• Ocean and Polar Research
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• v.33 no.3
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• pp.291-301
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• 2011

To investigate major factors controlling variations in water quality, principal component analysis and cluster analysis were used to analyze data sets of 12 parameters measured at 23 sampling stations of Jinhae Bay during winter and spring. Principal component analysis extracted three major factors controlling variations of water quality during winter and spring. In winter, major factors included freshwater input, polluted material input, and biological activity. Whereas in spring they were polluted material input, freshwater input, and suspended material input. The most distinct difference in the controlling factors between winter and spring was that the freshwater input was more important than the polluted material input in winter, but the polluted material input was more important than the freshwater input in spring. Cluster analysis grouped 23 sampling stations into four clusters in winter and five clusters in spring respectively. In winter, the four clusters were A (station 5), B (stations 1, 2), C (station 4), and D (the remaining stations). In spring, the five clusters included A (station 5), B (station 1), C (station 3), D (station 6), and E (the remaining stations). Intensive management of the water quality of Masan and Hangam bays could improve the water quality of Jinhae Bay since the polluted materials were mainly introduced into Jinhae Bay through Masan and Hangam bays.

• Bulletin of the Korean Chemical Society
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• v.24 no.6
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• pp.757-762
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• 2003

Since theoretical investigations of gas phase clusters enable the evaluation of intrinsic molecular properties and intermolecular interactions, one can predict the macroscopic properties of bulk matter, from a microscopic determination of the properties of individual atoms, molecules, or clusters. Based on the insights obtained from theoretical investigations of the properties of a large number of cluster systems (ranging from simple water clusters to large π-systems), we have investigated the properties of various novel molecular systems including endo/exohedral fullerenes, nanotori, nonlinear optical materials, ionophores/receptors, polypeptides, enzymes, organic nanotubes, nanowires, and electronic and nano-mechanical molecular devices. The present minireview highlights some of the interesting results obtained in the course of our extensive theoretical investigations of clusters and nanomaterials.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.177-190
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• 2009

Rehabilitation projects for old water mains typically require considerable capital investments. One of the economical ways of pursuing the rehabilitation projects is to focus on a specific area within the entire region under management. In this paper the hierarchical clustering methods that analyze spatial inter-relationship of location data are applied to about 8,000 water leak location data recorded in a case study area from 1992 to 1997. Among the hierarchical clustering methods Single, Complete, and Average Linkage Methods are used to identify clusters of the water leak locations and to divide the area according to the defined clusters. By comparing the clusters identified by the clustering methods, the best clustering method for the case study area is suggested. Prioritization of the area for maintenance is obtained based on the water leak incident intensity for the clustered area using the suggested best clustering method.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.245-257
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• 2022

Water quality characteristics and their spatial variations in the Nakdong River were statistically analyzed by multivariate techniques including correlation analysis, CA, and FA/PCA based on water quality parameters for 17 sites over 2017-2019, yielding PI values for primary factors. Site 10 indicated the highest parameter concentrations, and results of pearson's correlation analysis suggest that non-biodegradable organic matter had been distributed on the site. Five clusters were identified in order of descending pollution levels: I (Ib > Ia) > II (IIa > IIb) > III. Spatial variations started from sub-cluster Ib in which Daegu city and Geumho-river are joined. T-P, PO4-P, SS, COD, and TOC corresponded to VF 1 and 2, which were found to be principal components with strong influence on water quality. Sub-cluster Ib was strongly influenced by NO3-N and T-N compared to other clusters. According to the PIs, water quality pollution deteriorated due to non-biodegradable organic matter, nitrogen- and phosphorus-based nutrient salts in the middle and lower reaches, illustrating worsening water pollution due to inflows of anthropogenic sources on the Geumho-river, i.e., sewage and wastewater, discharged from Site 10, at which there is a concentration of urban, agricultural, and industrial areas.

• Bulletin of the Korean Chemical Society
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• v.24 no.2
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• pp.197-204
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• 2003

The intracluster ion-molecule reactions of $Ti^+(H_2O)_n,\;Ti^+(CH_3OCH_3)_n,\;and\;Ti^+(CH_3OD)_n$ complexes produced by the mixing of the laser-vaporized plasma and the pulsed supersonic beam were studied using a reflectron time-of-flight mass spectrometer. The reactions of $Ti^+$ with water clusters were dominated by the dehydrogenation reaction, which produces $TiO^+(H_2O)_n$ clusters. The mass spectra resulting from the reactions of $Ti^+\;with\;CH_3OCH_3$ clusters exhibit a major sequence of $Ti^+(OCH_3)_m(CH_3OCH_3)_n$ cluster ions, which is attributed to the insertion of $Ti^+$ ion into C-O bond of $CH_3OCH_3$ followed by $CH_3$ elimination. The prevalence of $Ti^+(OCH_3)_m(CH_3OD)_n$ ions in the reaction of $Ti^+\;with\;CH_3OD$ clusters suggests that D elimination via O-D bond insertion is the preferred decomposition pathway. In addition, the results indicate that consecutive insertion reactions by the $Ti^+$ ion occur for up to three precursor molecules. Thus, examination of $Ti^+$ insertion into three different molecules establishes the reactivity order: O-H > C-O > C-H. The experiments additionally show that the chemical reactivity of heterocluster ions is greatly influenced by cluster size and argon stagnation pressure. The reaction energetics and formation mechanisms of the observed heterocluster ions are also discussed.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.5
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• pp.261-269
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• 2023

In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.

• Proceedings of the Korean Vacuum Society Conference
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• 2005.02a
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• pp.27-27
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• 2005

• Journal of Korean Society of Water and Wastewater
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• v.21 no.2
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• pp.165-175
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• 2007

Performance indicators haven't been used for the assessment of the wastewater treatment facility or management in Korea yet, therefore they are going to be important parts in wastewater utilities because they are used to understand present situation and to compare one with other wastewater utilities. In this study, we used performance indicators to assess the condition of wastewater utilities and they were divided into four categories (A, B, C, and D). A category represented the condition of the planning & construction and composed of wastewater supply, disaster defence and employees. B category represented maintenance of wastewater utilities and were composed of manhole, sewer, and technical employees. C category showed the operation efficiency of wastewater utilities and D category represented the environmental load. To analyze the situation of wastewater utilities overall, cluster analysis was performed using four categori' es indicators. And CCC (Cubic Clustering Criterion) and R-square were used to decide the proper number of clusters, and wastewater utilities of 48 cities were divided into 5 groups(I, II, III, IV, and V groups). Each cluster was analyzed by average and standard deviation to understand the situation of wastewater utilities. A group analysis showed that IV and V clusters were insufficient, B group showed that I and IV groups were insufficient, C group showed all clusters are above average, and D group was also like C group.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.168-168
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• 2020

This study is to evaluate the drought-related bigdata characteristics published from South Korean by developing crawler. The 5 years (2013 ~ 2017) drought-related posted articles were collected from Korean internet search engine 'NAVER' which contains 13 main and 81 local daily newspapers. During the 5 years period, total 40,219 news articles including 'drought' word were found using crawler. To filter the homonyms liken drought to soccer goal drought in sports, money drought economics, and policy drought in politics often used in South Korea, the quality control was processed and 47.8 % articles were filtered. After, the 20,999 (52.2 %) drought news articles of this study were classified into four categories of water deficit (WD), water security and support (WSS), economic damage and impact (EDI), and environmental and sanitation impact (ESI) with 27, 15, 13, and 18 drought-related keywords in each category. The WD, WSS, EDI, and ESI occupied 41.4 %, 34.5 %, 14.8 %, and 9.3 % respectively. The drought articles were mostly posted in June 2015 and June 2017 with 22.7 % (15,097) and 15.9 % (10,619) respectively. The drought news articles were spatiotemporally compared with SPI (Standardized Precipitation Index) and RDI (Reservoir Drought Index) were calculated. They were classified into administration boundaries of 8 main cities and 9 provinces in South Korea because the drought response works based on local government unit. The space-time clustering between news articles (WD, WSS, EDI, and ESI) and indices (SPI and RDI) were tried how much they have correlation each other. The spatiotemporal clusters detection was applied using SaTScan software (Kulldorff, 2015). The retrospective and prospective cluster analyses were conducted for past and present time to understand how much they are intensive in clusters. The news articles of WD, WSS and EDI had strong clusters in provinces, and ESI in cities.

• Journal of Korean Society of Water and Wastewater
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• v.36 no.3
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• pp.149-165
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• 2022

The water consumption data of individual consumers must be analyzed and forecast to establish an effective water demand management plan. A k-mean cluster model that can monitor water use characteristics based on hourly water consumption data measured using automated meter reading devices and demographic factors is developed in this study. In addition, the quantification model that can estimate the daily water consumption is developed. K-mean cluster analysis based on the four clusters shows that the average silhouette coefficient is 0.63, also the silhouette coefficients of each cluster exceed 0.60, thereby verifying the high reliability of the cluster analysis. Furthermore, the clusters are clearly classified based on water usage and water usage patterns. The correlation coefficients of four quantification models for estimating water consumption exceed 0.74, confirming that the models can accurately simulate the investigated demographic data. The statistical significance of the models is considered reasonable, hence, they are applicable to the actual field. Because the use of automated smart water meters has become increasingly popular in recent year, water consumption has been metered remotely in many areas. The proposed methodology and the results obtained in this study are expected to facilitate improvements in the usability of smart water meters in the future.