• School Mathematics
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• v.7 no.4
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• pp.445-467
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• 2005

The purpose of this study was to investigate mathematics teaching of an elementary school teacher and to understand the meaning of it. This study was a qualitative case study using by analyzing metaphors. The notion of metaphors was newly set up. Traditionally, it had been regarded as a mere tool for better understanding, but it was recognized as the primary source of all of our concept(Sfard, 1998). The subject of this case study was a researcher 'I' and also an elementary school teacher. The three selves named Mee1, Mee2, Mee3, respectively. Mee1 was the 'I' who developed the 4th graders' activities on mathematical patterns in 1996 and wrote mathematics textbook for the 4th graders in 1998-1999. Mee2 was the 'I' who taught mathematical patterns to her students in 2002. Mee3 was the 'I' who criticized the teaching of Mee2 in 2005. [ADVENTURE], [HIDE-AND-SEEK], and [FIREWORKS DISPLAY] were deter-mined to be key metaphors of mathematics teaching. [ADVENTURE] of Mee] was focused on profound understanding of mathematics, [HIDE-AND-SEEK] of Mee2 on construction of mathematics, and [FIRE-WORKS DISPLAY] of Mee3 on making meaning and participating in communities. Studies of metaphors give us the power of understanding mathematics teaching and also generate it. And viewing mathematics teaching via metaphors makes teaching studies open to new ways.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.19-24
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• 2016

The minimum error entropy (MEE) algorithm is known to be superior in impulsive noise environment. In this paper, the optimum solutions and properties of the MEE algorithm are studied in regard to the robustness against impulsive noise. From the analysis of the behavior of optimum weight and factors related with mitigation of influence from large errors, it is revealed that the magnitude controlled input entropy plays the main role of keeping optimum weight of MEE undisturbed from impulsive noise. In the simulation, the optimum weight of MEE is shown to be the same as that of MSE criterion.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.87-95
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• 2009

As information theoretic learning techniques, error entropy minimization criterion (MEE) and maximum cross correntropy criterion (MCC) have been studied in depth for supervised learning. MEE criterion leads to maximization of information potential and MCC criterion leads to maximization of cross correlation between output and input random processes. The weighted combination scheme of these two criteria, namely, minimization of Error Entropy with Fiducial points (MEEF) has been introduced and developed by many researchers. As an approach to unsupervised, blind channel equalization, we investigate the possibility of applying constant modulus error (CME) to MEE criterion and some problems of the method. Also we study on the application of CME to MEEF for blind equalization and find out that MEE-CME loses the information of the constant modulus. This leads MEE-CME and MEEF-CME not to converge or to converge slower than other algorithms dependent on the constant modulus.

• Journal of the Korean Applied Science and Technology
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• v.37 no.1
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• pp.124-132
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• 2020

The purpose of this study was to investigate the biological activities such as cytotoxicity and anti-inflammation using Manjakani (Quercus infectoria Olivier) extract. Manjakani was extracted from hot DW and 80% ethanol. Cell viability was assessed using MTT assay on RAW 264.7 cells. Also, anti-inflammatory activities were measured through changes in the levels of nitric oxide (NO), prostaglandin E₂ (PGE₂), leukotrien B4 (LTB₄), pro-inflammatory cytokines (IL-1β, IL-6 and tumor necrosis factor (TNF)-α) and transcription factor on LPS-induced RAW264.7 cells. The results confirmed that significant cytotoxicity does not appear in the concentration range of 1, 5, and 10 ㎍/㎖ of both extracts of this study. The production of NO was slowed by approximately MDE 37.2% and MEE 43.7% at 10 ㎍/㎖ concentration. Also, level of PGE₂ and LTB₄ was decreased MDE 30.9%/MEE 43.7% and MDE 37.1%/MEE 43.7%. In the case of inflammatory cytokine was reduced to MDE 38.8%/MEE 50.8% for IL-1β, MDE 35.0%/MEE 44.2% for IL-6 and MDE 31.9%/MEE 36.6% for TNF-α at 10 ㎍/㎖ concentration. The mRNA expression of NF-κB, iNOS and COX-2 significantly decreased by MDE 44.0%/MEE 16.0%, MDE 44.0%/MEE 55.0% and MDE 45.0%/MEE 40.0%, respectively, following the 10 ㎍/mL sample treatment when compared to the control. Both extracts were effective in anti-inflammatory activity. In addition, both extracts showed efficient changes of production of NO, PGE₂, LTB₄, pro-inflammatory cytokines and transcription factor. But MEE was found to have a higher inhibitory effect than MDE. In other words, Manjakani was showed significant biological activities showing anti-inflammation without cytotoxicity. These results will be provided as fundamental data for further development of the new health food and therapeutics related to the results above.

• Structural Engineering and Mechanics
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• v.63 no.4
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• pp.481-495
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• 2017

The present article examines the static response of multilayered magneto-electro-elastic (MEE) beam in thermal environment through finite element (FE) methods. On the basis of the minimum total potential energy principle and the coupled constitutive equations of MEE material, the FE equilibrium equations of cantilever MEE beam is derived. Maxwell's equations are considered to establish the relation between electric field and electric potential; magnetic field and magnetic potential. A simple condensation approach is employed to solve the global FE equilibrium equations. Further, numerical evaluations are made to examine the influence of different in-plane and through-thickness temperature distributions on the multiphysics response of MEE beam. A parametric study is performed to evaluate the effect of stacking sequence and different temperature profiles on the direct and derived quantities of MEE beam. It is believed that the results presented in this article serve as a benchmark for accurate design and analysis of the MEE smart structures in thermal applications.

• Coupled systems mechanics
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• v.6 no.4
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• pp.465-485
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• 2017

In this paper, free vibration and static response of magneto-electro-elastic (MEE) beams has been investigated. To this end, a 3D finite element formulation has been derived by minimization the total potential energy and linear constitutive equation. The coupling between elastic, electric and magnetic fields can have a significant influence on the stiffness and in turn on the static behaviour of MEE beam. Further, different Barium Titanate ($BaTiO_3$) and Cobalt Ferric oxide ($CoFe_2O_4$) volume fractions results in indifferent coupled response. Therefore, through the numerical examples the influence of volume fractions and boundary conditions on the natural frequencies of MEE beam is illustrated. The study is extended to evaluate the static response of MEE beam under various forms of mechanical loading. It is seen from the numerical evaluation that the volume fractions, loading and boundary conditions have a significant effect on the structural behaviour of MEE structures. The observations made here may serve as benchmark solutions in the optimum design of MEE structures.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.27-33
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• 2011

For compensation of channel distortion from multipath fading and impulsive noise, a decision feedback equalizer (DFE) algorithm based on minimization of Error entropy (MEE) is proposed. The MEE criterion has not been studied for DFE structures and impulsive noise environments either. By minimizing the error entropy with respect to equalizer weight based on decision feedback structures, the proposed decision feedback algorithm has shown to have superior capability of residual intersymbol interference cancellation in simulation environments with severe multipath and impulsive noise.

• Structural Engineering and Mechanics
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• v.62 no.5
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• pp.519-535
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• 2017

In this article, static analysis of a magneto-electro-elastic (MEE) beam subjected to various thermal loading and boundary conditions has been investigated. Influence of pyroeffects (pyroelectric and pyromagnetic) on the direct quantities (displacements and the potentials) of the MEE beam under different boundary conditions is studied. The finite element (FE) formulation of the MEE beam is developed using the total potential energy principle and the constitutive equations of the MEE material taking into account the coupling between elastic, electric, magnetic and thermal properties. Using the Maxwell electrostatic and electromagnetic relations, variation of stresses, displacements, electric and magnetic potentials along the length of the MEE beam are investigated. Effect of volume fractions, aspect ratio and boundary conditions on the direct quantities in thermal environment has been determined. The present investigation may be useful in design and analysis of magnetoelectroelastic smart structures and sensor applications.

• Applied Science and Convergence Technology
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• v.24 no.3
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• pp.67-71
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• 2015

InP/InGaP quantum structures (QSs) were grown on GaAs (001) substrates by a migration-enhanced molecular beam epitaxy method. Temperature-dependent photoluminescence (PL) and emission wavelength-dependent time-resolved PL (TRPL) were performed to investigate the optical properties of InP/InGaP QSs as a function of migration enhanced epitaxy (MEE) growth cycles from 2 to 8. One cycle for the growth of InP QS consists of 2-s In and 2-s P supply with an interruption time of 10 s after each source supply. As the MEE growth cycle increases from 2 to 8, the PL peak is redshifted and exhibited different (larger, comparable, or smaller) bandgap shrinkages with increasing temperature compared to that of bulk InP. The PL decay becomes faster with increasing MEE cycles while the PL decay time increases with increasing emission wavelength. These PL and TRPL results are attributed to the different QS density and size/shape caused by the MEE repetition cycles. Therefore, the size and density of InP QSs can be controlled by changing the MEE growth cycles.

• Advances in nano research
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• v.12 no.1
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• pp.81-99
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• 2022

The aim of current work is to evaluate thermo-electrical characteristics of graphene nanoplatelets Reinforced Composite (GNPRC) coupled with magneto-electro-elastic (MEE) face sheet. In this regard, a cylindrical smart nanocomposite made of GNPRC with an external MEE layer is considered. The bonding between the layers are assumed to be perfect. Because of the layer nature of the structure, the material characteristics of the whole structure is regarded as graded. Both mechanical and thermal boundary conditions are applied to this structure. The main objective of this work is to determine critical temperature and critical voltage as a function of thermal condition, support type, GNP weight fraction, and MEE thickness. The governing equation of the multilayer nanocomposites cylindrical shell is derived. The generalized differential quadrature method (GDQM) is employed to numerically solve the differential equations. This method is integrated with Deep Learning Network (DNN) with ADADELTA optimizer to determine the critical conditions of the current sandwich structure. This the first time that effects of several conditions including surrounding temperature, MEE layer thickness, and pattern of the layers of the GNPRC is investigated on two main parameters critical temperature and critical voltage of the nanostructure. Furthermore, Maxwell equation is derived for modeling of the MEE. The outcome reveals that MEE layer, temperature change, GNP weight function, and GNP distribution patterns GNP weight function have significant influence on the critical temperature and voltage of cylindrical shell made from GNP nanocomposites core with MEE face sheet on outer of the shell.