• Journal of Korean Society on Water Environment
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• v.38 no.3
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• pp.133-142
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• 2022

Natural organic matter (NOM) is a heterogeneous mixture of organic matter with various polarities and molecular weights in an aquatic environment. This study investigated the effects of separation conditions (resin volume, organic matter, etc.) and the repeated use of the resin for the fractionation of organic components in the DAX resin fractionation method. The distribution characteristics of the organic components ((hydrophilic [Hi], hydrophobic acid [HoA], and hydrophobic neutral [HoN]) under the derived fractionation conditions were also analyzed. Constant fractionation results (i.e. HoA/Hi ratio) were obtained in the column capacity factor (i.e. the packed resin volume) in the range of 50 to 100. The resin-packed column maintained constant separation efficiency for up to two repeated uses. The above conditions were applied to wastewater and stream water samples (before and after rainfall). The results showed that the concentration of organic matter in the wastewater effluent was 2-15 times lower with an increased ratio of hydrophilicity to hydrophobicity (i.e. Ho/Hi) compared to the influent depending on the industrial wastewater classification. Particularly, HoN was found to have a high content distribution, 10.2-50.4% of the total dissolved organic matter (DOM), in the effluents. For the stream water, the content of Hi or HoN increased significantly after rainfall, suggesting a correlation with the distribution characteristics of pollutants from the stream watershed. The results provide useful data to enhance the reliability of the DAX resin fractionation and its application to environmental samples.

• Current Optics and Photonics
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• v.7 no.5
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• pp.511-517
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• 2023

Pipelines play an important role in urban water supply and drainage, oil and gas transmission, etc. This paper presents a technique for pattern recognition of fiber optic vibration signals collected by a distributed vibration sensing (DVS) system using a deep learning residual network (ResNet). The optical fiber is laid on the pipeline, and the signal is collected by the DVS system and converted into a 64 × 64 single-channel grayscale image. The grayscale image is input into the ResNet to extract features, and finally the K-nearest-neighbors (KNN) algorithm is used to achieve the classification and recognition of pipeline damage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.633-639
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• 2018

High-resolution images using remote sensing (RS) is importance to secure for spatial classification depending on the characteristics of the complex and various factors that make up the river environment. The purpose of this study is to evaluate the accuracy of the classification results and to suggest the possibility of applying the high resolution hyperspectral images obtained by using the drone to perform spatial classification. Hyperspectral images obtained from study area were reduced the dimensionality with PCA and MNF transformation to remove effects of noise. Spatial classification was performed by supervised classifications such as MLC(Maximum Likelihood Classification), SVM(Support Vector Machine) and SAM(Spectral Angle Mapping). In overall, the highest classification accuracy was showed when the MLC supervised classification was used by MNF transformed image. However, it was confirmed that the misclassification was mainly found in the boundary of some classes including water body and the shadowing area. The results of this study can be used as basic data for remote sensing using drone and hyperspectral sensor, and it is expected that it can be applied to a wider range of river environments through the development of additional algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.23-30
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• 2017

NDVI (Normalized Difference Vegetation Index) plays an important role in surface land cover classification and LST (Land Surface Temperature Extraction). Its characteristics do not full carry the information of the surface cover typically in urban areas even though it is widely used in analyses in urban areas as well as in vegetation. However, abnormal NDVI values are frequently found in urban areas. We, therefore, examined NDVI values on whether NDVI is appropriate for LST and whether there are considerations in NDVI analysis typically in urban areas because NDVI is strongly related to the surface emissivity calculation. For the study, we observed the influence of the surface settings (i.e., geometric shape and color) on NDVI values in urban area and transition features between three land cover types, vegetation, urban materials, and water. Interestingly, there were many abnormal NDVI values systematically derived by the surface settings and they might influence on NDVI and eventually LST. Also, there were distinguishable transitions based on the mixture of three surface materials. A transition scenario was described that there are three transition types of mixture (urban material-vegetation, urban material-water, and vegetation-water) based on the relationship of NDVI and LST even though they are widely distributed.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.202-212
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• 2012

Due to the deterioration of water supply network and the deficiency of raw water, the water utility of local governments have performed various projects to improve their revenue water ratio. However, it is very difficult to estimate the cost for maintaining the revenue water ratio at higher level after completing the project, because local governments have different conditions affecting the operating and maintenance cost of water supply network. The purpose of this study is to present a procedure to estimate the operating and maintenance cost required to maintain the target revenue water ratio of the water supply network. For this purpose, we estimated the cost used only for operation and maintenance of water supply network of 164 local governments with the aid of K-Mean Clustering Analysis and the data from 40 representative local governments. Then, the regression analysis was performed to find relationship between revenue water ratio and the operating and maintenance cost with two different data sets generated by two classification methods; the first method classifies the local governments by means of k-means clustering, and the other classifies the local governments according to the index standardized by the operating and maintenance cost per unit length of water mains per revenue water ratio. The results shows that the method based on the index standardized by the cost and revenue water ratio of each government produces more reliable results for finding regression equations between revenue water ratio and the operating and maintenance cost only for water supply network. The estimated regression equations for each group can be used to estimate the cost required to keep the target revenue water ratio of the local government.

• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.99-108
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• 2005

In this study, thirteen villages in Chonnam province were selected as case study sites and the spatial distribution of the facilities in the villages was examined to provide basic information fur the establishment of rural plans. According to the questionnaire survey, various problem such as environmental pollution, position, scene, management etc. was brought owing to cattle shed, and dissension was more or less seen by scale of facilities, management of facilities and waste, regional factor(stock farming management condition, life style and attitude of inhabitants) and topographical factor (height, position physical aspect of a mountain, distance with water resources etc.) etc.. The facilities could be classified into 6 types based on the their spatial locations: 1) Type 1, facilities located at the waterside; 2) Type 2, facilities located at the entrance of village; 3) Type 3 facilities, scattered in the residential area: 4) Type 4 facilities, collectivized in village; 5) Type 5 facilities, adjoining village; and 6) Type 6 facilities, scattered irregularly inside and outside of village. Based on the classification, possible implementations for the reduction of environmental impacts were suggested. The results of this study could be used as an example of study on the distribution, classification, and rearrangement of environment-impacting facilities in rural areas for improvement of their roles in providing amenity resources.

• Geomechanics and Engineering
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• v.25 no.1
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• pp.17-30
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• 2021

This paper develops a convenient approach for deterministic and probabilistic evaluations of tunnel face stability using support vector machine classifiers. The proposed method is comprised of two major steps, i.e., construction of the training dataset and determination of instance-based classifiers. In step one, the orthogonal design is utilized to produce representative samples after the ranges and levels of the factors that influence tunnel face stability are specified. The training dataset is then labeled by two-dimensional strength reduction analyses embedded within OptumG2. For any unknown instance, the second step applies the training dataset for classification, which is achieved by an ad hoc Python program. The classification of unknown samples starts with selection of instance-based training samples using the k-nearest neighbors algorithm, followed by the construction of an instance-based SVM-KNN classifier. It eventually provides labels of the unknown instances, avoiding calculate its corresponding performance function. Probabilistic evaluations are performed by Monte Carlo simulation based on the SVM-KNN classifier. The ratio of the number of unstable samples to the total number of simulated samples is computed and is taken as the failure probability, which is validated and compared with the response surface method.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.7
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• pp.387-394
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• 2016

Commercial 28 algae removal technologies that have been applied in domestic rivers and lakes with green tide were investigated, analyzed and classified. The classification of algae removal technologies was based on the three criteria (i.e., principle, flow rate of water body, and application period). Also, algae removal technologies were evaluated in terms of cost effectiveness, field applicability, effect durability, and eco friendliness. From the analysis results, technologies using physical, chemical, biological, and convergent controls were 32.2%, 25%, 21.4%, and 21.4%, respectively. The 75% of technologies have been applied to stagnant water body (${\leq}0.2m/s$). Also, algae harvesting ship with dissolved air flotation, conveyor belt and filtration processes and natural floating coagulant were found to have better field applicability, compared to other technologies. However, proper algae removal technology in specific rivers and lakes should be chosen after the evaluation of long-term pilot scale field test. Also, development of energy and resource recovery technologies from algae biomass is warranted.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.321-332
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• 2024

Understanding the status of surface cover in riparian zones is essential for river management and flood disaster prevention. Traditional survey methods rely on expert interpretation of vegetation through vegetation mapping or indices. However, these methods are limited by their ability to accurately reflect dynamically changing river environments. Against this backdrop, this study utilized satellite imagery to apply the Random Forest method to assess the distribution of vegetation in rivers over multiple years, focusing on the Naeseong Stream as a case study. Remote sensing data from Sentinel-2 imagery were combined with ground truth data from the Naeseong Stream surface cover in 2016. The Random Forest machine learning algorithm was used to extract and train 1,000 samples per surface cover from ten predetermined sampling areas, followed by validation. A sensitivity analysis, annual surface cover analysis, and accuracy assessment were conducted to evaluate their applicability. The results showed an accuracy of 85.1% based on the validation data. Sensitivity analysis indicated the highest efficiency in 30 trees, 800 samples, and the downstream river section. Surface cover analysis accurately reflects the actual river environment. The accuracy analysis identified 14.9% boundary and internal errors, with high accuracy observed in six categories, excluding scattered and herbaceous vegetation. Although this study focused on a single river, applying the surface cover classification method to multiple rivers is necessary to obtain more accurate and comprehensive data.

• Nuclear Engineering and Technology
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• v.33 no.2
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• pp.145-155
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• 2001

This simulation first allows us to define a transition zone from a bubble to jet mode of the argon out-flow and hereinafter to define a similar area for water-steam leak in the KALIMER SG (Korea Advanced Liquid Metal Reactor Steam Generator) using a water mock-up system, taking into account the KALIMER leak classification and tube bundle design, as a simulation of a real water-steam into sodium leak. in accordance with leak conditions in the KALIMER SG, the transition from bubbling to jetting is studied by means of turbulence regime simulation for argon out-flow through a very small orifice, which has the equivalent diameter of about 0.253 mm. finally the noise generation mechanism is explained from the existing experimental data. We also confirmed the possibility of micro-leak detection from the information of the bubbling mode through simulations and the experiment in this study.