• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• The Journal of Korean Academy of Sensory Integration
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• v.3 no.1
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• pp.23-35
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• 2005

Objectives : The purpose of the study is to understand the sensory processing capacity and behavioral characteristics for preschoolers without disabilities, and to investigate the relationship between sensory processing skills and the behavioral characteristics. Methods : Mothers of preschoolers without disabilities between ages of 4 and 6 who attend Y kindergarten which is located in Busan, H kindergarten in Suwon, S kindergarten in Gimhae was participated. Mothers filled out the questionnaire at home from 4th to 14th of January in 2004. We used SSP(short sensory profile) which was used by Kim, Mi-Sun in 2001 to understand the sensory processing skills. We also used Behavior During Testing Checklist find their places in Miller Assessment for preschoolers to understand behavior characteristics. The results were analyzed with SPSS 10.0. Results : 1. Total incidents in sensory processing were 157 out of 190. Among sub items of the sensory processing, the mark of lower energy/weak was highest with 4.39 point and the mark of taste/smell sensitivity was lowest with 3.60 point. Total incidents in behavioral characteristics were 20 out of 24. Among the area of behavioral characteristics, the mark of sensory responses/threshold area was highest with 2.73 point and the mark of social interaction area was lowest with 2.29 point. 2. Children's total sensory processing capacity correlates with behavioral characteristics, the more sensory processing capacity, the more behavioral characteristics. Sensory processing point correlates with behavioral characteristics points except this item, reaction to separation from caretaker. Conclusions : We hope that the children who have behavioral characteristics with difficulties in sensory processing skills can be distinguished on the basis of this studying. Also, as we find and relieve early stage of the symptoms, following study which can present based to facilitate children's social development and improve the learning ability.

• The Journal of Engineering Geology
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• v.30 no.3
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• pp.315-325
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• 2020

This study was performed to develop a model to predict landslides and determine the variable importance of landslides susceptibility factors based on the probabilistic prediction of landslides occurring on slopes along the road. Field survey data of 30,615 slopes from 2007 to 2020 in Korea were analyzed to develop a landslide prediction model. Of the total 131 variable factors, 17 topographic factors and 114 geological factors (including 89 bedrocks) were used to predict landslides. Automated machine learning (AutoML) was used to classify landslides and non-landslides. The verification results revealed that the best model, an extremely randomized tree (XRT) with excellent predictive performance, yielded 83.977% of prediction rates on test data. As a result of the analysis to determine the variable importance of the landslide susceptibility factors, it was composed of 10 topographic factors and 9 geological factors, which was presented as a percentage for each factor. This model was evaluated probabilistically and quantitatively for the likelihood of landslide occurrence by deriving the ranking of variable importance using only on-site survey data. It is considered that this model can provide a reliable basis for slope safety assessment through field surveys to decision-makers in the future.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.2
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• pp.121-127
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• 2015

A reduction of motor performance due to brain disorders can be screened by evaluating force tracking capabilities (FTCs). Existing studies have examined FTCs mainly using simple sinusoidal waves, of which repeated profiles have a critical limitation due to a learning effect in force tracking. The present study examined the effects of personal factors (age and gender) and sinusoidal wave factors (central force and complexity) on FTCs of healthy adults using composite sinusoidal wave profiles (CSWPs). FTCs were measured using Finger $Touch^{TM}$ for 30 seconds and quantified in terms of time within the target range (TWR, accuracy measure) and relative RMSE (RRMSE, variability measure). A total of 90 healthy adults in 20s to 70s with the equal gender ratio participated in the experiment consisting of combinations of 2 central force levels (6 N and 10 N) and 2 complexity levels (approximate entropy, ApEn = 0.03 and 0.06) of CSWPs. Significantly decreased FTCs (lower TWR and higher RRMSE) were found in aged adults, females, the low central force, and the high complexity. The detailed FTC decrements include a 43% reduced TWR and a 85% increased RRMSE of older adults in 70s as compared to those in 20s, a 17% reduced TWR and a 17% increased RRMSE of female as compared to those of male, a 30% reduced TWR and a 108% increased RRMSE at central force = 6N when compared to those at central force = 10N, and a 19% reduced TWR and a 30% increased RRMSE at ApEn = 0.06 as compared to those at ApEn = 0.03. The characteristics of FTCs for CSWPs can be of use in establishing an assessment protocol of motor performance for screening brain disorders.

• Journal of The Korean Association For Science Education
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• v.24 no.3
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• pp.468-480
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• 2004

It has been criticized that there are discrepancy between 'general statements' of the curriculum and subject-matter curricula. The possible reasons for this are as follows: The developers of the general statements were educational curriculum specialists. These specialists were not good enough to develop general statements and guidelines of subject matter curricula reflecting the characteristics of science contents, to examine developed science curriculum, and to give feedback to science curriculum developers. Under the present curriculum developing system where curriculum is developed in ten months or less by the research team commissioned unpredictably and imminently, it might be difficult to develop valid and precise science curriculum reflecting the purport of the general statements and teachers' needs. The inadequacy of these curriculum development processes resulted in (1) inconsistent statement about the school year to be applied to differentiated curriculum, (2) abstract and ambiguous stating about the characteristics, teaching-learning and assessment guidelines of enrichment activities, and (3) failure to reduce science contents to a reasonable level. Therefore curriculum development centers should be designated in advance to do basic research at ordinary times, and organized into a cooperative system among them. Two years or more of developing time and wider participation of scientists are recommended to develop more valid and precise science curriculum. In addition, commentaries on science curriculum should be published before textbook writing begins.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.461-470
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• 2020

This study analyzed the determinants of land compensation costs using the CALS (Continuous Acquisition & Life-Cycle Support) system to generate data for the construction (planning, design, building, management) process. For analysis, variables used in the related research on land costs were used, which included eight variables (Land Area, Individual Public Land Price, Appraisal & Assessment, Land Category, Use District 1, Terrain Elevation, Terrain Shape, and Road). Also, the variables were analyzed using the machine learning-based Xgboost algorithm. Individual Public Land Price was identified as the most important variable in determining land cost. We used a linear multiple regression analysis to verify the determinants of land compensation. For this verification, the dependent variable included was the Individual Public Land Price, and the independent variables were the numeric variable (Land Area) and factor variables (Land Category, Use District 1, Terrain Elevation, Terrain Shape, Road). This study found that the significant variables were Land Category, Use District 1, and Road.

• Journal of Wetlands Research
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• v.22 no.2
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• pp.106-112
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• 2020

Wetlands play an important function and role in hydrological, environmental, and ecological, aspects of the watershed. Water level in wetlands is essential for various analysis such as for the determination of wetland function and its effects on the environment. Since several wetlands are ungauged, research on wetland water level prediction are uncommon. Therefore, this study developed a water level prediction model using multiple regression analysis, principal component regression analysis, artificial neural network, and DNN to predict wetland water level. Geumjeong-Mountain Wetland located in Yangsan-city, Gyeongsangnam-do province was selected as the target area, and the water level measurement data from April 2017 to July 2018 was used as the dependent variable. On the other hand, hydrological and meteorological data were used as independent variables in the study. As a result of evaluating the predictive power, the water level prediction model using DNN was selected as the final model as it showed an RMSE value of 6.359 and an NRMSE value of 18.91%. This research study is believed to be useful especially as a basic data for the development of wetland maintenance and management techniques using the water level of the existing unmeasured points.

• Journal of The Korean Association For Science Education
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• v.21 no.4
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• pp.677-688
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• 2001

The purposes of this study are to investigate the school science high achievers' achievements in enrichment physics, logical thinking level, and to analyze the relationship between logical thinking level and the achievement in enrichment physics of high achievers in science. The subjects were 357th and 8th graders who achieved highly in school science. To assess their achievements in enrichment physics, we developed a new test consisting of descriptive problems which were based on middle school curriculum. Those problems require one or two steps of thinking process, not simple knowledge of science. To assess logical thinking level, we used the instrument called GALT(Group Assessment of Logical Thinking) developed by Roadranka et al. The results showed that the school science high achievers' average achievement in enrichment physics was low, 56.3 out of 150, which indicated that they had not done much of enrichment learning beyond middle school science curriculum. Just only 54% of the school science high achievers are in formal logical thinking level. From the analysis of relationship between their logical thinking level and the achievement in enrichment physics, the value of the correlation coefficient was 0.174, which means that they are not almost correlated. Therefore, it is not desirable to judge science gifted children just from achievement in school science or enrichment physics, so both(logical thinking and the achievement in enrichment physics) tests should be taken for selecting gifted student.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1881-1890
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• 2021

Particulate matter (PM) affects the human, ecosystems, and weather. Motorized vehicles and combustion generate fine particulate matter (PM_2.5), which can contain toxic substances and, therefore, requires systematic management. Consequently, it is important to monitor and predict PM_2.5 concentrations, especially in large cities with dense populations and infrastructures. This study aimed to predict PM_2.5 concentrations in large cities using meteorological and chemical variables as well as satellite-based aerosol optical depth. For PM_2.5 concentrations prediction, a random forest (RF) model showing excellent performance in PM concentrations prediction among machine learning models was selected. Based on the performance indicators R², RMSE, MAE, and MAPE with training accuracies of 0.97, 3.09, 2.18, and 13.31 and testing accuracies of 0.82, 6.03, 4.36, and 25.79 for R², RMSE, MAE, and MAPE, respectively. The variables used in this study showed high correlation to PM_2.5 concentrations. Therefore, we conclude that these variables can be used in a random forest model to generate reliable PM_2.5 concentrations predictions, which can then be used to assess the vulnerability of schools to PM_2.5.

• Journal of The Korean Association For Science Education
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• v.41 no.2
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• pp.155-169
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• 2021

This study aims at exploring the features of science teaching orientation (STO) and its relationships with other PCK (pedagogical content knowledge) components. To do this, based on the definition of STO by Friedrichsen, Driel, & Abell(2011) and PCK model by Magnusson, Krajcik, & Borko(1999), we observed one experienced elementary teacher's science lessons for 21 lesson hours (10 hours of 'Motion of Objects' and 11 hours of 'Light and Lens') and carried out qualitative analyses of the data obtained from lessons observation, teacher interviews, and CoRe (content representation) responses. We analyzed the teacher's three aspects of STO (i.e. beliefs about the goals and purpose of science teaching, beliefs about the nature of science, and beliefs about science teaching and learning) which can converge into an overall STO of 'inquiry'. And these aspects of STO appear to interact differently with four PCK components (i.e. curriculum knowledge, learner knowledge, instructional knowledge, and assessment knowledge) depending on the topic of the lesson. It is hoped that this in-depth understanding of the features of STO and its relationship with other PCK components would provide useful information on how to monitor and improve STO and PCK of elementary teachers.