• 대한수학교육학회지:학교수학
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• 제13권1호
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• pp.65-88
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• 2011

본 연구에서는 먼저 수학사에서 미적분학의 기본정리의 발달 과정을 고찰하고 기하적, 대수적, 형식적 관점에서 그 발생과정을 구분하여 배열한 다음, 이를 바탕으로 학생들이 겪을 수 있는 인식론적 장애와 교과서의 관련 내용을 분석하였다. 그리고 미적분학의 기본정리와 관련된 수학사, 학생들의 오류, 교과서 분석 내용을 바탕으로 미적분학의 기본정리를 학생들에게 의미충실하게 지도할 수 있도록 교사의 'folding back 사고 모형'을 개발하였다([그림 V-1] 참조). 'folding back 사고 모형'은 미적분학의 기본정리와 관련된 수학사, 학생들의 오류, 교과서 분석 내용을 바탕으로 교사가 어떤 교수학적 중재를 활용하는지를 결정하는 단계와 미적분학의 기본정리 개념의 역사발생적 배열 및 학생의 개념 이해 수준을 고려하여 재구성한 '발생적 이해 수준에 따른 개념 모형'([그림 V-2])을 중심으로 제작되었다. 'folding back 사고 모형'의 교수학적 중재 단계에서는 교사가 실제 수업을 설계할 때 활용할 수 있는 자기질문 형식의 'folding back 사고의 적용 요령'(<표 V-1>)을 개발하여 제시하였다. 본 연구에서 제안한 'folding back 사고 모형'은 Pirie-Kieren(1991)의 이론에서 제시된 folding back 개념을 활용하여 교사가 실제로 수학 수업을 설계할 때 수학사와 학생의 오류를 고려할 수 있도록 개발된 사고 모형이다. 이는 수학 교사의 전문성 신장을 이끌고 학생에게는 교과 내용을 배우면서 사고력을 향상 시킬 수 있는 수업을 제공하는데 기여할 수 있을 것이다.

• 한국환경과학회지
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• 제11권5호
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• pp.419-436
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• 2002

The current paper reports on the enhancement of O$_3$, CO, NO$_2$, and aerosols during the Asian dust event that occurred over Korea on 1 May 1999. To confirm the origin and net flux of the O$_3$, CO, NO$_2$, and aerosols, the meteorological parameters of the weather conditions were investigated using Mesoscale Meteorological Model 5(MM5) and the TOMS total ozone and aerosol index, the back trajectory was identified using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model(HYSPLIT), and the ozone and ozone precursor concentrations were determined using the Urban Ashed Model(UAM). In the presence of sufficiently large concentrations of NO$\sub$x/, the oxidation of CO led to O$_3$ formation with OH, HO$_2$, NO, and NO$_2$ acting as catalysts. The sudden enhancement of O$_3$, CO, NO$_2$ and aerosols was also found to be associated with a deepening cut-off low connected with a surface cyclone and surface anticyclone located to the south of Korea during the Asian dust event. The wave pattern of the upper trough/cut-off low and total ozone level remained stationary when they came into contact with a surface cyclone during the Asian dust event. A typical example of a stratosphere-troposphere exchange(STE) of ozone was demonstrated by tropopause folding due to the jet stream. As such, the secondary maxima of ozone above 80 ppbv that occurred at night in Busan, Korea on 1 May 2001 were considered to result from vertical mixing and advection from a free troposphere-boundary layer exchange in connection with an STE in the upper troposphere. Whereas the sudden enhancement of ozone above 100 ppbv during the day was explained by the catalytic reaction of ozone precursors and transport of ozone from a slow-moving anticyclone area that included a high level of ozone and its precursors coming from China to the south of Korea. The aerosols identified in the free troposphere over Busan, Korea on 1 May 1999 originated from the Taklamakan and Gobi deserts across the Yellow River. In particular, the 1000m profile indicated that the source of the air parcels was from an anticyclone located to the south of Korea. The net flux due to the first invasion of ozone between 0000 LST and 0600 LST on 1 May 1999 agreed with the observed ground-based background concentration of ozone. From 0600 LST to 1200 LST, the net flux of the second invasion of ozone was twice as much as the day before. In this case, a change in the horizontal wind direction may have been responsible for the ozone increase.

• Steel and Composite Structures
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• 제46권3호
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• pp.319-334
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• 2023

Localizing damages is an essential task to monitor the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Backpropagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions in thin, flat, and folded structures having 15⁰, 30⁰, 45⁰, and 60⁰ folding angle have been modeled and subjected to free vibration analysis by employing the Classical Plate Theory with Finite Element Method. A Four-nodded quadrilateral element having six degrees of freedom has been considered to represent those structures mathematically. The first ten natural frequencies have been obtained regarding healthy and cracked structures. To localize the crack, the ratios of the frequencies of the cracked flat and folded structures to those of healthy ones have been taken into account. Those ratios have been given to BPANN as the input variables, while the crack locations have been considered as the output variables. A total of 500 crack locations have been regarded within the dataset obtained from the results of the free vibration analysis. To build the best intelligent model, a feature search has been conducted for BAPNN regarding activation function, the number of hidden layers, and the number of hidden neurons. Regarding the analysis results, it is concluded that the BPANN is able to localize the cracks with an average accuracy of 95.12%.