• Journal of Electrochemical Science and Technology
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• v.12 no.1
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• pp.112-125
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• 2021

The new emerging "High entropy materials" attract the attention of the scientific society because of their simpler structure and spectacular applications in many fields. A novel nanocrystalline high entropy (Be,Mg,Ca,Sr,Zn,Ni)3O4 oxide has been successfully synthesized through mechanochemical treatment followed by sintering and air quenching. The present research work focuses on the possibility of single-phase formation in the aforementioned high entropy oxide despite the great difference in the atomic sizes of reactant alkaline earth and 3d transition metal oxides. Structural properties of (Be,Mg,Ca,Sr,Zn,Ni)3O4 high entropy oxide were explored by confirmation of its single-phase Fd-3m spinel structure by x-ray diffraction (XRD). Further, nanocrystalline nature and morphology were analyzed by scanning electron microscopy (SEM). Among thermal properties, thermogravimetric analysis (TGA) revealed that the (Be,Mg,Ca,Sr,Zn,Ni)3O4 high entropy oxide is thermally stable up to a temperature of 1200℃. Whereas phase evolution in (Be,Mg,Ca,Sr,Zn,Ni)3O4 high entropy oxide before and after sintering was analyzed through differential scanning calorimetry (DSC). Electrochemical studies of (Be,Mg,Ca,Sr,Zn,Ni)3O4 high entropy oxide consists of a comparison of thermodynamic and kinetic parameters of water and hydrazine hydrate oxidation. Values of activation energy for water oxidation (9.31 kJ mol-1) and hydrazine hydrate oxidation (13.93 kJ mol-1) reveal that (Be,Mg,Ca,Sr,Zn,Ni)3O4 high entropy oxide is catalytically more active towards water oxidation as compared to that of hydrazine hydrate oxidation. Electrochemical impedance spectroscopy is also performed to get insight into the kinetics of both types of reactions.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.219-220
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• 2002

To establish a thermodynamic basis for degradation, a hypothesis was made on the potential correlation between entropy and degradation for wear of machinery components. This paper reports an experimental study of wear of model machinery component pairs, on an accelerated testing basis. Measured were wear, friction, temperatures, and entropy flow. Results show a strong correlation between the referenced wear and the production of entropy flow. The hypothesis linking wear to entropy led to formulations consistent with the Archard/Holm wear law.

• Journal of the Korean Mathematical Society
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• v.50 no.4
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• pp.879-897
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• 2013

Shannon entropy is one of the widely used randomness measures especially for cryptographic applications. However, the conventional entropy tests are less sensitive to the inter-bit dependency in random samples. In this paper, we propose new online randomness test schemes for true random number generators (TRNGs) based on the mutual information between consecutive ${\kappa}$-bit output blocks for testing of inter-bit dependency in random samples. By estimating the block entropies of distinct lengths at the same time, it is possible to measure the mutual information, which is closely related to the amount of the statistical dependency between two consecutive data blocks. In addition, we propose a new estimation method for entropies, which accumulates intermediate values of the number of frequencies. The proposed method can estimate entropy with less samples than Maurer-Coron type entropy test can. By numerical simulations, it is shown that the new proposed scheme can be used as a reliable online entropy estimator for TRNGs used by cryptographic modules.

• Bulletin of the Korean Chemical Society
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• v.29 no.5
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• pp.1051-1054
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• 2008

The entropy production in a non-equilibrium state based on the reversible Oregonator model of the Belousov-Zhabotinskii (BZ) reaction system has been studied. The reaction affinity and the reaction rate for the individual steps have been calculated by varying the concentrations of key variables in the system. The result shows a linear relationship between the reaction affinity and the reaction rate in the given concentration range. However, the overall entropy calculated on the basic assumption that the entropy in a reaction system corresponds to the summation of a product of reaction affinity and reaction rate of individual steps shows a nonlinearity of the reaction system. The results well agrees with the fact that the entropy production is not linear or complicated function in a non-linear reaction system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3118-3126
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• 1994

This paper describes the use of the concept of (relative) entropy for effective characterization of the amplitude and the frequency distributions of the surface profile formed in machining operation. For this purpose, a theoretical model for surface texture formation in turning operation is developed first. Then, the concept of (relative) entropy is reviewed and its effectiveness is examined based on the simulation and experimental results. The results also suggest that under random tool vibration the effect of the geometrical factors on the surface texture formation can be successfully decomposed and therefore, identified by applying the concept of (relative) entropy.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.59-60
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• 2007

Entropy, one of leading metrics on anomalous traffic, attracts researcher's attention since a packet sampling and a traffic volume impact little on entropy value. In this paper, we apply the entropy metric to a domestic network traffic trace which has real anomalous traffics. We used source IP address/port and destination IP address/port that are important attributes of a packet as entropy variable We found that entropy value of multiple-port DoS attack shows something related to a staircase fashion. Also, we show a Possibility of detection of anomalous traffic on small time scale.

• Communications for Statistical Applications and Methods
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• v.27 no.4
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• pp.469-486
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• 2020

Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

• Journal of Environmental Science International
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• v.22 no.11
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• pp.1473-1479
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• 2013

Entropy is a measure of disorder or uncertainty. This terminology is qualitatively used in the understanding of its correlation to pollution in the environmental area. In this research, three different entropies were defined and characterized in order to quantify the qualitative entropy previously used in the environmental science. We are dealing with newly defined distinct entropies $E_1$, $E_2$, and $E_3$ originated from Shannon entropy in the information theory, reflecting concentration of three major green house gases $CO_2$, $N_2O$ and $CH_4$ represented as the probability variables. First, $E_1$ is to evaluate the total amount of entropy from concentration difference of each green house gas with respect to three periods, due to industrial revolution, post-industrial revolution, and information revolution, respectively. Next, $E_2$ is to evaluate the entropy reflecting the increasing of the logarithm base along with the accumulated time unit. Lastly, $E_3$ is to evaluate the entropy with a fixed logarithm base by 2 depending on the time. Analytical results are as follows. $E_1$ shows the degree of prediction reliability with respect to variation of green house gases. As $E_1$ increased, the concentration variation becomes stabilized, so that it follows from linear correlation. $E_2$ is a valid indicator for the mutual comparison of those green house gases. Although $E_3$ locally varies within specific periods, it eventually follows a logarithmic curve like a similar pattern observed in thermodynamic entropy.

• Journal of the Korean Chemical Society
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• v.53 no.1
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• pp.62-72
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• 2009

In this study, entropy definition and explanation in twelve general chemistry textbooks published in USA including what Korean universities select are analyzed. Analysis consists of two parts. One is diachronic analysis which focuses on the change between editions of same authors and the other is contents analysis composed of three sections‐ disorder in entropy definition and explanation, microstates number in entropy definition and explanation, possibility of alternative conception in learning statistical entropy and thermal entropy. As a result, the definition that entropy is the measure of disorder is denied and explanation using microstates number is introduced. Also, caution for the possibility of alternative conception that there are two different entropies is found. Reflecting the change in entropy explanation on new chemistry curriculum and reeducating teachers are meaningful on improvement of Korean chemistry education.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.22-29
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• 2010

A real-time detection and tracking of moving objects in video sequences is very important for smart surveillance systems. In this paper, we propose a novel algorithm for the detection of moving objects that is the entropy-based adaptive Gaussian mixture model (AGMM). First, the increment of entropy generally means the increment of complexity, and objects in unstable conditions cause higher entropy variations. Hence, if we apply these properties to the motion segmentation, pixels with large changes in entropy in moments have a higher chance in belonging to moving objects. Therefore, we apply the Clausius entropy theory to convert the pixel value in an image domain into the amount of energy change in an entropy domain. Second, we use an adaptive background subtraction method to detect moving objects. This models entropy variations from backgrounds as a mixture of Gaussians. Experiment results demonstrate that our method can detect motion object effectively and reliably.