• Title, Summary, Keyword: Entropy

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A Study of Pre-service Chemistry Teacher's Understanding on Entropy

  • Seo, Young-Jin;Hong, Hun-Gi
    • Journal of The Korean Association For Science Education
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    • v.32 no.3
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    • pp.415-427
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    • 2012
  • In this study, we conducted preliminary survey, diagnostic test and in-depth interview in order to study Korean pre-service chemistry teachers' understanding on entropy and investigate how Korean pre-service chemistry teachers deal with the natural phenomenon which is related to entropy conceptions. Firstly, as a result of the preliminary survey, it was found that pre-service chemistry teachers strongly recognized entropy as the degree of disorder. Secondly, the diagnostic test showed pre-service chemistry teachers were mostly confused about whether the entropy of the universe increases during a spontaneous change, and they had a tendency to interpret the natural phenomenon related to entropy change as the change of disorder. Finally, during in-depth interview, after we explained entropy change in all diagnostic test questions with the concept of microstate, pre-service chemistry teachers revealed a better understanding about entropy. Through this research, pre-service chemistry teachers had an opportunity to reflect on their deficiencies of entropy conceptions, which will ultimately help students to approach the concept of entropy more correctly.

Improving Sample Entropy Based on Nonparametric Quantile Estimation

  • Park, Sang-Un;Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.457-465
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    • 2011
  • Sample entropy (Vasicek, 1976) has poor performance, and several nonparametric entropy estimators have been proposed as alternatives. In this paper, we consider a piecewise uniform density function based on quantiles, which enables us to evaluate entropy in each interval, and study the poor performance of the sample entropy in terms of the poor estimation of lower and upper quantiles. Then we propose some improved entropy estimators by simply modifying the quantile estimators, and compare their performances with some existing estimators.

Speech Emotion Recognition Based on GMM Using FFT and MFB Spectral Entropy (FFT와 MFB Spectral Entropy를 이용한 GMM 기반의 감정인식)

  • Lee, Woo-Seok;Roh, Yong-Wan;Hong, Hwang-Seok
    • Proceedings of the KIEE Conference
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    • pp.99-100
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    • 2008
  • This paper proposes a Gaussian Mixture Model (GMM) - based speech emotion recognition methods using four feature parameters; 1) Fast Fourier Transform(FFT) spectral entropy, 2) delta FFT spectral entropy, 3) Mel-frequency Filter Bank (MFB) spectral entropy, and 4) delta MFB spectral entropy. In addition, we use four emotions in a speech database including anger, sadness, happiness, and neutrality. We perform speech emotion recognition experiments using each pre-defined emotion and gender. The experimental results show that the proposed emotion recognition using FFT spectral-based entropy and MFB spectral-based entropy performs better than existing emotion recognition based on GMM using energy, Zero Crossing Rate (ZCR), Linear Prediction Coefficient (LPC), and pitch parameters. In experimental Results, we attained a maximum recognition rate of 75.1% when we used MFB spectral entropy and delta MFB spectral entropy.

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Calculation of Data Reliability with Entropy for Fuzzy Sets

  • Wang, Hongmei;Lee, Sang-Hyuk
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.4
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    • pp.269-274
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    • 2009
  • Measuring uncertainty for fuzzy sets has been carried out by calculating fuzzy entropy. Fuzzy entropy of fuzzy set is derived with the help of distance measure. The distance proportional value between the fuzzy set and the corresponding crisp set is designed as the fuzzy entropy. The usefulness is verified by proving the proposed entropy. Generally, fuzzy entropy contains the complementary characteristics that the fuzzy entropies of fuzzy set and complementary fuzzy set have the same entropies. Discrepancy that low fuzzy entropy did not guarantee the data certainty was overcome by modifying fuzzy entropy formulation. Obtained fuzzy entropy is analyzed and discussed through simple example.

Reliability evaluation of water distribution network considering mechanical characteristics using informational entropy

  • Kashani, Mostafa Ghanbari;Hosseini, Mahmood;Aziminejad, Armin
    • Structural Engineering and Mechanics
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    • v.58 no.1
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    • pp.21-38
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    • 2016
  • Many studies have been carried out to investigate the important factors in calculating the realistic entropy amount of water distribution networks, but none of them have considered both mechanical and hydraulic characteristics of the networks. Also, the entropy difference in various networks has not been calculated exactly. Therefore, this study suggested a modified entropy function to calculate the informational entropy of water distribution networks so that the order of demand nodes and entropy difference among various networks could be calculated by taking into account both mechanical and hydraulic characteristics of the network. This modification was performed through defining a coefficient in the entropy function as the amount of outflow at each node to all dissipated power in the network. Hence, a more realistic method for calculating entropy was presented by considering both mechanical and hydraulic characteristics of network while keeping simplicity. The efficiency of the suggested method was evaluated by calculating the entropy of some sample water networks using the modified function.

Similarity Measure Construction with Fuzzy Entropy and Distance Measure

  • Lee Sang-Hyuk
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.4
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    • pp.367-371
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    • 2005
  • The similarity measure is derived using fuzzy entropy and distance measure. By the elations of fuzzy entropy, distance measure, and similarity measure, we first obtain the fuzzy entropy. And with both fuzzy entropy and distance measure, similarity measure is obtained., We verify that the proposed measure become the similarity measure.

A Modi ed Entropy-Based Goodness-of-Fit Tes for Inverse Gaussian Distribution (역가우스분포에 대한 변형된 엔트로피 기반 적합도 검정)

  • Choi, Byung-Jin
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.383-391
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    • 2011
  • This paper presents a modified entropy-based test of fit for the inverse Gaussian distribution. The test is based on the entropy difference of the unknown data-generating distribution and the inverse Gaussian distribution. The entropy difference estimator used as the test statistic is obtained by employing Vasicek's sample entropy as an entropy estimator for the data-generating distribution and the uniformly minimum variance unbiased estimator as an entropy estimator for the inverse Gaussian distribution. The critical values of the test statistic empirically determined are provided in a tabular form. Monte Carlo simulations are performed to compare the proposed test with the previous entropy-based test in terms of power.

An Improved Cross Entropy-Based Frequency-Domain Spectrum Sensing (Cross Entropy 기반의 주파수 영역에서 스펙트럼 센싱 성능 개선)

  • Ahmed, Tasmia;Gu, Junrong;Jang, Sung-Jeen;Kim, Jae-Moung
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.48 no.3
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    • pp.50-59
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    • 2011
  • In this paper, we present a spectrum sensing method by exploiting the relationship of previous and current detected data sets in frequency domain. Most of the traditional spectrum sensing methods only consider the current detected data sets of Primary User (PU). Previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. By considering the relationship of the previous and current spectrum sensing, cross entropy-based spectrum sensing is proposed to detect PU signal more effectively, which has a strengthened performance and is robust. When previous detected signal is noise, the discriminating ability of cross entropy-based spectrum sensing is no better than conventional entropy-based spectrum sensing. To address this problem, we propose an improved cross entropy-based frequency-domain spectrum sensing. Regarding the spectrum sensing scheme, we have derived that the proposed method is superior to the cross entropy-based spectrum sensing. We proceed a comparison of the proposed method with the up-to-date entropy-based spectrum sensing in frequency-domain. The simulation results demonstrate the performance improvement of the proposed spectrum sensing method.

A View on Extension of Utility-Based on Links with Information Measures

  • Hoseinzadeh, A.R.;Borzadaran, G.R.Mohtashami;Yari, G.H.
    • Communications for Statistical Applications and Methods
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    • v.16 no.5
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    • pp.813-820
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    • 2009
  • In this paper, we review the utility-based generalization of the Shannon entropy and Kullback-Leibler information measure as the U-entropy and the U-relative entropy that was introduced by Friedman et al. (2007). Then, we derive some relations between the U-relative entropy and other information measures based on a parametric family of utility functions.

Selection of data set with fuzzy entropy function (퍼지 엔트로피 함수를 이용한 데이터추출)

  • Lee, Sang-Hyuk;Cheon, Seong-Pyo;Kim, Sung-Shin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.349-352
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    • 2004
  • In this literature, the selection of data set among the universe set is carried out with the fuzzy entropy function. By the definition of fuzzy entropy, we have proposed the fuzzy entropy function and the proposed fuzzy entropy function is proved through the definition. The proposed fuzzy entropy function calculate the certainty or uncertainty value of data set, hence we can choose the data set that satisfying certain bound or reference. Therefore the reliable data set can be obtained by the proposed fuzzy entropy function. With the simple example we verify that the proposed fuzzy entropy function select reliable data set.

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