• Journal of Educational Research in Mathematics
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• v.24 no.2
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• pp.269-283
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• 2014

Recently, 3S Mathematics Education (Storytelling mathematics education, SMART mathematics education, and STEAM mathematics education) is emphasized. Based on recently published report on Storytelling mathematics textbook, we propose executable expression based SMART storytelling mathematics related to the elementary mathematic curriculum on 3D building blocks. We designed letters and expressions to represent three dimensional shape of 3D building blocks, and we compare its characteristics with that of LEGO blocks. We assert that text-based executable expressions not only construct what students want to make but also teachers can read students thinking process and can support educational help based on students needs. We also present linear function, quadratic function, and function variable concepts using executable expressions based on 3D building block as an example of SMART storytelling mathematics. This research was supported by the collaborated creativity mentoring project between Siheung City and college of education at Seoul National University. We hope designed executable expressions can be used for the development of SMART storytelling mathematics education.

• Applied Chemistry for Engineering
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• v.10 no.2
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• pp.259-262
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• 1999

The copper-catalyzed reaction of silicon with methanol was carried out in a mixed bed reactor to obtain tetramethyl orthosilicate (TMOS). In order to determine the kinetics of the reaction per active site on the silicon surface, a flow rate transition technique was employed. A kinetic study showed the reaction was in Linear relationship with the amount of contact mass and independent on the concentration of methanol. This result indicated that the rate-determining step was not the chemical process involving methanol, but the formation of silicon intermediate on the contact mass. On the basis of optimum experimental conditions, the maximum TMOS formation rate per g-silicon is 0.030 (g/min) at $210^{\circ}C$, in which activation energy was 8.5 kcal/mol and reaction rate equation was $k=4.09{\times}10^4\;exp$ ($-4.73{\times}10^3/T$).

• Journal of the Korean institute of surface engineering
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• v.51 no.3
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• pp.157-163
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• 2018

The anodic $TiO_2$ layers which are prepared in various anodization conditions exhibit their specific color depending on the thickness of $TiO_2$. In this study, the relationship between the color of $TiO_2$ layer, which is grown by PEO (Plasma electrolytic oxidation), and the thickness of the $TiO_2$ layer is investigated. To evaluate the color change of the $TiO_2$ layer, the value of color ($dE^*ab$) is measured and calculated by spectrophotometer and chromameter. As a result, it is found that $dE^*ab$ values and thickness of $TiO_2$ layers form a linear relationship with meaningful formular. This formula can be helpful to quantify the thickness of the $TiO_2$ layer by the numerical $dE^*ab$ values. In this process, the spectrophotometer shows more precise results than the chromameter dose. If fluoride ions ($F^-$) are included in the electrolyte, it will affect the $dE^*ab$ values of the $TiO_2$. layer. This is against the propensity, which is analyzed by XRD (X-ray diffraction) and XPS (X-ray photoelectron spectroscopy). It is important that the formular suggested in this study provides other metals which can be also anodized with the possibility of quantifying the thickness of the $TiO_2$ layer by the $dE^*ab$ values.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Journal of Sensor Science and Technology
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• v.8 no.2
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• pp.163-170
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• 1999

A programmable A/D converter for an embedded fiber-optic combustion pressure sensor has been designed with 8 N and P channel MOSFETs, respectively. A local field enhancement for reducing programming voltage during writing as well as erasing an EEPROM device is introduced. In order to observe linear programmability of the EEPROM device during programming mode, a cell is developed with a $1.2\;{\mu}m$ double poly CMOS fabrication process in MOSIS. It is observed that the high resolution, of say 10mVolt, is valid in the range 1.25volts to 2volts. The experimental result is used for simulating the programmable 8 bit A/D converter with Hspice. The A/D converter is demonstrated to consume low power, $37\;{\mu}W$ by utilizing a programming operation. In addition, the converter is attained at the conversion frequency of 333 MHz.

• Journal of fish pathology
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• v.1 no.2
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• pp.131-134
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• 1988

Radiocobalt was used as tracer to study the uptake of cobalt by fish either from water or food source, respectively. Four groups of goldfish were exposed to $^{57}Co$-labelled water under 4 different temperatures, while another four groups were fed labelled feed pellets at $15^{\circ}C$. Results indicate that water temperature has no significant effect on the uptake of cobalt from water. The uptake from water is quite a slow process since the cobalt uptaken from water reached 0.0006% of available activity at best on the 13th day of exposure. The uptake from a labelled feed source showed a linear increase with time over the period of ninety days. On the 90th day of experiment the percentage of available activity consumed seemed to be approaching an equilibrium point at roughly 12% of the total activity fed to the goldfish.

• Journal of Dairy Science and Biotechnology
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• v.26 no.2
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• pp.51-56
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• 2008

Using central composite design, we have designed optimization of the manufacturing of processed butter. And response surface analysis by least-square regression was used Statistical Analysis System(SAS). Central composite design can be achieved by response surface techniques that allow flexibility in modeling and analysis. Response surface methodology(RSM) was used to optimize hardness(%) using as independent variables; the content of butter($X_1$), ranging from 50 to 90(%), the content of soybean oil($X_2$), from 0 to 20(%), and the hydrogenated soybean oil($X_3$) from 0 to 4(%). The results on the regression coefficients calculated for overrun by response surface by least-square regression(RSREG) were followed. It was considered that the linear regression was significant(p<0.01). As for the processed butter, the regression model equation for the hardness(Y, %) to the change of an independent variable could be predicted as follow: $Y=60.88-8.92X_2-{29.3X_2}^2$. The optimal for the manufacturing of processed butter were determined at the content of butter of 88.22%, soybean oil of 6.71% and hydrogenated soybean oil of 2.36%, respectively. Optimum compositions were resulted in hardness of 65.78 N. Finally the reference sample(Butter in the morning, Seoul Dairy Co-op.) and processed butter manufacturing under the optimal conditions were compared with spreadability test. The spreadability scores result from reference sample and butter under optimal conditions was not found a significant difference.

• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.161-167
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• 2010

In this study, we implemented an experimental approach of ecological model development in order to emphasize the importance of input variable selection with respect to time-delayed arrangement between input and output variables. Time-series modeling requires relevant input variable selection for the prediction of a specific output variable (e.g. density of a species). Inadequate variable utility for input often causes increase of model construction time and low efficiency of developed model when applied to real world representation. Therefore, for future prediction, researchers have to decide number of time-delay (e.g. months, weeks or days; t-n) to predict a certain phenomenon at current time t. We prepared a total of 3,900 equation models produced by Time-Series Optimized Genetic Programming (TSOGP) algorithm, for the prediction of monthly averaged density of a potamic phytoplankton species Stephanodiscus hantzschii, considering future prediction from 0- (no future prediction) to 12-months ahead (interval by 1 month; 300 equations per each month-delay). From the investigation of model structure, input variable selectivity was obviously affected by the time-delay arrangement, and the model predictability was related with the type of input variables. From the results, we can conclude that, although Machine Learning (ML) algorithms which have popularly been used in Ecological Informatics (EI) provide high performance in future prediction of ecological entities, the efficiency of models would be lowered unless relevant input variables are selectively used.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.4
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• pp.42-51
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• 2018

Verticality problem during the installation process in offshore wind turbine substructures could degrade the safety of the whole structures. Therefore, in this paper, the design of vertically adjustable transition piece(T.P.), using a PS anchor and grout of anchor socket in concrete gravity based substructure(G.B.S.), was proposed. T.P. was designed for 5MW offshore wind trubine and can adjust up to $0.5^{\circ}$ in verticality, occurred during installation. The design plan for each members and design procedure for T.P. was proposed. Then based on the proposed design, actual design targeting sea of Jeju-island was carried out. Finally, by use of non-linear 3D Finite Element Analysis(F.E.A.), evaluation of design was performed. As a result of evaluation, by checking load transfer mechanism and stress of T.P, proposed design was considered safe up to $0.5^{\circ}$ of adjustment.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.297-306
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• 2007

Model reference control is control method such that overall response of a plant plus controller approaches that of a given reference model. The reference model provides desired trajectory the plant should follow. There are many kinds of control methods in MRC. However, this paper focuses on Model Reference Sliding Mode Control. The plant of these controls is an uncertain and linear system varying in time, of second order, and with SISO. In this paper, a design scheme of reference model is proposed for MRSMC. The scheme determines reference model based on the information on bounded control inputs, reference inputs and system parameters. It is used to choose a Fixed Reference Model in the process of controller design, to update Variable Reference Model when stepwise reference inputs change and to update Instant Reference Model at every sampling time. The simulation results show that the proposed method yields better control performance than the conventional MRC subject to the stepwise reference input when applied to the position control system for motor system.