• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.621-628
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• 2021

This paper proposes a method to calibrate a thermal camera with three different perspectives. In particular, the intrinsic parameters of the camera and re-projection errors were provided to quantify the accuracy of the calibration result. Three lenses of the camera capture the same image, but they are not overlapped, and the image resolution is worse than the one captured by the RGB camera. In computer vision, camera calibration is one of the most important and fundamental tasks to calculate the distance between camera (s) and a target object or the three-dimensional (3D) coordinates of a point in a 3D object. Once calibration is complete, the intrinsic and the extrinsic parameters of the camera(s) are provided. The intrinsic parameters are composed of the focal length, skewness factor, and principal points, and the extrinsic parameters are composed of the relative rotation and translation of the camera(s). This study estimated the intrinsic parameters of thermal cameras that have three lenses of different perspectives. In particular, image enhancement based on a deep learning algorithm was carried out to improve the quality of the calibration results. Experimental results are provided to substantiate the proposed method.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.221-229
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• 2008

The three dimensional model method is widely applied in resource development for feasibility study, mine design, excavation planning and process management by constructing the database of various data in 3 dimensional space. Most of geophysical surveys for the purpose of engineering and resource development are performed in 2 dimensional line survey due to the restriction of the field situation, technical or economical situation and so on. The acquired geophysical data are used as the input for the 2 dimensional inversion under the 2 dimensional assumption. But the geophysical data are affected by 3 dimensional space. Therefore in order to reduce the error caused by 2 dimensional assumption, the 2 dimensional inversion result must be interpreted considering the additional information such as 3 dimensional topography, geological structure, borehole survey etc. The applicability and usability of 3 dimensional modeling method are studied by reviewing the case study to the geophysical data acquired in field of engineering and resource development.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.7-19
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• 2005

Mode choice Analysis is essential analysis stage in transportation demand forecasting process. Therefore, methods for calibration and forecasting of mode choice model in aspect of practical view need to be discussed in depth. Since 1980s, choice models, especially Logit model, are spread widely and rapidly over academic area, research institutes and consulting firms in Korea like other developed countries in the world. However, the process of calibration and parameter estimation for practical application was not clearly explained in previous papers and reports. This study tried to explain clearly the calibration process of mode choice step by step and suggested a forecasting mode choice model that can be applicable in real policy analysis by using household survey data of Pusan metropolitan are. The study also suggested a way of estimating attributes which was not observed during the household survey commonly such as travel time and cost of unchosen alternative modes. The study summarized the statistical results of model specification for four different Logit models as a process to upgrade model capability of explanation for real traveler's choice behaviors. By using the analysis results, it also calculated the value of travel time and compared them with the values of other previous studies to test reliability of the estimated model.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.51-57
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• 2012

Hepatic vessel tree is the key structure for hepatic disease diagnosis and liver surgery planning. Especially, it is used to evaluate the donors' and recipients' liver for the LDLT(Living Donors Liver Transplantation) and estimate the volumes of left and right hepatic lobes for securing their life in the LDLT. In this study, we propose a method to apply canny edge detection that is not affected by noise to the liver images for automatic segmentation of hepatic vessels tree in contrast abdominal MDCT image. Using histograms and average pixel values of the various liver CT images, optimized parameters of the Canny algorithm are determined. It is more time-efficient to use the common parameters than to change parameters manually according to CT images. Candidates of hepatic vessels are extracted by threshold filtering around the detected the vessel edge. Finally, using a system which detects the true-negatives and the false-positives in horizontal and vertical direction, the true-negatives are added in candidate of hepatic vessels and the false-positives are removed. As a result of the process, the various hepatic vessel trees of patients are accurately reconstructed in 3D.

• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.533-543
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• 2020

In order to provide information for proper management of groundwater resources, it is necessary to estimate the rise time of groundwater level by calculating the delay time between the time series of precipitation and groundwater level and to understand the characteristics of groundwater level variation. In this study, total delay time (TDT) and cross correlation coefficient between the moving averaged precipitation generated by using the moving average method to take into account the preceding precipitation and the groundwater level were calculated and analyzed for the nine groundwater level monitoring wells in the Pyoseon watershed in the southeast of Jeju Island. As a result, when the moving averaged precipitation was used, the correlation with the groundwater level was higher in all monitoring wells than in the case of using the raw precipitation, so that it was possible to more clearly estimate the delay time between precipitation and groundwater level. When using the moving averaged precipitation, it had cross correlation coefficients of up to 0.57 ~ 0.58 with the time series data of the groundwater level, and had a relatively high correlation when considering the preceding precipitation of about 24 days on average. The TDT was about 32 days on average, and it was confirmed that the consideration of preceding precipitation plays an important role in estimating the TDT because the days of moving averaged precipitation greatly influences the calculation of the TDT. In addition, through the use of moving averaged precipitation, we found an error in estimating the TDT due to the use of raw precipitation. Through the method of estimating the TDT used in this study and the use of the R code for estimating the TDT presented in the appendix of this paper, it will be possible to estimate the TDT for other regions in the future relatively easily.

• Spatial Information Research
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• v.22 no.1
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• pp.35-43
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• 2014

The Triangle Mesh Warping method is suggested and applied in coordinate transformation to world geodetic system in this study. The common points of Uiwang city are used to compare the transformation accuracy of the suggested methods with existing national coordinate transformation methods. As a result, the Triangle Mesh Warping method was satisfied with accuracy criteria for positioning on a map larger than scale 1/1,000 with smaller number of common points and without distortion modeling. Additionally, in case of Guri and Pyeongtaek city that established the World Geodetic System, the suggested method generates the result of transformation accuracy better than 5cm. Based on the test, it was found that the suggested method improves the problem of securing many common points and reduces the problem of mis-match between the transformed data of adjacent areas. Accordingly, for transformation of large-scale topographic map, cadastral map, GIS DB and serial cadastral map to the World Geodetic System, it is judged that the Triangle Mesh Warping would be a good method for economical efficiency and accuracy using by minimum common point.

• Journal of KIISE
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• v.42 no.5
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• pp.642-651
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• 2015

A vanishing point is a point where parallel lines converge, and they become evident when a camera's lenses are used to project 3D space onto a 2D image plane. Vanishing point detection is the use of the information contained within an image to detect the vanishing point, and can be utilized to infer the relative distance between certain points in the image or for understanding the geometry of a 3D scene. Since parallel lines generally exist for the artificial structures within images, line-detection-based vanishing point-detection techniques aim to find the point where the parallel lines of artificial structures converge. To detect parallel lines in an image, we detect edge pixels through edge detection and then find the lines by using the Hough transform. However, the various textures and noise in an image can hamper the line-detection process so that not all of the lines converging toward the vanishing point are obvious. To overcome this difficulty, it is necessary to assign a different weight to each line according to the degree of possibility that the line passes through the vanishing point. While previous research studies assigned equal weight or adopted a simple weighting calculation, in this paper, we are proposing a new method of assigning weights to lines after noticing that the lines that pass through vanishing points typically belong to artificial structures. Experimental results show that our proposed method reduces the vanishing point-estimation error rate by 65% when compared to existing methods.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.462-469
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• 2023

In this study, we propose a method for evaluating the risk of collision between ships to support determination on the risk of collision in a situation in which ships encounter each other and to prevent collision accidents. Because several uncertainties are involved in the navigation of a ship, must be considered when evaluating the risk of collision. We apply the Dempster-Shafer theory to manage this uncertainty and evaluate the collision risk of each target vessel in real time. The distance at the closest point approach (DCPA), time to the closest point approach (TCPA), distance from another vessel, relative bearing, and velocity ratio are used as evaluation factors for ship collision risk. The basic probability assignments (BPAs) calculated by membership functions for each evaluation factor are fused through the combination rule of the Dempster-Shafer theory. As a result of the experiment using automatic identification system (AIS) data collected in situations where ships actually encounter each other, the suitability of evaluation was verified. By evaluating the risk of collision in real time in encounter situations between ships, collision accidents caused by human errora can be prevented. This is expected to be used for vessel traffic service systems and collision avoidance systems for autonomous ships.