• Journal of Climate Change Research
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• v.6 no.3
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• pp.209-221
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• 2015

Temperature is one of the most important factors affecting crop growth. The diurnal cycle of the scale factor [Tsc] for air temperature and the surface temperature of crop leaf and soil could be estimated by the following equation : $[Tsc]=0.5{\times}sin(X+C)+0.5$. The daily air temperature (E[Ti]) according to the E&E time [X] can be estimated by following equation using average (Tavg), maximum (Tm) and minimum (Tn) temperature : $E[Ti]=Tn+(Tm-Tn){\times}[0.5{\times}sin\;\{X+(9.646Tavg+703.65)\}+0.5]$. The crop leaf temperature in 24th June 2014 was high as the order of red pepper without mulching > red pepper with mulching > soybean under drought > soybean with irrigation > Chinese cabbage. The case in estimating crop leaf surface temperature using air temperature and soil surface temperature was lower in the deviation compared to the case using air temperature for Chinese cabbage and red pepper. These results can be utilized for the crop models as input data with estimation.

• Resources Recycling
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• v.28 no.4
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• pp.59-64
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• 2019

This study suggests a conceptual strategy and methodology for the risk assessment of the domestic abandoned mine fillers with fly ash. The fillers are composed of coal fly ash and solidification materials, and contain little toxic substances such as carbonates but also some heavy metals; therefore, those requires a risk assessment. The risk assessment should primarily focus on estimation of the effects to human health both on carcinogen and non-carcinogen aspects. The significant data such as toxicity and partition coefficients can be obtained from the national soil or mine environmental risk assessment guidelines. Accurate risk assessment of heavy metal contamination in the fillers may consume lots of time and efforts through site survey and instrumental analyses, etc. Moreover, it is inefficient to explore all of the factors as concentrations and categories in every heavy metal in the fillers, due to a high variety and complexity. Therefore, implementation of a preliminary risk assessment is suggested by using the literature data and the basic characteristics of the filler samples prior to the detailed risk assessment. Certainly, this presumes a thorough understanding of reliable sample analysis methods, exposure pathways, and relevant physicochemical and biological mechanisms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.247-254
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• 2019

Recently, in designing military equipment, considerable attention has been paid to maintaining operations, including reliability, maintenance, and maintenance time of equipment, from the early stages of development. Therefore, both users and developers stress the importance of design considering the maintenance time. This study evaluated the specific methodologies for predicting the realistic maintenance time, such as the access complexity of equipment, other than the standard maintenance time provided by the conventional method mil-hdbk-470a at the beginning of the design, and applied the time conversion factor using a measure of the maintenance complexity. In addition, the actual maintenance time reflecting the actual maintenance time of the developed equipment and the time-conversion factor applied was compared/verified to confirm the reliability of the data. In a study to set a target for repair and the repair of equipment design in the future, it is expected that the maintenance time of equipment that fails to measure the maintenance time for the initial actual equipment will be reflected as a more realistic time. Moreover, activities, such as research and design reflection activities, will be performed to reduce the maintenance time, operational maintenance cost, etc.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.259-266
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• 2023

It is very difficult to measure the performance of the machine learning model in the business service stage. Therefore, managing the performance of the model through the operational department is not done effectively. Academically, various studies have been conducted on the concept drift detection method to determine whether the model status is appropriate. The operational department wants to know quantitatively the performance of the operating model, but concept drift can only detect the state of the model in relation to the data, it cannot estimate the quantitative performance of the model. In this study, we propose a performance prediction model (PPM) that quantitatively estimates precision through the statistics of concept drift. The proposed model induces artificial drift in the sampling data extracted from the training data, measures the precision of the sampling data, creates a dataset of drift and precision, and learns it. Then, the difference between the actual precision and the predicted precision is compared through the test data to correct the error of the performance prediction model. The proposed PPM was applied to two models, a loan underwriting model and a credit card fraud detection model that can be used in real business. It was confirmed that the precision was effectively predicted.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.321-335
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• 2023

Monitoring sediment loads in natural rivers is the key process in river engineering, but it is costly and dangerous. In practice, suspended loads are directly measured, and total loads, which is a summation of suspended loads and bed loads, are estimated. This study proposes a real-time sediment discharge monitoring system using the horizontal acoustic Doppler current profiler (H-ADCP) and support vector regression (SVR). The proposed system is comprised of the SVR model for suspended sediment concentration (SVR-SSC) and for total loads (SVR-Q_TL), respectively. SVR-SSC estimates SSC and SVR-Q_TL mimics the modified Einstein procedure. The grid search with K-fold cross validation (Grid-CV) and the recursive feature elimination (RFE) were employed to determine SVR's hyperparameters and input variables. The two SVR models showed reasonable cross-validation scores (R²) with 0.885 (SVR-SSC) and 0.860 (SVR-Q_TL). During the time-series sediment load monitoring period, we successfully detected various sediment transport phenomena in natural streams, such as hysteresis loops and sensitive sediment fluctuations. The newly proposed sediment monitoring system depends only on the gauged features by H-ADCP without additional assumptions in hydraulic variables (e.g., friction slope and suspended sediment size distribution). This method can be applied to any ADCP-installed discharge monitoring station economically and is expected to enhance temporal resolution in sediment monitoring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.437-444
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• 2010

Soil moisture has been recognized as the essential parameter when understanding the complicated relationship between land surface and atmosphere in water and energy recycling system. It has been generally known that it is related with the temperature, wind, evaporation dependent on soil properties, transpiration due to vegetations and other constituents. There is, however, little research concerned about the relationship between soil moisture and these constitutes, thus it is needed to investigate it in detail. We estimated the soil moisture and then compared with field data using the hydrometerological data such as atmospheric temperature, specific humidity, and wind obtained from the Flux tower in Selmacheon, Korea. In the winter season, subterranean temperature showed highly positive correlation with soil moisture while it was negatively correlated from the spring to the fall. Estimation of seasonal soil moisture was compared with field measurements with the correlation of determination, R=0.82, 0.81, 0.82, and 0.96 for spring, summer, fall, and winter, respectively. Comprehensive relationship from this study can supply useful information about the downscaling of soil moisture with relatively large spatial resolutions, and will help to deepen the understanding of the water and energy recycling on the earth's surface.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.329-337
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• 2009

In this study we briefly introduce the electronic float system based on the GPS and RF communication technology and present some field application results. The system is capable of operating 15 floats simultaneously for making discharge measurement. Since the electronic floats (EFs) acquire flow paths, they can improve velocity measurement accuracy up to 10%. Additionally, measured velocities by the EFs show good agreement with those by an ADCP. Relative difference in sub-section area calculated by the electronic and conventional float methods is -79~71% and, due to convergent tendency of floats flowing along near banks, it increases much larger. It is possible to improve accuracy up to 5~6% in making discharge measurement by the electronic floats at site with irregular flow paths and section arrangement. The electronic float system is capable of calculating more accurate velocity and section area using position information based on GPS. By real-time measurement of velocity, cross-section area and discharge, the electronic float system is expected to reduce manpower and improve accuracy, rapidity and efficiency of flood discharge measurements.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.33-40
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• 2009

The critical lag of crosswalk pedestrians is an important parameter in analyzing traffic operation at unsignalized crosswalks, however there is few research in this field in Korea. The purpose of this study is to develop a model to estimate the critical lag. Among the elements which influence the critical lag, the age of pedestrians and the length of crosswalks, which have fuzzy characteristics, and the each lag which is rejected or accepted are collected on crosswalks of which lengths range from 3.5 m to 10.5 m. The values of the critical lag range from 2.56 sec. to 5.56 sec. The age and the length are divided to the 3 fuzzy variables each, and the critical lag of each case is estimated according to Raff's technique, so a total of 9 fuzzy rules are established. Based on the rules, an ANFIS (Adaptive Neuro-Fuzzy Inference System) model to estimate the critical lag is built. The predictability of the model is evaluated comparing the observed with the estimated critical lags by the model. Statistics of $R^2$, MAE, MSE are 0.96, 0.097, 0.015 respectively. Therefore, the model is evaluated to explain the result well. During this study, it is found that the critical lag increases rapidly over the pedestrian's age of 40 years.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.487-495
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• 2010

Soil moisture is a crucial factor in hydrological system which influences runoff, energy balance, evaporation, and atmosphere. United States National Aeronautic and Space Administration (NASA) and Department of Agriculture (USDA) have established Soil Moisture Experiment (SMEX) since 2002 for the global observations. SMEX provides useful data for the hydrological science including soil moisture and hydrometeorological variables. The purpose of this study is to investigate the relationship between remotely sensed soil moisture data from aircraft and satellite and ground based experiment. C-band of Polarimetric Scanning Radiometer (PSR) that observed the brightness temperature provides soil moisture data using a retrieval algorithm. It was compared with the In-situ data for 2-30 cm depth at four sites. The most significant depth is 2-10 cm from the correlation analysis. Most of the sites, two data are similar to the mean of data at 10 cm and the median at 7 cm and 10 cm at the 10% significant level using the Rank Sum test and t-test. In general, soil moisture data using the C-band of the PSR was established to fit the Normal, Log-normal and Gumbel distribution. Soil moisture data using the aircraft and satellites will be used in hydrological science as fundamental data. Especially, the C-band of PSR will be used to prove soil moisture at 7-10 cm depths.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.1-13
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• 2024

The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O₂/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O₂ m^-2 d^-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O₂ m^-2 d^-1 and lowest in June and July at 18 mmol O₂ m^-2 d^-1. These seasonal variations were similar to the vertical nitrate flux based on the ³He gas exchange rate and to the particulate organic carbon flux estimated by the ²³⁴Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.