• Earthquakes and Structures
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• v.17 no.4
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• pp.387-398
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• 2019

On the basis that ground motions may arrive at a structure from any horizontal direction and that different directions of seismic incidence would result in different structural dynamic responses, this paper focuses on orienting the crucial seismic incidence of transmission tower-line systems based on the wavelet energy method. A typical transmission tower-line system is chosen as the case study, and two finite element (FE) models are established in ABAQUS, with and without consideration of the interaction between the transmission towers and the transmission lines. The mode combination frequency is defined by considering the influence of the higher-order modes of the structure. Subsequently, wavelet transformation is performed to obtain the total effective energy input and the effective energy input rate corresponding to the mode combination frequency to further judge the critical angle of seismic incidence by comparing these two performance indexes under different seismic incidence angles. To validate this approach, finite element history analysis (FEHA) is imposed on both FE models to generate comparative data, and good agreement is found. The results demonstrate that the wavelet energy method can forecast the critical angle of seismic incidence of a transmission tower-line system with adequate accuracy, avoiding time-consuming and cumbersome computer analysis. The proposed approach can be used in future seismic design of transmission tower-line systems.

• New & Renewable Energy
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• v.18 no.1
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• pp.17-28
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• 2022

This paper presents an effective Markov transition matrix (EMTM), which will be used to calculate the wind speed at the target site in a wind farm to accurately predict wind energy production. The existing MTS prediction method using a Markov transition matrix (MTM) exhibits a limitation where significant prediction variations are observed owing to random selection errors and its bin width. The proposed method selects the effective states of the MTM and refines its bin width to reduce the error of random selection during a gap filling procedure in MTS. The EMTM reduces the level of variation in the repeated prediction of wind speed by using the coefficient of variations and range of variations. In a case study, MTS exhibited better performance than other MCP models when EMTM was applied to estimate a one-day wind speed, by using mean relative and root mean square errors.

• Journal of the Korean School Mathematics Society
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• v.2 no.1
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• pp.67-77
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• 1999

The purpose of this study was to design models of CAI programs for the graphing of quadratic functions. In order to achieve this aim, I researched the relationship between mathematics educations computer programing, and theoretical approaches of CAI. The CAI program, which was developed based on my research was then positively applied to the mathematics education class in a middle school. First of all, I selected two classes -An experimental class and a comparative class. The experimental class was taught using the CAI program and the comparative class was taught by conventional methods of instruction. The results of this study are as follows: 1. The class taught by using the CAI program scored higher academic achievement than the class taught by conventional methods of instruction. 2. The analysis of the two classes' academic scores shows that the instruction using CAI program is more effective than that by conventional methods in improving students' academic achievement. The followings are suggestion for developing CAI programs and students' understanding through this study. 1. Non computer specialists will require a few months to develope an effect CAI program. Thus, development of easier, more clearly defined and flexible models must be constructed. 2. Teachers should be eager to use pre-existing models to motivate their students irregardless of their own development of programs. 3. School should provide computer rooms with a perfect net work in proportion to class size. 4. CAI programs can make students understand faster and more directly than blackboard examples. However, inconsideration of mathematical characteristics, arithmetic by hand is more effective for the students' memory retention. Computers is an effective tool of instruction. But it is most effective when used in conjunction with other methods that complement its use.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1179-1185
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• 2007

The study of girder-to-column joints under experiment and numerical analysis was carried out to evaluate change of the flexural capacity of the joints with the 2-layer upper reinforcement of girder within rectangular section and the single-layered upper reinforcement at the girder flange. According to the analysis results using the flange width, the flange thickness and the location of reinforcements in the upper flange as variables, in the models with a same effective width, the increasing rate of capacity has nothing to do with the flange width with a same effective width. However, the capacity of the models with the upper reinforcements arranged close to the rectangular beam section is larger than that of the models with the upper reinforcements arranged remotely from the rectangular section. If the range of arrangement fur reinforcement exceeds the effective width, despite of increasing the flange thickness, the capacity is not increased.

• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.651-664
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• 2022

A precise prediction of the ultimate bond strength between rebar and surrounding concrete plays a major role in structural design, as it effects the load-carrying capacity and serviceability of a member significantly. In the present study, Gaussian models are employed for modelling bond strength of ribbed steel bars embedded in concrete. Gaussian models offer a non-parametric method based on Bayesian framework which is powerful, versatile, robust and accurate. Five different Gaussian models are explored in this paper-Gaussian Process (GP), Variational Heteroscedastic Gaussian Process (VHGP), Warped Gaussian Process (WGP), Sparse Spectrum Gaussian Process (SSGP), and Twin Gaussian Process (TGP). The effectiveness of the models is also evaluated in comparison to the numerous design formulae provided by the codes. The predictions from the Gaussian models are found to be closer to the experiments than those predicted using the design equations provided in various codes. The sensitivity of the models to various parameters, input feature space and sampling is also presented. It is found that GP, VHGP and SSGP are effective in prediction of the bond strength. For large data set, GP, VHGP, WGP and TGP can be computationally expensive. In such cases, SSGP can be utilized.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.299-304
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• 2023

Among artificial intelligence techniques, deep learning is a model that has been used in many places and has proven its effectiveness. However, deep learning models are not used effectively in everywhere. In this paper, we will show the limitations of deep learning models through comparison of regression analysis and deep learning models, and present a guide for effective use of deep learning models. In addition, among various techniques used for optimization of deep learning models, data normalization and data shuffling techniques, which are widely used, are compared and evaluated based on actual data to provide guidelines for increasing the accuracy and value of deep learning models.

• The Journal of Engineering Geology
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• v.14 no.2
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• pp.169-177
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• 2004

The permeation movements of groundwater recharge and contaminate materials receive a eat effect due to porosity and effective porosity of porous media which is composing underground consisted of saturation and unsaturated states. This study developed Frequency Domain Reflectometry(FDR) system and measurement sensor, and then carried out the laboratory experiments to measure effective porosity for unsaturated porous media. Also, I suggested dielectric mixing models(DMMs) which can calculate the effective porosity from relation of measured dielectric constants. In the experimental results the extent range of effective porosity of standard sand and river sand which are unsaturated soil sample were measured in about 65∼85 % for porosity. In relation of effective porosity and porosity, especially, effective porosity confirmed that displays decreasing a little tendency as porosity increases. This is because unsaturated soil did not reach in saturation enough by air of very small amount that exist in pore between soil particles.

• Journal of Environmental Impact Assessment
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• v.14 no.4
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• pp.157-164
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• 2005

Existing models that predict of Daily water supply include statistical models and neural network model. The neural network model was more effective than the statistical models. Only neural network model, which predict of Daily water supply, is focused on estimation of the operational control. Neural network model takes long learning time and gets into local minimum. This study proposes Neuro Genetic hybrid model which a combination of genetic algorithm and neural network. Hybrid model makes up for neural network's shortcomings. In this study, the amount of supply, the mean temperature and the population of the area supplied with water are use for neural network's learning patterns for prediction. RMSE(Root Mean Square Error) is used for a MOE(Measure Of Effectiveness). The comparison of the two models showed that the predicting capability of Hybrid model is more effective than that of neural network model. The proposed hybrid model is able to predict of Daily water, thus it can apply real time estimation of operational control of water works and water drain pipes. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 11.81% and the average error was lower than 1.76%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• KIEAE Journal
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• v.13 no.5
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• pp.89-96
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• 2013

Green roofs can reduce surface water runoff, provide a habitat for wildlife moderate the urban heat island effect, improve building insulation and energy efficiency, improve the air quality, create aesthetic and amenity value, and preserve the roof's waterproofing. Green roofs are mainly divided into three types : intensive, simple-intensive, and extensive. Especially, extensive roof environment is a harsh one for plant growth; limited water availability, wide temperature fluctuations, high exposure to wind and solar radiation create highly stressed environment. This study, aimed at extensive green roof, was carried out on the rooftop of the library at Seoul Women's Univ. from October to November, 2012 and from March to August, 2013. To suggest the most effective vegetation model for biodiversity and heat island mitigation, surface temperatures were monitored by each vegetation model. We found that herbaceous plants of Aster sphathulifolius, Aceriphyllum rossii and Belamcanda chinensis, shrub of Syringa patula 'Miss Kim', Thymus quinquecostatus var. japonica, Sedum species can mixing each other. Among them, the vegetation models including Sedum takesimense, Aster sphathulifolius, Thymus quinquecostatus var. japonica was more effective on the surface temperature mitigation, because the species have the tolerance and high ratio of covering, and also in water. Especially, in the treatment of bark mulching, they helped to increase the temperature of vegetation models. In the case of summer, temperature mitigation of vegetation models were no significant difference among vegetation types. Compared to surface temperature of June, July and August were apparent impact of temperature mitigation, it shows that temperature mitigation are strongly influenced by substrate water content.

• Geomechanics and Engineering
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• v.16 no.3
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• pp.257-271
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• 2018

In this paper, the effect of the homogenization models on buckling and free vibration is presented for simply supported functionally graded plates (FGM) resting on elastic foundation. The majority of investigations developed in the last decade, explored the Voigt homogenization model to predict the effective proprieties of functionally graded materials at the macroscopic-scale for FGM mechanical behavior. For this reason, various models have been used to derive the effective proprieties of FGMs and simulate thereby their effects on the buckling and free vibration of FGM plates based on comparative studies that may differ in terms of several parameters. The refined plate theory, as used in this paper, is based on dividing the transverse displacement into both bending and shear components. This leads to a reduction in the number of unknowns and governing equations. Furthermore the present formulation utilizes a sinusoidal variation of displacement field across the thickness, and satisfies the stress-free boundary conditions on the upper and lower surfaces of the plate without requiring any shear correction factor. Equations of motion are derived from Hamilton's principle. Analytical solutions for the buckling and free vibration analysis are obtained for simply supported plates. The obtained results are compared with those predicted by other plate theories. This study shows the sensitivity of the obtained results to different homogenization models and that the results generated may vary considerably from one theory to another. Comprehensive visualization of results is provided. The analysis is relevant to aerospace, nuclear, civil and other structures.