• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1997.11a
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• pp.109-111
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• 1997

In this paper, we have evaluated temperature, electric field, Pressure dependency and dielectric properties of EPDM XLPE and EPDM/XLPE\`s interface. Temperature dependency of EPDM had great influence with dielectric properties, but pressure and applied voltage of EPDM had no effect on dielectric properties. Dielectric properties of XLPE were influenced by not only temperature but also pressure and applied voltage. We knowed that dielectric properties of EPDM/XLPE were trended toward tendency of those of EPDM

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.8
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• pp.580-583
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• 2012

The dependency of processing pressure on the electrical performances in amorphous silicon-zinc-tin-oxide thin film transistors (SZTO-TFT) has been investigated. The SZTO channel layers were deposited by using radio frequency (RF) magnetron sputtering method with different partial pressure. The field effect mobility (${\mu}_{FE}$) increased and threshold voltage ($V_{th}$) shifted to negative direction with increasing pressure during deposition processing. As a result, oxygen vacancies generated in SZTO channel layer with increasing partial pressure resulted in negative shift in $V_{th}$ and increase in on-current.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.456-463
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by in-situ test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network(NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network(CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.39-45
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• 2012

In the standard CFD code, Lagrangian-Eulerian method is very popular to simulate the liquid spray penetrating into gaseous phase. Though this method can give a simple solution and low computational cost, it have been reported that the Lagrangian spray models have numerical grid dependency, resulting in serious numerical errors. Many researches have shown the grid dependency arise from two sources. The first is due to unaccurate prediction of the droplet-gas relative velocity, and the second is that the probability of binary droplet collision is dependent on the grid resolution. In order to solve the grid dependency problem, the improved spray models are implemented in the KIVA-3V code in this study. For reducing the errors in predicting the relative velocity, the momentum gain from the gaseous phase to liquid particles were resolved according to the gas-jet theory. In addition, the advanced algorithm of the droplet collision modeling which surmounts the grid dependency problem was applied. Then, in order to validate the improved spray model, the computation is compared to the experimental results. By simultaneously regarding the momentum coupling and the droplet collision modeling, successful reduction of the numerical grid dependency could be accomplished in the simulation of the high-pressure injection diesel spray.

• Structural Engineering and Mechanics
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• v.44 no.3
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• pp.289-303
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• 2012

Existing plane stress solutions for thin plates and disks have shown several qualitative features which are difficult to handle with the use of commercial numerical codes (non-existence of solutions, singular solutions, rapid growth of the plastic zone with a loading parameter). In order to understand the effect of temperature and pressure-dependency of the yield criterion on some of such features as well as on the distribution of residual stresses and strains, a semi-analytic solution for a thin hollow disk fixed to a rigid container and subject to thermal loading and subsequent unloading is derived. The material model is elastic-perfectly/plastic. The Drucker-Prager pressure-dependent yield criterion and the equation of incompressibity for plastic strains are adopted. The distribution of residual stresses and strains is illustrated for a wide range of the parameter which controls pressure-dependency of the yield criterion.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.286-292
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• 1997

Sound quality is becoming the major concern in passenger vehicle. The study on it has been done recently but it is not good enough. In order to improve the sound quality in passenger vehicle, so many noise sources must be considered and human feeling to the noise also be taken into account. In this paper, the sound quality was analyzed by vehicle road test which was carried out with varying the traveling speed. As basic factors for sound quality, only objective factors are considered such as loudness, sharpness, speech intelligibility, sound pressure level ... etc. The relations between sound pressure level and other factors are discussed from a point of view of traveling speed dependency. The frequency dependency of sound quality factor is also analyzed by frequency analysis.

• Journal of Forest and Environmental Science
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• v.30 no.4
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• pp.393-404
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• 2014

With consideration of proximate and intricate relationships among rural livelihood, farm land and forestry; this paper examined impact of land tenure reform on local peoples' forest dependency by taking Ethiopia as case study. The post 1975 major land tenure reform and associated activities such as land distribution and forest demarcation were found to be short of minimizing pressure on the forest as has been evidenced by percentage of new households established inside the forest and current level of dependency on the forest. With most of recently established households all making up the poor and very poor categories, together with overall of household composition which is dominated by dependent members coupled by current land tenure system that tie farmers with their land, future dependency on the already diminished forest seems to increase unabated. Reconsidering the existing land tenure system backed by policy for livelihood diversification, improvement in rural education and awareness on demographic issues can minimize future dependency on the forest.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3C
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• pp.115-125
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Journal of the Korean Society of Combustion
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• v.12 no.4
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• pp.1-7
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• 2007

Carbon monoxide (CO) is not only an important intermediate species in chemical reaction mechanisms of hydrocarbon fuel combustion, but also a crucial pollutant species emitted from automotive engines. To better understand the physical processes impacting CO emissions, the development of laser-based measurement techniques that can visualize in-cylinder CO distributions is desirable. Among these techniques, Laser-Induced Fluorescence (LIF) is a sensitive and species-selective detection technique capable of good spatial resolution. However, some technical matters such as deep UV excitation, severe pressure dependency of the LIF signal, and potential interference from other species have been major challenges for CO LIF application. This study is focused on investigating the feasibility of CO two-photon LIF in a direct-injection diesel engine operating at typical pressure and temperature conditions with commercial grade diesel fuel. Spectroscopic analysis shows that the CO fluorescence signal can be separated from $C_2$ Swan band or broadband fluorescence from PAHs when the signal is collected near 483 nm. The signal-to-noise ratio of CO LIF deteriorate rapidly as pressure is increased, following $P^{-1.49}$ which matches the theoretical signal pressure dependency.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1199-1203
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• 2008

It has been recognized that unsaturated soil behavior plays an importantrole in geomechanics. In the last decade several constitutive models have been proposed and used in the analysis. Many of them, however, are constructed in the frame work of rate independent model such as elasto-plastic one. Although rate dependency is an important characteristics of soil for both saturated and unsaturated soils, very few models have been developed taking account of rate dependency. In the present paper, we have developed an elasto-viscoplastic model considering an effect of suction based on the overstress-type viscoplasticity with soil structure degradation. In the model, we have adopted an averaged pore pressure composed of pore water pressure and air pressure to determine the effective stress.