• Informatization Policy
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• v.24 no.1
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• pp.100-112
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• 2017

This study verified the relationship between internet use, family relationship, and cyber violence victimization by comparing models. 2013 The survey of Internet addiction of National Information Society Agency was used in this study to verify relationship between variables. We compared the model which internet use impact cyber violence victimization through mediating fully family relationship and other model which internet use influence cyber violence victimization through mediating partially family relationship. Based on final model (model 1), More internet use was related to lower family bond and lower family bond was associated with more cyber violence victimization. This results imply that family relationship have an important role in relationship between internet use and cyber violence victimization rather than internet use impact directly cyber violence victimization.

• Journal of the Korea Concrete Institute
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• v.22 no.3
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• pp.381-388
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• 2010

In this study, characteristics of the seismic response of the non-earthquake resistant reinforced concrete (RC) frame were identified. The test building is designed to withstand only gravity loads and not in compliance with modern seismic codes. Smooth bars were utilized for the reinforcement. Members are provided with minimal amount of stirrups to withstand low levels of shear forces and the core concrete is virtually not confined. Columns are slender and more flexible than beams, and beam-column connections were built without stirrups. Through the modeling of an example RC frame, the feasibility of the fiber elementbased 3D nonlinear analysis method was investigated. Since the torsion is governed by the fundamental mode shape of the structure under dynamic loading, pushover analysis cannot predict torsional response accurately. Hence, dynamic response history analysis is a more appropriate analysis method to estimate the response of an asymmetric building. The latter method was shown to be accurate in representing global responses by the comparison of the analytical and experimental results. Analytical models without rigid links provided a good estimation of reduced stiffness and strength of the test structure due to bond-slip, by forming plastic hinges closer to the column ends. However, the absence of a proper model to represent the bond-slip poased the limitations on the current inelastic analysis schemes for the seismic analysis of buildings especially for those with round steel reinforcements. Thus, development of the appropriate bond-slip model is in need to achieve more accurate analysis.

• Applied Biological Chemistry
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• v.51 no.3
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• pp.171-176
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• 2008

The comparative molecular similarity indices analysis (CoMSIA) models between 3${\beta}$-Hydroxy-12-oleanen-28-oic acid (1-30) analogues as substrate molecule and their inhibitory activities ($pI_{50}$) against protein tyrosine phosphatase (PTP)-1B were derived and discussed quantitatively. Listing in order, the CoMFA>CoMSIA${\geq}$HQSAR>2D-QSAR model, these QSAR models had the better statistical values. The optimized CoMSIA F1 model at grid 3.0${\AA}$ had the best predictability and fitness ($q^2$=0.754 and $r^2$=0.976) by field fit alignment. The order of contribution ratio (%) of CoMSIA fields concerning the inhibitory activities was a H-bond acceptor (48.9%), steric field (25.8%) and hydrophobic field (25.4%), respectively. Therefore, the inhibitory activities of substrate molecules against PTP-1B were dependent upon H-bond acceptor field (A) of $R_4$-group. From the analytical results of CoMSIA contour maps, oleanolic acid derivatives will have better inhibition activities if $R_1$ group has H-bond acceptor disfavor, $R_3$group has steric disfavor and $R_4$ group has steric, hydrophobic, H-bond favor.

• Journal of the Korean Chemical Society
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• v.29 no.1
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• pp.31-37
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• 1985

N-Acetyl-1-phenylalanyl-1-phenylalanine methyl ester (APhPhMe), N-acetyl-l-phenylalanine methyl ester (APhMe) and N-acetyl-1-phenylalanyl-1-alanine methyl ester (APhAlMe) were used as model compounds to investigate a protein denaturation under various temperatures and pressures. Overall, the solubility of APhPhMe in water increased with increasing pressure and that of APhMe decreased. However, the solubility of APhAlMe was nearly same. The values of volume change of APhPhMe were -0.9, -1.47, -1.09, -1.52 ml/mole at 20, 30, 40 and 50$^{\circ}C$, respectively, and those of APhMe were +6.0, +7.0, +7.5 ml/mole at 20, 30 and 40$^{\circ}C$, respectively. But those of APhAlMe were nearly zero at the measured temperature. The experimental result seems to be explained by the hydrophobic interaction and hydrogen bond of peptide bonds. In the compounds which have only peptide bonds and which have both a pretty large hydrophobic group and a peptide bond in the molecules, the hydrogen bond between peptide bonds is more dominant than the hydrophobic interaction. However, when the number of peptide bond and hydrophobic group increase simultaneously, the hydrophobic interaction seems to be more dominant.

• Journal of the Korean Society of Safety
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• v.28 no.2
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• pp.55-59
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• 2013

The analytical model was constituted to evaluate the flexural strength of UHPFRC(ultra high performance fiber reinforced concrete) member. The analytical approach was attemped to study the effect of the joint and the result compared with the experimental study to verify the analytical model. The calculated value tends to underestimate about 23%~25% in comparison with the experimental result of the jointed test member because the bond stress between precast UHPFRC and cast-in-place UHPFRC surface is not considered in the analytical model. But in the case of the continuous test member, the analytical model provides reasonable results for the flexural strength of UHPFRC member.

• Steel and Composite Structures
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• v.3 no.2
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• pp.75-95
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• 2003

A numerical model is presented to simulate the mechanical behaviour of composite steel and concrete columns taking into account the interaction between the hollow steel section and the concrete core. The model, based on displacement finite element methods with an Updated Lagrangian formulation, allows for geometrical and material non linearities combined with heating over all or a part of the section and column length. Comparisons of numerical calculations made using the model with 33 fire resistance tests show that the model is able to predict the fire resistance, expressed in minutes of fire exposure, of composite columns with a good accuracy.

• Computers and Concrete
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• v.10 no.5
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• pp.489-505
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• 2012

This paper presents a simplified grid beam model for simulating the nonlinear response of reinforced concrete flat-plate structures. The beam elements are defined with nonlinear behavior for bending moment and torsion. The flexural stiffness and torsional strength of the beam elements are defined based on experimental data to implicitly account for slab two-way bending effects. A failure criterion that considers the interaction between the punching strength and slab flexural behavior is incorporated in the model. The effects of bond-slip of slab reinforcement on connection stiffness are examined. The proposed grid beam model is validated by simulating large-scale tests of slab-column connections subjected to concentric gravity loading and unbalanced moment. This study also determines the critical parameters for a hysteretic model used to simulate flat-plates subjected to cyclic lateral loading.

• Structural Engineering and Mechanics
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• v.61 no.5
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• pp.605-615
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• 2017

Shear failure of reinforced concrete (RC) beams is a major concern for structural engineers. It has been shown through various studies that the shear strength and ductility of RC beams can be improved by adding steel fibers to the concrete. An accurate model predicting the shear strength of steel fiber reinforced concrete (SFRC) beams will help SFRC to become widely used. An artificial neural network (ANN) model consisting of an input layer, a hidden layer of six neurons and an output layer was developed to predict the shear strength of SFRC slender beams without stirrups, where the input parameters are concrete compressive strength, tensile reinforcement ratio, shear span-to-depth ratio, effective depth, volume fraction of fibers, aspect ratio of fibers and fiber bond factor, and the output is an estimate of shear strength. It is shown that the model is superior to fourteen equations proposed by various researchers in predicting the shear strength of SFRC beams considered in this study and it is verified through a parametric study that the model has a good generalization capability.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.301-307
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• 2015

A bond-based peridynamic model has been shown to be capable of analyzing many of dynamic brittle fracture phenomena. However, there have been issued limitations on handling constitutive models of various materials. Especially, it assumes bonds act independently of each other, so that Poisson's ratio for 3D model is fixed as 1/4 as well as taking only account the bond stretching results in a volume change not a shear change. In this paper a state-based peridynamic model of dynamic brittle fracture is presented. The state-based peridynamic model is a generalized peridynamic model that is able to directly use a constitutive model from the standard theory. It permits the response of a material at a point to depend collectively on the deformation of all bonds connected to the point. Thus, the volume and shear changes of the material can be reproduced by the state-based peridynamic theory. For a linearly elastic solid, a plane stress model is introduced and the damage model suitable for the state-based peridynamic model is discussed. Through a convergence study under decreasing the peridynamic nonlocal region($\delta$-convergence), the dynamic fracture model is verified. It is also shown that the state-based peridynamic model is reliable for modeling dynamic crack propagatoin.