• Research in Mathematical Education
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• v.19 no.1
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• pp.61-79
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• 2015

This study discussed about how pseudo-thinking process actually occurs in the mind of the students, used Piaget's frame work of the assimilation and accommodation process. The data collection is conducted using Think-Out-Loud (TOL) method. The study reveals that pseudo thinking process of covariational reasoning occurs originally from incomplete assimilation, incomplete accommodation process or both. Based on this, three models of incomplete thinking structure constructions are established: (1) Deviated thinking structure, (2) Incomplete thinking structure on assimilation process, and (3) Incomplete thinking structure on accommodation process.

• Microbiology and Biotechnology Letters
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• v.21 no.2
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• pp.181-186
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• 1993

The functions of n-alkane inducible genes, ALI1 and POX18Cm isolated from Canida maltosa were investigated, using it's distruptants. As a result, it is suggested that ALI1 is essential for n-alkane assimilation in C. mltosa and it regulates genes related to assimilation of n-alkane (ALI1, P450alk POX18Cm) at transcriptional level. Nuclear localization experiments indicated that ALI1 was located and functioned in the nucleus. POX18Cm is considered as a peroxisomal nonspecific lipid transfer protein gene related to n-alkane assimilation in C. maltosa also regulated by ALI1. But it had no significant effect on n-alkane assimilation in C. maltosa.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.363-370
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• 2017

Data assimilation is an initializing method for air quality forecasting such as PM10. It is very important to enhance the forecasting accuracy. Optimal interpolation is one of the data assimilation techniques. It is very effective and widely used in air quality forecasting fields. The technique, however, requires too much memory space and long execution time. It makes the PM10 air quality forecasting difficult in real time. We propose a fast optimal interpolation data assimilation method for PM10 air quality forecasting using a new kernel tridiagonal sparse matrix and CUDA massively parallel processing architecture. Experimental results show the proposed method is 5~56 times faster than conventional ones.

• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.619-632
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• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• Korean Management Science Review
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• v.30 no.2
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• pp.63-77
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• 2013

Recently, many companies are interested in adopting cloud computing as their IT strategy. However, no distinct results have appeared in the substantial implementation of this technology. The main reason for such result is from the absence of research models leading to high impact studies on cloud computing. Thus, this study attempts to find a possible answer for the following research question : what factors influence an organizational assimilation of cloud computing? This study investigates Technology-Push (TP)/Need-Pull (NP) theory as a main factor affecting cloud computing assimilation. Also, the study examines the moderating role of organizational readiness. TP includes of perceived benefits, vendor pressure, cost savings, and IT activity intensity while NP includes competitor orientation, information technology policy, technological turbulence, and performance gaps. In addition, organizational readiness suggests two variables, financial resources and technological knowledge. Result from 217 adopting organizations showed that all of these factors with exception of competitor orientation and vendor pressure, have statistically significant impact on assimilation of cloud computing. The implications of the findings propose a theoretical framework for the foundation of studies on cloud computing assimilation, which can server as important practical guidelines for technology development.

• Journal of Ecology and Environment
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• v.29 no.5
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• pp.433-438
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• 2006

To elucidate the mechanisms by which algal food quality affect Daphnia growths, we measured carbon incorporation rates and respiration rates of Daphnia magna with Cryptomonad Rhodomonas minuta, green algae Scenedesmus acutus and cyanobacteria Synechococcus sp. with varying physiological states as food. Carbon assimilation rates were high with R. minuta and S. acutus and low with Synechococcus sp. showing a similar pattern to the growth rate pattern. There was no clear difference among respiration rates of three algal species. Carbon assimilation rates and respiration rates of D. magna appeared to be independent on Molar C:P ratios in algal foods. Carbon growth efficiencies (incorporated carbon per assimilated carbon amount) were lower when D. magna fed with Synechococcus sp. than fed with R. minuta or S. acutus. Analysis of variance results show that carbon assimilation rates which were sum of incorporation and respiration rates and carbon growth efficiencies were only dependant on species affiliation. Overall, our results showed that algal species with varying ${\omega}3$ polyunsaturated fatty acid content led different carbon incorporation rates and overall carbon assimilation rates of D. magna.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1141-1154
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• 2018

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

• Atmosphere
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• v.28 no.2
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• pp.113-121
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• 2018

In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

• Atmosphere
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• v.23 no.2
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• pp.143-160
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• 2013

The effect of 3DVAR (Three Dimension Variational data Assimilation) was examined by comparing observation and the simulations of CNTL (to which data assimilation was not applied) and ALL (to which data assimilation was applied using ground observation data and radar data) for the case of a heavy snowfall event (case A) of 11-12 February 2011 in the Yeongdong region. In case A, heavy snow intensively came in the Yeongdong coastal region rather than Daegwallyeong, in particular, around the Gangneung and Donghae regions with total precipitation in Bukgangneung at approximately 91 mm according to the AWS observation. It can be seen that compared to CNTL, ALL simulated larger precipitation along the Yeongdong coastline extending from Sokcho to Donghae while simulating smaller precipitation for inland areas including Daegwallyeong. On comparison of the total accumulated precipitations from simulations of CNTL and ALL, and the observed total accumulated precipitation, the positive effect of the assimilation of ground observation data and radar data could be identified in Bukgangneung and Donghae, on the other hand, the negative effect of the assimilation could be identified in the Daegwallyeong and Sokcho regions. In order to examine the average accuracy of precipitation prediction by CNTL and ALL for the entire Gangwon region including the major points mentioned earlier, the three hour accumulated precipitation from simulations of CNTL and ALL were divided into 5, 10, 15, 20, 25 and 30 mm/3hr and threat Scores were calculated by forecasting time. ALL showed relatively higher TSs than CNTL for all threshold values although there were some differences. That is, when considered generally based on the Gangwon region, the accuracy of precipitation prediction from ALL was improved somewhat compared to that from CNTL.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.85-97
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• 2015

This study examined that the assimilated web technologies can contribute to IS(information system) success. Through hierarchical regression analysis, the following findings are identified. First, top management championship, strategic investment rationale, and computer use and access affected web technology assimilation, and then web technology assimilation influenced on IS development success positively. Second, top management championship had more influence than other independent variables in strategies dimension of web technologies assimilation while strategic investment rationale did in activities dimension. Third, the strategies assimilation was more dominant than the activities assimilation for IS success. Thus it is concluded that IT including web technologies brings organizations a powerful business tool and high profit.