• Journal of Climate Change Research
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• v.7 no.1
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• pp.69-75
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• 2016

Recently, many countries all over the world have been suffered from disaster caused by climate change. Especially in case of developed countries, the disaster is concentrated in the industry sector. In this research, we analyzed industrial vulnerable homogeneous hotspot for the climate change using spatial autocorrelation analysis on the south Korea. Homogeneous hot spot areas through autocorrelation analysis indicate the spatial pattern of areas interacted each other. Industry sector have responsibility of green house gas emissions, and should adapt to the climate change caused by greenhouse gas already released. So, we integrated the areas sensitive to mitigation option with the areas hardly adapt to climate change because of vulnerable infrastructure. We expected that the result of this research could contribute to the decision-making system of climate change polices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1351-1372
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• 2022

A self-organizing multiple unmanned aerial vehicles (multi-UAVs) deployment based on virtual forces has a difficulty in ensuring the quality-of-experience (QoE) of users because of the difference between the assumed center for users in a hotspot and an actual center for users in the hotspot. This discrepancy is aggravated in a non-uniform and mobile user distribution. To address this problem, we propose a new density based virtual force (D-VF) multi-UAVs deployment algorithm which employs a mean opinion score (MOS) as a metric of QoE. Because MOS is based on signal-to-noise ratio (SNR), a sum of users' MOS is a good metric not only to secure a wide service area but to enhance the link quality between multi-UAVs and users. The proposed algorithm improves users' QoE by combining virtual forces with a random search force for the exploration of finding multi-UAVs' positions which maximize the sum of users' MOS. In simulation results, the proposed deployment algorithm shows the convergence of the multi-UAVs into the position of maximizing MOS. Therefore, the proposed algorithm outperforms the conventional virtual force-based deployment scheme in terms of QoE for non-uniform user distribution scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2606-2626
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• 2022

In this paper, a unmanned aerial vehicle (UAV) access deployment algorithm is proposed, which is based on an improved virtual force model to solve the poor coverage quality of UAVs caused by limited number of UAVs and random mobility of users in the deployment process of UAV base station. First, the UAV-adapted Harris Hawks optimization (U-AHHO) algorithm is proposed to maximize the coverage of users in a given hotspot. Then, a virtual force improvement model based on user perception (UP-VFIM) is constructed to sense the mobile trend of mobile users. Finally, a UAV motion algorithm based on multi-virtual force sharing (U-MVFS) is proposed to improve the ability of UAVs to perceive the moving trend of user equipments (UEs). The UAV independently controls its movement and provides follow-up services for mobile UEs in the hotspot by computing the virtual force it receives over a specific period. Simulation results show that compared with the greedy-grid algorithm with different spacing, the average service rate of UEs of the U-AHHO algorithm is increased by 2.6% to 35.3% on average. Compared with the baseline scheme, using UP-VFIM and U-MVFS algorithms at the same time increases the average of 34.5% to 67.9% and 9.82% to 43.62% under different UE numbers and moving speeds, respectively.

• ETRI Journal
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• v.46 no.2
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• pp.333-346
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• 2024

Various techniques for noninvasively focus microwave energy on lesions have been proposed for thermotherapy. To focus the microwave energy on the lesion, a focusing parameter, which is referred to as the magnitude and phase of microwaves radiated from an external array antenna, is very important. Although the finite-difference time-domain (FDTD)-based time-reversal (TR) focusing algorithm is widely used, it has a long processing time if the focusing target position changes or if optimization is needed. We propose a technique to obtain multistatic data (MSD) based on Green's function and use it to derive the focusing parameters. Computer simulations were used to evaluate the electric fields inside the object using the FDTD method and Green's function as well as to compare the focusing parameters using FDTD- and MSD-based TR focusing algorithms. Regardless of the use of Green's function, the processing time of MSD-based TR focusing algorithms reduces to approximately 1/2 or 1/590 compared with the FDTD-based algorithm. In addition, we optimize the focusing parameters to eliminate hotspots, which are unnecessary focusing positions, by adding phase-reversed electric fields and confirm hotspot suppression through simulations.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.233-243
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• 2015

The ecosystem fragmentation due to transportation infrastructure causes road-kill phenomenon. When making policy for reducing road-kill it is important to select target-species in order to enhance its efficiency. However, many corridors installed in Korea have been raised issues about their effectiveness due to lack of considerations such as target-species selection, site selection, and management, etc. In this study, we are to grasp relationship between road-kill area and habitat patches and suggest that spatial location of habitat patches should be considered as one of the important factors when making policy for reducing road-kill. Habitat patches were presumed from overlying suitability index that chosen by literature review and road-kill hotspot was determined by Getis-Ord $G_i^*$ analysis. Afterwards, we performed a correlation analysis between $G_i$ Z-score and the distance from habitat patches to the roads. As a result, there is a negative correlation between two variables, It affects the $G_i^*$ Z-score going up if the habitat patches and the roads become closer.

• Journal of the Korean association of regional geographers
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• v.21 no.4
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• pp.739-750
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• 2015

This study aims to investigate the possibility of crime prevention through CCTV by analyzing the appropriateness of the CCTV location, whether it is installed in the hotspot of crime-prone areas, and exploring the crime prevention effect and transition effect. The real crime and CCTV locations of case city were converted into the spatial data by using GIS. The data was analyzed by hotspot analysis and weighted displacement quotient (WDQ). The results demonstrated that there was no significant effect in the installation of CCTV on crime prevention. This indicates that CCTV should be installed and managed in a more scientific way reflecting local crime situations. In terms of CCTV, the methods of spatial analysis such as GIS, which can evaluate the installation effect, and the methods of economic analysis like cost-benefit analysis should be developed. In addition, these methods should be distributed to local governments across the nation for the appropriate installation of CCTV and operation. This study intended to find a design guideline of the optimum CCTV installation. In this regard, this study is meaningful in that it will contribute to the creation of a safe city.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.23-29
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• 2015

In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.12
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• pp.655-663
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• 2017

It is difficult to manage hotspot area and to establish the reduction plan considering with spatial-distribution on Korea TMDLs (Total Maximun Daily Loads) system. To solve this problems, methods of Load Duration Curve (LDC) using long-term flow and water quality data, and spatial-analysis were applied on present TMDLs. Jinwi A watershed which is enforced TMDLs plan were selected to study area. Results of application of suggested methods in this study to Jinwi watershed, Hwangguji tributary was selected to hotspot area and Jinwi tributary was exclued. Also, middle area of Hwangguji tributary was needed a reduction plan for the protection of non-point source pollution. In downstream area, livestock manure should be managed additionally. The new methods suggested in this study were useful to increase healthiness for total watershed.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.14-25
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• 2018

The operation of high-speed rail (HSR) has an effect on the agglomeration economies, and the impact is shown as a relocation of individual firm and worker to where business activity can be maximized. The proximity to the HSR station could be considered as a core district to maximize the industrial benefit through the HSR network. From this perspective, this study considers the agglomeration effect of HSR within the HSR station-area and analyzed the agglomerated spatial pattern through hotspot analysis by service industry in the cases of Korea and Japan using GIS. This study analyzed the service industry within 1km distance from 8 HSR stations of Korea and 4 Kyushu Shinkansen stations of Japan. The results suggest that the hotspot patterns are observed in the service industry within 1km distance from the HSR station of Korea and Japan, except for two HSR stations of Gupo station and Kagoshima-Chuo station. Leisure, amusement, association, and other specific service industries could be affected by HSR passengers and knowledge-spillovers through HSR station. Therefore, the observed hotspot districts near the HSR station-area could explain an agglomeration pattern of the service industry through a closeness to the HSR station. Further, we could expect that the impact of HSR affects the service industry, and the impact could attract business activities of the service-area to maximize their benefit from HSR travelers. With the result, it is required to build up a supportive policy to maximize the HSR's impact on the service industry when considering the HSR station-area development.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.693-704
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• 2021

The purpose of this study is to evaluate the relationship between heat wave and river water quality. The daily maximum air temperature (Tmax) of 91 meteorological stations of the Korea Meteorological Administration and 13 river water quality factors (DO, BOD, COD, TOC, TN, DTN, NH4-N, NO2-N, NO3-N, TP, DTP, PO4-P, Chl-a) of Ministry of Environment were analyzed. The correlation analysis was performed on Tmax and water quality factors, and the determination coefficients (R²) of DO, Chl-a, and TN with Tmax showed high values of 0.782, 0.609, and 0.691 respectively. To analyze the spatial impact between heat waves and water quality factors, the heat wave intensity (HWI) and heat wave duration (HWD) were calculated using the Tmax. The hotspot and spatial statistical analyses were applied for spatial impact evaluation. As a result of hotspot analysis, the heat wave index (HWD, HWI) showed high spatial pattern in the downstream of Nakdong River basin, and Chl-a and TN showed the same pattern. In case of spatial statistical analysis for water quality due to heat wave, the most obvious spatial variability was DO.