• 천문학회보
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• 제46권1호
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• pp.32.3-33
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• 2021

We present H I gas kinematics and star formation activities of NGC 6822, a dwarf galaxy located in the Local Volume at a distance of ~ 490 kpc. We perform profile decomposition of the line-of-sight velocity profiles of the high-resolution (42.4" × 12" spatial; 1.6 km/s spectral) H I data cube taken with the Australia Telescope Compact Array (ATCA). For this, we use a new tool, the so-called BAYGAUD (BAYesian GAUssian Decompositor) which is based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, allowing us to decompose a line-of-sight velocity profile into an optimal number of Gaussian components in a quantitative manner. We classify the decomposed H I gas components of NGC 6822 into bulk-narrow, bulk-broad, and non_bulk with respect to their velocity and velocity dispersion. We correlate their gas surface densities with the surface star formation rates derived using both GALEX far-ultraviolet and WISE 22 micron data to examine the impact of gas turbulence caused by stellar feedback on the Kennicutt-Schmidt (K-S) law. The bulk-narrow component that resides within r25 is likely to follow the linear extension of the Kennicutt-Schmidt (K-S) law for molecular hydrogen (H2) at the low gas surface density regime where H I is not saturated.

• 한국해양공학회지
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• 제28권6호
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• pp.552-559
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• 2014

In general, the number of underwater transient signals is very limited for research on automatic recognition. Data-dependent feature extraction is one of the most effective methods in this case. Therefore, we suggest WPCC (Wavelet packet ceptsral coefficient) as a feature extraction method. A wavelet packet best tree for each data set is formed using an entropy-based cost function. Then, every terminal node of the best trees is counted to build a common wavelet best tree. It corresponds to flexible and non-uniform filter bank reflecting characteristics for the data set. A GMM (Gaussian mixture model) is used to classify five classes of underwater transient data sets. The error rate of the WPCC is compared using MFCC (Mel-frequency ceptsral coefficients). The error rates of WPCC-db20, db40, and MFCC are 0.4%, 0%, and 0.4%, respectively, when the training data consist of six out of the nine pieces of data in each class. However, WPCC-db20 and db40 show rates of 2.98% and 1.20%, respectively, while MFCC shows a rate of 7.14% when the training data consists of only three pieces. This shows that WPCC is less sensitive to the number of training data pieces than MFCC. Thus, it could be a more appropriate method for underwater transient recognition. These results may be helpful to develop an automatic recognition system for an underwater transient signal.

• 한국정보통신학회논문지
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• 제21권2호
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• pp.259-264
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• 2017

신생아의 출생체중은 자궁내발육부전이나 과체중출생아를 진단하는 데 사용되는 등, 의학적으로 여러 가지 중요한 정보를 제공한다. 본 논문에서는 2011년부터 2013년까지 한국에서 태어난 신생아의 출생체중 데이터를 분석하고, 생물학적으로 부자연스러운 체중 분포를 관찰할 수 있음을 보인다. 이러한 비상식적인 체중 분포는 데이터 수집과정 등에서 오류가 존재함을 의미하는데, 특히 임신주수가 28주에서 32주인 신생아들의 체중 데이터에서 현저한 오류 데이터를 관찰할 수 있다. 이를 보정하기 위해, 본 논문은 가우시안 혼합 모델을 사용하여 오류 데이터와 정상 데이터를 예측하고, 오류 데이터로 예측된 자료들을 삭제하는 과정을 제안한다. 제안된 보정 과정을 통하여 보다 자연스럽고 의학적으로 의미 있는 출생체중 백분율을 구할 수 있음을 보인다.

• 한국해안해양공학회지
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• 제6권1호
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• pp.88-93
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• 1994

유한수심에서의 불규칙파에 적용할 수 있는 파고의 확률분포함수를 2가지 해석적 방법으로 유도하였다. 첫번째 방법으로 새로이 유도된 확률분포함수는 Rayleigh 확률분포함수에 대한 직교 다항식을 유도함으로써 급수형태로 표시된다. 유도된 확률밀도함수를 비정규성이 강한 천해에서 측정한 파랑자료와 비교하였다. 확률밀도함수가 자료의 막대그래프와 잘 일치하였으나, 확률밀도함수가 급수로 표시되어 있기 때문에 파고가 큰 부분에서 음의 확률값이 된다. 비록 음의 확률값의 크기가 작다 하더라도 파고의 극치분포함수를 구하기에 부적절하다고 판단된다. 두번째 방법은 최대 엔트로피 법(maximum entropy method)을 적용하여 파고 분포와 매우 잘 일치하며, 극치파고분포와 파고의 통계적인 특성 등을 추정하는 데 매우 유용함을 알 수 있다. 그러나 최대 엔트로피 법을 사용했을 경우, 비정규분포 특성을 나타내는 변위의 분포함수와 파고의 분포함수 사이의 함수관계를 구할 수 없었다.

• 센서학회지
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• 제26권1호
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• pp.1-6
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• 2017

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

• 천문학회보
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• 제36권2호
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• pp.131.2-131.2
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• 2011

We present performance of artificial neural network multivariate classifier in identifying non-astrophysical origin noise transients from the gravitational wave channel of Laser Interferometer Gravitational-wave Observatory (LIGO). LIGO has successfully conducted six science runs, achieving the sensitivity as planned and producing many fruitful scientific results. It has been well observed that the detector noise is non-Gaussian and non-stationary, which results in large excess of noise transients called glitches arising from instrumental and environmental artifacts. Great efforts have been committed to reduce the glitches by tuning the detector instruments and by vetoing them but further improvement is still needed. To this end, there have been efforts to incorporate data from hundreds of auxiliary, physical and environmental channels into identifying the glitches in the gravitational wave channel. We introduce a multivariate classification method using Artificial Neural Networks (ANNs) that efficiently handles large number of variables. In this poster, we present preliminary results of the application of our ANN algorithm to data from LIGO's Science Run 4 and compare its performance with conventional vetoing method.

• 대한의용생체공학회:의공학회지
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• 제15권1호
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• pp.83-88
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• 1994

The transform trellis code is an optimal source code as a block size and the constraint length of a shift register go to infinite for stationary Gaussian sources with the squared-error distortion measure. However to implement this code, we have to choose the finite block size and constraint length. Moreover real-world sources are inherently non stationary. To overcome these difficulties, we developed a training algorithm for the transform trellis code. The trained transform trellis code which uses the same rates to each block led to a variation in the resulting distortion from one block to another. To alleviate this non-uniformity in the encoded image, we constructed clusters from the variance of the training data and assigned different rates for each cluster.

• 제어로봇시스템학회논문지
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• 제9권5호
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• pp.368-373
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• 2003

This paper presents a cost-effective 3D foot scanner system that provides the 3-dimensional point cloud foot data to design the custom footwear. To measure the 3-dimensional point cloud data of the foot, a CCD camera, a Non-Gaussian laser line projector and optical triangulation method are employed. Furthermore, the integrated system employs a measurement base, a frame grabber, a CCD moving cart, a stepping motor and a computer. The measurement result is saved as 3D dxf format and it could be converted to 2D essential data fer a shoe design. The experimental results demonstrate that the proposed system have the decent resolution of 1mm which is enough for last and shoe design.

• 한국정보통신학회논문지
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• 제9권6호
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• pp.1341-1345
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• 2005

비선형이고 정규분포에 따르지 않는 state-space모형분석에서 순차적 몬테 칼로(SMC)는 유용한 도구 중의 하나이다. 모수와 시그럴을 동시에 추정하기 위해 Monte Carlo particle filters를 사용할 수가 있다. 그러나 SMC는 여러단계의 반복을 요구하는 특별한 particle filtering 기법을 필요로 하게 된다. 본 논문은 particle filtering과 순차적 hybrid Monte Carlo(SHMC)을 결합하는 방법을 제시하고자 한다. 실험을 위해 짱뚱어 자료를 사용하였다.

• Wind and Structures
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• 제21권1호
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• pp.1-23
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• 2015

Wind tunnel testing of a low-rise building with openings (holes) of different sizes and shapes on a roof corner is conducted to measure the internal and external pressures from the building model. Detailed analysis of the testing data is carried out to investigate the characteristics of the internal and external pressures of the building with different openings' configurations. Superimposition of the internal and external pressures makes the emergence of positive net pressures on the roof. The internal pressures demonstrate an overall uniform distribution. The probability density function (PDF) of the internal pressures is close to the Gaussian distribution. Compared with the PDF of the external pressures, the non-Gaussian characteristics of the net pressures weakened. The internal pressures exhibit strong correlation in frequency domain. There appear two humps in the spectra of the internal pressures, which correspond to the Helmholtz frequency and vortex shedding frequency, respectively. But, the peak for the vortex shedding frequency is offset for the net pressures. Furthermore, the internal pressure characteristics indirectly reflect that the length of the front edge enhances the development of the conical vortices.The objective of this study aims to further understanding of the characteristics of internal, external and net pressures for low-rise buildings in an effort to reduce wind damages to residential buildings.