• Proceedings of the Korean Society for Language and Information Conference
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• 1998.02a
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• pp.195-205
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• 1998

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.457-458
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• 1993

• The Mathematical Education
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• v.62 no.3
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• pp.363-380
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• 2023

This study analyzed the difficulties and mathematical modeling knowledge improvement that an elementary school teacher experienced in modifying a mathematics textbook task to a mathematical modeling task. To this end, an elementary school teacher with 10 years of experience participated in teacher-researcher community's repeated discussions and modified the average task in the data and pattern domain of the 5th grade. The results are as followings. First, in the process of task modification, the teacher had difficulties in reflecting reality, setting the appropriate cognitive level of mathematical modeling tasks, and presenting detailed tasks according to the mathematical modeling process. Second, through repeated task modifications, the teacher was able to develop realistic tasks considering the mathematical content knowledge and students' cognitive level, set the cognitive level of the task by adjusting the complexity and openness of the task, and present detailed tasks through thought experiments on students' task-solving process, which shows that teachers' mathematical modeling knowledge, including the concept of mathematical modeling and the characteristics of the mathematical modeling task, has improved. The findings of this study suggest that, in terms of the mathematical modeling teacher education, it is necessary to provide teachers with opportunities to improve their mathematical modeling task development competency through textbook task modification rather than direct provision of mathematical modeling tasks, experience mathematical modeling theory and practice together, and participate in teacher-researcher communities.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.75-82
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• 2009

In order to help general users to analyze the KOMPSAT-2 data, an application of sensor modeling to commercial software was explained in this document. The sensor modeling is a basic step to extract the quantity and quality information from KOMPSAT-2 data. First, we introduced the contents and type of ancillary data offered with KOMPSAT-2 PAN image data, and explained how to use it with commercial software. And then, we applied the polynomial-base and refine RFM sensor modeling with ground control points. In the polynomial-base sensor modeling, the accuracy which is average RMSE of check points is highest when the satellite position was calculated by type of 1st order function and the satellite attitude was calculated by type of 1st order function for (Y axis), (Z axis) or constant for (X axis), (Y axis), (Z axis) in perspective center position and satellite attitude parameters. As a result of refine RFM sensor modeling, the accuracy is less than 1 pixel when we applied affine model..

• Smart Media Journal
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• v.2 no.2
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• pp.28-32
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• 2013

In this paper, we present a method to reduce complexity of depth modeling modes (DMM) that are used in the current 3D-HEVC standardization. DMM adds four modes to the existing HEVC intra prediction modes for accurate object edge representation in the depth map. Especially, Mode 3 requires distortion calculation of numerous pre-defined wedgelets, inducing high complexity. The proposed method employs absolute differences of neighboring pixels in the sides of the reference block to find high intensity changing positions. Based on such positions, the number of wedgelet candidates is reduced to six and distortion calculation is skipped for irrelevant wedgelets. Experimental results show complexity reduction by 3.1% on average, while maintaining similar coding performance.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.170-178
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• 2012

Dipterocarps or Dipterocarpaceae is a commercially important timber producing and dominant keystone tree family in the rain forests of Borneo. Borneo's landscape is changing at an unprecedented rate in recent years which affects this important biodiversity. This paper attempts to model the natural occurrence (distribution including those areas with natural forests before being converted to other land uses as opposed to current distribution) of dipterocarp species in Sarawak which is important for forest biodiversity conservation and management. Local modeling method of Inverse Distance Weighting was compared with commonly used statistical method (Binary Logistic Regression) to build the best natural distribution models for three genera (12 species) of dipterocarps. Database of species occurrence data and pseudoabsence data were constructed and divided into two halves for model building and validation. For logistic regression modeling, climatic, topographical and edaphic parameters were used. Proxy variables were used to represent the parameters which were highly (p>0.75) correlated to avoid over-fitting. The results show that Inverse Distance Weighting produced the best and consistent prediction with an average accuracy of over 80%. This study demonstrates that local interpolation method can be used for the modeling of natural distribution of dipterocarp species. The Inverse Distance Weighted was proven a better method and the possible reasons are discussed.

• Membrane and Water Treatment
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• v.9 no.5
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• pp.363-371
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• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.448-453
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• 2008

This study describes design and development techniques of estimation models for process modeling. One case study is undertaken to design a model using standard gas furnace data. Neural networks (NN) and genetic programming (GP) are each employed to model the crucial relationships between input factors and output responses. In the case study, two models were generated by using 70% training data and evaluated by using 30% testing data for genetic programming and neural network modeling. The model performance was compared by using RMSE values, which were calculated based on the model outputs. The average RMSE for training and testing were 0.8925 (training) and 0.9951 (testing) for the NN model, and 0.707227 (training) and 0.673150 (testing) for the GP model, respectively. As concern the results, the NN model has a strong advantage in model training (using the all data for training), and the GP model appears to have an advantage in model testing (using the separated data for training and testing). The performance reproducibility of the GP model is good, so this approach appears suitable for modeling physical fabrication processes.

• The Journal of the Acoustical Society of Korea
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• v.22 no.1
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• pp.23-27
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• 2003

Recently attempts to we the syllable as the recognition unit to enhance performance in continuous speech recognition hate been reported. However, syllables are worse in their trainability than phones and the former have a disadvantage in that contort-dependent modeling is difficult across the syllable boundary since the number of models is much larger for syllables than for phones. In this paper, we propose a method to enhance the trainability for the syllables in Korean and phoneme-context dependent syllable modeling across the syllable boundary. An experiment in which the proposed method is applied to word recognition shows average 46.23% error reduction in comparison with the common syllable modeling. The right phone dependent syllable model showed 16.7% error reduction compared with a triphone model.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.293-297
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• 2006

Submarine groundwater discharge (SGD) and the interface between seawater and freshwater in an unconfined coastal aquifer was evaluated by numerical modeling. A two-dimensional vertical cross section of the aquifer was constructed. Coupled flow and salinity transport modeling were peformed by using a numerical code FEFLOW In this study, we investigated the changes in groundwater flow and salinity transport in coastal aquifer with hydraulic condition such as the magnitude of recharge flux, hydraulic conductivity. Especially, transient simulation considering tidal effect and seasonal change of recharge rate was simulated to compare the difference between quasi-steady state and transient state. Results show that SGD flux is in proportion to the recharge rate and hydraulic conductivity, and the interface between the seawater and the freshwater shows somewhat retreat toward the seaside as recharge flux increases. Considered tidal effect, SGD flux and flow directions are affected by continuous change of the sea level and the interface shows more dispersed pattern affected by velocity variation. The cases which represent variable daily recharge rate instead of annual average value also shows remarkably different result from the quasi-steady case, implying the importance of transient state simulation.