• 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.

• Korean Journal of Cognitive Science
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• v.10 no.3
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• pp.77-83
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• 1999

With a surge of interest in OCR in 1990s a large number of handwriting or h handprinting databases have been built one after another around the world. One problem that researches encounter today is that all the databases differ in various ways including the script qualities. This paper proposes a method for measuring handwriting qualities that can be used for comparison of databases and objective test for character recognizers. The key idea i involved is classifying character samples into a number of groups each characterizing a set of qualities. In order to evaluate the proposed method we carried out experiments on KU-1 database. The result we achieve is meaningful and the method is helpful for the target tasks.

• Advances in nano research
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• v.12 no.2
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• pp.223-239
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• 2022

Object detection has always been to pursue objects with particular properties or representations and to predict details on objects including the positions, sizes and angle of rotation in the current picture. This was a very important subject of computer vision science. While vision-based object tracking strategies for the analysis of competitive videos have been developed, it is still difficult to accurately identify and position a speedy small ball. In this study, deep learning (DP) network was developed to face these obstacles in the study of tennis motion tracking from a complex perspective to understand the performance of athletes. This research has used CNN-VGG 16 to tracking the tennis ball from broadcasting videos while their images are distorted, thin and often invisible not only to identify the image of the ball from a single frame, but also to learn patterns from consecutive frames, then VGG 16 takes images with 640 to 360 sizes to locate the ball and obtain high accuracy in public videos. VGG 16 tests 99.6%, 96.63%, and 99.5%, respectively, of accuracy. In order to avoid overfitting, 9 additional videos and a subset of the previous dataset are partly labelled for the 10-fold cross-validation. The results show that CNN-VGG 16 outperforms the standard approach by a wide margin and provides excellent ball tracking performance.

• Journal of Magnetics
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• v.18 no.4
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• pp.405-411
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• 2013

The structural, magnetic and magnetocaloric properties of $CoMn_{1-x}Cr_xGe$ (x=0.05-0.125) have been investigated by using electron microscopy, x-ray diffraction, calorimetric and magnetic measurements. In this study, our aim is to justify the magnetocaloric effect by tuning the structural and magnetic transition temperature with Cr doping on CoMnGe pure system. The substitution of Cr for Mn leads to a decrease of both structural and magnetic transition temperatures. However, structural and magnetic transition temperatures do not close to each other. From magnetization measurement, we calculate that isothermal entropy change associated with magnetic transition can be as high as 3.82 J $kg^{-1}K^{-1}$ at 302 K in a field of 7 T. Meanwhile, structural phase transition contribution to isothermal entropy change is calculated as 5.85 J $kg^{-1}K^{-1}$ at 322 K for 7 T.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.105-114
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• 2018

Various data analysis methods used for customer type analysis are very important for game companies to understand their type and characteristics in an attempt to plan customized content for our customers and to provide more convenient services. In this paper, we propose a k-mode cluster analysis algorithm that uses information uncertainty by extending information entropy to reduce information loss. Therefore, the measurement of the similarity of attributes is considered in two aspects. One is to measure the uncertainty between each attribute on the center of each partition and the other is to measure the uncertainty about the probability distribution of the uncertainty of each property. In particular, the uncertainty in attributes is taken into account in the non-probabilistic and probabilistic scales because the entropy of the attribute is transformed into probabilistic information to measure the uncertainty. The accuracy of the algorithm is observable to the result of cluster analysis based on the optimal initial value through extensive performance analysis and various indexes.

• Korean Journal of Food Science and Technology
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• v.22 no.1
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• pp.1-6
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• 1990

The thermal diffusivity of defatted and nondefatted starches were measured on the basis of one dimensional semi-infinitive theory. Differential scanning calorymetry was used to study the effects of cooling rate, fat and water contents on the enthalpy and entropy changes with the cooling rate of $-2.5{\sim}10^{\circ}C/min$. Thermal diffusivity of defatted and nondefatted straches were determined to be $4.14{\times}10^{-4}{\sim}4.96{\times}10^{-4}(m^2/h),\;4.09{\times}10^{-4}{\sim}4.81{\times}10^{-4}(m^2/h)$ in unfrozen state, and $2.78{\times}10^{-3}{\sim}3.91{\times}10^{-3}(m^2/h),\;2.26{\times}10^{-3}{\sim}3.57{\times}1-^{-3}(m^2/h)$ in frozen state respectively. On decreasing temperatures in frozen state, thermal diffusivities of starches were increased and entropy and enthalpy were decreased, and more rapid cooling rates resulted in a decrease in entropy. A linear relation was observed between enthropy, enthaly and water content. Thermal diffusivity was decreased, and entropy was increasing fat content. With water content ranging from 35 to 90%, enthalpy and entropy of straches were found to be $107{\sim}216 (kcal /moi),\;0.45{\sim}0.94(kcal/mol.\;K)$, respectively.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.6
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• pp.34-51
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• 2008

Today, the Internet is a part of our life. For that reason, we regard revealing characteristics of Internet traffic as an important research theme. However, Internet traffic cannot be easily manipulated because it usually occupy huge capacity. This problem is a serious obstacle to analyze Internet traffic. Many researchers use various sampling techniques to reduce capacity of Internet traffic. In this paper, we compare several famous sampling techniques, and propose efficient sampling scheme. We chose some sampling techniques such as Systematic Sampling, Simple Random Sampling and Stratified Sampling with some sampling intensities such as 1/10, 1/100 and 1/1000. Our observation focused on Traffic Volume, Entropy Analysis and Packet Size Analysis. Both the simple random sampling and the count-based systematic sampling is proper to general case. On the other hand, time-based systematic sampling exhibits relatively bad results. The stratified sampling on Transport Layer Protocols, e.g.. TCP, UDP and so on, shows superior results. Our analysis results suggest that efficient sampling techniques satisfactorily maintain variation of traffic stream according to time change. The entropy analysis endures various sampling techniques well and fits detecting anomalous traffic. We found that a traffic volume diminishment caused by bottleneck could induce wrong results on the entropy analysis. We discovered that Packet Size Distribution perfectly tolerate any packet sampling techniques and intensities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2809-2817
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• 2010

The scholarly concern of train industry has been improved, since country focuses on this field. Especially, train maintenance facility has been studied for construction, because the facility is important to inspect the train that transports passenger and cargo. Various operation plans and criteria are considered to build train maintenance facility. In this paper, the decision making of train maintenance facility for construction is studied and analyzed with simulation, because mathematical theory is restricted to consider various operation plans and criteria. Through simulation, we analyze warm-up after selecting dependent factors, and extract data. The data is used to select a alternative in this problem, Multiple Attribute Decision Making(MADM). Previous study is difficult, complex and subjective for decision making. However, entropy measurement we used help decision maker for decision making, easily, simply, and objectively. This method can have decision maker choose the best alternative in case the train maintenance facility construction is fast revitalized.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.257-264
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• 2014

This paper presents the core competencies diagnosis system which targeted our collegiate students in an attempt to induce the core competencies for reinforcing the learning and employment capabilities. Because these days data give rise to a high level of redundancy and dimensionality with time complexity, they are more likely to have spurious relationships, and even the weakest relationships will be highly significant by any statistical test. So as to address the measurement of uncertainties from the classification of categorical data and the implementation of its analytic system, an uncertainty measure of rough entropy and information entropy is defined so that similar behaviors analysis is carried out and the clustering ability is demonstrated in the comparison with the statistical approach. Because the acquired and necessary competencies of the collegiate is deduced by way of the results of the diagnosis, i.e. common core competencies and major core competencies, they facilitate not only the collegiate life and the employment capability reinforcement but also the revitalization of employment and the adjustment to college life.