381
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• 2006

A seismic survey for gas hydrate have performed over the East sea by the KIGAM since 1997. General indicator of gas hydrate in seismic data is commonly inferred from the BSR(Bottom Simulating Reflector) that occurred parallel to the sea floor, amplitude decrease at the top of the BSR, amplitude blanking at the bottom of the BSR, decrease of the interval velocity and the reflection phase reversal at the BSR. In this paper we had analyzed optimum parameters of the field data to detect the 9as hydrate. Shot delay correction is applied 95ms, spherical divergence correction is applied velocity library 3, bandpass filter is applied 25-30-115-120Hz deconvolution operator length is applied 60ms, lag is 6ms and accurate velocity analysis NMO correction, stack is performed. Geobit 2.11.0 developed by the KIGAM was used for all data processing. Processing results say that the BSR occurred parallel to the sea floor were shown at 3,150m/s of two way travel time from the sea floor through shot point 5,000-5,610, and identified the interval velocity decrease around BSR and the reflection phase reversal corresponding to the reflection at the sea floor.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.148-152
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• 2008

Multichannel seismic profiles reveal a strong bottom simulating reflector (BSR) occurring below the seafloor in the plain of the Ulleung Basin, East Sea (Japan Sea). The essential characteristics of the BSR include its cross-cutting relationship to strata, strong amplitude, and reverse polarity with respect to the seafloor reflection, representing the base of the gas hydrate stability zone (BHSZ). The BSR reflection coefficient ranging from -0.23 to -0.26 is 1.5${\sim}$1.7 times that of the seafloor reflection and interval velocities decrease to less than 700 m/s below the BSR. These features indicate the existence of free gas beneath the GHSZ. Heat flow, estimated from the BSR depth as $95{\sim}98mW/m^2$, is in good agreement with measured values. Therefore, the BSR can be efficiently used to estimate regional distribution of heat flow in the Ulleung Basin.

• Journal of Microbiology and Biotechnology
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• v.24 no.12
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• pp.1609-1621
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• 2014

The plant pathogen Burkholderia gladioli, which has a broad host range that includes rice and onion, causes bacterial panicle blight and sheath rot. Based on the complete genome sequence of B. gladioli BSR3 isolated from infected rice sheaths, the genome of B. gladioli BSR3 contains the luxI/luxR family of genes. Members of this family encode N-acyl-homoserine lactone (AHL) quorum sensing (QS) signal synthase and the LuxR-family AHL signal receptor, which are similar to B. glumae BGR1. In B. glumae, QS has been shown to play pivotal roles in many bacterial behaviors. In this study, we compared the QS-dependent gene expression between B. gladioli BSR3 and a QS-defective B. gladioli BSR3 mutant in two different culture states (10 and 24 h after incubation, corresponding to an exponential phase and a stationary phase) using RNA sequencing (RNA-seq). RNA-seq analyses including gene ontology and pathway enrichment revealed that the B. gladioli BSR3 QS system regulates genes related to motility, toxin production, and oxalogenesis, which were previously reported in B. glumae. Moreover, the uncharacterized polyketide biosynthesis is activated by QS, which was not detected in B. glumae. Thus, we observed not only common QS-dependent genes between B. glumae BGR1 and B. gladioli BSR3, but also unique QS-dependent genes in B. gladioli BSR3.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• The Journal of the Acoustical Society of Korea
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• v.38 no.3
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• pp.334-339
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• 2019

In this study, the vibration test method to nondestructively evaluate the possibility of vehicle BSR (Buzz, Squeak, Rattle) noise generation in spot-welded structures was proposed. The weld quality was predicted by analyzing the local vibration transmission characteristics for the beam-shaped structure attached to testing spots. The bending stiffness was evaluated from the identified vibration properties. From the change in the stiffness, the weld quality was evaluated. For verification of the proposed method, the welded specimens were fabricated with partial changes in welding parameters. The local vibration transfers were measured. The frequency bands affected by the weld quality was identified. The capability of evaluating the welding parameters including defect position and quality variations was investigated. The proposed method enables fast quality evaluation to minimize the possibility of BSR noise generation in the manufactured vehicle.

• Journal of the KSME
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• v.52 no.1
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• pp.32-36
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• 2012

차량에서의 BSR은 주로 내장재에서 발생하는데, 최근의 복잡한 제품 디자인, 폴리머 계열 소재 사용 및 전기자동차 보급과 맞물려 증가하는 추세이다. 특히 사용 초기에는 나타나지 않다가 이음새, 체결부 및 재료의 열화로 인해 사용 중 발생하는 일이 더 큰 문제가 되고 있다. 이 글에서는 차량 내장재의 BSR 발생문제 및 개선방안에 대해 소개하고자 한다.

• Journal of the KSME
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• v.52 no.1
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• pp.45-49
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• 2012

플라스틱과 같은 고분자 재료는 특유의 부정형 분자 구조 때문에 기온의 변화 등의 외부적 요인에 의하여 초기 설계에 사용된 고유의 기계적 물성이 변화함에 따라 형태의 변형이 발생하여 부품으로 쓰였을 때 체결부가 느슨해지거나 마찰을 유발하여 이음, 즉 BSR을 발생시킨다. 이 글에서는 고분자 재료의 물리적 거동 특성 및 BSR 발생메커니즘에 어떤 영향을 미치는지에 대하여 기술하고자 한다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.330-331
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• 2010

In this paper, BSR noise from an instrument panel of a vehicle are investigated with integrated experimental methods. First, potential source regions of the instrument panel for BSR are localized by using the module-excitor and near-acoustic field visualization system. Then, subjective evaluation of BSR nosie from the detected potential noise source regions is made with the Zwicker's loudness and time-varying loudness methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.5
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• pp.353-363
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• 1990

This paper analyzes effect of Data Bit Jitter(DBJ) on the Bit Slip Rate(BSR) of the receiver Data Tracking Loop(DTL). In particular, we point out the characteristic jitter parameters that can be used to estimate the BSR performance for the low frequency parts respectively. We also propose a new format for the DBJ specification, which is more sophisticated than the conventional method but is believed to be more practical and accurate in predicting DBJ effect on the receiver BSR performance. In the proposed method, receive dependent parameters are identified and weighting between different parts of jitter spectrum are properly considered.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.151-156
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• 2007

In December 2006, 2D surface streamer and Ocean Bottom Seismometer (OBS) data were acquired in the Ulleung basin in Korea where strong Bottom Simulating Reflectors (BSR) were shown as a result of 2D and 3D multichannel (MCS) reflection survey. The aim of this study is to provide another reliable source for estimating P wave velocity around BSR depth using OBS data in addition to velocity information from 2D surface seismic data. Four OBSs were deployed and four 20-km shot lines which pass two OBSs respectively were designed. To derive P wave velocity profile, interactive interval velocity analysis using ${\tau}$-p trajectory matching method (Kumar, 2005) was used for OBS data and semblance analysis was used for surface data. The seismic profiles cross the OBS instruments in two different directions yield recordings for four different azimuths. This raised the confidence for the results. All velocity profiles in the vicinity of BSR depth of four OBS sites show almost definite velocity changes which we could consider as upper BSR and free gas layer. Making comparison between velocity from OBS and that from 2D seismic semblance velocity analysis gives consistency in result.