• Journal of Korean Society on Water Environment
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• v.32 no.5
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• pp.450-457
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• 2016

The Total Maximum Daily Load (TMDL) is a watershed management system that involves the establishment of the target water quality, the calculation of permission loading (allocation loading), and the control of total pollutants for each unit watershed. Allocation loading is assessed through the comprehensive implementation assessment of the previous year's plan. Assessment results are used for follow-up management measures such as the limit of development and updating of TMDL Management Implementation Plans for the next planning period. Although detailed assessment criteria are important, they are not currently available. Therefore, we suggested assessment criteria by comparing two methods('integration method' and 'separation method') using combination point and non-point discharge loading. We also examined the penalty criteria considering controllable load local government and updating methods of the TMDL Management Implementation Plan for the next planning period.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11C
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• pp.1076-1082
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• 2005

Recently, there have been much efforts in the image segmentation using morphological approach. Among them, the watershed algorithm is one of powerful tools which can take advantages of both of the conventional edge-based segmentation and region-based segmentation. The concept of watershed is based on topographic analogy. But, its high sensitivity to noise yields a very large number of resulting segmented regions which leads to oversegmentation. So we suggest the restricted waterfall algorithm which reduce the oversegmentation by eliminate not only local minima but also local maxima. As a result, the restricted waterfall algorithm has a good segmented image than the other methods, and has a better binary image than the histogram thresholding method.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.159-166
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• 2021

In order to analyze cell images, accurate segmentation of each cell is indispensable. However, the reality is that accurate cell image segmentation is not easy due to various noises, dense cells, and inconsistent shape of cells. Therefore, in this paper, we propose an algorithm that combines marker-based watershed segmentation and ellipse fitting method for glioblastoma cell segmentation. In the proposed algorithm, in order to solve the over-segmentation problem of the existing watershed method, the marker-based watershed technique is primarily performed through "seeding using local minima". In addition, as a second process, the concave point search using ellipse fitting for final segmentation based on the connection line between the concave points has been performed. To evaluate the performance of the proposed algorithm, we compared three algorithms with other algorithms along with the calculation of segmentation accuracy, and we applied the algorithm to other cell image data to check the generalization and propose a solution.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.2
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• pp.1-10
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• 2003

This paper presents an efficient method for image segmentation based on a multiresolution application of a wavelet transform and watershed segmentation algorithm. The procedure toward complete segmentation consists of four steps: pyramid representation, image segmentation, region merging and region projection. First, pyramid representation creates multiresolution images using a wavelet transform. Second, image segmentation segments the lowest-resolution image of the pyramid using a watershed segmentation algorithm. Third, region merging merges the segmented regions using the third-order moment values of the wavelet coefficients. Finally, the segmented low-resolution image with label is projected into a full-resolution image (original image) by inverse wavelet transform. Experimental results of the presented method can be applied to the segmentation of noise or degraded images as well as reduce over-segmentation.

• Journal of Korean Society on Water Environment
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• v.37 no.4
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• pp.263-274
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• 2021

This study presents the achievements and limitations of the voluntary-based Total Maximum Daily Load (TMDL) through statistical analysis of water quality monitoring data and performance assessments of TMDL plans implemented in the Gyeongan watershed. The results clearly showed that responsible local governments complied the allocated TMDL and the designated water quality goals were successfully achieved in the required period. This was possible because the Ministry of Environment provided innovative incentives, such as, relaxations of the existing tight land-use regulations and full-scale financial aids for constructing and operating public treatment facilities to draw local government voluntary participation. However, a couple of problems which decreased the effectiveness and efficiency of the voluntary TMDL were identified. The different TMDL implementation schedules between upstream (Yongin) and downstream (Gwangju) governments caused delay in water quality improvement and exaggerated TMDL allocation to the local development which made excessive investment in the treatment facilities. Although it is not directly related to the voluntary scheme, technical methods for establishing and assessing the water quality goals should be improved so that the effects of flow conditions on water quality are properly assessed. We expect that results of this case study contribute to developing a more effective voluntary-based scheme for the implementation of the so-called 'tributary TMDL' in the future.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.814-818
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• 2004

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.2
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• pp.69-77
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• 2001

An artificial neural network model was developed to analyze and forecast daily steamflow flow a small watershed. Error Back propagation neural networks (EBPN) of daily rainfall and runoff data were found to have a high performance in simulating stremflow. The model adopts a gradient descent method where the momentum and adaptive learning rate concepts were employed to minimize local minima value problems and speed up the convergence of EBP method. The number of hidden nodes was optimized using Bayesian information criterion. The resulting optimal EBPN model for forecasting daily streamflow consists of three rainfall and four runoff data (Model34), and the best number of the hidden nodes were found to be 13. The proposed model simulates the daily streamflow satisfactorily by comparison compared to the observed data at the HS#3 watershed of the Baran watershed project, which is 391.8 ha and has relatively steep topography and complex land use.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5B
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• pp.273-285
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• 2012

Current TMDL based on the 'Polluter Pays Principle' in Republic of Korea is individually operated by each local government for the designed allocated pollution load of unit watershed and unit district. However, unlike the motion of the air contaminants, the polluted contaminants in a river move from upstream to downstream, and a river can affect to districts more than two. In addition, a decision making on the construction of a sewage treatment facilities follows the concept of 'economy of scale'. These reasons support the collaboration among local governments in order to reduce the costs in improving water quality. This study suggested a method to reduce water quality management cost by redistributing reduction load considering cost-effectiveness for an entire watershed. The assessment on the suggested method is conducted in Youngsan river watershed. Without variation in total load, reduction load assigned for unit watershed and unit district is retributed in the region where pollutant source is concentrated, and then water quality and cost reduction improved from the redistribution of reduction load is analyzed. The results show that the cost saved by the suggested method is KRW 124 billion for scenario-1 and 172 billion for scenario-2 considering total cost of KRW 788 billion for the existing plan. We expect that the suggested method is a good example to reduce water quality management cost in local governments for TMDL.

• Journal of the Earthquake Engineering Society of Korea
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• v.18 no.6
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• pp.271-278
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• 2014

Seismic intensity deduced from instrumental data has been evaluated using the empirical relationship between intensity and peak ground acceleration (PGA) during an earthquake. The Japan Meteorological Agency (JMA) developed a seismic intensity meter, which can estimate the real-time seismic intensity from seismic motions observed at a local site to evaluate the damage during the earthquake more correctly. This paper proposes a practical application of the JMA intensity to dams during the 2013 earthquake in Yeongcheon, Korea. In the present paper, seismic intensity was estimated from the relationships between accelerations observed at Yeongcheon Dam. Estimated seismic intensities were in the range of 0 to 3, which was verified from the displacements of dams and the variation of the ground water level observed at Yeongcheon dam during the earthquake. The JMA intensity, which is determined by considering the frequency, duration of cyclic loading, etc., was 0 (zero) and there was no damage to Yeoncheon dam during the earthquake.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.637-644
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• 2006

Biomedical image is often complex. An applied image analysis system should deal with the images which are of quite low quality and are challenging to segment. This paper presents a framework for color cell image segmentation by learning and classification online. It is a robust two-stage scheme using kernel method and watershed transform. In first stage, a two-class SVM is employed to discriminate the pixels of object from background; where the SVM is trained on the data which has been analyzed using the mean shift procedure. A real-time training strategy is also developed for SVM. In second stage, as the post-processing, local watershed transform is used to separate clustering cells. Comparison with the SSF (Scale space filter) and classical watershed-based algorithm (those are often employed for cell image segmentation) is given. Experimental results demonstrate that the new method is more accurate and robust than compared methods.