• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1107-1118
• /
• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• The Korean Journal of Pesticide Science
• /
• v.19 no.4
• /
• pp.370-393
• /
• 2015

This study was conducted to compare STQ method, multi-residue method in Korean food code and QuEChERS method for validated selected and accuracy, reproducibility and efficiency. A total of 45 selected and targeted pesticides were the analyzed by GC and 5 of them were crops (apple, potato, green pepper, rice, soy bean). $R^2$ values were calculated in the standard calibration curve was over 0.990. Recovery tests were performed by three replications in two levels and the relative standard deviation of the repeated experiments was less than 30%. The average percentage of recoveries in the multi-residue method in Korean food code was 89.13%, QuEChERS method was 92.45% and STQ method was 85.28%. In addition, matrix effects in multi-residue method in Korean food code was 24.61%, QuEChERS method was 23.98% and STQ method showed 11.24%. The STQ method is easy and showed high clean-up effect in extracting the sample solution than the QuEChERS method and clean-up with C18, PLS, PSA cartridge columns. A large volume of the sample was injected in order to compensable for the problem, that occurred due to high detection limit in the analyser. When the STQ method was applied using a large volume injector, the standard calibration curve showed a higher linearity $R^2=0.990$, and method detection limit was 0.01 mg/kg. It showed an average recovery of 91.84% and the relative standard deviations of three replications repeated in two level process was less than 30% and had an average matrix effect of 17.90%.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.12 no.2
• /
• pp.82-98
• /
• 2009

This study applied SWAT model to analyze suspended sediment load that is influence on the high density turbid water in Donghyang and Cheoncheon basin, which are located in the upstream of Yongdam Dam. GIS data such as DEM, land cover map and soil map, and meteorological data were used as the input data of SWAT model. And the rating curve equation and Q-SS equation of Donghyang and Cheoncheon gauge station were applied as the measured values of them. As the result of flowout, the coefficient of determination ($R^2$) and the Nash-Sutcliffe coefficient of efficiency (EI) of model calibration showed high as 0.87 and 0.87 at Donghyang gauge station, and the $R^2$ and EI of model validation were high as 0.95 at Cheoncheon gauge station. Also, as the result of suspended sediment load, the $R^2$ and EI of model calibration were high as 0.77 and 0.76 at Donghyang gauge station, and the $R^2$ and EI of model validation marked high as 0.867 and 0.80 at Cheoncheon gauge station. It is considered that the suspended sediment load of 2003 showed the highest due to rainfall amounts and rainfall intensity in using SWAT model. The results of suspended sediment modeled in this study can be applied to the decision-making support data for the evaluation of soil erosion possibility and turbid water potential in the management of reservoir.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.6
• /
• pp.127-136
• /
• 2010

In multi-view video, illumination disharmony between neighboring views can occur on account of different location of each camera and imperfect camera calibration, and so on. Such discrepancy can be the cause of the performance decrease of multi-view video coding by mismatch of inter-view prediction which refer to the pictures obtained from the neighboring views at the same time. In this paper, we propose an efficient histogram-based prefiltering algorithm to compensate mismatches between the luminance and chrominance components in multi-view video for improving its coding efficiency. To compensate illumination variation efficiently, all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching. A Cosited filter that is used for chroma subsampling in many video encoding schemes is applied to each color component prior to histogram matching to improve its performance. The histogram matching is carried out in the RGB color space after color space converting from YCbCr color space. The effective color conversion skill that has respect to direction of edge and range of pixel value in an image is employed in the process. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with other methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.3
• /
• pp.143-149
• /
• 2018

Recently, due to the large-scale damage of natural disasters caused by global climate change, a monitoring system applying remote sensing technology is being constructed in disaster areas. Among remote sensing platforms, the drone has been actively used in the private sector due to recent technological developments, and has been applied in the disaster areas owing to advantages such as timeliness and economical efficiency. This paper deals with the development of a preprocessing system that can map the drone image data in a near-real time manner as a basis for constructing the disaster monitoring system using the drones. For the research purpose, our system is based on the SURF algorithm which is one of the computer vision technologies. This system aims to performs the desired correction through the feature point matching technique between reference images and shot images. The study area is selected as the lower part of the Gahwa River and the Daecheong dam basin. The former area has many characteristic points for matching whereas the latter area has a relatively low number of difference, so it is possible to effectively test whether the system can be applied in various environments. The results show that the accuracy of the geometric correction is 0.6m and 1.7m respectively, in both areas, and the processing time is about 30 seconds per 1 scene. This indicates that the applicability of this study may be high in disaster areas requiring timeliness. However, in case of no reference image or low-level accuracy, the results entail the limit of the decreased calibration.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.58 no.4
• /
• pp.21-35
• /
• 2016

This study is to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for multi-purpose dams and multi-function weirs operation in Namhan river basin ($12,577km^2$) of South Korea. The SWAT was calibrated (2005 ~ 2009) and validated (2010 ~ 2014) considering of 4 multi-purpose dams and 3 multi-function weirs using daily observed dam inflow and storage, evapotranspiration, soil moisture, and groundwater level data. Firstly, the dam inflow was calibrated by the five steps; (step 1) the physical rate between total runoff and evapotranspiration was controlled by ESCO, (step 2) the peak runoff was calibrated by CN, OV_N, and CH_N, (step 3) the baseflow was calibrated by GW_DELAY, (step 4) the recession curve of baseflow was calibrated by ALPHA_BF, (step 5) the flux between lateral flow and return flow was controlled by SOL_AWC and SOL_K, and (step 6) the flux between reevaporation and return flow was controlled by REVAPMN and GW_REVAP. Secondly, for the storage water level calibration, the SWAT emergency and principle spillway were applied for water level from design flood level to restricted water level for dam and from maximum to management water level for weir respectively. Finally, the parameters for evapotranspiration (ESCO), soil water (SOL_AWC) and groundwater level fluctuation (GWQMN, ALPHA_BF) were repeatedly adjusted by trial error method. For the dam inflow, the determination coefficient $R^2$ was above 0.80. The average Nash-Sutcliffe efficiency (NSE) was from 0.59 to 0.88 and the RMSE was from 3.3 mm/day to 8.6 mm/day respectively. For the water balance performance, the PBIAS was between 9.4 and 21.4 %. For the dam storage volume, the $R^2$ was above 0.63 and the PBIAS was between 6.3 and 13.5 % respectively. The average $R^2$ for evapotranspiration and soil moisture at CM (Cheongmicheon) site was 0.72 and 0.78, and the average $R^2$ for groundwater level was 0.59 and 0.60 at 2 YP (Yangpyeong) sites.

• Korean Journal of Soil Science and Fertilizer
• /
• v.31 no.2
• /
• pp.114-119
• /
• 1998

Intensity and stability of the blue color of phospho-molybdate complex in P analysis are known to be influenced by the matrix, reducing regent and acidity of the extractants. Objective of this research was to compare the efficiency of the color-developing reagents for P concentrations in distilled water and extracts of Lancaster, Mehlich II, and Mehlich III methods. Efficiencies on which to base this study were evaluated by the optimum ranges of P, reproducibility of calibration curve and stability of the developed color. Color-developing reagents employed were ammonium molybdate-1,2,4- aminonaphtholsulfonic acid (ANS), ammonium molybdate-ascorbic acid-bismuth subcarbonate (AB), and ammonium molybdate-ascorbic acid-antimony potassium tartarate (AA). The ANS revealed the lowest sensitivity but the widest ranges for P concentrations in color development. On the other hand, the AA bore the narrowest color-developing ranges and its sensitivity was similar to AB. However, at P concentrations lower than $0.5mg\;L^{-1}$, AA was more sensitive than AB. Based on the data on the ranges of calibration curve, stability of color and reproducibility of analytical data. AA reagent was considered to be suitable for the determination of P in distilled water and AB reagent was practically recommendable for soil P analysis in extracts by Lancaster, Mehlich II, and Mehlich III procedures.

• Korean Journal of Construction Engineering and Management
• /
• v.17 no.3
• /
• pp.143-155
• /
• 2016

Recently, the interest on applying AVM(Around View Monitoring) systems in construction equipments have been increasing due to the demand for better control, work efficiency and safety. Most of the existing AVM systems have been developed focusing on the application in automobiles and only several AVM systems have been developed for construction equipments. However, the original technology of AVM remained the same as in the automobiles that failed to consider the main properties of construction equipments and suggest appropriate range of AVM display (Top-view). Therefore, the purpose of this study is to suggest a pilot type of AVM system for construction equipment. Accordingly, literature review, deduction of main consideration factors, selection of sensors, system design, algorithm development of a pilot type of AVM system for construction equipment have been conducted. A laboratory experiment has also been conducted for the deduction of further improvements. As a result, a minimum image refresh rate of 20 fps has been achieved that clearly reflects the actual situation of the equipment and also, the actual motions of Boom, Arm, Bucket have been displayed appropriately on the AVM system based on the angle data collected by sensors. However, the experiment results have also shown that the following tasks still remain for future work: 1)Improvement of AVM image interpolation, 2)Development of calibration module for variety construction equipment.

• Korean Journal of Ecology and Environment
• /
• v.40 no.1
• /
• pp.155-162
• /
• 2007

Water balance is the major factor in forest ecosystem, and is closely related to the vegetation and topographic characteristics within a watershed. The hydrologic response of a forest watershed was investigated with the hydrological model. The deterministic, lumped parameter model (BROOK90) was selected and used to evaluate the applicability of the model for simulating daily runoff on the steep, forested watershed. The model was calibrated and validated against the streamflow data measured at the Bukmoongol watershed. The deviation in runoff volume $(D_v)$ was -1.7% for the calibration period, and the $D_v$ value for the validation period was 4.6%. The correlation coefficient (r) and model efficiency (E) on monthly basis were 0.922,0.847, respectively, for the calibration period, while the r- and E-value for the validation period were 0.941, 0.871, respectively. Overall, the simulated streamflows were close to the observations with respect to total runoff volume, seasonal runoff volume, and baseflow index for the simulation period. BROOK90 model was able to reproduce the trend of runoff with higher correlation during the simulation period.

• Food Science of Animal Resources
• /
• v.38 no.5
• /
• pp.1109-1119
• /
• 2018

In this paper, we report the development of a nondestructive prediction model for lean meat percentage (LMP) in Korean pig carcasses and in the major cuts using a machine vision technique. A popular vision system in the meat industry, the VCS2000 was installed in a modern Korean slaughterhouse, and the images of half carcasses were captured using three cameras from 175 selected pork carcasses (86 castrated males and 89 females). The imaged carcasses were divided into calibration (n=135) and validation (n=39) sets and a multilinear regression (MLR) analysis was utilized to develop the prediction equation from the calibration set. The efficiency of the prediction equation was then evaluated by an independent validation set. We found that the prediction equation - developed to estimate LMP in whole carcasses based on six variables - was characterized by a coefficient of determination ($R^2_v$) value of 0.77 (root-mean square error [RMSEV] of 2.12%). In addition, the predicted LMP values for the major cuts: ham, belly, and shoulder exhibited $R^2_v$ values${\geq}0.8$ (0.73 for loin parts) with low RMSEV values. However, lower accuracy ($R^2_v=0.67$) was achieved for tenderloin cuts. These results indicate that the LMP in Korean pig carcasses and major cuts can be predicted successfully using the VCS2000-based prediction equation developed here. The ultimate advantages of this technique are compatibility and speed, as the VCS2000 imaging system can be installed in any slaughterhouse with minor modifications to facilitate the on-line and real-time prediction of LMP in pig carcasses.