• Research in Mathematical Education
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• v.20 no.1
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• pp.11-19
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• 2016

Investigating students' lived mathematical experiences presents dual challenges for the researcher. On the one hand, we must respect that students' experiences are not directly accessible to us and are likely very different from our own experiences. On the other hand, we might not want to rely upon the students' own characterizations of what constitutes mathematics because these characterizations could be limited to the formal products students learn in school. I suggest a characterization of mathematics as objectified action, which would lead the researcher to focus on students' operations-mental actions organized as objects within structures so that they can be acted upon. Teachers' and researchers' models of these operations and structures can be used as a launching point for understanding students' experiences of mathematics. Teaching experiments and clinical interviews provide a means for the teacher-researcher to infer students' available operations and structures on the basis of their physical activity (including verbalizations) and to begin harmonizing with their mathematical experience.

• Research in Mathematical Education
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• v.26 no.3
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• pp.253-270
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• 2023

This study aims to investigate the extent to which Korean high school textbooks incorporate opportunities for students to engage in the mathematical modeling process through tasks related to exponential and logarithmic functions. The tasks in three textbooks were analyzed based on the actions required for each stage in the mathematical modeling process, which includes identifying essential variables, formulating models, performing operations, interpreting results, and validating the outcomes. The study identified 324 units across the three textbooks, and the reliability coefficient was 0.869, indicating a high level of agreement in the coding process. The analysis revealed that the distribution of tasks requiring engagement in each of the five stages was similar in all three textbooks, reflecting the 2015 revised curriculum and national curriculum system. Among the 324 analyzed tasks, the highest proportion of the units required performing operations found in the mathematical modeling process. The findings suggest a need to include high-quality tasks that allow students to experience the entire process of mathematical modeling and to acknowledge the limitations of textbooks in providing appropriate opportunities for mathematical modeling with a heavy emphasis on performing operations. These results provide implications for the development of mathematical modeling activities and the reconstruction of textbook tasks in school mathematics, emphasizing the need to enhance opportunities for students to engage in mathematical modeling tasks and for teachers to provide support for students in the tasks.

• Proceedings of the Microbiological Society of Korea Conference
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• 2008.05a
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• pp.150-155
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• 2008

• Journal of Korean Society of Transportation
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• v.7 no.1
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• pp.5-18
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• 1989

Understanding the future level of car ownership is essential in order to formulate various transportation policies. Despite its importance, however, a revies of literature indicates that previous studies treated car ownership as a linear function of income, GNP, degree of urbanization and etc. more detaild and accurate models of car ownership should be possible if information on major variables determining car ownership can be gathered. In this paper, three approaches have been chosen to develop mathematical models to predict future increase in car ownership in Korea. The three methords developed are : income distribution methords ; multiple regression models ; forecasting curves.

• Journal of the Korean Institute of Navigation
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• v.23 no.2
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• pp.11-22
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• 1999

This paper is concerned with the development of a tractable model to assist liner shipping companies in the decision-making of empty container repositioning and leasing. A hybrid methodology is presented which properly accounts for the specific characteristics of empty container management. For this mathematical models are developed based on dynamic network models, covering both land and marine segment. Then a stochastic method is presented to deal with the uncertainty of the future demand and supply. Especially, the concept of opportunity cost has been introduced in order to explain interactions between the variation of the future demand and supply and the stock level at each depot.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.4-146
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• 2001

Various methods have been proposed for the time series prediction. Most of the conventional methods only optimize parameters of mathematical models, but to construct an appropriate functional form of the model is more difficult in the first place. We employ the Genetic Programming (GP) to construct the functional form of prediction models. Our method is distinguished because the model parameters are optimized by using Back-Propagation (BP)-like method and the prediction model includes discontinuous functions, such as if and max, as node functions for describing complicated phenomena. The above-mentioned functions are non-differentiable, but the BP method requires derivative. To solve this problem, we develop ...

• The Pure and Applied Mathematics
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• v.24 no.4
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• pp.211-226
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• 2017

In this paper, machine learning models employed in various fields are discussed and applied to KOSPI200 stock index return forecasting. The results of hyperparameter analysis of the machine learning models are also reported and practical methods for each model are presented. As a result of the analysis, Support Vector Machine and Artificial Neural Network showed a better performance than k-Nearest Neighbor and Random Forest.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.2012-2015
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• 2010

In this paper, the mathematical models of the superheater and the desuperheater are derived based on the fundamental laws of physics, mass and energy balance. The parameters of the models are developed for the 500[MW] thermal power plant using the actual data. The simulated model outputs are well matched with the actual ones. It is expected that the proposed models are useful for the temperature controller design of the thermal power plant.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.22-29
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• 2008

In order to improve the efficiency of a main transformer in a tilting train, the optimal operation of a cooling system is necessary. For the development of optimal control algorithms of a cooling system, mathematical models of a main transformer cooling system were developed. These include dynamic models of a main transformer, an oil pump, an oil cooler, a blower, and a pipe. Control algorithms for a blower and an oil pump were selected in order to identify the effectiveness of dynamic models. A simulation program was developed by using the developed dynamic models and the selected control algorithms. Simulation results showed good predictions of dynamic behaviors of a main transformer cooling system. Therefore, dynamic models, which were developed in this study, may be effectively used to develop control algorithms of a main transformer cooling system.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.31-45
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• 2013

PURPOSES : Determination of particle packing model variables that can be used for formulation of new DEM based particle packing model by examining existing particle packing models METHODS : Existing particle packing models are thoroughly examined by analytical reformulation and sensitivity analysis in order to set up DEM based new particle packing model and to determine its variables. All model equations considered in this examination are represented with consistent expressions and are compared to each others to find mathematical and conceptual similarity in expressions. RESULTS : From the examination of existing models, it is observed that the models are very similar in their shapes although the derivation of the models may be different. As well, it is observed that variables used in some existing models are comprehensive enough to estimate particle packing but not applicable to DEM simulation. CONCLUSIONS : A set of variables that can be used in DEM based particle packing model is determined.