• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.695-703
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• 2018

This study was conducted to suggest a sustainable farming practice forresource recycling in vegetable gardens of North Korea. In North Korea, farmers are allowed to own private vegetable gardens less than $100m^2$. However, usage of fertilizers in private vegetable gardens is very limited due to economic sanctions by UN security council. If North and South Korea initiated the cooperative action in the near future, agricultural sector would be the highest priority cooperation area. Considering the current North Korean situation in agriculture, we would like to suggest a method for producing organic fertilizer manure. For raw materials for producing manure, we selected corn byproduct, which is the most abundant material, and rabbits' feces, which are easily obtained from individual private farms in North Korea. As we cannot get corn byproducts and rabbits' feces from North Korea, we prepared samples of corn byproducts and rabbits; feces from many places in South Korea. After statistical analysis of variance, there was no significant difference in the T-N contents of corn byproducts from Gyeonggi, Gangwon, Chungnam, Chungbuk, Jeollabuk and Gyeongsangnam-dos, which indicates that the fertilizing quality of corn byproducts does not vary significantly in the spatial scale of South. Korea. In this sense, if we use corn samples from Gyeonggi province, they would not be very different from those of North Korean regions. Physicochemical properties of rabbits' feces were different between those eating feed grains and those eating plants only. Hence, we used rabbits' feces of the rabbits from Yeonchun area, which were fed by plants only. Using three different mixing ratios of corn byproducts and rabbits' feces, composting was conducted for 60 days. The mixing ratio of 1:1 produced the manure with % T-N of 1.98% and OM/N ratio of 31.7 after 30 days of composting, which is comparable to the quality of commercial manure.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.527-536
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• 2022

The purpose of this study is to predict changing traffic environments and related economic effects by reflecting the changed KTDB and socio-economic indicators pertaining to Mulgeum station, a general railway stop, when it is confirmed as a KTX stop. To analyze the data of this study, socioeconomic indicators and the general status of transportation facility operations were investigated with reference to related statistical data, centered on the country overall and on Yangsan city in particular. In addition, we investigated and referenced the railroad facility construction plan and train operation plan, which are national high-level plans related to land development and transportation network construction. Currently, there are only ITX trains (4 times/day) and Mugunghwa trains (29 times/day) that stop at Mulgeum station in Yangsan, meaning that passengers cannot use KTX trains in the Yangsan area. In particular, the need for a KTX stop at Mulgeum station has been continuously raised because train users in the Yangsan area have inconvenient transportation in that they must travel 40 minutes to Ulsan station or 30 minutes to Gupo station to use the KTX. As a result of analyzing railroad transportation demand that will change in the future as the KTX stop at Mulgeum station is confirmed, the number of passengers boarding and arriving at Mulgeum station is predicted to be 1,674 passengers/day by 2025. In addition, the numbers of train passengers that are converted from Ulsan and Gupo stations due to the stop at Mulgeum station are predicted to be 594 passengers/day boarding and 562 passengers/day arriving by 2025. In the future, if Yangsan citizens use the KTX Mulgeum station, the access time to Mulgeum station can be shortened to 22 minutes from 65 minutes, and it is predicted that the inconvenience of transferring between railroads will be resolved, with the waiting time for transfers reduced by up to a maximum of 40 minutes. Therefore, the economic effect of creating a KTX stop at Mulgeum station was analyzed to be B/C=1.823 when general railroad operating costs are not taken into account and B/C=2.127 when general railroad operating costs are considered. In conclusion, when using KTX trains to visit the Seoul Metropolitan Area, it takes 2 hours and 43 minutes to use Mulgeum station without using Ulsan station or Gupo station, which is considered to be very effective for reducing travel times and improving the economic feasibility of this development; it is also expected that Yangsan city will be able to improve accessibility and mobility to the Seoul Metropolitan Area by breaking free from the disgrace of being a remote location given its link to KTX in the future.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.603-611
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• 2022

In urban areas, the impermeable area continues to increase due to urbanization, which interferes with the surface penetrating and infiltrating of rainwater, causing most rainwater runoff to the surface, deepening the distortion of water circulation. Distortion of water circulation affects not only flood disasters caused by rainfall and runoff, but also various aspects such as dry stream phenomenon, deterioration of water quality, and destruction of ecosystem balance, and the Ministry of Environment strongly recommends the use of Low Impact development (LID) techniques. In order to apply the LID technique, it is necessary to set a rainwater management target to handle the increase in outflow after the development of the target site, and the current standard sets the rainwater management target using the 10-year daily rainfall. In this study, the difference from the current standards was analyzed through statistical analysis and classification of independent rainfall ideas using inter-event time definition (IETD) in setting the target amount of rainwater management to improve water circulation. Using 30-year rainfall data from 1991 to 2020, methods such as autocorrelation coefficient (AC) analysis, variation coefficient (VC) analysis, and annual average number of rainfall event (NRE) analysis were applied, and IETD was selected according to the target rainfall period. The more samples the population had, the more IETD tended to increase. In addition, by analyzing the duration and time distribution of independent rainfall according to the IETD, a plan was proposed to calculate the standard design rainfall according to the rainwater management target amount. Therefore, it is expected that it will be possible to set an improved rainwater management target amount if sufficient samples of independent rainfall ideas are used through the selection of IETD as in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.595-601
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• 2008

The purpose of this study is to investigate the trends and patterns of various kind of water uses in a household by metering in Korea. Water use components are classified by toilet, washbowl, bathing, laundry, kitchen, miscellaneous. Flow meters are installed in 140 household selected by sampling in all around Korea. The data are gathered by web-based data collection system from the year 2002 to 2006, considering pre-investigated data such as occupation, revenue, family members, housing types, age, floor area, water saving devices, education, miscellaneous. Reliable data are selected by upper fence method for each observed water use component and statistical characteristics are estimated for each residential type to determine liter per capita per day. Estimated domestic per capita day show an indoor water use with the range from 150 lpcd to 169 lpcd for each housing type as the order of high rise apartment, multi-house, and single house. As the order of consuming amount among water use components, it is investigated that toilet (38.5 lpcd) is the first, and the second is laundry water (30.8 lpcd), the third is kitchen (28.4 lpcd), the fourth is bathtub (24.7 lpcd), the next is washbowl (15.4 lpcd). The results are compared with water uses in U.K. and U.S. As life style has been changed into western style, pattern of water use in Korea is tend to be similar with the U.S. water use pattern. Compared with the surveying results by Bradley, on 1985. Thirty liter of total use increased with the advancement of economic level, and a little change of water use pattern can be found. Especially, toilet water take almost half part of total water use and laundry water shows lowest as 11% in surveying at the year of 1985. But, this study shows that 39 liter, 28% of toilet water, has been decreased by the spread of saving devices and campaign. It is supposed that the spread large sized laundry machine make by-hand laundry has been decreased and water use increased. Unit water amount of each end-use in household can be applied to design factor for water and wastewater facilities, and it play a role as information in establishing water demand forecasting and conservation policy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.603-614
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• 2008

End-uses of household water have been changed by a life style, housing type, weather, water rate and water supply facilities etc. and those variables can be considered as an internal and exogenous factors to estimate long-term demand forecasts. Analysis of influential factors on water consumption in households would give an explanation to cause on the change of trend and would help predicting the water demand of end-use in household. The purpose of this study is to analyze the demand trends and patterns of household water uses by metering and questionnaire such as occupation, revenue, numbers of family member, housing types, age, floor area and installation of water saving device, etc. The peak water uses were shown at Saturday among weekdays and July in a year based on the analysis results of water use pattern. A steep increase of total water volume can be found in the analysis of water demand trend according to temperature from $-14^{\circ}C$ to $0^{\circ}C$, while there are no significant variations in the phase of more than $0^{\circ}C$, with an almost stable demand. Washbowl water shows the highest and toilet water shows the lowest relation with temperature in correlation analysis results. In the results of ANOVA to find the significant difference in each unit water use by exogenous factors such as housing type, occupation, number of generation, residential area and income et al., difference was shown in bathtub water by housing type and shown in kitchen, toilet and miscellaneous water by numbers of resident. Especially, definite differences in components except washbowl and bathtub water, could be found by numbers of resident. Based on the result, average residents in a house should be carefully considered and the results can be applied as reference information, in decision making process for predicting water demand and establishing water conservation policy. It is expected that these can be used as design factors in planning stage for water and wastewater facilities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.885-894
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• 2006

The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.297-306
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• 2023

Saemangeum Lake is the largest artificial lake in Korea. The continuous deterioration of lake water quality necessitates the introduction of novel water quality management strategies. Therefore, this study aims to identify the spatiotemporal water quality characteristics of Saemangeum Lake using data from the National Water Quality Measurement Network and provide basic information for water quality management. In the water quality parameters of Saemangeum Lake, water temperature and total phosphorous content were correlated, and salt, total nitrogen content, pH, and chemical oxygen demand were significantly correlated. Other parameters showed a low correlation. The spatial principal component analysis of Saemangeum Lake showed the characteristics of its four zones. The mid-to-downstream section of the river affected by freshwater inflow showed a high nutrient salt concentration, and the deep-water section of the drainage gate and the lake affected by seawater showed a high salt concentration. Two types of water qualities were observed in the intermediate water area where river water and outer sea water were mixed: waters with relatively low salt and high chemical oxygen demand, and waters with relatively low salt and high pH concentration. In the principal component analysis by time, the water quality was divided into four groups based on the observation month. Group I occurred during May and June in late spring and early summer, Group II was in early spring (March-April) and late autumn (November-December), Group III was in winter (January-February), and Group IV was in summer (July-October) during high temperatures. The water quality characteristics of Saemangeum Lake were found to be affected by the inflow of the upper Mangyeong and Dongjin rivers, and the seawater through the Garuk and Shinshi gates installed in the Saemangeum Embankment. In order to achieve the target water quality of Saemangeum Lake, it is necessary to establish water quality management measures for Saemangeum Lake along with pollution source management measures in the upper basin.

• Journal of the Korean Society of Radiology
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• v.81 no.5
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• pp.1151-1163
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• 2020

Purpose This study aimed to evaluate changes of subprosthetic pannus on cardiac CT and determine its relationship to echocardiographic findings in patients with mechanical aortic valve replacement (AVR). Materials and Methods Between April 2011 and November 2017, 17 AVR patients (56.8 ± 8.9 years, 12% male) who showed pannus formation on CT and had undergone both follow-up CT and echocardiography were included. The mean interval from AVR to the date of pannus detection was 10.5 ± 7.1 years. In the initial and follow-up CT and echocardiography, the pannus extent and echocardiographic parameters were compared using paired t-tests. The relationship between the opening angle of the prosthetic valve and the pannus extent was evaluated using Pearson correlation analysis. Results The pannus extent was significantly increased on CT (p < 0.05). The peak velocity (3.9 ± 0.8 m/s vs. 4.2 ± 0.8 m/s, p = 0.03) and mean pressure gradient (36.4 ± 15.5 mm Hg vs. 42.1 ± 15.8 mm Hg, p = 0.03) were significantly increased. The mean opening angles of the mechanical aortic leaflets were slightly decreased, but there was no statistical significance (73.1 ± 8.3° vs. 69.4 ± 12.1°, p = 0.12). The opening angle of the prosthetic leaflets was inversely correlated with the pannus extent (r = -0.57, p < 0.001). Conclusion The pannus extent increases over time, increasing transvalvular peak velocity and the pressure gradient. CT can be used to evaluate the pannus extent associated with hemodynamic changes that need to be managed by surgical intervention.