• 소성∙가공
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• 제31권5호
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• pp.273-280
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• 2022

Although the mechanical properties of high-entropy alloys depend on the annealing conditions, limited works were established to investigate the annealing effect on the mechanical properties of Mo-added high-entropy alloys. Therefore, in the present work, the annealing effects on the microstructural evolution and mechanical properties of Mo-added high-entropy alloy were investigated. As a result, incomplete recrystallization from the limited annealing time not only suppresses deformation-induced phase transformation during cryogenic tensile test but also induces a deformation instability that results into the ductility reduction compare with the fully recrystallized sample. This result represents adjustment of annealing time is useful to control both transformation-induce plasticity and deformation instability of high-entropy alloys, and this can be applied to control the mechanical properties of metallic alloys by combining pre-straining and subsequent annealing.

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.151-159
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• 1997

In sample surveys, we expect preferred samples that reduce the survey cost and increase the precision of estimators will be selected. Goodman and Kish (1950) introduced controlled selection as a method of sample selection that increases the probability of drawing preferred samples, while decreases the probability of drawing nonpreferred samples. In this paper, we obtain the controlled plans using the maximum entropy principle, and when the order of nonpreferred samples is considered, we propose the algorithm to obtain a controlled plan.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.31-39
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• 2006

In many cases, we frequently get a desired information based on the appropriate statistical analysis of collected data sets. Lots of statistical theory rely on the assumption of the normality of the data. In this paper, we compare the empirical power of some normality tests including sample entropy quantity. Monte carlo simulation is conducted for the calculation of empirical power of considered normality tests by varying sample sizes for various distributions.

• 한국재료학회지
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• 제28권8호
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• pp.445-451
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• 2018

We report the structural, magnetic and magnetocaloric properties of $Sr_{1.8}Pr_{0.2}FeMo_{1-x}W_xO_6$($0.0{\leq}x{\leq}0.4$) samples prepared by the conventional solid state reaction method. The X-ray diffraction analysis confirms the formation of the tetragonal double perovskite structure with a I4/mmm space group in all the synthesized samples. The temperature dependent magnetization measurements reveal that all the samples go through a ferromagnetic to paramagnetic phase transition with an increasing temperature. The Arrott plot obtained for each synthesized sample demonstrates the second order nature of the magnetic phase transition. A magnetic entropy change is obtained from the magnetic isotherms. The values of maximum magnetic entropy change and relative cooling power at an applied field of 2.5 T are found to be $0.40Jkg^{-1}K^{-1}$ and $69Jkg^{-1}$ respectively for the $Sr_{1.8}Pr_{0.2}FeMoO_6$ sample. The tunability of magnetization and excellent magnetocaloric features at low applied magnetic field make these materials attractive for use in magnetic refrigeration technology.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.30-33
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• 2001

The number of hidden neurons of the feed-forward neural networks is generally decided on the basis of experience. The method usually results in the lack or redundancy of hidden neurons, and causes the shortage of capacity for storing information of learning overmuch. This research proposes a new method for optimizing the number of hidden neurons bases on information entropy, Firstly, an initial neural network with enough hidden neurons should be trained by a set of training samples. Second, the activation values of hidden neurons should be calculated by inputting the training samples that can be identified correctly by the trained neural network. Third, all kinds of partitions should be tried and its information gain should be calculated, and then a decision-tree correctly dividing the whole sample space can be constructed. Finally, the important and related hidden neurons that are included in the tree can be found by searching the whole tree, and other redundant hidden neurons can be deleted. Thus, the number of hidden neurons can be decided. In the case of building a neural network with the best number of hidden units for tea quality evaluation, the proposed method is applied. And the result shows that the method is effective

• Journal of Information Processing Systems
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• 제16권2호
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• pp.508-521
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• 2020

We compared a novel encoding Lempel-Ziv complexity (ELZC) with three common complexity algorithms i.e., approximate entropy (ApEn), sample entropy (SampEn), and classic Lempel-Ziv complexity (CLZC) so as to determine a satisfied complexity and its corresponding quality indices for assessing quality of multi-lead electrocardiogram (ECG). First, we calculated the aforementioned algorithms on six artificial time series in order to compare their performance in terms of discerning randomness and the inherent irregularity within time series. Then, for analyzing sensitivity of the algorithms to content level of different noises within the ECG, we investigated their change trend in five artificial synthetic noisy ECGs containing different noises at several signal noise ratios. Finally, three quality indices based on the ELZC of the multi-lead ECG were proposed to assess the quality of 862 real 12-lead ECGs from the MIT databases. The results showed the ELZC could discern randomness and the inherent irregularity within six artificial time series, and also reflect content level of different noises within five artificial synthetic ECGs. The results indicated the AUCs of three quality indices of the ELZC had statistical significance (>0.500). The ELZC and its corresponding three indices were more suitable for multi-lead ECG quality assessment than the other three algorithms.

• 응용통계연구
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• 제20권1호
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• pp.79-89
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• 2007

Arizono와 Ohta(1989)에 의해 소개된 정규성 검정은 쿨백-라이블러 판별정보를 이용하고 있으며, 검정통계량의 유도에 기반이 되는 판별정보의 추정량을 얻기 위해 Vasicek(1976)의 표본엔트로피와 분산의 최대가능도 추정량을 사용했다. 그런데 두 추정량은 편향성을 가지게 되므로 보다 정확한 판별정보의 추정을 위해 비편향 추정량을 사용하는 것이 바람직하다. 본 논문에서는 편향을 수정한 엔트로피 추정량과 분산의 균일최소분산비편향 추정량을 사용하여 판별정보의 추정량을 구하고 이로부터 유도되는 검정통계량을 사용하는 개선된 정규성 검정을 제시한다. 제안한 검정의 특성을 규명하고 검정력 비교를 위해서 모의실험을 수행한다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.115-125
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• 2021

Simulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the "curse of dimensionality" when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm is an advanced stochastic optimization algorithm based on a probability model, which has the potential to deal with high-dimensional optimization problems. Currently, the CE algorithm is still in the theoretical research stage and rarely applied to actual engineering optimization. One reason is that the Monte Carlo (MC) method is used to estimate the high-dimensional integrals in parameter update, leading to a large sample size. This paper proposes an improved CE algorithm based on quasi-Monte Carlo (QMC) estimation using high-dimensional truncated Sobol subsequence, referred to as the QMC-CE algorithm. The optimization performance of the proposed algorithm is better than that of the original CE algorithm. With a set of identical control parameters, the tests on six standard test functions and a hull form optimization problem show that the proposed algorithm not only has faster convergence but can also apply to complex simulation optimization problems.

• 응용통계연구
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• 제21권2호
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• pp.301-312
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• 2008

상호정보(mutual information: MI)는 설명변수의 목적변수에 대한 예측정도를 나타내는 척도로서, 목적변수에 대한 설명 변수의 중요도 순위를 구하거나 목적 변수를 잘 설명해주는 설명변수의 집합을 구하는 변수선택문제에 유용하게 사용된다. 본 논문에서는 연속형 설명변수와 범주형 목적변수로 구성된 데이터로부터 결합확률분포를 추정하지 않고도 MI 추정량을 구할 수 있는 Sample-spacing 방법에 대한 연구를 수행하였다. 몬테 칼로 모의 실험과 실제데이터에 대한 실험결과, MI 추정을 위해 Sample-spacing 방법을 사용할 때 m = 1을 사용하면 충분히 신뢰할만한 결과를 얻을 수 있다는 것을 알 수 있었다.

• 대한수학회지
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• 제33권2호
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• pp.319-332
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• 1996

Many authors have studied multiple stochastic integrals in pursuit of the existence of product processes in terms of multiple integrals. But there has not been much research into the structure of the product processes themselves. In this direction, a study which gives emphasis on sample path continuity and boundedness properties was initiated in Pyke[9]. For details of problem set-ups and necessary notations, see [9]. Recently the weak limits of U-processes are shown to be chaos processes, which is product of the same Brownian measures, see [2] and [7].