• Journal of Korea Water Resources Association
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• v.39 no.3 s.164
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• pp.261-274
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• 2006

This study performs a daily long-term runoff analysis for 30 years to forecast medium- and long-term probabilistic reservoir inflows on the Soyang River basin. Snowmelt is computed by Anderson's temperature index snowmelt model and potenetial evaporation is estimated by Penman-combination method to produce input data for a rainfall-runoff model. A semi-distributed TOPMODEL which is composed of hydrologic rainfall-runoff process on the headwater-catchment scale based on the original TOPMODEL and a hydraulic flow routing model to route the catchment outflows using by kinematic wave scheme is used in this study It can be observed that the time variations of the computed snowmelt and potential evaporation are well agreed with indirect observed data such as maximum snow depth and small pan evaporation. Model parameters are calibrated with low-flow(1979), medium-flow(1999), and high-flow(1990) rainfall-runoff events. In the model evaluation, relative volumetric error and correlation coefficient between observed and computed flows are computed to 5.64% and 0.91, respectively. Also, the relative volumetric errors decrease to 17% and 4% during March and April with or without the snowmelt model. It is concluded that the semi-distributed TOPMODEL has well performance and the snowmelt effects for the long-term runoff computation are important on the study area.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.11-16
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• 2022

As an interest in the development of artificial intelligence(AI) technology in the water supply sector increases, we have developed an AI algorithm that can predict improvement decision-making ratings through repetitive learning using the data of pipe condition evaluation results, and present the most reliable prediction model through a verification process. We have developed the algorithm that can predict pipe ratings by pre-processing 12 indirect evaluation items based on the 2020 Han River Basin's basic plan and applying the AI algorithm to update weighting factors through backpropagation. This method ensured that the concordance rate between the direct evaluation result value and the calculated result value through repetitive learning and verification was more than 90%. As a result of the algorithm accuracy verification process, it was confirmed that all water pipe type data were evenly distributed, and the more learning data, the higher prediction accuracy. If data from all across the country is collected, the reliability of the prediction technique for pipe ratings using AI algorithm will be improved, and therefore, it is expected that the AI algorithm will play a role in supporting decision-making in the objective evaluation of the condition of aging pipes.

• Korean Journal of Food Science and Technology
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• v.40 no.2
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• pp.152-159
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• 2008

The purpose of this study was to determine the accurate quantification of vitamin A in infant formula by comparing two different standard stock solutions as well as various sample weights using high performance liquid chromatography. The sources of uncertainty in measurement, such as sample weight, final smaple vloume, and the instrumental results, were identified and used as parameters to determine the combined standard uncertainty based on GUM(guide to the expression of uncertainty in measurement) and the Draft EURACHEM/CITAC Guide. The uncertainty components in measuring were identified as standard weight, purity, molecular weight, dilution of the standard solution, calibration curve, recovery, reproducibility, sample weight, and final sample volume. Each uncertainty component was evaluated for type A and type B and included to calculate the combined uncertainty. The analytical results and combined standard uncertainties of vitamin A according to the two different methods of stock solution preparation were 627 ${\pm}$ 33 ${\mu}$g R.E./100 g for 1,000 mg/L of stock solution, and 627 ${\pm}$ 49 ${\mu}$g R.E./100 g for 100 mg/L of stock solution. The analytical results and combined standard uncertainties of vitamin A according to the various sample weighs were 622 ${\pm}$ 48 ${\mu}$g R.E./100 g, 627 ${\pm}$ 33 ${\mu}$g R.E./100 g, and 491 ${\pm}$ 23 ${\mu}$g R.E./100 g for 1 g, 2 g, and 5 g of sampling, respectively. These data indicate that the preparation method of standard stock solution and the smaple amount were main sources of uncertainty in the analysis results for vitamin A. Preparing 1,000 mg/L of stock solution for standard material sampling rather than 100 mg, and sampling not more than 2 g of infant formula, would be effective for reducing differences in the results as well as uncertainty.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.447-463
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• 2019

Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.173-182
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• 2013

The early Sea-viewing Wide Field-of-view Sensor(SeaWiFS) atmospheric correction algorithm which is the basis of the atmospheric correction algorithm for Geostationary Ocean Color Imager(GOCI) assumes that water-leaving radiances is negligible at near-infrared(NIR) wavelengths. For this reason, all of the satellite measured radiances at the NIR wavelengths are assigned to aerosol radiances. However that assumption would cause underestimation of water-leaving radiances if it were applied to turbid Case-2 waters. To overcome this problem, Management Unit of the North Sea Mathematical Models(MUMM) atmospheric correction algorithm has been developed for turbid waters. This MUMM algorithm introduces new parameter ${\alpha}$, representing the ratio of water-leaving reflectance at the NIR wavelengths. ${\alpha}$ is calculated by statistical method and is assumed to be constant throughout the study area. Using this algorithm, we can obtain comparatively accurate water-leaving radiances in the moderately turbid waters where the NIR water-leaving reflectance is less than approximately 0.01. However, this algorithm still underestimates the water-leaving radiances at the extremely turbid water since the ratio of water-leaving radiance at two NIR wavelengths, ${\alpha}$ is changed with concentration of suspended particles. In this study, we modified the MUMM algorithm to calculate appropriate value for ${\alpha}$ using an iterative technique. As a result, the accuracy of water-leaving reflectance has been significantly improved. Specifically, the results show that the Root Mean Square Error(RMSE) of the modified MUMM algorithm was 0.002 while that of the MUMM algorithm was 0.0048.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.1-15
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• 2000

To reconstruct 3- D shape, It is a common strategy to acquire multiple range Images from different viewpoints and integrate them into a common coordinates In this paper, we particularly focus on the registration and integration processes for combining all range Images into one surface model. For the registration, we propose the 2-step registration algorithm, which consists of 2 steps the rough registration step using all data points and the fine registration step using the high-curved data points For the integration, we propose a new algorithm, referred to as ‘multi-registration’ technique, to alleviate the error accumulation problem, which occurs during applying the pair-wise registration to each range image sequentially, in order to transform them into a common reference frame Intensive experiments are performed on the various real range data In experiments, all range images were registered within 1 minutes on Pentium 150MHz PC The results show that the proposed algorithms registrate and integrate multiple range Images within a tolerable error bound in a reasonable computation time, and the total error between all range Images are equalized with our proposed algorithms.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.90-102
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• 2017

In this study, various types of nutrient models were tested by using two tears's water quality data collected from the stormwater wetland in Korea. Based on results, most important factor influencing nitrogen removal was hydraulic loading rate, which indicates that surface area of wetland is more important than its volumetric capacity, and model proposed by WEF was found to give a least error between measured and calculated values. For the phosphorus, in case assuming a power relationship between rate constant and temperature, the best prediction result were obtained, but temperature was most sensitive parameter affecting phosphorus removal. In addition, denitrification was always a limiting step for the nitrogen removal in this particular wetland mostly due to the lack of carbon source and high dissolved oxygen concentration. In this paper, several alternatives to improve nitrogen removal, including proper arrangement and designation of wetland elements and use of floating plants or synthetic fiber mat to control oxygen level and to capture the algal particles were proposed and discussed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.29-33
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• 2007

All pixels of image sensor do not react uniformly even if the light of same radiance enters into the camera. This non-uniformity comes from the sensor pixel non-uniformity and non-uniformity induced by the changing transmission of the telescope over the field. The first contribution to the non-uniformity has high spatial frequency nature and has an influence on the result and quality of the data compression. The second source of non-uniformity has low frequency nature and has no influence of the compression result. As the contribution resulting from the sensor PRNU(Photo Response Non-Uniformity) is corrected inside the camera electronics, the effect of the remaining non-uniformity to the compression result will be negligible. The non-uniformity correction result shall have big difference according to the sensor modeling and the calculation method to get correction coefficient. Usually, the sensor can be modeled with one dimensional coefficients which are a gain and a offset for each pixel. Only two measurements are necessary theoretically to get coefficients. However, these are not the optimized value over the whole illumination level. This paper proposes the algorithm to calculate the optimized non-uniformity correction coefficients over whole illumination radiance. The proposed algorithm uses several measurements and the least square method to get the optimum coefficients. The proposed algorithm is verified using the own camera electronics including sensor, electrical test equipment and optical test equipment such as the integrating sphere.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.1-8
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• 2016

In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.26-49
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• 2018

The purpose of this study was to verify the reliability of the solar radiation model and discuss its applicability to the urban area of Seoul for summer heat stress mitigation. We extended the study area closer to the city scale and enhanced the spatial resolution sufficiently to determine pedestrian-level urban radiance. The domain was a $4km^2$ residential area with high-rise building sites. Radiance modelling (SOLWEIG) was performed with LiDAR (Light Detection and Ranging)-based detailed geomorphological land cover shape. The radiance model was evaluated using surface energy balance (SEB) observations. The model showed the highest accuracy on a clear day in summer. When the mean radiation temperature (MRT) was simulated, the highest value was for a low-rise building area and road surface with a low shadow effect. On the other hand, for high-rise buildings and vegetated areas, the effect of shadows was large and showed a relatively low value of mean radiation temperature. The method proposed in this study exhibits high reliability for the management of heat stress in urban areas at pedestrian height. It is applicable for many urban micro-climate management functions related to natural and artificial urban settings; for example, when a new urban infrastructure is planned.