• Biomaterials and Biomechanics in Bioengineering
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• v.2 no.2
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• pp.97-109
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• 2015

A series of amphiphilic graft copolymers were synthesized by varying the number of graft chains and graft chain lengths. The polarity of the hydrophobic graft chain on the copolymers was varied their solution properties. The glass transition temperature of the copolymers was in the low-temperature region, because of the amorphous nature of poly (trimethylene carbonate) (PTMC). The surface morphology of the lyophilized colloid gel had a bundle structure, which was derived from the combination of poly(N-hydroxyethylacrylamide)( poly(HEAA)) and PTMC. The solution properties were evaluated using dynamic light scattering and fluorescence measurements. The particle size of the graft copolymers was about 30-300 nm. The graft copolymers with a higher number of repeating units attributed to the TMC (trimethylene carbonate) component and with a lower macromonomer ratio showed high thermal stability. The critical association concentration was estimated to be between $2.2{\times}10^{-3}$ and $8.9{\times}10^{-2}mg/mL$, using the pyrene-based fluorescence probe technique. These results showed that the hydrophobic chain of the graft copolymer having a long PTMC segment had a low polarity, dependent on the number of repeating units of TMC and the macromonomer composition ratio. These results demonstrated that a higher number of repeating units of TMC, with a lower macromonomer composition, was preferable for molecular encapsulation.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.2
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• pp.85-91
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• 2016

The most important factor in the structural design of ships and offshore structures operating in arctic region is ice load, which results from ice-structure interaction during the ice collision process. The mechanical properties of ice related to strength and failure, however, show very complicated aspect varying with temperature, volume fraction of brine, grain size, strain rate and etc. So it is nearly impossible to establish a perfect material model of ice satisfying all the mechanical characteristics completely. Therefore, in general, ice collision analysis was carried out by relatively simple material models considering only specific aspects of mechanical characteristics of ice and it would be the most significant cause of inevitable errors in the analysis. Especially, it is well-known that the most distinctive mechanical property of ice is high dependency on strain rate. Ice shows brittle attribute in higher strain rate while it becomes ductile in lower strain rate range. In this study, the simulation method of ice collision to ship hull using the nonlinear dynamic FE analysis was dealt with. To consider the strain rate effects of ice during ice-structural interaction, strain rate dependent constitutive model in which yield stress and hardening behaviors vary with strain rate was adopted. To reduce the huge amount of computing time, the modeling range of ice and ship structure were restricted to the confined region of interest. Under the various scenario of ice-ship hull collision, the structural behavior of hull panels and failure modes of ice were examined by nonlinear FE analysis technique.

• Tribology and Lubricants
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• v.37 no.4
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• pp.144-150
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• 2021

The most cost-effective method of reducing abrasive wear in mechanical parts is increasing their hardness with thin hard coatings. In practice, the composite hardness of the coated substrate is more important than that of the substrate or coating. After full unloading of the load applied to an indenter, its indentation hardness evaluated based on the dent created on the test piece was almost dependent on plastic deformation of the substrate. Following the first part of this study, which proposes a new Brinell hardness test method for a coated surface, the remainder of the study is focused on practical application of the method. Indentation analyses of a rigid sphere and elastic-perfect plastic materials were performed using finite element analysis software. The maximum principal stress and plastic strain distributions as well as the dent shapes according to the substrate yield stress and coating thickness were compared. The substrate yield stress had a significant effect on the dent size, which in turn determines the Brinell hardness. In particular, plastic deformation of the substrate produced dents regardless of the state of the coating layer. The hardness increase by coating behaved differently depending on the substrate yield stress, coating thickness, and indentation load. These results are expected to be useful when evaluating the composite hardness values of various coated friction surfaces.

• Advances in nano research
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• v.7 no.4
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• pp.249-263
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• 2019

In the current paper, an exact solution method is carried out for analyzing the thermo-mechanical vibration of curved FG nano-beams subjected to uniform thermal environmental conditions, by considering porosity distribution via nonlocal strain gradient beam theory for the first time. Nonlocal strain gradient elasticity theory is adopted to consider the size effects in which the stress for not only the nonlocal stress field but also the strain gradients stress field is considered. It is perceived that during manufacturing of functionally graded materials (FGMs) porosities and micro-voids can be occurred inside the material. Material properties of curved porous FG nanobeam are assumed to be temperature-dependent and are supposed to vary through the thickness direction of beam which modeled via modified power-law rule. Since variation of pores along the thickness direction influences the mechanical and physical properties, porosity play a key role in the mechanical response of curved FG nano-structures. The governing equations and related boundary condition of curved porous FG nanobeam under temperature field are derived via the energy method based on Timoshenko beam theory. An analytical Navier solution procedure is utilized to achieve the natural frequencies of porous FG curved nanobeam supposed to thermal loading. The results for simpler states are confirmed with known data in the literature. The effects of various parameters such as nonlocality parameter, porosity volume fractions, thermal effect, gradient index, opening angle and aspect ratio on the natural frequency of curved FG porous nanobeam are successfully discussed. It is concluded that these parameters play key roles on the dynamic behavior of porous FG curved nanobeam. Presented numerical results can serve as benchmarks for future analyses of curve FG nanobeam with porosity phases.

• Advances in nano research
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• v.10 no.5
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• pp.449-460
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• 2021

Flexoelectricity is an interesting materials' property that is more touchable in small scales. This property beside the sandwich structures placed in the center of scientists' attention due to their extraordinary effects on the mechanical properties. Furthermore, in the passage of decades, more elaborated sandwich structures took into consideration results from using honeycomb core. This kind of structure, inspiring from honeycomb core, provides more stiffness to weight ratio, which plays a crucial role in different industries. In this paper, based on the Love-Kirchhoff's hypothesis, Hamilton's principle, modified couple stress theory and Fourier series analytical method, equations of motion for a sandwich plate containing a honeycomb core integrated by two face-sheets have derived and solved analytically. The equations of both face sheets have derived by flexoelectricity consideration. Moreover, it should be noticed that the whole structure rests on the visco-Pasternak foundation. Conducting current research provided an acceptable and throughout study based on flexoelectricity to address the effect of materials' characteristics, length-scale parameter, aspect, and thickness ratios and boundary conditions on the natural frequency of honeycomb sandwich plates. Also, based on the presented figures and tables, there is a close agreement between previous studies and recent work. Due to the high ratio of strength to weight, current model analyzing is capable of taking into account for different vehicles' manufacturing in a high range of industries.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.4
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• pp.333-339
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• 2021

Injection lipolysis or mesotherapy gained popularity for local fat dissolve as an alternative to surgical liposuction. Phosphatidylcholine (PPC) and aminophyl-line (AMPL) are commonly used compounds for mesotherapy, but their efficacy and safety as lipolytic agents have been controversial. Glycerophosphocholine (GPC) is a choline precursor structurally similar to PPC, and thus introduced in aesthetics as an alternative for PPC. This study aimed to evaluate the effects of GPC on adipocytes differentiation and lipolysis and compared those effects with PPC and AMPL using in vitro and in vivo models. Adipogenesis in 3T3-L1 was measured by Oil Red O staining. Lipolysis was assessed by measuring the amount of glycerol released in the culture media. To evaluate the lipolytic activity of GPC on a physiological condition, GPC was subcutaneously injected to one side of inguinal fat pads for 3 days. Lipolytic activity of GPC was assessed by hematoxylin and eosin staining in adipose tissue. GPC significantly suppressed adipocyte differentiation of 3T3-L1 in a concentration-dependent manner (22.3% inhibition at 4 mM of GPC compared to control). Moreover, when lipolysis was assessed by glycerol release in 3T3-L1 adipocytes, 6 mM of GPC stimulated glycerol release by two-fold over control. Subcutaneous injection of GPC into the inguinal fat pad of mice significantly reduced the mass of fat pad and the size of adipocytes of injected site, and these effects of GPC were more prominent over PPC and AMPL. Taken together, these results suggest that GPC is the potential therapeutic agent as a local fat reducer.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05b
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• pp.171-176
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• 1997

UO$_2$-Gd$_2$O$_3$fuel has been sintered to study the effect of powder property and sintering atmospheres on densification and microstructure. Three types of powders have been used; AUC-UO$_2$ powder and ADU-UO$_2$ powder were mixed with Gd$_2$O$_3$ Powder, and co-milled AUC-UO$_2$ and Gd$_2$O$_3$ powder. UO$_2$-(2, 5, 10)wt% Gd$_2$O$_3$pellets have been sintered at 168$0^{\circ}C$ for 4 hours in the mixture of H$_2$ and $CO_2$ gases, of which oxygen potential has been controlled by the ratio of $CO_2$ to H$_2$ gas. Densities of UO$_2$-Gd$_2$O$_3$ fuel pellets are quite dependent on powder types, and UO$_2$-Gd$_2$O$_3$ fuel using co-milled UO$_2$ powder yields the highest density. A long range homogeneity of Gd is determined by powder mixing. As the oxygen potential of sintered atmosphere increases, the sintered densities of UO$_2$-Gd$_2$O$_3$ pellets decrease but grain size increases. In addition, (U, Gd)O$_2$ solid solution becomes more homogeneous. The UO$_2$-Gd$_2$O$_3$fuel having adequate density and homogeneous microstructure can be fabricated by co-milling powder and by high oxygen potential.

• Progress in Medical Physics
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• v.33 no.4
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• pp.63-71
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• 2022

Purpose: To clarify the relationship between the diameter of the simulated bead and the Z-resolution of the tomosynthesis image. Methods: A simulated bead was placed on a 1,024×1,024×1,024-pixel base image. The diameters were set to 0.025, 0.05, 0.1, 0.2, 0.3, 0.7, 1.0, and 1.3 mm. A bead was placed at the center of the base image and projected at a simulated X-ray angle range of ±45° to obtain a projected image. A region of interest was placed at the center of the bead image and the slice sensitivity profile (SSP) was obtained by acquiring pixel values in the z-direction. The full width at half maximum of the SSP was defined as the Z-resolution and the frequency response was obtained by the 1-D Fourier transform of the SSP. Results: Z-resolution increased with increasing bead diameter. However, there was no change in Z-resolution between 0.025 and 0.1 mm. The frequency response was similar to that of the Z-resolution, with a significant difference between 0.1 and 0.2 mm diameter. Conclusions: Z-resolution is dependent on the diameter of the bead, which should be selected considering the pixel size of the tomosynthesis image.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.