• Journal of Educational Research in Mathematics
• /
• v.22 no.3
• /
• pp.371-386
• /
• 2012

This research assumes two facts; One is that the mathematics curriculum reform of Korea in 2007 would have been better if it had been a revise instead of deletion and the other is that every school curriculum should be of help for the sound enhancement of all 6 types of logical concepts that appears in the Piaget's theory of cognitive development. What our mathematics curriculum has introduced as a correlation is not the one of the 6 logical concepts that Piaget had thought in his theory of cognitive development. In order to see the reason of that difference, we check the difference of jargons among the academic denominations, such as Pedagogy, Psychology and Statistics through their college textbooks. Because we suppose that the mismatch of 'Piaget's vs Curriculum's correlation' is due to the mis-communication among scholars of different academic denominations. With what we learned via the above analytical study leaned on an abduction and to get some idea on them for the potential future construction of school Statistics curriculum when it should be returned, which we believe so, we observe two foreign highschool mathematics textbooks briefly. As a result of the study, we found that the concept of correlation in Pedagogy contain all kinds of relation while it was stingy in Statistics. Here we report a main result; A careful discretion among similar concepts of correlation, such as linear relationship(correlation), stochastic change along conditions(dependence), central comparison(other relation) are needed for the potential future curriculum. And if new curriculum contains the linear correlation then we strongly recommend to involve the regression line to connect it with the linear function chapter.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.9 no.6
• /
• pp.133-141
• /
• 2009

The main objective of water distribution system is to supply enough water to users with proper pressure. Hydraulic analysis of water distribution system can be divided into Demand Driven Analysis (DDA) and Pressure Driven Analysis (PDA). Demand-driven analysis can give unrealistic results such as negative pressures in nodes due to the assumption that nodal demands are always satisfied. Pressure-driven analysis which is often used as an alternative requires a Head-Outflow Relationship (HOR) to estimate the amount of possible water supply at a certain level of pressure. However, the lack of data causes difficulty to develop the relationship. In this study, effective supply, which is the possible amount of supply while meeting the pressure requirement in nodes, is proposed to estimate the serviceability and user's convenience of the network. The effective supply is used to calculate Subsystem Importance Index (SII) which indicates the effect of isolating a subsystem on the entire network. Harmony Search, a stochastic search algorithm, is linked with EPANET to maximize the effective supply. The proposed approach is applied in example networks to evaluate the capability of the network when a subsystem is isolated, which can also be utilized to prioritize the rehabilitation order or evaluate reliability of the network.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.2
• /
• pp.3-12
• /
• 2010

In previous studies, the digital measurement systems and analysis algorithms were developed by using the related techniques, such as the aerial photograph detection and high resolution satellite image process. However, these studies were limited in 2-dimensional geo-processing. Therefore, it is necessary to apply the 3-dimensional spatial information and coordinate system for higher accuracy in recognizing and locating of geo-features. The objective of this study was to develop a stochastic algorithm for the optimal sensor placement using the 3-dimensional spatial analysis method. The 3-dimensional information of the LiDAR was applied in the sensor field algorithm based on 2- and/or 3-dimensional gridded points. This study was conducted with three case studies using the optimal sensor placement algorithms; the first case was based on 2-dimensional space without obstacles(2D-non obstacles), the second case was based on 2-dimensional space with obstacles(2D-obstacles), and lastly, the third case was based on 3-dimensional space with obstacles(3D-obstacles). Finally, this study suggested the methodology for the optimal sensor placement - especially, for ground-settled sensors - using the LiDAR data, and it showed the possibility of algorithm application in the information collection using sensors.

• Journal of Korea Port Economic Association
• /
• v.26 no.1
• /
• pp.222-233
• /
• 2010

This paper aims at predicting the BDI from Jan. to Dec. 2010 using such econometric techniues of the univariate time series as stochastic ARIMA-type models and Hodrick-Prescott filtering technique. The multivariate cause-effect econometric model is not employed for not assuring a higher degree of forecasting accuracy than the univariate variable model. Such a cause-effect econometric model also fails in adjusting itself for the post-sample. This article introduces the two ARIMA models and five Intervention-ARIMA models. The monthly data cover the period January 2000 through December 2009. The out-of-sample forecasting performance is compared between the ARIMA-type models and the random walk model. Forecasting performance is measured by three summary statistics: root mean squared error (RMSE), mean absolute error (MAE) and mean error (ME). The RMSE and MAE indicate that the ARIMA-type models outperform the random walk model And the mean errors for all models are small in magnitude relative to the MAE's, indicating that all models don't have a tendency of overpredicting or underpredicting systematically in forecasting. The pessimistic ex-ante forecasts are expected to be 2,820 at the end of 2010 compared with the optimistic forecasts of 4,230.

• Clean Technology
• /
• v.24 no.3
• /
• pp.239-248
• /
• 2018

In this study, pervaporation experiments of water, ethanol and IPA (Isopropyl alcohol) single components and water/ethanol, water/IPA mixtures were carried out using zeolite 4A membranes developed by Fine Tech Co. Ltd. Those membranes were fabricated by hydrothermal synthesis (growth in hydrothermal condition) after uniformly dispersing the zeolite seeds on the tubular alumina supports. They have a pore size of about $4{\AA}$ by ion exchange of $Na^+$ to the LTA structure with Si/Al ratio of 1.0, and shows strong hydrophilic property. Physical characteristics of prepared membranes were evaluated by using SEM (surface morphology), porosimetry (macro- or meso- pore analysis), BET (micropore analysis), and load tester (compressive strength). Pervaporation experiments with various temperature and concentration conditions confirmed that the zeolite 4A membrane can selectively separate water from ethanol and IPA. Water/ethanol separation factor was over 3,000 and water/IPA separation factor was over 1,500 (50 : 50 wt%, initial feed concentration). Pervaporation behaviors of single components and binary mixtures were predicted using ACM (activity coefficient model), GMS (generalized Maxwell Stefan) model and DGM (Dusty Gas Model). The adsorption and diffusion coefficients of the zeolite top layer were obtained by parameter estimation using GA (Genetic Algorithm, stochastic optimization method). All the calculations were carried out using MATLAB 2018a version.

• Journal of the Korea Society for Simulation
• /
• v.22 no.2
• /
• pp.101-107
• /
• 2013

Because forest fires are predicted to increase in severity and frequency under global climate change with important environmental implications, an understanding of fire dynamics is critical for mitigation of these negative effects. For the reason, researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed the simulation models to mimic the forest fire spread patterns. In this study, we suggested a novel model considering the wind effect. Our theoretical forest was comprised of two different tree species with varying probabilities of transferring fire that were randomly distributed in space at densities ranging from 0.0 (low) to 1.0 (high). We then studied the distributional patterns of burnt trees using a two-dimensional stochastic cellular automata model with minimized local rules. We investigated the time, T, that the number of burnt trees reaches 25% of the whole trees for different values of the initial tree density, fire transition probability, and the degree of wind strength. Simulation results showed that the values of T decreased with the increase of tree density, and the wind effect decreased in the case of too high or low tree density. We believe that our model can be a useful tool to explore forest fire spreading patterns.

• Computational Structural Engineering
• /
• v.8 no.3
• /
• pp.103-111
• /
• 1995

Evaluating nonlinear response of a MDOF system under dynamic stochastic loads such as seismic excitation usually requires excessive computational efforts. To alleviate this computational difficulty, an approximation is developed in which the MDOF inelastic system is replaced by a simple nonlinear equivalent system(ENS).Me ENS retains the most important properties of the original system such as dynamic characteristics of the first two modes and the global yielding behavior of the MDOF system. The system response is described by the maximum global(building) and local(interstory) drifts. The equivalency is achieved by two response scaling factors, a global response scaling factor R/sub G/, and a local response scaling factor R/sub L/, applied to the responses of the ENS to match those of the original MDOF system. These response scaling factors are obtained as functions of ductility and mass participation factors of the first two modes of structures by extensive regression analyses based on results of responses of the MDOF system and the ENS to actual ground accelerations recorded in past earthquakes. To develop the ENS with two response scaling factors, Special Moment Resisting Steel Frames are considered. Then, these response scaling factors are applied to the response of ENS to obtain the nonlinear response of MDOF system.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.27 no.3
• /
• pp.199-206
• /
• 2014

In this paper, a scheme to evaluate the response variability for functionally graded material (FGM) beam with varying sectional area is presented. The randomness is assumed to appear in a spatial domain along the beam axis in the elastic modulus. The functionally graded material categorized as composite materials, however without the drawbacks of delamination and occurrence of cracks due to abrupt change in material properties between layers in the conventional composite materials. The functionally graded material is produced by the gradual solidification through thickness direction, which endows continuous variation of material properties, which makes this material performs in a smooth way. However, due to difficulties in tailoring the gradients, to have uncertainty in material properties is unavoidable. The elastic modulus at the center section is assumed to be random in the spatial domain along the beam axis. Introducing random variables, defined in terms of stochastic integration, the first and second moments of responses are evaluated. The proposed scheme is verified by using the Monte Carlo simulation based on the random samples generated employing the spectral representation scheme. The response variability as a function of correlation distance, the effects of material and geometrical parameters on the response variability are investigated in detail. The efficiency of the proposed scheme is also addressed by comparing the analysis time of the proposed scheme and MCS.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.9 no.2
• /
• pp.88-99
• /
• 2007

Soil moisture is one of the essential components in determining surface hydrological processes such as infiltration, surface runoff as well as meteorological, ecological and water quality responses at watershed scale. This paper discusses soil moisture transfer processes measured at hillslope scale in the Gwangneung forest catchment to understand and provide the basis of stochastic structures of soil moisture variation. Measured soil moisture series were modelled based upon the developed univariate model platform. The modeling consists of a series of procedures: pre-treatment of data, model structure investigation, selection of candidate models, parameter estimation and diagnostic checking. The spatial distribution of model is associated with topographic characteristics of the hillslope. The upslope area computed by the multiple flow direction algorithm and the local slope are found to be effective parameters to explain the distribution of the model structure. This study enables us to identify the key factors affecting the soil moisture distribution and to ultimately construct a realistic soil moisture map in a complex landscape such as the Gwangneung Supersite.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.2
• /
• pp.122-131
• /
• 2010

This paper introduces the concept of a virtual ecosystem and reports the following three mathematical approaches that could be widely used to construct such an ecosystem, along with examples: (1) a molecular dynamics simulation approach for animal flocking behavior, (2) a stochastic lattice model approach for termite colony behavior, and (3) a rule-based cellular automata approach for biofilm growth. The ecosystem considered in this study consists of artificial organisms and their environment. Each organism in the ecosystem is an agent that interacts autonomously with the dynamic environment, including the other organisms within it. The three types of model were successful to account for each corresponding ecosystem. In order to accurately mimic a natural ecosystem, a virtual ecosystem needs to take many ecological variables into account. However, doing so is likely to introduce excess complexity and nonlinearity in the analysis of the virtual ecosystem's dynamics. Nonetheless, the development of a virtual ecosystem is important, because it can provide possible explanations for various phenomena such as environmental disturbances and disasters, and can also give insights into ecological functions from an individual to a community level from a synthetic viewpoint. As an example of how lower and higher levels in an ecosystem can be connected, this paper also briefly discusses the application of the second model to the simulation of a termite ecosystem and the influence of climate change on the termite ecosystem.