• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.59-62
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• 2024

Non-fungible tokens (NFTs) are interchangeable rights to digital assets such as art, in-game items, collectibles or music, etc. NFTs have the potential to be infinitely useful in many industries by increasing security and processing costs for transactions and providing a new platform for the gigeconomy to work through. Its markets have grown fast and significantly since early 2021. We investigate the uses of NFTs and research the facts and figures on the usage of NFTs supporting websites. Using daily data between 2019 to 2021. NFTs took the world by storm in 2021, bringing forth a digital art revolution while becoming one of the fastest-growing asset classes of the year. While the NFTs market has been growing at a rapid pace, many are still wary of entering it because of the theoretical insanity around its worth. NFTs have been out there for quite some time and this trend doesn't plan to go any further. NFTs services have many practical use cases and their potential will only grow over time. While celebrities dive into this marketplace to maintain their onlinepresence andincrease their Net worth.

• Korean Journal of Ecology and Environment
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• v.39 no.4 s.118
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• pp.424-434
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• 2006

This study investigates bacteria-zooplankton grazing link and factors affecting their grazing relationship at trophically different two sites (Paldang Dam and Kyungan Stream) of Lake Paldang Ecosystem from April to December, 2005. Zooplankton were divided into two size groups; microzooplankton (MICZ) : 60-200 ${\mu}m$ and macrozooplankton (MACZ): >200 ${\mu}m$), and their grazing rates on bacteria were conducted for each size group separately. Bacterial abundance and seasonal change pattern were similar between two sites. MICZ, mostly rotifers (e.g., Brachionus, Keratella, Polyathra) were numerically dominant at both sites, while carbon biomass was highest in cladocerans. Zooplankton biomass was higher at the Kyungan Steam site compared to Paldang Dam site, and their high biomass during spring decreased as they were passing through the storm events in summer season at both sites. Zooplankton clearance rate (CR) was high in spring and autumn while low in summer at Paldang Dam site. However, zooplankton CR was high during the summer at Kyungan Stream site. Bacterial C-flux was high in spring and autumn when MACZ (esp. cladecerans) developed at a high biomass level at both sites. Overall, MACZ community CR and carbon flux (C-flux) were higher than those of MICZ, and the degree of difference between them was higher at Kyungan Stream site. Short hydraulic residence time and physical disturbance caused by summer storm event appeared to affect the zooplankton grazing on bacteria at both sites. The results of this study indicate that bacteria are potentially important carbon source of zooplankton, and that both biotic (e.g,, prey and predator taxa composition and abundance) and physical parameters appear to alter energy transfer in the planktonic food web of this river-reservoir hybrid system.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.299-309
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• 2006

In recent years, a large natural disasters have occurred due to worldwide abnormal weather and the amount of damage has been increased more resulting from high density population and a large-sized buildings of the urbanized area. In this study. we estimate the flooded area according to rainfall probability intensify and sea level in Woreong dong, Masan occurred flood damages by typhoon Maemi using SWMM, a dynamic rainfall-runoff simulation model in urban area, and then analyze the damage of flood expected area through connecting with GIS database. In result, we can predict accurately expected area of inundation according to the rainfall intensity and sea level rise through dividing the study area into sub-area and estimating a flooded area and height using SWMM. We provide also the shelter information available for urban planning and flood risk estimation by landuse in expected flood area. Further research for hazard management system construction linked with web or wireless communication technology expects to increase its application.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.162-162
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• 2022

Stormwater management is an essential component of land-use planning and development. Due to the additional challenges posed by climate change and urbanization, various stormwater management schemes have been developed to limit flood damages and ease water quality concerns. Nature-based solutions (NBS) are increasingly used as cost-effective measures to manage stormwater runoff from various land uses. Specifically, constructed wetlands were already considered as socially acceptable green stormwater infrastructures that are widely used in different countries. There is a large collection of published literature regarding the effectiveness or efficiency of constructed wetlands in treating stormwater runoff; however, metadata analyses using bibliographic information are very limited or seldomly explored. This study was conducted to determine the trends of publication regarding stormwater treatment wetlands using a bibliometric analysis approach. Moreover, the research productivity of various countries, authors, and institutions were also identified in the study. The Web of Science (WoS) database was utilized to retrieve bibliographic information. The keywords ("constructed wetland*" OR "treatment wetland*" OR "engineered wetland*" OR "artificial wetland*") AND ("stormwater*" or "storm water*") were used to retrieve pertinent information on stormwater treatment wetlands-related publication from 1990 up to 2021. The network map of keyword co-occurrence map was generated through the VOSviewer software and the contingency matrices were obtained using the Cortext platform (www.cortext.net). The results obtained from this inquiry revealed the areas of research that have been adequately explored by past studies. Furthermore, the extensive collection of published scientific literature enabled the identification of existing knowledge gaps in the field of stormwater treatment wetlands.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.106-120
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• 2006

Natural or man-made disaster has been expected to be one of the potential themes that can integrate human geography and physical geography. Typhoons like Rusa and Maemi caused great loss to insurance companies as well as public sectors. We have implemented a natural disaster management system for a private insurance company to produce better estimation of hazards from high wind as well as calculate vulnerability of damage. Climatic gauge sites and addresses of contract's objects were geo-coded and the pressure values along all the typhoon tracks were vectorized into line objects. National GIS topog raphic maps with scale of 1: 5,000 were updated into base maps and digital elevation model with 30 meter space and land cover maps were used for reflecting roughness of land to wind velocity. All the data are converted to grid coverage with $1km{\times}1km$. Vulnerability curve of Munich Re was ad opted, and preprocessor and postprocessor of wind velocity model was implemented. Overlapping the location of contracts on the grid value coverage can show the relative risk, with given scenario. The wind velocities calculated by the model were compared with observed value (average $R^2=0.68$). The calibration of wind speed models was done by dropping two climatic gauge data, which enhanced $R^2$ values. The comparison of calculated loss with actual historical loss of the insurance company showed both underestimation and overestimation. This system enables the company to have quantitative data for optimizing the re-insurance ratio, to have a plan to allocate enterprise resources and to upgrade the international creditability of the company. A flood model, storm surge model and flash flood model are being added, at last, combined disaster vulnerability will be calculated for a total disaster management system.