• Communications of Mathematical Education
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• v.33 no.4
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• pp.471-488
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• 2019

This paper aims to examine how mathematical history is used in $ textbooks according to the 2015-Revised Curriculum. We analyze the distribution and characteristics of making use of the mathematical history in the nine textbooks, using the framework suggested by Jankvist (2009) on the whys and hows of using historical tasks. First, the tasks related to mathematical history in the textbooks are mostly used as an affective tool, while few tasks are used as a cognitive tool. Second, most of the historical tasks of the type of an affective tool are introducing the anecdotes of mathematicians or in the history of mathematics, and only one case is trying to show human nature of mathematics by illuminating the difficulties mathematicians were faced with. Third, all the mathematical history tasks used as affective tools and goals are illumination materials, while only two out of the ten tasks in the category of a cognitive tool are illumination materials, yet eight others are modular ones. Considering the importance and value of using mathematical history in the math education, this paper recommends that more modular materials on mathematical history tasks in the category of cognitive tools and goals should be developed and their deployment in the textbooks or courses should be promoted. $

• Journal of Elementary Mathematics Education in Korea
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• v.6 no.1
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• pp.23-40
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• 2002

Historically, the use of algorithms has been emphasized in the mathematics curriculum at the elementary school mathematics. The current reform movement in our country are seemed to emphasize the importance of algorithms in favor of problem-solving approaches, the conceptualization of mathematical processes and applications of mathematics in real world situations. Recently, children may come to school with a fairly well-developed attitude about mathematics and mathematical ideas. That is, they do not come to school and to learning mathematics with a clean slate. Because they have already formed some partial mathematical concepts in a wide variety of contexts. Many kindergarten children have attended pre-school programs where they played with blocks, made patterns, and started adding and subtracting. It seems that there are psychological change attitudes of the children in upper grades toward learning mathematics. In our elementary school mathematics, almost every student are still math anxious or have developed math anxiety because of paper-pencil test. In these views, this paper is devoted to introduce and apply to second grade students in ND-elementary school in Taegu City the new method for learning addition and subtraction so called ‘Mrs Weill's Hill’, which is believed as a suitable method for children with mathematical teaming disabilities and Math anxiety.

• The Mathematical Education
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• v.50 no.2
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• pp.213-231
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• 2011

The purpose of this study is to analyze the 6th graders' understanding of the concepts of variable on various aspects of school algebra. For this purpose, the test of concepts of variable targeting a sixth-grade class was conducted and then two students were selected for in-depth interview. The level of mathematics achievement of the two students was not significantly different but there were differences between them in terms of understanding about the concepts of variable. The results obtained in this study are as follows: First, the students had little basic understanding of the variables and they had many cognitive difficulties with respect to the variables. Second, the students were familiar with only the symbol '${\Box}$' not the other letters nor symbols. Third, students comprehended the variable as generalizers imperfectly. Fourth, the students' skill of operations between letters was below expectations and there was the student who omitted the mathematical sign in letter expressions including the mathematical sign such as x+3. Fifth, the students lacked the ability to reason the patterns inductively and symbolize them using variables. Sixth, in connection with the variables in functional relationships, the students were more familiar with the potential and discrete variation than practical and continuous variation. On the basis of the results, this study gives several implications related to the early algebra education, especially the teaching methods of variables.

• The Mathematical Education
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• v.58 no.3
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• pp.367-381
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• 2019

This investigation engaged elementary and middle school pre-service teachers in a task of modeling and explaining the magnitude of $0.14m^2$ and examined their responses. The study analyzed both successful and unsuccessful responses in order to reflect on the patterns of misconceptions relative to pre-service teachers' prior knowledge. The findings suggest a need to promote opportunities for pre-service teachers to make connections between different domains through meaningful tasks, to reason abstractly and quantitatively, to use proper language, and to refine conceptual understanding. While mathematics teacher educators (MTEs) could use such mathematical tasks to identify the mathematical content needs of pre-service teachers, MTEs generally use instructional time to connect content and pedagogy. More importantly, an early and consistent exposure to a combined experience of mathematics and pedagogy that connects and deepens key concepts in the program's curriculum is critical in defining the important content knowledge for K-8 mathematics teachers.

• Advances in nano research
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• v.16 no.6
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• pp.623-638
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• 2024

This study investigates the thermal post-buckling behavior of concrete eccentric annular sector plates reinforced with graphene oxide powders (GOPs). Employing the minimum total potential energy principle, the plates' stability and response under thermal loads are analyzed. The Haber-Schaim foundation model is utilized to account for the support conditions, while the transform differential quadrature method (TDQM) is applied to solve the governing differential equations efficiently. The integration of GOPs significantly enhances the mechanical properties and stability of the plates, making them suitable for advanced engineering applications. Numerical results demonstrate the critical thermal loads and post-buckling paths, providing valuable insights into the design and optimization of such reinforced structures. This study presents a machine learning algorithm designed to predict complex engineering phenomena using datasets derived from presented mathematical modeling. By leveraging advanced data analytics and machine learning techniques, the algorithm effectively captures and learns intricate patterns from the mathematical models, providing accurate and efficient predictions. The methodology involves generating comprehensive datasets from mathematical simulations, which are then used to train the machine learning model. The trained model is capable of predicting various engineering outcomes, such as stress, strain, and thermal responses, with high precision. This approach significantly reduces the computational time and resources required for traditional simulations, enabling rapid and reliable analysis. This comprehensive approach offers a robust framework for predicting the thermal post-buckling behavior of reinforced concrete plates, contributing to the development of resilient and efficient structural components in civil engineering.

• Journal of Microbiology and Biotechnology
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• v.17 no.3
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• pp.496-510
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• 2007

This paper describes the use of a discrete mathematical model to represent the basic mechanisms of regulation of the bacteria E. coli in batch fermentation. The specific phenomena studied were the changes in metabolism and genetic regulation when the bacteria use three different carbon substrates (glucose, glycerol, and acetate). The model correctly predicts the behavior of E. coli vis-a-vis substrate mixtures. In a mixture of glucose, glycerol, and acetate, it prefers glucose, then glycerol, and finally acetate. The model included 67 nodes; 28 were genes, 20 enzymes, and 19 regulators/biochemical compounds. The model represents both the genetic regulation and metabolic networks in an integrated form, which is how they function biologically. This is one of the first attempts to include both of these networks in one model. Previously, discrete mathematical models were used only to describe genetic regulation networks. The study of the network dynamics generated 8 $(2^3)$ fixed points, one for each nutrient configuration (substrate mixture) in the medium. The fixed points of the discrete model reflect the phenotypes described. Gene expression and the patterns of the metabolic fluxes generated are described accurately. The activation of the gene regulation network depends basically on the presence of glucose and glycerol. The model predicts the behavior when mixed carbon sources are utilized as well as when there is no carbon source present. Fictitious jokers (Joker1, Joker2, and Repressor SdhC) had to be created to control 12 genes whose regulation mechanism is unknown, since glycerol and glucose do not act directly on the genes. The approach presented in this paper is particularly useful to investigate potential unknown gene regulation mechanisms; such a novel approach can also be used to describe other gene regulation situations such as the comparison between non-recombinant and recombinant yeast strain, producing recombinant proteins, presently under investigation in our group.

• Advances in nano research
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• v.9 no.3
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• pp.211-220
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• 2020

This paper investigates the effect of linear and non-linear distribution of carbon nanotube volume fraction in the FG-CNTRC beams on the critical buckling by using higher-order shear deformation theories. Here, the material properties of the CNTRC beams are assumed to be graded in the thickness direction according to a new exponential power law distribution in terms of the carbon nanotube volume fractions. The single-walled carbon nanotube is aligned and distributed in the polymeric matrix with different patterns of reinforcement; the material properties of the CNTRC beams are described by using the rule of mixture. The governing equations are derived through using Hamilton's principle. The Navier solution method is used under the specified boundary conditions for simply supported CNTRC beams. The mathematical models provided in this work are numerically validated by comparison with some available results. New results of critical buckling with the non-linear distribution of CNT volume fraction in different patterns are presented and discussed in detail, and compared with the linear distribution. Several aspects of beam types, CNT volume fraction, exponent degree (n), aspect ratio, etc., are taken into this investigation. It is revealed that the influences of non-linearity distribution in the beam play an important role to improve the mechanical properties, especially in buckling behavior. The results show that the X-Beam configuration is the strongest among all different types of CNTRC beams in supporting the buckling loads.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.237-248
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• 2010

When scenes in the real world are perceived for the purpose of computer/robot vision fields, there are great deals of texture based patterns in them. This paper introduces a texture feature representation on a coordinate system in which many different patterns can be represented with a mathematical model (Gabor function). The representation of texture features of each pattern on the coordinate system results in the high performance/competence of texture pattern classification. A decision tree algorithm is used to classify pattern data represented on the proposed coordinate system. The experimental results for the texture pattern classification show that the proposed method is better than previous researches.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.239-244
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• 2011

In this paper, we analyzed the electrical characteristics with crack pattern in crystalline solar cell. crystalline solar cells with a thin substrate, even small shocks can be easily damaged. Before the module goes through many processes, because the solar cells are at risk of a crack. That occurred early in the PV module micro-crack is not easily detection by eye test or output test. Because the EL (Electroluminescence) device has been detected using. PV module is made by laminated of a variety of materials. By different properties of each material will affect the crack. For this reason, the crack will grow and affect the output. And We analyzed the three crack patterns in crystalline solar cell. A growth of cracks on crystalline solar cell was interpreted by analysing generated cracks on the PV modules. Based on this interpretation, an electrical output value was calculated by mathematical modeling on electrical output characteristic with each crack patterns.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.391-406
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• 2014

The performance of General-Purpose computation on Graphics Processing Units (GPGPU) is heavily dependent on the memory access behavior. This sensitivity is due to a combination of the underlying Massively Parallel Processing (MPP) execution model present on GPUs and the lack of architectural support to handle irregular memory access patterns. Application performance can be significantly improved by applying memory-access-pattern-aware optimizations that can exploit knowledge of the characteristics of each access pattern. In this paper, we present an algorithmic methodology to semi-automatically find the best mapping of memory accesses present in serial loop nest to underlying data-parallel architectures based on a comprehensive static memory access pattern analysis. To that end we present a simple, yet powerful, mathematical model that captures all memory access pattern information present in serial data-parallel loop nests. We then show how this model is used in practice to select the most appropriate memory space for data and to search for an appropriate thread mapping and work group size from a large design space. To evaluate the effectiveness of our methodology, we report on execution speedup using selected benchmark kernels that cover a wide range of memory access patterns commonly found in GPGPU workloads. Our experimental results are reported using the industry standard heterogeneous programming language, OpenCL, targeting the NVIDIA GT200 architecture.