• Journal of Communications and Networks
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• 제14권1호
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• pp.1-9
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• 2012

We consider a receiving node, located at the origin, and a Poisson point process (PPP) that models the locations of the desired transmitter as well as the interferers. Interference is known to be non-Gaussian in this scenario. The capacity bounds for additive non-Gaussian channels depend not only on the power of interference (i.e., up to second order statistics) but also on its entropy power which is influenced by higher order statistics as well. Therefore, a complete statistical characterization of interference is required to obtain the capacity bounds. While the statistics of sum of signal and interference is known in closed form, the statistics of interference highly depends on the location of the desired transmitter. In this paper, we show that there is a tradeoff between entropy power of interference on the one hand and signal and interference power on the other hand which have conflicting effects on the channel capacity. We obtain closed form results for the cumulants of the interference, when the desired transmitter node is an arbitrary neighbor of the receiver. We show that to find the cumulants, joint statistics of distances in the PPP will be required which we obtain in closed form. Using the cumulants, we approximate the interference entropy power and obtain bounds on the capacity of the channel between an arbitrary transmitter and the receiver. Our results provide insight and shed light on the capacity of links in a Poisson network. In particular, we show that, in a Poisson network, the closest hop is not necessarily the highest capacity link.

• 대한산업공학회지
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• 제27권1호
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• pp.1-10
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• 2001

In the reverse engineering, surfaces are modeled for new products by interpolating the digitized data points obtained by measuring the existing shapes. However, many measuring or deviation errors are happened during the measuring process. If these errors are ignored, designers could get undesirable results. Therefore, it is important to handle such errors and fairing procedure with the esthetics criteria is needed during surface modeling process. This paper presents algorithms for the fairing of B-spline surfaces. The algorithms are based on automatic repositioning of control points for B-spline surfaces. New positions of the control points are determined by solving a non-linear programming of which the objective functions are derived variously using derived surfaces and constraints are established by distance measures between the original and the modified control points. Changes in surface shapes are analyzed by illustrations of their shapes and continuous plotting of gaussian and mean curvatures.

• 한국해안·해양공학회논문집
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• 제34권6호
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• pp.315-324
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• 2022

2차원 조파수조 내에서 취득된 규칙파 실험데이터를 머신러닝 기법으로 분석하여 천수 변형을 경험한 파랑으로부터 조파기의 입력파고를 예측하는 모델을 수립하고 그 성능을 검증하였다. 이를 위해 가장 대표적인 머신러닝 기법인 인공신경망(NN)과 비모수 회귀분석 방법 중 하나인 가우시안 과정 회귀(GPR) 모델을 각각 수립하고 두 모델의 예측 성능을 비교하였다. 전체 실험자료를 모두 한꺼번에 활용한 경우와 쇄파 발생 여부에 따라 자료를 구분한 경우에 대해 독립적으로 분석을 수행하였다. 데이터를 구분하지 않은 경우에는 NN 및 GPR 모델 모두 조파기 입력파고 값과 계측값 사이의 오차가 비교적 크게 나타났다. 반면에 데이터를 비쇄파 및 쇄파 조건으로 구분하면 조파기 입력파고의 예측 정확도가 크게 향상되었다. 두 모델 중에서는 NN 모델보다 GPR 모델의 성능이 전반적으로 더 우수한 것으로 나타났다.

• Journal of Advanced Marine Engineering and Technology
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• 제25권5호
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• pp.1058-1064
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• 2001

In this paper, the development of probability distribution estimation program for fatigue crack growth lives was summarize. The probability distribution estimation program of life was developed to increase the reliability of life estimation. In this study, it is considered that the cause of scatter in fatigue crack growth data is due to material inhomogeneity. The material resistance to fatigue crack growth is modelled as a spatial stochastic process, which varies randomly along the crack path. We developed the GUI program to estimate the probability distribution and reliability using the non-Gaussian stochastic process method. This program can be used for the reliability assessment.

• 한국정밀공학회지
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• 제4권2호
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• pp.36-46
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• 1987

An optical technique using laser for non-contact measurement of surface roughness and form accuracy of ground surfaces is presented. It is found that, when a ground surface is illuminated by a beam of laser light, the roughness height and slope distribution has significant influence on the pattern of reflection and it maintains an unique Gaussian distribution relationship with the surface roughness. The principle idea of the optical measurement system is therefore monitor the radiation, and then calibrate it in process against surface roughness by means of necessary digital data processing. On the other hand, measuring the form accuracy of a ground surface is accomplished by using a triangular method, which is based on observing the movement of an image of a spot of light projected onto the surface. The image is focused, through a series of lenses for magnification, on a photodetector array lf line configur- ation. Then the relative movement of image and consequently the form accuracy of the surface can be obtained through appropriate calibration procedures. Experimental test showed that the optical roughness measurement technique suggested in this work is very efficient for most industrial applications being capable of monitoring the roughness heights ranging 0.1 to 0.6 .$\mu$m CLA values. And form accuracy can be measured in process with a resolution of 10 .$\mu$m.

• Journal of the Korean Statistical Society
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• 제26권2호
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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.

• 한국분말재료학회지
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• 제10권5호
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• pp.318-324
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• 2003

The nano-scale crystallite sizes of uranium oxide powders in simulated spent fuel were measured by the neutron diffraction line broadening method in order to analyze the sintering behavior of the dry process fuel. The mixed $UO_2$ and fission product powders were dry-milled in an attritor for 30, 60, and 120 min. The diffraction patterns of the powders were obtained by using the high resolution powder diffractometer in the HANARO research reactor. Diffraction line broadening due to crystallite size was measured using various techniques such as the Stokes' deconvolution, profile fitting methods using Cauchy function, Gaussian function, and Voigt function, and the Warren-Averbach method. The non-uniform strain, stacking fault and twin probability were measured using the information from the diffraction pattern. The realistic crystallite size could be obtained after separation of the contribution from the non-uniform strain, stacking fault and twin.

• 한국공작기계학회논문집
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• 제16권1호
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• pp.26-32
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• 2007

This study was carried out fusion-welded butt joints in SWS 490A high strength steel subjected to tensile test that load-deflection curve. The windowed or short-time Fourier transform(WFT or STFT) makes possible for the analysis of non-stationary or transient signals into a joint time-frequency domain and the wavelet transform(WT) is used to decompose the acoustic emission(AE) signal into various discrete series of sequences over different frequency bands. In this paper, for acoustic emission signal analysis to use a continuous wavelet transform, in which the Gabor wavelet base on a Gaussian window function is applied to the time-frequency domain. A wavelet transform is demonstrated and the plots are very powerful in the recognition of the acoustic emission features. As a result, the technique of acoustic emission is ideally suited to study variables which control time and stress dependent fracture or damage process in metallic materials.

• The Journal of the Acoustical Society of Korea
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• 제13권2E호
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• pp.68-75
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• 1994

신호처리의 많은 분야에서, 심하게 비가우시안 성질을 가지는 분포, 혹은 분포의 중간은 가우시안 특성을 가지지만 양 끝에서는 편차가 크게 나는 분포를 다루어야 하는 경우가 종종 있다. 이러한 편차에 효과적으로 대처하기 위하여 본 논문에서는 음성 신호의 여기 신호로서 혼합 분포(mixture distribution)을 고려한다. 이것은 음성 분석시 피치 주파수가 미치는 영향을 감소시키며, 배경 잡음을 제거하는 데에도 효과적이다. 음성 신호 파라미터의 추정 및 향상을 위하여 EM 알고리즘을 사용하묘, 향상 과정에서는 강인 칼만 필터링 기법을, 파라미터 추정 관정에서는 검출/추정 기법을 사용한다. 실험 결과, 본 논문에서 제안하는 알고리즘이 입력 신호대잡음비가 열악한 경우에 기존의 것보다 우수한 성능을 보인다.

• Nuclear Engineering and Technology
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• 제46권5호
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• pp.619-632
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• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.