• Journal of The Korean Association For Science Education
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• v.37 no.6
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• pp.1025-1035
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• 2017

The purposes of this study are to analyze the merits and limits of flipped learning by suggesting the ALP model for efficient application and to test the effects of the new ALP model. The process of new model and program development is based on ADDIE in this study. This study consists of two steps. First through literature research on the difficulties of the flipped learning, the elements are extracted to develop new model. Second, these elements were placed according to the teaching and learning flow, which resulted in the procedures. As a result, the ALP model was developed. The ALP model is a new model for applying teaching and learning methods for efficient application of the flipped learning. This model was applied to elementary science classes to test its effects in scientific communication skill. Interviews and cognitive survey were also conducted to collect additional information. The results of this study are as follows: There were various difficulties in flipped learning. Based on literature research results, the ALP model and the science programs for elementary students have been developed. The experimental group showed statistically meaningful improvement in scientific communication skill. The scientific communication skill has two subcategories: the forms and the types. According to the form analysis results, the experimental group showed a statistically meaningful improvement in the form of Table and Picture, but not in the form of Writing and Number. With the same reason given previously, this study confirmed that the application of ALP model improves the students' visual form communication skills such as Table and Picture better than reading form communication skills such as Writing and Number. According to the type analysis results, the experimental group showed a statistically meaningful improvement in "the scientific insistence" type, and "the justification" which is the sub element of "the scientific insistence" type. With this reason, this study suggests that the class applied ALP model gives students more time and opportunities to learn. Though the survey and interviews about the student's awareness of the class with applied the ALP model, this study showed that students actively exchanged their opinions in the class with applied ALP model.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.486-491
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• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.

• Research in Mathematical Education
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• v.17 no.1
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• pp.1-14
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• 2013

Stochastic phenomena induce us to construct a probability model and structure our thinking; corresponding models help us to understand and interpret the reality. They in turn equip us with tools to recognize, reconstruct and solve problems. Therefore, various implications in terms of methodology as well as epistemology naturally flow from different adoptions of models for probability. Right from the basic scenarios of different perspectives to explore reality, students are occasionally exposed to misunderstanding and misinterpretations. With realistic examples a multi-faceted image of probability and different interpretation will be considered in mathematical modelling activities. As an exploratory investigation, mathematical modelling activity for probability learning was elaborated through semiotic analysis. Especially, the coherence structure in mathematical modelling discourse was reviewed form a semiotic perspective. The discourses sampled from group activities were analyzed on the basis of semiotic perspectives taxonomical coherence relations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.709-722
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• 2014

In the $21^{st}$ century, IT reform has led to the development of cyber-infrastructure owing to the outstanding enhancement of computer and network performance. The ripple effect has continued to increase. Accordingly, this study suggests a new computational research environment using mobile devices. In order to simplify the access of supercomputer, Science AppStore, task management and virtualization technologies are developed on mobile devices. User can be able to research by utilizing computational science SW such as compressible flow solver and nano device simulation tool that in installed on supercomputer in mobile environments. Also, this research environment makes it possible to monitor the simulation result and covers 14 university, 33 subjects, and 1,202 individuals.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.419-426
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• 1999

A novel motion analysis system is presented in this paper. The proposed system is inspired by processing functions observed in the fly visual system, which detects changes in input light intensities, determines motion on both the local and the wide-field levels. The system has several differences from conventional motion analysis system. First, conventional systems usually focused on matching similar feature or optical flow, but neural network is applied in this system. Back propagation is used by learning method, and Tine Delay Neural Network (TDNN) is also used as analysis method. Second, while conventional systems usually limited on only two frames of sequence, the proposed system accept multiple frames of sequence. The experimental results showed a 94.7% correct rate with a speed of 71.47 milli seconds for real and synthetic images.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.2
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• pp.69-77
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• 2001

An artificial neural network model was developed to analyze and forecast daily steamflow flow a small watershed. Error Back propagation neural networks (EBPN) of daily rainfall and runoff data were found to have a high performance in simulating stremflow. The model adopts a gradient descent method where the momentum and adaptive learning rate concepts were employed to minimize local minima value problems and speed up the convergence of EBP method. The number of hidden nodes was optimized using Bayesian information criterion. The resulting optimal EBPN model for forecasting daily streamflow consists of three rainfall and four runoff data (Model34), and the best number of the hidden nodes were found to be 13. The proposed model simulates the daily streamflow satisfactorily by comparison compared to the observed data at the HS#3 watershed of the Baran watershed project, which is 391.8 ha and has relatively steep topography and complex land use.

• Proceedings of the KAIS Fall Conference
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• 2011.05b
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• pp.1037-1040
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• 2011

본 연구는 B시의 요양보호사 교육원의 교육생 230명을 대상으로 학습동기가 학습몰입에 미치는 영향을 알아보고자 하였다. 내재적 학습동기와 외재적 학습동기가 학습몰입과 상관관계를 가지고 있었으며, 학습과제에 대한 몰입은 학습동기가 증가될수록 높아지는 성향을 나타내었다. 그러나 외제적 학습동기보다 내재적 학습동기가 학습몰입과 더 높은 상관관계를 가지고 있는 것으로 나타났다. 따라서, 학습몰입은 내재적 학습 동기 뿐 아니라 사회적 성공동기와 상대적 유능성 동기와 같은 외재적 동기와도 부분적인 상관관계를 나타내고 있었다. 요양보호사 인력양성의 발전을 요양보호사 교육에 대한 다각적인 측면의 연구가 필요한 것으로 보인다.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.415-418
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• 1996

Etching Process, one of the most important process in semiconductor fabrication, has input control part of which components are pressure, gas flow, RF power and etc., and plasma gas which is complex and not exactly understood is used to etch wafer in etching chamber. So this process has not real-time feedback controller based on input-output relation, then it uses EPD(End Point Detection) signal to determine when to start or when to stop etching. Various type EPD controller control etching process using EPD signal obtained from optical intensity of etching chamber. In development EPD controller we concentrate on compensation of this signal intensity and setting the relative signal magnitude at first of etching. We compensate signal intensity using neural network learning method and set the relative signal magnitude using fuzzy inference method. Potential of this method which improves EPD system capability is proved by experiences.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1100-1106
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• 2004

In this report, a self-organizing fuzzy neural network is proposed to control chemical feeding, which is one of the most important problems in water treatment process. In the case of the learning according to raw water quality, the self-organizing fuzzy network, which can be driven by plant operator, is very effective, Simulation results of the proposed method using the data of water treatment plant show good performance. This algorithm is included to chemical feeder, which is composed of PLC, magnetic flow-meter and control valve, so the intelligent control of chemical feeding is realized.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.45-48
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• 2006

The system that can generate biological brain information processing mechanism more precisely may have several abilities such as exact cognition, situation decision, learning and inference, and output decision. In this paper, to implement high level information processing and thinking ability in a complex system, the information processing layer based on the biological brain is introduced. The biological brain information processing mechanism, which is analyzed in this paper, provides fundamental information about intelligent engineering system, and the design of the layer that can mimic the functions of a brain through engineering definitions can efficiently introduce an intelligent information processing method having a consistent flow in various engineering systems. The applications proposed in this paper are expected to take several roles as a unified model that generates information process in various areas, such as engineering and medical field, with a dream of implementing humanoid artificial intelligent system.