• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.413-415
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• 2015

How galaxy evolution differs in different environments is one of the intriguing questions in the study of structure formation. While galaxy properties are clearly distinguished in different environments in the local universe, it is still an open issue what causes this environmental dependence of various galaxy properties. To address this question, in this work, we investigate the build-up of passive galaxies over a wide redshift range, from z ~ 2 to z ~ 0.5, focusing on its dependence on galaxy environment. In the UKIDSS/Ultra Deep Survey (UDS) field, we identify high-redshift galaxy cluster candidates within this redshift range. Then, using deep optical and near-infrared data from Subaru and UKIRT available in this field, we analyze and compare the stellar population properties of galaxies in the clusters and in the field. Our results show that the environmental effect on galaxy star-formation properties is a strong function of redshift as well as stellar mass - in the sense that (1) the effect becomes significant at small redshift, and (2) it is stronger for low-mass ($M_{\ast}<10^{10}M_{\odot}$) galaxies. We have also found that galaxy stellar mass plays a more significant role in determining their star-formation property - i.e., whether they are forming stars actively or not - than their environment throughout the redshift range.

• Korean Journal of Materials Research
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• v.19 no.4
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• pp.186-191
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• 2009

Thermoelectric power and resistivity are measured for the perovskite $LaNi_{1-x}Ti_xO_3$ ($x{\leq}0.5$) in the temperature range 77 K - 300 K. The measured thermoelectric power of $LaNi_{1-x}Ti_xO_3$ ($x{\leq}0.5$) increases linearly with temperature and is represented by A + BT. The x = 0.1 sample showed metallic behavior, the x = 0.3 showed metal and insulating transition around 150 K, and x = 0.5 showed insulating behavior the over the whole temperature range. The electrical resistivity of x = 0.1 shows linear temperature dependence over the whole temperature range and $T^2$ dependence. On the other hand, the electrical resistivity of x = 0.3 shows a linear relation between $ln{\rho}$ and $T^{-1/4}$ (variable range hopping mechanism) in the range of 77 K to 150 K. For x = 0.5, the temperature dependence of resistivity is characteristic of insulating materials; the resistivity data was fitted to an exponential law, such as ln(${\rho}/T$) and $T^{-1}$, which is usually attributed to a small polaron hopping mechanism. These experimental results are interpreted in terms of the spin polaron (x = 0.1) and variable range hopping (x = 0.3) or small polaron hopping (x = 0.5) of an almost localized $Ni^{3+}$ 3d polaron.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1489-1496
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• 2009

Amorphous indium-gallium-zinc-oxide thin-film-transistors (TFTs) were modeled successfully. Dependence of TFT characteristics on structure, thickness, and equilibrium electron-density of the active layer was studied. For mono-active-layer TFTs, a thinner active layer had higher field-effect mobility. Threshold voltage showed the smallest absolute value for the 20 nm active-layer. Subthreshold swing showed almost no dependence on active-layer thickness. For the double-active-layer case, better switching performances were obtained for TFTs with bottom active layers with higher equilibrium electron density. TFTs with thinner active layers had higher mobility. Threshold voltage shifted in the minus direction as a function of the increase in the thickness of the layer with higher equilibrium electron-density. Subthreshold swing showed almost no dependence on active-layer structure. These data will be useful in optimizing the structure, the thickness, and the doping ratio of the active layers of oxide-semiconductor TFTs.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1805-1816
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• 1999

This paper presents the Module Class Dependency Graph for expressing the dependency relations between classes effectively. The object-oriented language is developed independently at design time, and consists of relationship between classes. Therefore we need to consider these characteristics of independence, and to express effectively the relation of classes which is existed in class hierarchy. In the System Dependence Graph and Class Dependence Graph, the relationship of classes is not expressed. To express the class relationship, we propose the Module Class Dependence Graph, and we verify the effectiveness of this method applying to object constructor, inheritance relationship and dynamic binding. Also, we presents the expressing method of parameter to identify the member data of classes. Using this Module Class Dependency Graph, we can analyze the relationship of module class correctly at design time. This method can be applied to reverse engineering, testing, visualization and other various fields to analyze system.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.100-108
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• 2019

The purpose of this study is to analyze the influence of university students' dependence on smart-phone on career attitude maturity and the mediating effect of interpersonal problem in the analysis path. For this purpose, the study implemented a survey on students of universities in Seoul and Gyeonggi-do area and carry out a structural equation for empirical verification with a total of 218 copies. As a result, first, high level of daily life disturbance and virtual world orientation of university students, have a positive effect on interpersonal problems. Second, high level of daily life disturbance and virtual world orientation of university students, have a negative effect on career attitude maturity. Third, interpersonal problems of college students had a negative effect on career attitude maturity, and they were found to be fully mediated in relation to smart-phone dependence and career attitude maturity. Therefore, this study suggests that it can be used as a basic data for the development and application of various programs promoting the career attitude maturity of university students.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.310-323
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• 2023

Urbanization and income distribution issues are global interest, and the results of studies on the impact of urbanization on income inequality are different for each country and period. This study analyzes the impact of urbanization on income inequality using regional data from 2000-2021. In particular, serial correlation, spatial dependence, and common factor effects of the Gini coefficient are confirmed and analyzed through a dynamic spatial panel regression model. As a result, urbanization has a positive effect on reducing income inequality. Therefore, it is necessary to continuously promote regional urbanization to improve the income distribution problem. Areas with already high urbanization rates should reduce income inequality by narrowing the wage gap by expanding training opportunities for low-skilled workers, and need to come up with measures to prevent counter-urbanization.

• Proceedings of the IEEK Conference
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• 2004.06b
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• pp.505-508
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• 2004

Gate length dependent data of intrinsic MOSFET equivalent circuit parameters are extracted using a direct extraction technique based on simple 2-port parameter equations. The relatively scalable data with respect to gate length are obtained. These data are verified to be acrurate by observing good correspondence between modeled and measured S-parameters up to 30GHz. These data will be helpful to construct RF scalable MOSFET model.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.3
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• pp.192-198
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• 2004

The heavy dependence of modern science-based agriculture on chemicals such as fertilizers and pesticides, and heavy machinery gave rise to questions about long-term sustainability of agriculture in relation to degradation of soil quality. The research achievements and trends in developing soil quality indicators were introduced and discussed in this report. Organization for Economic Cooperation and Development (OECD) established 13 agri-environment indicators including soil quality indicator in 1994, collected the soil data and methodologies for development of soil quality indicators in OECD member countries responded to OECD questionnaires and published the OECD reports, Environmental Indicators for Agriculture Volume 1, 2, and 3. Leading countries such as USA, Canada and New Zealand collected national data and evaluated the data in aspect of soil quality. They developed the various methods for selecting a minimum data set (MDS), scoring the soil properties and calculating soil quality index integrating the score of each soil property.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.115-123
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• 2012

In animal tumorigenicity data, tumor onsets occur at several sites and onset times cannot be exactly observed. Instead, the existence of tumors is examined only at death time or sacrifice time of the animal. Such an incomplete data structure makes it difficult to investigate the effect of treatment on tumor onset times; in addition, such dependence should be considered when censoring due to death is related with tumor onset. A bivariate frailty effect is incorporated to model bivariate tumor onsets and to connect death with tumor. For the inference of parameters, EM algorithm is applied and a real NTP(National Toxicology Program) dataset is analyzed as an illustrative example.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.523-544
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• 2018

Bivariate distributions play a fundamental role in survival and reliability studies. We consider a regression model for bivariate survival times under right-censored based on the bivariate Kumaraswamy Weibull (Cordeiro et al., Journal of the Franklin Institute, 347, 1399-1429, 2010) distribution to model the dependence of bivariate survival data. We describe some structural properties of the marginal distributions. The method of maximum likelihood and a Bayesian procedure are adopted to estimate the model parameters. We use diagnostic measures based on the local influence and Bayesian case influence diagnostics to detect influential observations in the new model. We also show that the estimates in the bivariate Kumaraswamy Weibull regression model are robust to deal with the presence of outliers in the data. In addition, we use some measures of goodness-of-fit to evaluate the bivariate Kumaraswamy Weibull regression model. The methodology is illustrated by means of a real lifetime data set for kidney patients.