• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.35-48
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• 2021

In this study, the assessment of field applicability of in-situ remediation of nitrate-contaminated groundwater located in Yesan-gun was performed. Zero-valent iron/bio composite media injected PRB (Permeable Reactive Barrier) and monitoring well were installed in the contaminated groundwater site and monitored main remediation indicators during the PRB operation. Nitrate, nitrite, ammonia, Fe ion, TOC, and turbidity were analyzed and the diversity and population of microorganism in the PRB installed site were investigated for the verification of effect of injected PRB. In the study site where is an agricultural area, a river flows from west to east that forms a river boundary and the southern area has an impermeable sector. It was found that nitrate flows into the river, which is similar as groundwater flow. Simulation result for the fate of nitrate in groundwater showed steady state of nitrate arrived after 3~5 years passed. However, it is just to consider current conditions with no additional input of contaminant source, if additional input of contaminant source occurs contamination dispersion and time for steady state are expected to be increased. The monitoring results showed that Fe ion, TOC and turbidity in groundwater were not clearly changed in concentration after PRB installation, which indicates adaptability of the injected PRB for remediation of groundwater with no additional harmful effect to water quality. The concentration of nitrate maintained less than 5mg/L until 42 days after PRB installation and recovered its initial concentration after 84 days passed and showed termination of reactivity of injected zero-valent iron/bio composite media for removal nitrate. Nitrite and ammonia ions found after installation of PRB indicates reductive removal of nitrate. And the outstanding increase of microorganism diversity and population of Betaproteobacteria Class which includes denitrification microorganism explains biologically reductive removal of nitrate in injected PRB.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• The Journal of Engineering Geology
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• v.32 no.3
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• pp.411-420
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• 2022

Recently, research using remote sensing has been active in various fields such as environment, science, and society. The results of research using remote sensing are not only numerical results, but also play an important role in solving and preventing social and scientific problems. The purpose of this thesis is to tell the correlation between the data provided and each data by using remote sensing technology for the tidal flat environment. The purpose of this study is to obtain high-resolution data using artificial satellites during remote sensing to find out information on tidal flat currents. Tidal flats created by erosion, sedimentation, low tide, and high tide contain information about the tidal flat slope and information about the ecosystem. Therefore, it can be considered as one of the very important studies to analyze the overall tidal flow channel. This paper creates a DEM (Digital Elevation Model) through TanDEM-X, and DEM is used as the most basic data to create a tidal channel. The research area is a tidal flat located in the middle of the west coast of Ganghwado tidal flat. By analyzing the tidal channel created, various information such as the slope direction of Ganghwado tidal flat and the shape of the tidal channel can be grasped. It is expected that the results of this study will increase the importance and necessity of using DEM data for tidal flat research in the future, and that high-quality results can be obtained.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.2
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• pp.167-176
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• 2021

When producing recycled asphalt mix, it is important that the old binder of reclaimed asphalt pavement(RAP) should be well melted during blending in the mixer. The recycled asphalt mix is produced by instant mixing(IM) of all materials(RAP, virgin asphalt and new aggregates) all together in the mixer. However, in the same recycled mix, the binder around RAP aggregate was found to show higher oxidation level than the binder coated around the virgin aggregate because the old binder of RAP was not rejuvenated properly while instant mixing. The partially-rejuvenated RAP binder is assumed to be a high stiffness point in IM recycled mix. In this study, the stage mixing(SM) method was introduced; blending RAP and virgin asphalt for the first stage, and then mixing all together with hot new aggregates for the second stage. To compare the effect of the two mixing methods on moisture resistance of recycled mixes, a statistical t-test was performed between SM and IM using indirect tensile strength(ITS) and tensile strength ratio(TSR). Three conditioning methods were used; a 16-h freezing and then 24-h submerging, 48-h submerging, and 72-h submerging in 60℃ water. It was found that the TSR(=ITS_wet/ITS_dry) values of the mixes prepared by SM was clearly higher than the IM mixes, and coefficients of variation of SM mixes were lower than the IM mixes. It was also observed that the ITS_WET of SM was significantly different from the IM at α=0.05 level by statistical t-test. The ITS_WET of SM mix was reduced less than the IM mix in severer conditioned mixes. Therefore, it was concluded that the stage mixing method was an important blending technique for producing better-quality of recycled asphalt mixes, which would show higher moisture resistance than the recycled mixes produced by conventional instant mixing.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.11-18
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• 2021

A novel microwave dielectric composite material for ultra-low temperature co-fired ceramics (ULTCC) with (1-x)BaWO₄-xBaV₂O₆ (x=0.54~0.85) composition was prepared by firing a mixture of BaWO₄ and BaV₂O₆. Shrinkage tests showed that the ceramic composite begins to densify at a temperature as low as 550℃ and can be sintered at 650℃ with 98% of relative density under the influence of BaV₂O₆. X-ray diffraction analysis showed that BaWO₄ and BaV₂O₆ coexisted and no secondary phase was detected in the sintered bodies, implying good chemical compatibility between the two phases. Near-zero temperature coefficients of the resonant frequency (𝛕_f) could be achieved by controlling the relative content of the two phases, due to their positive and negative 𝛕_f values, respectively. With increasing BaV₂O₆ (x from 0.53 to 0.85), the 𝛕_f value of the composites increased from -7.54 to 14.49 ppm/℃, ε_r increased from 10.08 to 11.17 and the quality factor (Q×f value) decreased from 47,661 to 37,131 GHz. The best microwave dielectric properties were obtained for x=0.6 samples with ε_r=10.4, Q×f=44,090 GHz, and 𝛕_f=-2.38 ppm/℃. Chemical compatibility experiments showed the developed composites are compatible with aluminum electrode during co-firing process.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.60-75
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• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.283-295
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• 2023

With the development of sensor and satellite technology, numerous high-resolution and multi-spectral satellite images have been available. Due to their wavelength-dependent reflection, transmission, and scattering characteristics, multi-spectral satellite images can provide complementary information for earth observation. In particular, the short-wave infrared (SWIR) band can penetrate certain types of atmospheric aerosols from the benefit of the reduced Rayleigh scattering effect, which allows for a clearer view and more detailed information to be captured from hazed surfaces compared to the visible band. In this study, we proposed a multi-resolution transform-based image fusion method to combine visible and SWIR satellite images. The purpose of the fusion method is to generate a single integrated image that incorporates complementary information such as detailed background information from the visible band and land cover information in the haze region from the SWIR band. For this purpose, this study applied the Laplacian pyramid-based multi-resolution transform method, which is a representative image decomposition approach for image fusion. Additionally, we modified the multiresolution fusion method by combining a haze-guided weight map based on the prior knowledge that SWIR bands contain more information in pixels from the haze region. The proposed method was validated using very high-resolution satellite images from Worldview-3, containing multi-spectral visible and SWIR bands. The experimental data including hazed areas with limited visibility caused by smoke from wildfires was utilized to validate the penetration properties of the proposed fusion method. Both quantitative and visual evaluations were conducted using image quality assessment indices. The results showed that the bright features from the SWIR bands in the hazed areas were successfully fused into the integrated feature maps without any loss of detailed information from the visible bands.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

• Resources Recycling
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• v.33 no.4
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• pp.47-61
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• 2024

As a recycling technology for recovering zinc contained in large amounts in electric arc furnace dust (EAFD), the most commercialized technology in the world is the Wealz Kiln Process. The Wealz Kiln Process is a process in which components such as Zn and Pb in EAFD are reduced/volatile (endothermic reaction) in high-temperature Kiln and then re-oxidized (exothermic reaction) in the gas phase and recovered in the form of Crude zinc oxide (60wt%Zn) in the Bag Filter installed at the rear end of Kiln. In this study, an experimental Wealz kiln was produced to investigate the optimal process variable value for practical application to the recycling process of large-scale kiln on a commercial scale. Additionally, Pellets containing EAFD, reducing agents, and limestone were continuously loaded into Kiln, and the amount of input, heating temperature, and residence time were examined to obtain the optimal crude zinc oxide recovery rate. In addition, the optimal manufacturing conditions of Pellets (drum tilt angle, moisture addition, mixing time, etc.) were also investigated. In addition, referring to the SiO₂-CaO-FeO ternary system diagram, the formation behavior of a low melting point compound, a reaction product inside Kiln according to the change in the basicity of Pellet, and the reactivity (adhesion) with the castable constructed on the inner wall of Kiln were investigated. In addition, in order to quantitatively investigate the possibility of using anthracite as a substitute for Coke, a reducing agent, changes in the temperature distribution inside Kiln, where oxidation/reduction reactions occur due to an increase in the amount of anthracite, the quality of Crude zinc oxide, and the behavior of tar in anthracite were also investigated.

• Korean Journal of Ecology and Environment
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• v.37 no.1 s.106
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• pp.26-35
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• 2004

We investigated the effect of physicochemical environmental factors on the community dynamics of phytoplanktons and bacteria at the Hoeya Dam Reservoir, a drinking water reservoir for Ulsan city. Water samples were collected and analyzed every two to four weeks at three sites along the reservoir from April to October, 2001. During the study period, the Secchi depths were between 0.4 and 3.5 m. At the surface layer of water column, temperature ranged 10.2 ~ $32.0^{\circ}C$, pH 7.3${\sim}$9.6, dissolved oxygen 5.5 ${\sim}$ 12.4 mg $L^{-1}$, $BOD_5$ 0.8 ${\sim}$ 5.0 mg $L^{-1}$, $COD_{Mn}$ 3.7 ${\sim}$ 10.0 mg $L^{-1}$, and Chl-a 8.9 ${\sim}$ 60.9 mg $m^{-3}$. At the bottom layer, temperature varied 7.2 ${\sim}$ $28.9^{\circ}C$, pH 7.1 ${\sim}$ 9.3, dissolved oxygen 0.6 ${\sim}$ 9.7 mg $L^{-1}$, $BOD_5$ 0.8 ${\sim}$ 4.5 mg $L^{-1}$, $COD_{Mn}$ 3.9 ${\sim}$ 10.0 mg $L^{-1}$, and Chl-a 4.3 ${\sim}$ 81.9 mg $m^{-3}$. The numbers of phytoplanktons were 7.4${\pm}10^2{\sim}2.6{\pm}10^5$ cells $mL^{-1}$ at surface and 2.5${\pm}10^2{\sim}2.4{\pm}10^4$ cells $mL^{-1}$ at bottom, and were positively correlated with water temperature and Chl- a concentration. Genus Stephanodiscus and genus Oscillatoria dominated on April and on May, respectively. Cyanobacterial blooms of Aphanizomenon, Microcystis, Anabaena were observed from June to early September, and thereafter Stephanodiscus and Aulacoseiral dominated again. Total microbial counts ranged 1.73${\pm}10^4{\sim}1.68{\pm}10^5$ cells $mL^{-1}$, and were positively correlated with water temperature and phytoplankton counts at surface water. Heterotrophic plate counts (HPCs) ranged 30${\sim}4.1{\pm}10^3$ CFU $mL^{-1}$, and were positively correlated with $BOD_5$ and $NO^3\;^-$-N concentration at bottom water. Unlike the total microbial counts, the numbers of fecal coliforms and fecal streptococci as well as HPCs were higher at the bottom than the surface layer and were highest at the upper a site among the three sampling sites. Since the concentrations of fecal coliforms and streptococci were still high at the bottom of site c, where intake for water treatment plant is located, it appeared that special management of water treatment processes may be needed especially after strong rainfall.