• Journal of the Society of Naval Architects of Korea
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• v.46 no.5
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• pp.498-509
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• 2009

Present study is concerned with the simulation of plasticity models for the cyclic stressstrain behavior of aluminum alloy AC4C-T6 that can be used for primary materials of LNG cargo pump. Material model of cyclic hardening and plasticity for aluminum alloy AC4C-T6 was investigated through experiments and numerical simulations. Monotonic tensile and cyclic tension-compression test under symmetric load cycles was performed at both room temperature and cryogenic temperature of $-165^{\circ}C$. Based on the experimental data plastic hardening models were evaluated for isotropic/kinematic/combined hardening. FEA (Finite Element Analysis) models which describe the cyclic stress-strain relationship were evaluated for the simulation of plasticity. An appropriate hardening model is proposed comparing the results of FEA with those of experiments.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.7
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• pp.559-563
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• 2002

A threshold voltage model of SiC N-channel MOSFETs for high-temperature and hard radiation environments has been developed and verified by comparing with experimental results. The proposed model includes the difference in the work functions, the surface potential, depletion charges and SiC/$SiO_2$acceptor-like interface state charges as a function of temperature. Simulations of the model shoved that interface slates were the most dominant factor for the threshold voltage decrease as the temperature increase. To verify the model, SiC N-chnnel MOSFETS were fabricated and threshold voltages as a function of temperature were measured and compared wish model simulations. From these comparisons, extracted density of interface slates was $4{\times}10^{12}\textrm{cm}^{-2}eV^{-1}$.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.33-45
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• 2015

Currently, Internet is used an essential tool in the business area. Despite this importance, there is a risk of network attacks attempting collection of fraudulence, private information, and cyber terrorism. Firewalls and IDS(Intrusion Detection System) are tools against those attacks. IDS is used to determine whether a network data is a network attack. IDS analyzes the network data using various techniques including expert system, data mining, and state transition analysis. This paper tries to compare the performance of two data mining models in detecting network attacks. They are decision tree (C4.5), and neural network (FANN model). I trained and tested these models with data and measured the effectiveness in terms of detection accuracy, detection rate, and false alarm rate. This paper tries to find out which model is effective in intrusion detection. In the analysis, I used KDD Cup 99 data which is a benchmark data in intrusion detection research. I used an open source Weka software for C4.5 model, and C++ code available for FANN model.

• Journal of Environmental Science International
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• v.5 no.4
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• pp.429-440
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• 1996

A global carbon cycle model (GCCM), that incorporates interaction among the terrestrial biosphere, ocean, and atmosphere, was developed to study the carbon cycling aid global carbon budget, especially due to anthropogenic $CO_2$ emission. The model that is based on C, 13C and 14C mass balance, was calibrated with the observed $CO_2$ concentration, $\delta$13C and $\Delta$14C in the atmosphere, Δ14C in the soil, and $\Delta$14C in the ocean. Also, GCCM was constrained by the literature values of oceanic carbon uptake and CO, emissions from deforestation. Inputs (forcing functions in the model) were the C, 13C and 14C as $CO_2$ emissions from fossil fuel use, and 14C injection into the stratosphere by bomb-tests. The simulated annual carbon budget of 1980s due to anthropoRenic $CO_2$ shows that the global sources were 5.43 Gt-C/yr from fossil fuel use and 0.91 Gt-C/yr from deforestation, and the sinks were 3.29 Gt-C/yr in the atmosphere, 0.90 Gt-C/yr in the terrestrial biosphere and 2.15 Gt-C/yr in the ocean. The terrestrial biosphere is currently at zero net exchange with the atmosphere, but carbon is lost cia organic carbon runoff to the ocean. The model could be utilized for a variety of studies in $CO_2$ policy and management, climate modeling, $CO_2$ impacts, and crop models.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.10 no.1
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• pp.100-106
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• 2014

There is a growing need to introduce advanced pressure vessel steels with higher strength and toughness for the optimizatiooCn of the design and construction of longer life and larger capacity nuclear power plants. SA508 Gr.4N Ni-Cr-Mo low alloy steels have superior strength and fracture toughness, compared to SA508 Gr.3 Mn-Mo-Ni low alloy steel. Therefore, the application of SA508 Gr.4N low alloy steel could be considered to satisfy the strength and toughness required in advanced nuclear power plants. The purpose of this study is to characterize the microstructure and mechanical properties of SA508 Gr.4N low alloy steels. 1 ton ingot of SA508 Gr.4N model alloy was fabricated by vacuum induction melting followed by forging, quenching, and tempering. The predominant microstructure of the SA508 Gr.4N model alloy is tempered martensite having small packet and fine Cr-rich carbides. The yield strength at room temperature was 540MPa, and it was decreased with an increase of test temperature while DSA phenomenon occurred at around $288^{\circ}C$. Overall transition property of SA508 Gr.4N model alloy was much better than SA508 Gr.3 low alloy steel. The index temperature, $T_{41J}$, of SA508 Gr.4N model alloy was $-132^{\circ}C$ in Charpy impact tests, and reference nil-ductility transition temperature, $RT_{NDT}$ of $-105^{\circ}C$ was obtained from drop weight tests. From the fracture toughness tests performed in accordance with the ASTM standard E1921 Master curve method, the reference temperature, $T_0$ was $-147^{\circ}C$, which was improved more than $60^{\circ}C$ compared to SA508 Gr.3 low alloy steels.

• Journal of Energy Engineering
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• v.23 no.1
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• pp.58-66
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• 2014

Catalytic gasification of a low rank coal- Inner Mongolian lignite has been carried out with carbon dioxide. The gasification reactions were performed in a thermogravimetric analyzer at temperatures of $600^{\circ}C$ to $900^{\circ}C$. The kinetic parameters were evaluated using three different gas-solids reaction models and the prediction ability of each model were compared. Among the models evaluated, the modified volumetric model was found to correlate best both the non-catalytic and catalytic gasification reactions. The theoretical models, homogeneous and shrinking-core models, were found to satisfactorily correlate gasification reactions for the non-catalytic and $FeSO_4$-catalyzed reactions. In case of alkali metal catalysts, the catalytic activity was mostly pronounced at a low temperature of $600^{\circ}C$ and observed to decrease by 50% as the temperature was increased to $700^{\circ}C$, and it remained nearly constant at temperature over $800^{\circ}C$. The order of catalytic activity was found to be: $K_2CO_3$ > $Na_2CO_3$ > $K_2SO_4$ > $FeSO_4$.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.17-25
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• 2013

TIn this paper, we propose a model automatically scoring a student's answer for a descriptive problem by using a voting method. Considering the model construction cost, the proposed model does not separately construct the automatic scoring model per problem type. In order to utilize features useful for automatically scoring the descriptive answers, the proposed model extracts feature values from the results, generated by comparing the student's answer with the answer sheet. For the purpose of improving the precision of the scoring result, the proposed model collects the scoring results classified by a few machine learning based classifiers, and unanimously selects the scoring result as the final result. Experimental results show that the single machine learning based classifier C4.5 takes 83.00% on precision while the proposed model improve the precision up to 90.57% by using three machine learning based classifiers C4.5, ME, and SVM.

• Publications of The Korean Astronomical Society
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• v.4 no.1
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• pp.1-15
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• 1989

A jet plasmoid model for 3C.449 has been constructed by introducing a plasma.ejecting black hole orbiting around the center of its parent cD galaxy. We examined the characteristics of the jet trajectory by varying the values of (1) orbiting radius and velocity of the black hole, (2) plasma ejection velocity, (3) size, mass and space velocity of the parent galaxy, (4) size of the galactic core and (5) the density of the intergalactic medium. In our model calculation the effect of the gravity by the parent galaxy and the ram pressure by the intergalactic medium have been taken in account. It is found that our dynamical model accounts reasonably well for the observed structure of 3C449. Our proposed model suggests that the buoyancy force near the galactic center plays an important role in the formation of the curved structure of the radio jet.

• The Korean Journal of Ecology
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• v.28 no.6
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• pp.353-363
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• 2005

We developed a local-scale ecophysiological model, Sim-CYCLE Fine by modifying Sim-CYCLE which was developed for a global scale simulation. Sim-CYCLE fine is able to simulate not only carbon fluxes but also plant growth with various time-steps from an hour to a month. The model outputs of $CO_2$ flux and biomass/LAI were highly reliable; we validated the model results with measurements from the eddy covariance technique and the harvest method ($R^2$ values of around 0.9 for both). The results suggested that the phonology and the seasonal dynamics of the $C_3/C4$ plant communities affected significantly the carbon fluxes and the plant growth during the plant growing season.

• Journal of Microbiology and Biotechnology
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• v.25 no.9
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• pp.1417-1424
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• 2015

In this study, we tried to characterize Streptomyces peucetius CYP157C4 with homology modeling using three cytochrome P450 (CYP) structures (CYP157C1, CYP164A2, and CYP107L1), having discovered that CYP157C4 lacks the ExxR motif that was considered invariant in all CYPs. We used Discovery Studio 3.5 to build our model after first assessing the stereochemical quality and side-chain environment, and a 7-ethoxycoumarin substrate was docked into the final model. The model-substrate complex allowed us to identify functionally important residues and validate the active-site architecture. We found a distance of 4.56 Å between the 7-ethoxycoumarin and the active site of the heme, and cloning and an in vitro assay of the CYP157C4 showed the dealkylation of the substrate. Since the details regarding this group of CYP structures are still unknown, the findings of this study may provide elucidation to assist with future efforts to find a legitimate substrate.