• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.96-104
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• 2011

A halftoning method is used to obtain a binary image visually similar to a continuous gray-level image through the image output devices employing the limited number of gray-levels. As a halftoning method, the error diffusion method is widely used in various applications because of its low computational complexity and good image quality. However, this method weakens the edge in the process of error diffusion to the neighboring pixels. In this case, degradation of the edge quality and damage of the vivid image is expected. To solve these problems, the proposed method determines the adaptive error filter considering the error information of the present pixel and edge distribution of the neighbor pixels. Compared with the conventional methods for enhancing edges, the proposed method involves relatively a few process resources because of its simple procedure, still considerably improving the edges in the halftone image. To evaluate the objective image quality, the performance of the proposed method is compared with that of the conventional method in terms of the edge correlation and the local average accordance.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.125-134
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• 2010

It is occurred bus arrival time errors when a bus arrives at a bus stop because of a variety of traffic condition such as traffic signal cycle, the time to get on and off a bus, a bus-only lane and so on. In this paper, bus delay time which is occurred as the result of traffic condition was estimated with Markov Chain process and bus arrival time at each bus stop was predicted with it. As the result of the study, it is confirmed to improve accuracy than the method of bus arrival time prediction with existing method (weighed moving average method) in case predicting bus arrival time using 7 by 7 and 9 by 9 matrixes.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.615-620
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• 2009

Nowadays, wireless infrastructures such as sensor networks are widely used in many different areas. In case of sensor networks, the wirelessly connected sensors can execute different kind of tasks in a diversity of environments, and one of the most important parameter for a successful execution of such tasks is the location information of each node. As to localization problems in WSNs, there are ToA (Timer of Arrival), RSS (Received Signal Strength), AoA (Angle of Arrival), etc. In this paper, we propose a modification of existing ToA and RSS based methods, adding a weighted average scheme to measure more precisely the distance between nodes. The comparison experiments with the traditional ToA method show that the average error value of proposed method is reduced by 0.1 cm in indoor environment ($5m{\times}7m$) and 0.6cm in outdoor environment ($10{\times}10m$).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.4
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• pp.413-422
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• 2012

After development of GPS in the 1960's, the United States released SA(Selective Availability) in 2000 and then the GPS has become commercialized to the present. The result of repeatedly developed GPS observation, the GPS real-time observation methods is RTK which basically always needs two base stations and has a fault of the accuracy decreasing as the distance between a mobile station and a receiver is increasing. Because of these weakness, VRS method has come out. VRS(Virtual Reference Station) generates the imaginary point near mobile station from several observatory datum of GPS, sets the accurate location of mobile station, thus shows high reliability and mobility. Now, the cadastral datum point is used with azimuth, repetition, and graphical traversing method for traverse network. The result of measurement indicates many problems because of different accomplishment interval given point, restrictions on the length of the conductor, many errors on the observations. So, this study did comparative analysis of the cadastral datum points through VRS method by Continuously Operating Reference Station. Through the above comparative analysis, The comparative result between surveyed result with repetition method through total station observed Cadastral Control Points and surveyed result with VRS-RTK has shown that average error of x-axis is -0.08m, average error of y-axis, +0.07m and average distance error is +0.11m.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.75-82
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• 2023

Data for measuring the flow rate of streams are used as important basic data for the development and maintenance of water resources, and many experts are conducting research to make more accurate measurements. Especially, in Korea, monsoon rains and heavy rains are concentrated in summer due to the nature of the climate, so floods occur frequently. Therefore, it is necessary to measure the flow rate most accurately during a flood to predict and prevent flooding. Thus, the U.S. Geological Survey (USGS) introduces 1, 2, 3 point method using a flow meter as one way to measure the average flow rate. However, it is difficult to calculate the average flow rate with the existing 1, 2, 3 point method alone.This paper proposes a new 1, 2, 3 point method formula, which is more accurate, utilizing one probabilistic entropy concept. This is considered to be a highly empirical study that can supplement the limitations of existing measurement methods. Data and Flume data were used in the number of holesman to demonstrate the utility of the proposed formula. As a result of the analysis, in the case of Flume Data, the existing USGS 1 point method compared to the measured value was 7.6% on average, 8.6% on the 2 point method, and 8.1% on the 3 point method. In the case of Coleman Data, the 1 point method showed an average error rate of 5%, the 2 point method 5.6% and the 3 point method 5.3%. On the other hand, the proposed formula using the concept of entropy reduced the error rate by about 60% compared to the existing method, with the Flume Data averaging 4.7% for the 1 point method, 5.7% for the 2 point method, and 5.2% for the 3 point method. In addition, Coleman Data showed an average error of 2.5% in the 1 point method, 3.1% in the 2 point method, and 2.8% in the 3 point method, reducing the error rate by about 50% compared to the existing method.This study can calculate the average flow rate more accurately than the existing 1, 2, 3 point method, which can be useful in many ways, including future river disaster management, design and administration.

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.2
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• pp.83-91
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• 2017

Objectives: The purpose of this study was to evaluate the error of the leaf position accuracy of the MLC due to the gravity effect according to the gantry angle by using picket fence test using EPID and GafChromic EBT3 film. Materials and Methods: A 5 cm solid phantom was placed on the table and the SAD was set to 100 cm. The EBT3 film was placed exactly over the solid phantom and covered a 1.5 cm solid phantom and the picket fence test was performed. The EPID was measured under the same conditions as the EBT3 film at SID 100 cm. The gantry angles were measured at $0^{\circ}$, $90^{\circ}$, $180^{\circ}$ and $270^{\circ}$ in order to evaluate the position of the MLC according to the gantry angle. For the geometric evaluation of the MLC, the leaf position accuracy of the MLC was analyzed using the analysis program. Results: In case of EPID, when the gantry angle was changed to $0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$, the difference of the position errors of the leaves was 0.18 mm, 0.31 mm, 0.20 mm, 0.26 mm on the average and the maximum values of the errors were respectively 0.44 mm, 0.54 mm, 0.34 mm, 0.44 mm. In case of EBT3 film, when the gantry angle was changed to $0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$, the difference of the position errors of the leaves was 0.19 mm, 0.21 mm, 0.19 mm, 0.31 mm on the average and the maximum values of the errors were respectively 0.35 mm, 0.45 mm, 0.36 mm, 0.48 mm. Conclusion: In this study, we analyzed the position error of the leaf of the MLC according to the gantry angle, and confirmed the position error of the leaf by gravity effect. As a result of comparing the leaf position accuracy using EPID and EBT3 film according to the variation of gantry angle, a larger error occurred in the error analysis method using EPID than that of EBT3 film. Therefore, in the case of IMRT based on MLC, as well as verification of accurate dosimetry should be conducted, it is considered that the quality control and verification for the precise operation of the MLC will be needed. and it is necessary to compare and verify the method of analysis.

• Progress in Medical Physics
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• v.24 no.4
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• pp.290-294
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• 2013

Stereotactic Radiosurgery require high accuracy and precision of patient positioning and target localization. We evaluate the real time positioning accuracy of isocenter using optic guided patient positioning system, ExacTrac (BrainLab, Germany), during spinal radiosurgery procedure. The system is based on real time detect multiple body markers attached on the selected patient skin landmarks. And a custom designed patient positioning verification tool (PPVT) was used to check the patient alignment and correct the patient repositioning before radiosurgery. In this study, We investigate the selected 8 metastatic spinal tumor cases. All type of tumors commonly closed to thoracic spinal code. To evaluate the isocenter positioning, real time patient alignment and positioning monitoring was carried out for comparing the current 3-dimensional position of markers with those of an initial reference positions. For a selected patient case, we have check the isocenter positioning per every 20 millisecond for 45 seconds during spinal radiosurgery. In this study, real time average isocenter positioning translation were $0.07{\pm}0.17$ mm, $0.11{\pm}0.18$ mm, $0.13{\pm}0.26$ mm, and $0.20{\pm}0.37$ mm in the x (lateral), y (longitudinal), z (vertical) directions and mean spatial error, respectively. And body rotations were $0.14{\pm}0.07^{\circ}$, $0.11{\pm}0.07^{\circ}$, $0.03{\pm}0.04^{\circ}$ in longitudinal, lateral, table directions and mean body rotation $0.20{\pm}0.11^{\circ}$, respectively. In this study, the maximum mean deviation of real time isocenter positioning translation during spinal radiosurgery was acceptable accuracy clinically.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.368-375
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• 2023

In this study, we examined the error characteristic and bias correction method for one-month temperature forecast data produced through joint development between the Rural Development Administration and the H ong Kong University of Science and Technology. For this purpose, hindcast data from 2013 to 2021, weather observation data, and various environmental information were collected and error characteristics under various environmental conditions were analyzed. In the case of maximum and minimum temperatures, the higher the elevation and latitude, the larger the forecast error. On average, the RMSE of the forecast data corrected by the linear regression model and the XGBoost decreased by 0.203, 0.438 (maximum temperature) and 0.069, 0.390 (minimum temperature), respectively, compared to the uncorrected forecast data. Overall, XGBoost showed better error improvement than the linear regression model. Through this study, it was found that errors in prediction data are affected by topographical conditions, and that machine learning methods such as XGBoost can effectively improve errors by considering various environmental factors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.461-467
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• 2006

To detect individual vehicular speed, double loop detection technique has been widely used. This paper investigates four methodologies to measure individual speed using only a single loop sensor in a traveling lane. Two methods developed earlier include estimating the speed by means of (Case 1) the slop of inductance wave form generated by the sensor and (Case 2) the average vehicle lengths. Two other methods are newly developed through this study, which are estimations by measuring (Case 3) the mean of wheelbases using the sensor installed traversal to the traveling lane and (Case 4) the mean of wheel tracks by the sensor installed diagonally to the traveling lane. These four methodologies were field-tested and their accuracy of speed output was compared statistically. This study used Equality Coefficient and Mean Absolute Percentage Error for the assessment. It was found that the method (Case 1) was best accurate, followed by method (Case 4), (Case 2), and (Case 3).

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.