• School Mathematics
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• v.19 no.1
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• pp.189-208
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• 2017

The purpose of this study is to capture and explain the roles that signs and attention play in the fraction learning process, through a previous study that employs Deleuze's perspective on sign and the role of attention. From this case study of elementary school students, we found that signs are a prerequisite for learning and that learning takes place as different forms of attention shifts. The various types of semiotic resources used by teachers and students have been found to play an important role in coordinating collective attention between teachers and students.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.182-186
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• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• Education of Primary School Mathematics
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• v.19 no.1
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• pp.31-45
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• 2016

In this study, the case of error became the object of learning, and the investigator applied these cases to an actual class and established three study problems in order to achieve the purpose of this study. The results of analysis of students' errors in figure based on before achievement test are shown as follows: First, the most errors occurred in the figure was the ones from deficient mastery of prerequisite concepts and definitions. Specially, the errors from deficient mastery of prerequisite concepts and definitions have the majority. it is very high ratio even if it considers an influence of an evaluation question item. so, I think it is necessary to teach concept related figure above all. Second, as the results of application 'finding errors' to a class, there is a meaningful difference in the mathematical achievement and reasoning ability within significance level 5%. This means 'finding errors' is one of the teaching method that it develops the mathematical achievement and reasoning ability.

• Journal of the Korean Institute of Educational Facilities
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• v.23 no.1
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• pp.3-12
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• 2016

This thesis examines the shape, organization, background, and significance of the classroom space in highly appraised elementary schools since the inauguration of public education in modern times in the fields of education or architecture. This thesis acknowledges that classroom shapes comprise an auditorium-like space for a large-scale study group, a square-shaped classroom designed for simultaneous teaching for single class, and bent and L-shaped classrooms for various learning activities. Whereas the square-shaped classroom for simultaneous teaching which has lasted until now evolved around 1870, the post-1930s era witnessed the emergence of a composition in which classroom and outside space are associated, of an atypical classroom, and of Functional Unit where common space and classrooms are assembled. It is deemed that the emergence of the atypical classroom comes from the reinterpretation of learning and space pursuant to progressive pedagogical philosophy and child development theories and functional architecture theories. Thus, this thesis verifies that school construction and learning space can be newly created and the synthesis between education, child development studies, and architecture is a prerequisite to such a creation.

• East Asian mathematical journal
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• v.39 no.2
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• pp.93-117
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• 2023

The aim of this study is to explore the pre-service math teachers' characteristics of education to develop their AI literacy and SW competency, and to derive some implications. We conducted a 14-hours AI and SW education program for pre-service teachers with theory and practice, and an analysis on class observation data, video frames of classes and interview, Python programming assignments and papers. The results of this case study for 3 pre-service teachers are as follows. First, two students understood artificial neural network and deep learning system accurately, furthermore, all students conducted a couple of explorations related with performance improvement of deep learning system with interest. Second, coding and exploration activities using Python improved students' computational thinking as well as SW competency, which help them give convergence education in the future. Third, they responded positively to the necessity of AI literacy and SW competency development, and to applying coding to math class. Lastly, it's necessary to endeavor to give a coding education to the student's eye level according to his or her prerequisite and to ease the burden of student's studying AI technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

• Journal of Korean Home Economics Education Association
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• v.31 no.1
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• pp.77-88
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• 2019

This study was to execute the flipped learning as a learner-centered teaching and learning method in the course on family living culture for home economics education students in a college of education, and to investigate its effect. Flipped learning was designed in three stages(Pre class/In class/After class), and a questionnaire survey was distributed to 40 students to measure the class satisfaction. In addition, class worksheets and reflection journals that students wrote after every class were analyzed. Students positively evaluated flipped learning because they could take non-competition class with questions and discussion, etc. escaping from a one-way lecture. This study found that the level of class satisfaction was high due to high learning effect as the dual learning was available in case of prerequisite learning or individual learning. In particular, the class using Visual Thinking was considered interesting and useful in understanding and summarizing the learning contents. This study has shown that the willingness to take other flipped learning class in their major was high. To conclude, this study has found positive learning effects in the learner-centered teaching and learning method or flipped learning for the course concerning family living culture. This researcher expects that flipped learning may be utilized in the secondary education in the future as an effective learner-centered teaching and learning method for the purpose of fostering talents for the future in the era of the fourth industrial revolution.

• Journal of Gifted/Talented Education
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• v.24 no.6
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• pp.897-916
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• 2014

In this study, we presented a teaching-learning method that can apply process-focused assessment for mathematical creativity of problem solving process of the gifted student, By necessity of appropriate teaching-learning program development to the level and ability of students who belong to high school gifted classes and courses evaluation for students who participated in education programs for the gifted. In the construction implementation process of students utilizing a kind of teaching-learning software, GeoGebra. We analyzed process of a variety of creative constructing figures using interfaces of GeoGebra and algebraic calculation. Utilizing 'Construction Protocol' and 'Navigation Bar' of GeoGebra, We identified computer languages, construction order, run times used in construction process of individual student and found mathematical creativity of students in the process. Comparing this result with prerequisite learning degree of individual student, We verified that this teaching-learning method can apply at the high school gifted classes as well as institutes for the gifted education in the city office.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1037-1048
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• 2022

A radioactive isotope identification algorithm is a prerequisite for a low-resolution scintillation detector applied to an unmanned radiation monitoring system. In this paper, a sparse representation with dictionary learning approach is proposed and applied to plastic gamma-ray spectra. Label-consistent K-SVD was used to learn a discriminative dictionary for the spectra corresponding to a mixture of four isotopes (¹³³Ba, ²²Na, ¹³⁷Cs, and ⁶⁰Co). A Monte Carlo simulation was employed to produce the simulated data as learning samples. Experimental measurement was conducted to obtain practical spectra. After determining the hyper parameters, two dictionaries tailored to the learning samples were tested by varying with the source position and the measurement time. They achieved average accuracies of 97.6% and 98.0% for all testing spectra. The average accuracy of each dictionary was above 96% for spectra measured over 2 s. They also showed acceptable performance when the spectra were artificially shifted. Thus, the proposed method could be useful for identifying radioisotopes in gamma-ray spectra from a plastic scintillation detector even when a dictionary is adapted to only simulated data. Furthermore, owing to the outstanding properties of sparse representation, the proposed approach can easily be built into an insitu monitoring system.

• Journal of the Korean School Mathematics Society
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• v.10 no.2
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• pp.187-206
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• 2007

The purpose of this study is to know what is the difficulties that mathematics underachievers are suffering from the area of mathematical function and how to overcome this difficulties. For this study, we have selected two mathematics underachievers and carried out the inspection. The mathematics underachievers have undergone the difficulties of understanding mathematical problems, the difficulties from the deficit of prerequisite and basic learning, the difficulties of finding the answer typically and the difficulties of classifying an algebraic symbol, the difficulties of calculating the gradient of the straight line passing through two points.