• Electronic Materials Letters
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• v.14 no.6
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• pp.774-783
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• 2018

Full maximum-entropy mobility-spectrum analysis (FMEMSA) is the best algorithm among mobility spectrum analyses by which we can obtain a set of partial-conductivities associated with mobility values (mobility spectrum) by analyzing magnetic-field-dependent conductivity-tensors. However, it is restricted to a direct band-gap semiconductor and should be modified for materials with other band structures. We developed the modified version of FMEMSA which is appropriate for a material with a single anisotropic valley, or an indirect-band-gap semiconductor quantum-well with a single non-degenerate conduction-band valley e.g., (110)-oriented AlAs quantum wells with a single anisotropic valley. To demonstrate the reliability of the modified version, we applied it to several sets of synthetic measurement datasets. The results demonstrated that, unlike existing FMEMSA, the modified version could produce accurate mobility spectra of materials with a single anisotropic valley.

• Water Engineering Research
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• v.1 no.2
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• pp.95-105
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• 2000

A method is presented which enables easily the computation of the suspended sediment discharge as the mean sediment concentration and mean flow velocity. This method has significant advantages over the traditional method, which principally depend on a set of measured concentration data. The method is based on both a new sediment concentration and mean sediment concentration equations which have been derived from the entropy concept used in statistical mechanics and information theory: (1) The sediment concentration distribution equations derived, are capable of describing the variation of the concentration in the vertical direction. (2) The mean concentration equation derived, is capable of calculating easily the mean concentration by using only one measured concentration in open channel. The present study mainly addresses the following two subjects : (1) new sediment concentration and mean sediment concentration equations are derived from the entropy concept : (2) An efficient and useful method of suspended sediment-discharge measurements is developed which can facilitate the estimation of suspended sediment-discharge in open channel. Flume and laboratory data are used to carry out the research task outlined above. An efficient method for determining the suspended sediment-discharge in the open channel has been developed. The method presented also is efficient and applicable in estimating the sediment transport in rivers and the sediment deposit in the reservoirs, and can drastically reduce the time and cost of sediment measurements.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.391-411
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• 2023

Aggregates play the skeleton and supporting role in the construction field, high-precision measurement and high-efficiency analysis of aggregates are frequently employed to evaluate the project quality. Aiming at the unbalanced operation time and segmentation accuracy for multi-class segmentation algorithms of aggregate images, a Chaotic Sparrow Search Algorithm (CSSA) is put forward to optimize it. In this algorithm, the chaotic map is combined with the sinusoidal dynamic weight and the elite mutation strategies; and it is firstly proposed to promote the SSA's optimization accuracy and stability without reducing the SSA's speed. The CSSA is utilized to optimize the popular multi-class segmentation algorithm-Multiple Entropy Thresholding (MET). By taking three METs as objective functions, i.e., Kapur Entropy, Minimum-cross Entropy and Renyi Entropy, the CSSA is implemented to quickly and automatically calculate the extreme value of the function and get the corresponding correct thresholds. The image adaptive multi-class segmentation model is called CSSA-MET. In order to comprehensively evaluate it, a new parameter I based on the segmentation accuracy and processing speed is constructed. The results reveal that the CSSA outperforms the other seven methods of optimization performance, as well as the quality evaluation of aggregate images segmented by the CSSA-MET, and the speed and accuracy are balanced. In particular, the highest I value can be obtained when the CSSA is applied to optimize the Renyi Entropy, which indicates that this combination is more suitable for segmenting the aggregate images.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.318-320
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• 2017

본 연구는 리튬이온 배터리의 엔트로피를 측정하는 방법인 ETM(Electro Thermodynamics Measurement)을 상용 장비에 적용하는 방법에 관한 것이다. 그리고 엔트로피 측정에 필요한 온도변경시간과 배터리의 relaxation 시간을 최소화함으로써, 측정의 정확성을 유지하면서 측정 시간을 최소화 했다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.1
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• pp.154-159
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• 2008

This study proposes how to decide mean velocity which is one of the very important and efficient discharge measurement in water resources area. In order to achieve this goal, Chiu's velocity distribution equation recently developed from the probability and entropy concepts is used to establish, analyze and compare a linkage between the mean velocity obtained from the Manning's equation which is well known in the world. Besides, it becomes clear that a channel cross section also has a propensity to establish and maintain an equilibrium state that can be measured and classified by a function of entropy M, ratio of mean and maximum velocities irrespective of including sediment or varied channel slope. Therefore, The linkage to be established in this study can be used to compute the cross sectional velocity distribution with the maximum velocity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.107-113
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• 2014

The derivation of optimal information from decision table is based on the concept of indiscernibility relation and approximation space in rough set. Because decision table is more likely to be susceptible to the superposition or inconsistency in decision table, the reduction of attributes is a important concept in knowledge representation. While complete subsets of the attribute's domain is considered in algebraic definition, incomplete subsets of the attribute's domain is considered in information-theoretic definition. Therefore there is a marked difference between algebraic and information-theoretic definition. This paper proposes a conditional entropy using rough set as information theoretical measures in order to deduct the optimal information which may contain condition attributes and decision attribute of information system and shows its effectiveness.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.307-314
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• 2017

Terrain referenced navigation(TRN) system is an attractive method for obtaining position based on terrain measurements and a terrain map. We focus on TRN systems based on the point mass filter(PMF) which is one of the recursive Bayesian method. In this paper, we propose two kinds of performance index for Bayesian filter. The proposed indices are based on entropy and mutual information from information theory. The first index measures roughness of terrain based on entropy of likelihood. The second index named by information gain, which is the mutual information between priori and posteriori distribution, is a quantity of information gained by updating measurement at each step. The proposed two indices are used to determine whether the solution from TRN is adequate for TRN/INS integration or not, and this scheme gives the performance improvement. Simulation result shows that the proposed indices are meaningful and the proposed algorithm performs better than normal TRN algorithm.

• Metals and materials international
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• v.24 no.6
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• pp.1285-1292
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• 2018

Microstructural properties of as-grown and annealed CoCrFeMnNi high entropy alloy (HEA) oxynitride thin films were investigated. The CoCrFeMnNi HEA oxynitride thin film was grown by magnetron sputtering method using an air gas, and annealed under the argon plus air flow for 5 h at $800^{\circ}C$. The as-grown film was homogeneous and uniform composed of nanometer-sized crystalline regions mixed with amorphous-like phase. The crystalline phase in the as-grown film was face centered cubic structure with the lattice constant of 0.4242 nm. Significant microstructural changes were observed after the annealing process. First, it was fully recrystallized and grain growth happened. Second, Ni-rich region was observed in nanometer-scale range. Third, phase change happened and it was determined to be $Fe_3O_4$ spinel structure with the lattice constant of 0.8326 nm. Hardness and Young's modulus of the as-grown film were 4.1 and 150.5 GPa, while those were 9.4 and 156.4 GPa for the annealed film, respectively.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.661-672
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• 2008

In this paper an algorithm, based on extracting a certain target of an image, is proposed that is capable of performing bilevel thresholding of image with multimodal distribution. Each pixel in the image has a membership value which is used to denote the characteristic relationship between the pixel and its belonging region (i.e. the object or background). Using the membership values of image set, a new measurement, which simultaneously measures the measure of fuzziness and the conditional entropy of the image, is calculated. Then, thresholds are found by optimally minimizing calculated measurement. In addition, a fuzzy range is defined to improve the threshold values. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively extract the meaningful target from the input image. The resulting image can preserve the object region we target very well.