• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.19-27
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• 2015

Technologies of wind power generation for development of alternative energy technology have been accumulated over the past 20 years. Wind power generation is environmentally friendly and economical because it uses the wind blowing in nature as energy resource. In order to operate wind power generation efficiently, it is necessary to accurately predict wind speed changing every moment in nature. It is important not only averagely how well to predict wind speed but also to minimize the largest absolute error between real value and prediction value of wind speed. In terms of generation operating plan, minimizing the largest absolute error plays an important role for building flexible generation operating plan because the difference between predicting power and real power causes economic loss. In this paper, we propose a method of wind speed prediction using numeric prediction algorithm-based wind speed forecast model made to analyze the wind speed forecast given by the Meteorological Administration and pattern value for considering seasonal property of wind speed as well as changing trend of past wind speed. The wind speed forecast given by the Meteorological Administration is the forecast in respect to comparatively wide area including wind generation farm. But it contributes considerably to make accuracy of wind speed prediction high. Also, the experimental results demonstrate that as the rate of wind is analyzed in more detail, the greater accuracy will be obtained.

• Korean Chemical Engineering Research
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• v.48 no.6
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• pp.717-724
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• 2010

The flash point is one of the most important physical properties used to determine the potential for fire and explosion hazards of flammable liquids. Despite the needs of the experimental flash point data for the design and construction of chemical plants, there is often a significant gap between the demands for the data and their availability. This study have built and compared two models of partial least squares(PLS) and support vector machine(SVM) to predict the experimental flash points of 893 organic compounds out of DIPPR 801. As the independent variables of the models, 65 functional groups were chosen based on the group contribution method that was oriented from the assumption that each fragment of a molecule contributes a certain amount to the value of its physical property, and the logarithm of molecular weight was added. The prediction errors calculated from cross-validation were employed to determine the optimal parameters of two models. And, an optimization technique should be used to get three parameters of SVM model. This work adopted particle swarm optimization that is one of heuristic optimization methods. As the selection of training data can affect the prediction performance, 100 data sets of randomly selected data were generated and tested. The PLS and SVM results of the average absolute errors for the whole data range from 13.86 K to 14.55 K and 7.44 K to 10.26 K, respectively, indicating that the predictive ability of the SVM is much superior than PLS.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.561-572
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• 2014

The backwater effect at a tributary junction increases the risk of flood damage such as inundation and levee overflow. In particular, the rapid increase in water level may cause injury to persons. The purpose of this research is the development of the real-time flood forecasting technique as a part of the non-structural flood damage reduction measures. To this end, the factors causing a water level rising at a junction were examined, and the empirical formula for predicting flood level at a junction was developed using the calculated discharge and water level data from the well-constructed hydraulic model. The water level predictions show that average absolute error is about 0.2~0.3m with the maximum error of 1.0m and peak time can be captured prior to 0~5 hr. From the results of this study, the real-time flood forecasting system of a tributary junction can be easily constructed, and this system is expected to be utilized for reduction of flood inundation damage.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.123-129
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• 2017

This paper proposes a new nonnegative matrix factorization (NMF) based direction-of-arrival (DOA) estimation method for multiple sound sources using a dual microphone array. First of all, sound signals coming from the dual microphone array are segmented into consecutive analysis frames, and a steered-response power phase transform (SRP-PHAT) beamformer is applied to each frame so that stereo signals of each frame are represented in a time-direction domain. The time-direction outputs of SRP-PHAT are stored for a pre-defined number of frames, which is referred to as a time-direction block. Next, In order to estimate DOAs robust to noise, each time-direction block is normalized along the time by using a block subtraction technique. After that, an unsupervised NMF method is applied to the normalized time-direction block in order to cluster the directions of each sound source in a multiple sound source environments. In particular, the activation and basis matrices are used to estimate the number of sound sources and their DOAs, respectively. The DOA estimation performance of the proposed method is evaluated by measuring a mean absolute error (MAE) and the standard deviation of errors between the oracle and estimated DOAs under a three source condition, where the sources are located in [$-35{\circ}$, 5m], [$12{\circ}$, 4m], and [$38{\circ}$, 4.m] from the dual microphone array. It is shown from the experiment that the proposed method could relatively reduce MAE by 56.83%, compared to a conventional SRP-PHAT based DOA estimation method.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.81-87
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• 2016

It is important to analyze the exact damage information for fast recovery when natural disasters cause damage on river-side facilities such as dams, bridges, embankments etc. In this study, we shows the method to effectively damage analysis plan using UAV(Unmanned aerial vehicle) images and accuracy assessment of it. The UAV images are captured on area near the river-side facilities and the core methodology for damage analysis are image matching and change detection algorithm. The result(point cloud) from image matching is to construct 3-dimensional data using by 2-dimensional images, it extracts damage areas by comparing the height values on same area with reference data. The results are tested absolute locational precision compared by post-processed aerial LiDAR data named reference data. The assessment analysis test shows our matching results 10-20 centimeter level precision if external orientation parameters are very accurate. This study shows suggested method is very useful for damage analysis in a large size structure like river-side facilities. But the complexity building can't apply this method, it need to the other method for damage analysis.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1013-1027
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• 2021

Images taken with KOMPSAT-3 have additional NIR and PAN bands, as well as RGB regions of the visible ray band, compared to imagestaken with a standard camera. Furthermore, electrical and optical properties must be considered because a wide radius area of approximately 17 km or more is photographed at an altitude of 685 km above the ground. In other words, the camera sensor of KOMPSAT-3 is distorted by each CCD pixel, characteristics of each band,sensitivity and time-dependent change, CCD geometry. In order to solve the distortion, correction of the sensors is essential. In this paper, we propose a method for detecting uniform regions in side-slider-based KOMPSAT-3 images using segment-based noise analysis. After detecting a uniform area with the corresponding algorithm, a correction table was created for each sensor to apply the non-uniformity correction algorithm, and satellite image correction was performed using the created correction table. As a result, the proposed method reduced the distortion of the satellite image,such as vertical noise, compared to the conventional method. The relative radiation accuracy index, which is an index based on mean square error (RA) and an index based on absolute error (RE), wasfound to have a comparative advantage of 0.3 percent and 0.15 percent, respectively, over the conventional method.

• The Journal of Korean Society for Radiation Therapy
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• v.28 no.2
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• pp.179-186
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• 2016

Purpose : To figure out if the treatment plan for rectum, bladder and prostate that have a lot of interfraction errors satisfies dosimetric limits without adaptive plan by analyzing MR image. Materials and Methods : This study was based on 5 prostate cancer patients who had IMRT(total dose: 70Gy) Using ViewRay MRIdian System(ViewRay, ViewRay Inc., Cleveland, OH, USA) The treatment plans were made on the same CT images to compare with the plan quality according to adaptive plan, and the Eclipse(Ver 10.0.42, Varian, USA) was used. After registrate the 5 treatment MR images to the CT images for treatment plan to analyze the interfraction changes of organ, we measured the dose volume histogram and the changes of the absolute volume for each organ by appling the first treatment plan to each image. Over 5 fractions, the total dose for PTV was $V_{36.25}$ Gy $${\geq_-}$$ 95%. To confirm that the prescription dose satisfies the SBRT dose limit for prostate, we measured $V_{100%}$, $V_{95%}$, $V_{90%}$ for CTV and $V_{100%}$, $V_{90%}$, $V_{80%}$ $V_{50%}$ of rectum and bladder. Results : All dose average value of CTV, rectum and bladder satisfied dose limit, but there was a case that exceeded dose limit more than one after analyzing the each image of treatment. After measuring the changes of absolute volume comparing the MR image of the first treatment plan with the one of the interfraction treatment, the difference values were maximum 1.72 times at rectum and maximum 2.0 times at bladder. In case of rectum, the expected values were planned under the dose limit, on average, $V_{100%}=0.32%$, $V_{90%}=3.33%$, $V_{80%}=7.71%$, $V_{50%}=23.55%$ in the first treatment plan. In case of rectum, the average of absolute volume in first plan was 117.9 cc. However, the average of really treated volume was 79.2 cc. In case of CTV, the 100% prescription dose area didn't satisfy even though the margin for PTV was 5 mm because of the variation of rectal and bladder volume. Conclusion : There was no case that the value from average of five fractions is over the dosimetric limits. However, dosimetric errors of rectum and bladder in each fraction was significant. Therefore, the precise delivery is needed in case of prostate SBRT. The real-time tracking and adaptive plan is necessary to meet the precision delivery.

• Progress in Medical Physics
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• v.20 no.1
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• pp.43-50
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• 2009

The 4 bank mico-MLC (mMLC; Acculeaf, Direx, Isral) has been commissioned for clinical use of linac based stereotactic radiosurgery. The geometrical parameters to control the leaves were determined and comparisons between measured and calculated by the calculation model were performed in terms of absolute dose (cGy/100 MU). As a result of evaluating calculated dose for various field sizes and depths of 5 and 10 cm in water in the geometric condition of fixed SSD (source to surface distance) and fixed SCD (source to chamber distance), most of differences were within 1% for 6 MV and 15 MV x-rays. The penumbral widths at the isocenter were approximately evaluated to 0.29~0.43 cm depending on the field size for 6 MV and 0.36~0.51 cm for 15 MV x-rays. The average transmission and leakage for 6 MV and 15 MV x-rays were 6.6% and 7.4% respectively in single level of leaves fully closed. In case of dual level of leaves fully closed the measured transmission is approximately 0.5% for both 6 MV and 15 MV x-rays. Through the commissiong procedure we could verify the dose characteristics of mMLC and approximately evaluate the error ranges for treatment planning system.

• Radiation Oncology Journal
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• v.25 no.4
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• pp.249-260
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• 2007

Purpose: In order to enhance the quality of IMRT as employed in Korea, we developed a remote monitoring system. The feasibility of the system was evaluated by conducting a pilot study. Materials and Methods: The remote monitoring system consisted of a head and neck phantom and a user manual. The phantom contains a target and three OARs (organs at risk) that can be detected on CT images. TLD capsules were inserted at the center of the target and at the OARs. Two film slits for GafchromicEBT film were located on the axial and saggital planes. The user manual contained an IMRT planning guide and instructions for IMRT planning and the delivery process. After the manual and phantom were sent to four institutions, IMRT was planed and delivered. Predicted doses were compared with measured doses. Dose distribution along the two straight lines that intersected at the center of the axial film was measured and compared with the profiles predicted by the plan. Results: The measurements at the target agreed with the predicted dose within a 3% deviation. Doses at the OARs that represented the thyroid glands showed larger deviations (minimum 3.3% and maximum 19.8%). The deviation at OARs that represented the spiral cord was $0.7{\sim}1.4%$. The percentage of dose distributions that showed more than a 5% of deviation on the lines was $7{\sim}27%$ and $7{\sim}14%$ along the horizontal and vertical lines, respectively. Conculsion: Remote monitoring of IMRT using the developed system was feasible. With remote monitoring, the deviation at the target is expected to be small while the deviation at the OARs can be very large. Therefore, a method that is able to investigate the cause of a large deviation needs to be developed. In addition, a more clinically relevant measure for the two-dimensional dose comparison and pass/fail criteria need to be further developed.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.266-279
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• 2014

For the evaluation of roadway safety, diverse methods, including before-after studies, simple comparison using historic traffic accident data, methods based on experts' opinion or literature, have been applied. Especially, many research efforts have developed traffic accident prediction models in order to identify critical elements causing accidents and evaluate the level of safety. A traffic accident prediction model must secure predictability and transferability. By acquiring the predictability, the model can increase the accuracy in predicting the frequency of accidents qualitatively and quantitatively. By guaranteeing the transferability, the model can be used for other locations with acceptable accuracy. To this end, traffic accident prediction models using non-linear regression, artificial neural network, and structural equation were developed in this study. The predictability and transferability of three models were compared using a model development data set collected from 90 signalized intersections and a model validation data set from other 33 signalized intersections based on mean absolute deviation and mean squared prediction error. As a result of the comparison using the model development data set, the artificial neural network showed the highest predictability. However, the non-linear regression model was found out to be most appropriate in the comparison using the model validation data set. Conclusively, the artificial neural network has a strong ability in representing the relationship between the frequency of traffic accidents and traffic and road design elements. However, the predictability of the artificial neural network significantly decreased when the artificial neural network was applied to a new data which was not used in the model developing.