• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.10
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• pp.872-881
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• 2012

The Flight Model (FM) of a high-resolution electro-optical camera (EOS-C Ver.3.0), the mission payload of an Earth observation satellite, was successfully developed by Satrec Initiative. We designed it to give improved thermal representatives compared with the Structural-Thermal Model (STM) by optimizing the thermal characteristics based on the STM thermal vacuum test results. We developed the FM and verified the workmanship by performing the acceptance level thermal vacuum test. We also conducted the verification of its Thermal Mathematical Model (TMM) by the thermal balance test. As the result, it was confirmed that TMM faithfully represents the thermal characteristics of the EOS-C Ver.3.0 FM.

• Journal of Educational Research in Mathematics
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• v.24 no.2
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• pp.103-124
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• 2014

The process of analogical reasoning can be conventionally summarized in five steps : Representation, Access, Mapping, Adaptation, Learning. The purpose of this study is to develop more detailed model for reason of analogies considering the distinct characteristics of the mathematical education based on the process of analogical reasoning which is already established. Ultimately, This model is designed to facilitate students to use analogical reasoning more productively. The process of developing model is divided into three steps. The frist step is to draft a hypothetical model by looking into historical example of Leonhard Euler(1707-1783), who was the great mathematician of any age and discovered mathematical knowledge through analogical reasoning. The second step is to modify and complement the model to reflect the characteristics of students' thinking response that proves and links analogically between the law of cosines and the Pythagorean theorem. The third and final step is to draw pedagogical implications from the analysis of the result of an experiment.

• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.315-321
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• 1999

The purpose of this study is to develop a mathematical model for system identification in order to predIct muscle force based on eledromyographic signal. Therefore, a finding of the relalionship between characteristics of electromyographic signal and the corre spondng muscle force should be necessiiry through dynamic, joint model. To develop the dynamic joint model, the upper limb mcludmg the wrist and elbow joint has been considered. The kinematic and dynamic data, such as joint angular displacement, velocity, deceleration along with the moment of inertla, required to establish the dynamic model has been obtained by electrical flexible goniometer which has two degree-of-frcedoms. ln this model, muscle force can be predicted only electromyographs through the relationship between the integrated lorce and the mtegrated electromyographic signal over the duration of muscle contraclion in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.45-54
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• 2006

To obtain realistic stress-strain relation in concrete, it is necessary to improve the constitutive model for creep and shrinkage of concrete. This study is made up with predicting model of creep using rheological approach and mathematical development which is solution for phenomenon of concrete creep. Long-term deformation components are combined based on traditional 4-parameters model. Creep deformation is obtained adequately using 4-parameters determined by considering aging effect and microprestress among gels. And coefficient of effective viscosity is able to represent both basic creep and total creep included drying creep. This study attempt to establish mathematical model considering effects of aging, hydration, and variations of pore humidity. It can predict both basic creep and total creep. Values of result between prediction and experiment have greater than correlation factor 99%. Additionally experimental results report bad consentaneity with highway design specification adopting FIB MC 90. Rather than those are similar to FIB MC 90 rev.99.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.21-45
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• 2023

This study presents a machine learning program designed to identify impactful papers in the field of mathematics education. To achieve this objective, we examined the impact of papers from a scientific econometrics perspective, developed a mathematics education research network, and defined the impact of mathematics education research using PageRank, a network centrality index. We developed a machine learning model to determine the impact of mathematics education research and identified the journals with the highest percentage of impactful articles to be the Journal for Research in Mathematics Education (25.66%), Educational Studies in Mathematics (22.12%), Zentralblatt für Didaktik der Mathematik (8.46%), Journal of Mathematics Teacher Education (5.8%), and Journal of Mathematical Behaviour (5.51%). The results of the machine learning program were similar to the findings of previous studies that were read and evaluated qualitatively by experts in mathematics education. Significantly, the AI-assisted impact evaluation of mathematics education research, which typically requires significant human resources and time, was carried out efficiently in this study.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.10b
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• pp.883-887
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• 1998

Hydration is the main reason for the growth of the material properties. A exact parameter to control the chemical and physical process is not the time, but the degree of hydration. Therefore, it is reasonable that development all material properties should be formulated in terms of degree of hydration. Mathematical formulation of degree of hydration is based on combination of reaction rate functions. The effect of moisture conditions as well as temperature on the rate of reaction is considered in the degree of hydration model. This effect is subdivided into two contributions: water shortage and water distribution. The former is associated with the effect of on the progress of hydration. The water needed for progress of hydration do not exist and there is not enough space for the reaction products to form. The latter is associated with the effect of free capillary water distribution in the pore system. Physically absorption layer does not contribute to progress of hydration and only free water is available for further hydration.

• The Mathematical Education
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• v.42 no.3
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• pp.303-325
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• 2003

This study sought to provide an explanation of university students' concept understanding on the infinity and infinite process and utilized a psychological constructivist perspective to examine the differences in transitions that students make from static concept of limit to actualized infinity stage in context of problems. Open-ended questions were used to gather data that were used to develop an explanation concerning student understanding. 47 university students answered individually and were asked to solve 16 tasks developed by Petty(1996). Microgenetic method with two cases from the expert-novice perspective were used to develop and substantiate an explanation regarding students' transitions from static concept of limit to actualized infinity stage. The protocols were analyzed to document student conceptions. Cifarelli(1988)'s levels of reflective abstraction and Robert(1982) and Sierpinska(1985)'s three-stage concept development model of infinity and infinite process provided a framework for this explanation. Students who completed a transition to actualized infinity operated higher levels of reflective abstraction than students who was unable to complete such a transition. Developing this ability was found to be critical in achieving about understanding the concept of infinity and infinite process.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.5
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• pp.67-74
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• 2019

In this paper, mathematical models of a simulation code are presented. The simulation code was developed for the startup analysis of an open cycle liquid rocket engine (LRE). Most of the components comprising an LRE, including the priming process in the propellant feeding line, were considered. A startup simulation of a 75-tonf LRE, which was used for the KSLV-II test launch vehicle (TLV), was performed. The simulation results showed good agreement with the engine acceptance test results, thus proving the validity of the startup simulation code.

• International Journal of Reliability and Applications
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• v.4 no.4
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• pp.183-190
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• 2003

Rail breaks and derailments can cause a huge loss to rail players due to loss of service, revenue, property or even life. Maintenance has huge impact on reliability and safety of railroads. It is important to identify factors behind rail degradation and their risks associated with rail breaks and derailments. Development of mathematical models is essential for prediction and prevention of risks due to rail and wheel set damages, rail breaks and derailments. This paper addresses identification of hazard modes, estimation of probability of those hazards under operating, curve and environmental condition, probability of detection of potential hazards before happening and severity of those hazards for informed strategic decisions. Emphasis is put on optimal maintenance and operational decisions. Real life data is used for illustration.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.