• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.44.2-45
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• 2021

As implied by the zodiacal light and spacecraft impact measurements, the space between large bodies in our Solar System is filled with interplanetary dust particles (IDPs). IDPs give us deeper insight into the composition and evolution of the Solar System, as well as being a crucial reference for extrasolar research. IDPs can be interpreted as bearers of carbon and organic materials, and thus, their interaction with Earth can be considered as important factors for the birth of terrestrial life. One of the key routes of IDPs entering Earth is via meteoroid streams (Love and Brownlee 1993). The Geminid meteoroid stream is a notable example. Together with its source asteroid (3200) Phaethon, the Phaethon-Geminid stream complex (PGC) (Whipple 1983; Gustafson 1989) can potentially provide information on the properties and evolution of IDPs in near-Earth space. DESTINY+* is a JAXA/ISAS spacecraft planned to launch in 2024 to explore the physical and chemical features of near-Earth IDPs and uncover the dust ejection mechanism of active near-Earth asteroids, especially Phaethon (Arai et al. 2018). Previous studies on the dust ejection mechanism of Phaethon have various degrees of success in explaining the ejection of submillimeter particles and try to recreate the dust replenishment rate of the Geminid stream. However, none of them are satisfactory for explaining the observed Geminid stream, especially for larger particles of a millimeter and centimeter scales. Inspired by the discovery of rotational mass shedding in the Main Belt region (Jewitt et al., 2014), we investigate a dust ejection scenario by rotational instability on Phaethon. Using the N-body integrator MERCURY6 (Chambers 1999; modified by Jeong 2014), we performed a long-term integration of dust particles of various sizes ejected at ~1 m/s. Through this process, we discuss the implications Phaethon's rotation may have on its ejection, the formation and evolution of IDP by this mechanism, and contribute to the DESTINY+ mission.

• Informatization Policy
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• v.30 no.2
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• pp.68-85
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• 2023

In this study, we collected data from live commerce streaming. Streamimg data were then categorized based on the degree of chatting activation, with the distribution of text responses generated by consumers analyzed. From a total of 2,282 streaming data on NAVER Shopping Live -which has the largest share in the domestic live commerce market- we selected 200 streaming data with the most active viewer responses and finally chose the streams that had steep increase or decrease in viewer responses. We synthesized variables from the existing literature on live commerce viewing intentions and participation motivations to create a table of variables for the purpose of the study. Then we applied them with events in the broadcast. Through this study, we identified which components of the broadcast stimulate the variables of consumer response found in previous studies, moreover, we empirically identified the motivations of consumers to participate in live commerce through data.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.172-172
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• 2020

In recent years, soil erosion has come to be regarded as an essential environmental problem in human life. Soil erosion causes various on- and off-site problems such as ecosystem destruction, decreased agricultural productivity, increased riverbed deposition, and deterioration of water quality in streams. To solve these problems caused by soil erosion, it is necessary to quantify where, when, how much soil erosion occurs. Empirical erosion models such as the Universal Soil Loss Equation (USLE) family models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well by utilizing big data related to climate, geography, geology, land use, etc. within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models remain powerful tools to distinguish erosion-prone areas at the macro scale but physics-based models are necessary to better analyze soil erosion and deposition and eroded particle transport. In this study, the physics-based Surface Soil Erosion Model (SSEM) was upgraded based on field survey information to produce sediment yield at the watershed scale. The modified model (hereafter MoSE) adopted new algorithms on rainfall kinematic energy and surface flow transport capacity to simulate soil erosion more reliably. For model validation, we applied the model to the Doam dam watershed in Gangwon-do and compared the simulation results with the USLE outputs. The results showed that the revised physics-based soil erosion model provided more improved and reliable simulation results than the USLE in terms of the spatial distribution of soil erosion and deposition.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.1-8
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• 2024

In the API gateway, API composition is an essential function that can reduce the number of client calls and prevent over-fetching and under-fetching. API composition that operate with IMJ (In-Memory Join) consume a lot of resources, putting a burden on the performance of the API gateway. In this paper, to improve the problem of IMJ-style API composition, we propose SAPIC (Stream-based API Composition), which delivers the data to be composed to the client by streaming. SAPIC calls each MSA API that makes up the client response data and immediately streams the received response data to the client, reducing the resource consumption of the API gateway and providing faster response time compared to IMJ. As a result of a comparison experiment with GraphQL, a representative API combination technology, SAPIC recorded a maximum CPU occupancy rate of approximately 21 to 70 % lower, a maximum heap usage rate of approximately 16 to 74 % lower, and a throughput rate that was 1 to 2.3 times higher than GraphQL.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.335-344
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• 2023

Brachydiplax chalybea flavovittata, a climate-sensitive biological indicator species, was first observed and recorded at Jeju Island in Korea in 2010. Overwintering was recently confirmed in the Yeongsan River area. This study was aimed to predict the potential distribution patterns for the larvae of B. chalybea flavovittata and to understand its ecological characteristics as well as changes of population under global climate change circumstances. Data was collected both from the Global Biodiversity Information Facility (GBIF) and by field surveys from May 2019 to May 2023. We used for the distribution model among downloaded 19 variables from the WorldClim database. MaxEnt model was adopted for the prediction of potential and future distribution for B. chalybea flavovittata. Larval distribution ranged within a region delimited by northern latitude from Jeju-si, Jeju Special Self-Governing Province (33.318096°) to Yeoju-si, Gyeonggi-do (37.366734°) and eastern longitude from Jindo-gun, Jeollanam-do (126.054925°) to Yangsan-si, Gyeongsangnam-do (129.016472°). M type (permanent rivers, streams and creeks) wetlands were the most common habitat based on the Ramsar's wetland classification system, followed by Tp type (permanent freshwater marshes and pools) (45.8%) and F type (estuarine waters) (4.2%). MaxEnt model presented that potential distribution with high inhabiting probability included Ulsan and Daegu Metropolitan City in addition to the currently discovered habitats. Applying to the future scenarios by Intergovernmental Panel on Climate Change (IPCC), it was predicted that the possible distribution area would expand in the 2050s and 2090s, covering the southern and western coastal regions, the southern Daegu metropolitan area and the eastern coastal regions in the near future. This study suggests that B. chalybea flavovittata can be used as an effective indicator species for climate changes with a monitoring of their distribution ranges. Our findings will also help to provide basic information on the conservation and management of co-existing native species.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.447-458
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• 2003

The basic assumption of conventional data mining methodology is that the data set of a knowledge discovery process should be fixed and available before the process can proceed. Consequently, this assumption is valid only when the static knowledge embedded in a specific data set is the target of data mining. In addition, a conventional data mining method requires considerable computing time to produce the result of mining from a large data set. Due to these reasons, it is almost impossible to apply the mining method to a realtime analysis task in a data stream where a new transaction is continuously generated and the up-to-dated result of data mining including the newly generated transaction is needed as quickly as possible. In this paper, a new mining concept, open data mining in a data stream, is proposed for this purpose. In open data mining, whenever each transaction is newly generated, the updated mining result of whole transactions including the newly generated transactions is obtained instantly. In order to implement this mechanism efficiently, it is necessary to incorporate the delayed-insertion of newly identified information in recent transactions as well as the pruning of insignificant information in the mining result of past transactions. The proposed algorithm is analyzed through a series of experiments in order to identify the various characteristics of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.59-67
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• 2006

OFDM (Orthogonal frequency Division Multiplexing) systems convert serial data stream to N parallel data streams and modulate them to N orthogonal subcarriers. Thus spectrum utilization efficiency of the OFDM systems are high and high-speed data transmission is possible. However, with the OFDM systems using the same modulation method at all subcarriers, the error probability is dominated by the subcarriers which experience deep fades. Therefore, in order to enhance the performance of the system adaptive modulation is required, with which the modulation methods of the subcarriers are determined according to the estimated SNRs. The IEEE 802.11a system selects various transmission speed between 6 and 54 Mbps according to the modulation mode. There are three typical methods for SNR estimation: Direct estimation method uses the frequency domain symbols to estimate SNR directly by minimizing MSE (Mean Square Error), EVM method utilizes the distance between the demodulated constellation points and received complex values, and the method utilizing the Viterbi algorithm uses the cumulative minimum distance in decoding process to estimate the SNR indirectly. Through comparison analyses of three methods we propose a new SNR estimation method, which employs both the EVM method and the Viterbi algorithm. Finally, we perform extensive computer simulations to confirm the performance improvement of the proposed adaptive OFDM systems on the basis of IEEE 802.11a.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.91-98
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• 2008

In digital broadcasting, it is possible to multiplex maximum one hundred audio or music programs into MPEG-2 transport stream, which is suitable for transmitting through one channel. In order to check if multiplex music programs are transmitted well, we need a multiplex audio monitoring system that monitors the programs in real-time. In analog broadcasting, we have used hardware-based audio monitoring system for a small number music programs. However, the effectiveness of hardware-based audio monitoring system from the cost and function viewpoint is so low that a new system is needed for digital broadcasting. In this paper, we have designed and implemented a software-based audio monitoring system to satisfy these requirements. In this implementation, only one PC is used without other hardware facilities, and the system monitors digital broadcasting music programs effectively. Transmitted digital broadcasting streams are demultiplexed into many music programs and the realtime value of audio level and packet error information for these programs are displayed in the screen. Thus, the system detects and shows the abnormal transmitting programs automatically. Simulation results show that effective realtime multiplex audio monitoring is possible for digital broadcasting music programs.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.13-23
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• 2021

This study intended to assess the reliability of topographic data using satellite imaging data. The topographical data using actual instrumentation data and satellite image data were established and applied to the rainfall-leak model, S-RAT, and the topographical data and outflow data were compared and analyzed. The actual measurement data were collected from the Water Resources Management Information System (WAMIS), and satellite image data were collected from MODIS observation sensors mounted on Terra satellites. The areas subject to analysis were selected for two rivers with more than 80% mountainous areas in the Han River basin and one river basin with more than 7% urban areas. According to the analysis, the difference between instrumentation data and satellite image data was up to 50% for peak floods and up to 17% for flood totals in rivers with high mountains, but up to 13% for peak floods and up to 4% for flood totals. The biggest difference in the video data is Landuse, which shows that MODIS satellite images tend to be recognized as cities up to 60% or more in urban streams compared to WAMIS instrumentation data, but MODIS satellite images are found to be less than 5% error in forest areas.