• Advances in nano research
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• v.17 no.2
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• pp.181-195
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• 2024

This study introduces a novel functionally graded material model, termed the "Coated Functionally Graded Graphene-Reinforced Composite (FG GRC)" model, for investigating the free vibration response of plates, highlighting its potential to advance the understanding and application of material property variations in structural engineering. Two types of coated FG GRC plates are examined: Hardcore and Softcore, and five distribution patterns are proposed, namely FG-A, FG-B, FG-C, FG-D, and FG-E. A modified displacement field is proposed based on the higher-order shear deformation theory, effectively reducing the number of variables from five to four while accurately accounting for shear deformation effects. To solve the equations of motion, an analytical solution based on the Galerkin approach was developed for FG GRC plates resting on a viscoelastic Winkler/Pasternak foundation, applicable to various boundary conditions. A comprehensive parametric analysis elucidates the impact of multiple factors on the fundamental frequencies. These factors encompass the types and distribution patterns of the coated FG GRC plates, gradient material distribution, porosities, nonlocal length scale parameter, gradient material scale parameter, nanoplate geometry, and variations in the elastic foundation. Our theoretical research aims to overcome the inherent challenges in modeling structures, providing a robust alternative to experimental analyses of the mechanical behavior of complex structures.

• Journal of Microbiology and Biotechnology
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• v.34 no.8
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• pp.1580-1591
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• 2024

Menopause is induced by spontaneous ovarian failure and leads to life quality deterioration with various irritating symptoms. Hormonal treatment can alleviate these symptoms, but long-term treatment is closely associated with breast and uterine cancer, and stroke. Therefore, developing alternative therapies with novel anti-menopausal substances and improved safety is needed. In our study, heat-killed Bifidobacterium breve HDB7040 significantly promoted MCF-7 cell proliferation in a dose-dependent manner under estrogen-free conditions, similar to 17β-estradiol. This strain also triggered ESR2 expression, but not ESR1, in MCF-7 cells. Moreover, administrating HDB7040 to ovariectomized (OVX) Sprague-Dawley (SD) female rats reduced estrogen deficiency-induced weight gain, fat mass, blood triglyceride, and total cholesterol levels. It also recovered collapsed trabecular microstructure by improving trabecular morphometric parameters (bone mineral density, bone volume per tissue volume, trabecular number, and trabecular separation) and decreasing blood alkaline phosphatase levels with no significant changes in uterine size and blood estradiol. HDB7040 also significantly regulated the expression of Tff1, Pgr, and Esr2, but not Esr1 in uteri of OVX rats. Heat-killed B. breve HDB7040 exerts an anti-menopausal effect via the specific regulation of ERβ in vitro and in vivo, suggesting its potential as a novel substance for improving and treating menopausal syndrome.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.4
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• pp.127-135
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• 2006

In this study, steel deck bridges are chosen as analytic model to show the structural behaviors generated by high temperature of pavement and to formulate the simplified approximate analysis of thermal effects. In general, the thermal effect is changed by the material property of pavements and environmental temperature as well as shape, size and boundary conditions of bridge. Specially, this effect is the representative initial stress problem dependent on time. The thermal effect, however, does not depend on time and thermal effect is regarded as initial load in this study. After these thermal loading is modelled as moving loads, influence lines of reactions of shoes are calculated and the successive pavement steps with arbitrary segments are determined to minimize the thermal effect of shoes by influence line.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.5
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• pp.63-72
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• 2012

In contemporary times, "environmental designers" need to consider both exterior and interior aspects because of the growing trend in dissolution between exterior and interior spaces. To quantify "spatial sense" which serves as the standard for environmental design, this study has asked 63 subjects to evaluate 15 interior and 14 exterior spaces. The "spaciousness (small-large)", "openness(closed-open)", "warmness(warm-cold)", "brightness(bright-dark)", "softness(soft-hard)", "spatial intimacy" and "frequency of visit" were adopted as variables of spatial sense. Through the analysis of these variables, this study could gain the difference between spatial sense for exterior and interior environments, quantify the spatial sense that physically and psychologically appropriates to human beings. The result of this study can be summarized as follows: Twice the amount of spaciousness was observed between the interior and exterior spaces. And the standard on intimate space is established with W/H ratio of 5.71 and high Window/Wall Area ratio in the interior and an area of 3,800m2 and a W/H ratio of 5.57 in exterior. The difference between the spatial sense in the interior and exterior space is mostly dependent on the psychological sense. The increase of physical size caused by the interior space to be perceived as cold, dark and hard psychologically, but exterior space to be perceived as warm, bright and soft. Psychological senses, especially softness, affect spatial intimacy to the greatest extent among the given variables. As the psychological senses for interior spaces were largely independent from the given space's size and perceptive senses, the size of the interior space, which exhibited spatial intimacy, could not be deduced. In comparison to this, due to the high dependency between the psychological senses for exterior spaces and the given space's size and perceptive senses. The study also showed that interior and exterior spaces have relatively different spatial sense and physical standards. Such research results are predicted to provide applicable standards for environmental designers for exterior and interior spaces in the future.

• Management & Information Systems Review
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• v.36 no.4
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• pp.117-127
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• 2017

In recent times the size of the world IPO in general has skyrocketed. Specifically, China's financial market development is becoming important as both the size of China's capital market and the number of companies going public are gradually increasing. This has led to a rapid development of venture vapital(VC) institutions in China for the past couple of decades. This study focuses on one of the three markets of China's Shenzhen Stock Exchange-the Growth Enterprise Board((GEB) hereafter, ChiNext). The ChiNext is established in October, 2009 to enable hi-tech or high growth potential technology companies that find it relatively difficult to fulfil the listing requirements of either the Shenzhen Main Board or Small and Medium Size Enterprise Board(SMEB) to go public. This study covers a three-year period(2012/01/-2015/01) and analyze first day initial return of 83 venture capital-backed companies and 53 non-venture capital-backed companies using T-test. Regression analysis is used as to examine the variables affecting IPO's first-day return. The empirical results are four-fold. First, the level of first day return of venture-backed is significantly lower than non venture capital backed support in the Chinese venture capital market. Second, the level of first-day return of listed companies supported by foreign venture capital is significantly higher than that of companies receiving domestic venture capital support. Third, the firms that have a large number of venture capital firms showed a low level of first-day return. Fourth, regression result for the IPO first-day return which is as dependent variable indicates that the venture capital support(VCAP), number of venture capital(VCNum), offering size(Lnsize) and PER all affect have negative effect on the first day initial return. Also, the venture capital type(VCType), turnover ratio and the the firm type(Tech-firms) statistically affect IPO first day return positively. Finally, by shedding more light on the IPO first-day return, this paper provides meaningful information to investors about the Chinese IPO market.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.43-54
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• 2001

Genetic differentiation of populations is resulted from the environmental and the genetic effects, and the interactions between them. Whereas, the major factors influencing to the genetic differentiation within populations are the gene flow induced by seed or pollen dispersial, the microsite heterogeneity, and the density-dependent distribution of individuals. For the purpose of studying spatial genetic structure and the distribution pattern of Korean pines(Pinus koraiensis), we set up one $100{\times}100m$ plot at a Korean pine stand in Quercus mongolica community on Mt. Jumbong in Korea. To estimate the coefficient of spatial autocorrelation as Moran's index and an analogue, simple block distance, isozyme markers were analyzed in 325 Korean pines. For 11 polymorphic loci observed in 9 enzyme systems, the average percentage of polymorphic loci, the observed and expected heterozygocity were 72.2% 0.200, and 0.251, respectively. It was revealed the excess of homozygotes was observed in the plot, which suggests that here may be more number of consanguineous trees than expected. On the basis of isozyme genotypes observed in this study, 325 trees were classified into 147 groups in which the maximum number of trees for one group was 34. From the distance class of 24-32m, the genetic heterogeneity began to increase. The variation of simple block distance against the growth performance by tree height and diameter also showed the same trend at 24~32m class. According to high fixation index(F=0.204), the spatial genetic structure within a stand, the analysis of the growth performance, and the distribution patterns of identical genotypes, we inferred that the genetic structure of a Korean pine stand in Mt. Jumbong has been maintained rather density-dependent mechanism than the gene flow, such as the pollen dispersial or the heavy input of seeds following the forest gaps. The genetic patchy size was determined between 24~32m, which suggests that the selection of individuals for the ex situ conservation of Korean pine in Mt. Jumbong may be desirable to be made with the spatial distance over 37 meters between trees.

• 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.

• Journal of the Mineralogical Society of Korea
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• v.21 no.3
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• pp.321-329
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• 2008

Amorphous silica nanoparticles are among the most fundamental $SiO_2$ compounds, having implications in diverse geological processes and technological applications. Here, we explore structural details of amorphous silica nanoparticles with varying particle sizes (7 and 14 nm) using $^{29}Si$ and $^{1}H$ MAS NMR spectroscopy together with quantum chemical calculations to have better prospect for their size-dependent atomic structures. $^{29}Si$ MAS NMR spectra at 9.4 T resolve $Q^2,\;Q^3$ and $Q^4$ species at -93 ppm, -101 ppm, -110 ppm, respectively. The fractions of $Q^2,\;Q^3,\;O^4$ species are $7{\pm}1%,\;27{\pm}2%$, and $66{\pm}2%$ for 7 nm amorphous silica nanoparticles and $6{\pm}1%,\;21{\pm}2%$, and $73{\pm}2%$ for 14 nm amorphous silica nanoparticles. Whereas it has been suggested that $Q^2$ and $Q^3$ species exist on particles surfaces, the difference in $Q^{2}\;+\;Q^{3}$ fraction in both 7 and 14 nm particles is not significant, suggesting that $Q^2$ and $Q^3$ species could exist inside particles. $^{1}H$ MAS NMR spectra at 11.7 T shows diverse hydrogen environments, including physisorbed water, hydrogen bonded silanol, and non-hydrogen bonded silanol with varying hydrogen bond strength. The hydrogen contents in the 7nm silica nanoparticles (including water and hydroxyl groups) are about 3 times of that of 14 nm particles. The larger chemical shills for proton environments in the former suggest stronger hydrogen bond strength. The fractions of non-hydrogen bonded silanols in the 14 nm amorphous silica nanoparticles are larger than those in 7 nm amorphous silica nanoparticles. This observation suggests closer proximity among hydrogen atoms in the nanoparticles with smaller diameter. The current results with high-resolution solid-state NMR reveal previously unknown structural details in amorphous silica nanoparticles with particle size.

• Journal of Astronomy and Space Sciences
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• v.22 no.1
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• pp.1-12
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• 2005

The Korean VLBI Network (KVN) will open a new field of research in astronomy, geodesy and earth science using the newest three Elm radio telescopes. This will expand our ability to look at the Universe in the millimeter regime. Imaging capability of radio interferometry is highly dependent upon the antenna configuration, source size, declination and the shape of target. In this paper, imaging simulations are carried out with the KVN system configuration. Five test images were used which were a point source, multi-point sources, a uniform sphere with two different sizes compared to the synthesis beam of the KVN and a Very Large Array (VLA) image of Cygnus A. The declination for the full time simulation was set as +60 degrees and the observation time range was -6 to +6 hours around transit. Simulations have been done at 22GHz, one of the KVN observation frequency. All these simulations and data reductions have been run with the Astronomical Image Processing System (AIPS) software package. As the KVN array has a resolution of about 6 mas (milli arcsecond) at 220Hz, in case of model source being approximately the beam size or smaller, the ratio of peak intensity over RMS shows about 10000:1 and 5000:1. The other case in which model source is larger than the beam size, this ratio shows very low range of about 115:1 and 34:1. This is due to the lack of short baselines and the small number of antenna. We compare the coordinates of the model images with those of the cleaned images. The result shows mostly perfect correspondence except in the case of the 12mas uniform sphere. Therefore, the main astronomical targets for the KVN will be the compact sources and the KVN will have an excellent performance in the astrometry for these sources.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.